Incidence and risk factors of institutionalisation in Parkinson's disease and atypical parkinsonism

INTRODUCTION

The basic epidemiology of institutionalisation (the need for long-term care in an institution) in parkinsonism is unclear. We aimed to identify the incidence of, and risk factors for, institutionalisation in Parkinson's disease (PD) and atypical parkinsonism (AP).

METHODS

We analysed data from a prospective population-based incidence cohort of parkinsonism in North-East Scotland (the PINE study). 556 newly-diagnosed participants (PD, N = 200; AP, N = 98; controls, N = 258), recruited between 2002 and 2009, were prospectively followed life-long with data collection on place of residence. We determined the incidence and baseline predictors of institutionalisation using Cox regression.

RESULTS

The median follow-up time was 9.3, 4.4, and 10.8 years in PD, AP, and controls respectively. 70 (35 %) PD, 53 (54 %) AP, and 43 (16 %) controls became institutionalised. The incidence rates of institutionalisation in PD, AP, and controls were 5.1, 20.8, and 1.8 per 100 person-years respectively. The median time to institutionalisation was 11.8 years in PD and 3.5 years in AP. Multivariable Cox regression showed that AP (HR versus PD = 3.05 [95 % CI 1.90,4.91]), increasing age (HR for 10-year increase = 1.82 [95 % CI 1.40,2.36]), poorer cognition (HR for MMSE<24 versus MMSE>27 = 2.62 [95 % CI 1.45, 4.73]), more-severe parkinsonian impairment (UPDRS part 3) (HR for 10-point increase = 1.25 [95 % CI 1.05, 1.48]) were independently associated with higher hazards of institutionalisation. Sex, co-morbidity, smoking history, and living alone were not associated with institutionalisation.

CONCLUSION

Institutionalisation is much more frequent in parkinsonism, particularly in AP, than in controls. AP, older age, severe parkinsonian impairment, and poorer cognition were independent baseline predictors of institutionalisation.

External validation of models for predicting cumulative live birth over multiple complete cycles of IVF treatment

STUDY QUESTION

Can two prediction models developed using data from 1999 to 2009 accurately predict the cumulative probability of live birth per woman over multiple complete cycles of IVF in an updated UK cohort?

SUMMARY ANSWER

After being updated, the models were able to estimate individualized chances of cumulative live birth over multiple complete cycles of IVF with greater accuracy.

WHAT IS KNOWN ALREADY

The McLernon models were the first to predict cumulative live birth over multiple complete cycles of IVF. They were converted into an online calculator called OPIS (Outcome Prediction In Subfertility) which has 3000 users per month on average. A previous study externally validated the McLernon models using a Dutch prospective cohort containing data from 2011 to 2014. With changes in IVF practice over time, it is important that the McLernon models are externally validated on a more recent cohort of patients to ensure that predictions remain accurate.

STUDY DESIGN, SIZE, DURATION

A population-based cohort of 91 035 women undergoing IVF in the UK between January 2010 and December 2016 was used for external validation. Data on frozen embryo transfers associated with these complete IVF cycles conducted from 1 January 2017 to 31 December 2017 were also collected.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Data on IVF treatments were obtained from the Human Fertilisation and Embryology Authority (HFEA). The predictive performances of the McLernon models were evaluated in terms of discrimination and calibration. Discrimination was assessed using the c-statistic and calibration was assessed using calibration-in-the-large, calibration slope, and calibration plots. Where any model demonstrated poor calibration in the validation cohort, the models were updated using intercept recalibration, logistic recalibration, or model revision to improve model performance.

MAIN RESULTS AND THE ROLE OF CHANCE

Following exclusions, 91 035 women who underwent 144 734 complete cycles were included. The validation cohort had a similar distribution age profile to women in the development cohort. Live birth rates over all complete cycles of IVF per woman were higher in the validation cohort. After calibration assessment, both models required updating. The coefficients of the pre-treatment model were revised, and the updated model showed reasonable discrimination (c-statistic: 0.67, 95% CI: 0.66 to 0.68). After logistic recalibration, the post-treatment model showed good discrimination (c-statistic: 0.75, 95% CI: 0.74 to 0.76). As an example, in the updated pre-treatment model, a 32-year-old woman with 2 years of primary infertility has a 42% chance of having a live birth in the first complete ICSI cycle and a 77% chance over three complete cycles. In a couple with 2 years of primary male factor infertility where a 30-year-old woman has 15 oocytes collected in the first cycle, a single fresh blastocyst embryo transferred in the first cycle and spare embryos cryopreserved, the estimated chance of live birth provided by the post-treatment model is 46% in the first complete ICSI cycle and 81% over three complete cycles.

LIMITATIONS, REASONS FOR CAUTION

Two predictors from the original models, duration of infertility and previous pregnancy, which were not available in the recent HFEA dataset, were imputed using data from the older cohort used to develop the models. The HFEA dataset does not contain some other potentially important predictors, e.g. BMI, ethnicity, race, smoking and alcohol intake in women, as well as measures of ovarian reserve such as antral follicle count.

WIDER IMPLICATIONS OF THE FINDINGS

Both updated models show improved predictive ability and provide estimates which are more reflective of current practice and patient case mix. The updated OPIS tool can be used by clinicians to help shape couples' expectations by informing them of their individualized chances of live birth over a sequence of multiple complete cycles of IVF.

STUDY FUNDING/COMPETING INTEREST(S)

This study was supported by an Elphinstone scholarship scheme at the University of Aberdeen and Aberdeen Fertility Centre, University of Aberdeen. S.B. has a commitment of research funding from Merck. D.J.M. and M.B.R. declare support for the present manuscript from Elphinstone scholarship scheme at the University of Aberdeen and Assisted Reproduction Unit at Aberdeen Fertility Centre, University of Aberdeen. D.J.M. declares grants received by University of Aberdeen from NHS Grampian, The Meikle Foundation, and Chief Scientist Office in the past 3 years. D.J.M. declares receiving an honorarium for lectures from Merck. D.J.M. is Associate Editor of Human Reproduction Open and Statistical Advisor for Reproductive BioMed Online. S.B. declares royalties from Cambridge University Press for a book. S.B. declares receiving an honorarium for lectures from Merck, Organon, Ferring, Obstetric and Gynaecological Society of Singapore, and Taiwanese Society for Reproductive Medicine. S.B. has received support from Merck, ESHRE, and Ferring for attending meetings as speaker and is on the METAFOR and CAPRE Trials Data Monitoring Committee.

TRIAL REGISTRATION NUMBER

N/A.

ESHRE good practice recommendations on recurrent implantation failure

STUDY QUESTION

How should recurrent implantation failure (RIF) in patients undergoing ART be defined and managed?

SUMMARY ANSWER

This is the first ESHRE good practice recommendations paper providing a definition for RIF together with recommendations on how to investigate causes and contributing factors, and how to improve the chances of a pregnancy.

WHAT IS KNOWN ALREADY

RIF is a challenge in the ART clinic, with a multitude of investigations and interventions offered and applied in clinical practice, often without biological rationale or with unequivocal evidence of benefit.

STUDY DESIGN SIZE DURATION

This document was developed according to a predefined methodology for ESHRE good practice recommendations. Recommendations are supported by data from the literature, if available, and the results of a previously published survey on clinical practice in RIF and the expertise of the working group. A literature search was performed in PubMed and Cochrane focussing on 'recurrent reproductive failure', 'recurrent implantation failure', and 'repeated implantation failure'.

PARTICIPANTS/MATERIALS SETTING METHODS

The ESHRE Working Group on Recurrent Implantation Failure included eight members representing the ESHRE Special Interest Groups for Implantation and Early Pregnancy, Reproductive Endocrinology, and Embryology, with an independent chair and an expert in statistics. The recommendations for clinical practice were formulated based on the expert opinion of the working group, while taking into consideration the published data and results of the survey on uptake in clinical practice. The draft document was then open to ESHRE members for online peer review and was revised in light of the comments received.

MAIN RESULTS AND THE ROLE OF CHANCE

The working group recommends considering RIF as a secondary phenomenon of ART, as it can only be observed in patients undergoing IVF, and that the following description of RIF be adopted: 'RIF describes the scenario in which the transfer of embryos considered to be viable has failed to result in a positive pregnancy test sufficiently often in a specific patient to warrant consideration of further investigations and/or interventions'. It was agreed that the recommended threshold for the cumulative predicted chance of implantation to identify RIF for the purposes of initiating further investigation is 60%. When a couple have not had a successful implantation by a certain number of embryo transfers and the cumulative predicted chance of implantation associated with that number is greater than 60%, then they should be counselled on further investigation and/or treatment options. This term defines clinical RIF for which further actions should be considered. Nineteen recommendations were formulated on investigations when RIF is suspected, and 13 on interventions. Recommendations were colour-coded based on whether the investigations/interventions were recommended (green), to be considered (orange), or not recommended, i.e. not to be offered routinely (red).

LIMITATIONS REASONS FOR CAUTION

While awaiting the results of further studies and trials, the ESHRE Working Group on Recurrent Implantation Failure recommends identifying RIF based on the chance of successful implantation for the individual patient or couple and to restrict investigations and treatments to those supported by a clear rationale and data indicating their likely benefit.

WIDER IMPLICATIONS OF THE FINDINGS

This article provides not only good practice advice but also highlights the investigations and interventions that need further research. This research, when well-conducted, will be key to making progress in the clinical management of RIF.

STUDY FUNDING/COMPETING INTERESTS

The meetings and technical support for this project were funded by ESHRE. N.M. declared consulting fees from ArtPRED (The Netherlands) and Freya Biosciences (Denmark); Honoraria for lectures from Gedeon Richter, Merck, Abbott, and IBSA; being co-founder of Verso Biosense. He is Co-Chief Editor of Reproductive Biomedicine Online (RBMO). D.C. declared being an Associate Editor of Human Reproduction Update, and declared honoraria for lectures from Merck, Organon, IBSA, and Fairtility; support for attending meetings from Cooper Surgical, Fujifilm Irvine Scientific. G.G. declared that he or his institution received financial or non-financial support for research, lectures, workshops, advisory roles, or travelling from Ferring, Merck, Gedeon-Richter, PregLem, Abbott, Vifor, Organon, MSD, Coopersurgical, ObsEVA, and ReprodWissen. He is an Editor of the journals Archives of Obstetrics and Gynecology and Reproductive Biomedicine Online, and Editor in Chief of Journal Gynäkologische Endokrinologie. He is involved in guideline developments and quality control on national and international level. G.L. declared he or his institution received honoraria for lectures from Merck, Ferring, Vianex/Organon, and MSD. He is an Associate Editor of Human Reproduction Update, immediate past Coordinator of Special Interest Group for Reproductive Endocrinology of ESHRE and has been involved in Guideline Development Groups of ESHRE and national fertility authorities. D.J.M. declared being an Associate Editor for Human Reproduction Open and statistical Advisor for Reproductive Biomedicine Online. B.T. declared being shareholder of Reprognostics and she or her institution received financial or non-financial support for research, clinical trials, lectures, workshops, advisory roles or travelling from support for attending meetings from Ferring, MSD, Exeltis, Merck Serono, Bayer, Teva, Theramex and Novartis, Astropharm, Ferring. The other authors had nothing to disclose.

DISCLAIMER

This Good Practice Recommendations (GPR) document represents the views of ESHRE, which are the result of consensus between the relevant ESHRE stakeholders and are based on the scientific evidence available at the time of preparation. ESHRE GPRs should be used for information and educational purposes. They should not be interpreted as setting a standard of care or be deemed inclusive of all proper methods of care, or be exclusive of other methods of care reasonably directed to obtaining the same results. They do not replace the need for application of clinical judgement to each individual presentation, or variations based on locality and facility type. Furthermore, ESHRE GPRs do not constitute or imply the endorsement, or favouring, of any of the included technologies by ESHRE.

Assessing Performance and Clinical Usefulness in Prediction Models With Survival Outcomes: Practical Guidance for Cox Proportional Hazards Models

Risk prediction models need thorough validation to assess their performance. Validation of models for survival outcomes poses challenges due to the censoring of observations and the varying time horizon at which predictions can be made. This article describes measures to evaluate predictions and the potential improvement in decision making from survival models based on Cox proportional hazards regression.

As a motivating case study, the authors consider the prediction of the composite outcome of recurrence or death (the "event") in patients with breast cancer after surgery. They developed a simple Cox regression model with 3 predictors, as in the Nottingham Prognostic Index, in 2982 women (1275 events over 5 years of follow-up) and externally validated this model in 686 women (285 events over 5 years). Improvement in performance was assessed after the addition of progesterone receptor as a prognostic biomarker.

The model predictions can be evaluated across the full range of observed follow-up times or for the event occurring by the end of a fixed time horizon of interest. The authors first discuss recommended statistical measures that evaluate model performance in terms of discrimination, calibration, or overall performance. Further, they evaluate the potential clinical utility of the model to support clinical decision making according to a net benefit measure. They provide SAS and R code to illustrate internal and external validation.

The authors recommend the proposed set of performance measures for transparent reporting of the validity of predictions from survival models.

A comparison of perinatal outcomes following fresh blastocyst or cleavage stage embryo transfer in singletons and twins and between singleton siblings

STUDY QUESTION

Are perinatal outcomes following fresh blastocyst versus fresh cleavage stage embryo transfer (ET) different in singletons, twins, and between singleton siblings?

SUMMARY ANSWER

Singleton babies conceived following fresh blastocyst, versus cleavage stage, ET are less likely to be small for gestational age (SGA) or to have a congenital anomaly (a result confirmed by comparing singleton siblings), while singletons born following fresh blastocyst ET were at a higher risk of being large for gestational age (LGA) than their sibling born following fresh cleavage stage ET.

WHAT IS KNOWN ALREADY

Blastocyst stage transfer is now the preferred strategy in most IVF units. Previous studies have suggested that babies conceived through blastocyst transfer are at increased risk of preterm birth and LGA.

STUDY DESIGN SIZE DURATION

A national population-based retrospective cohort study was performed using linked Human Fertilisation and Embryology Authority (HFEA) data on 130 516 IVF and ICSI livebirths occurring from 103 062 women between 2000 and 2017.

PARTICIPANTS/MATERIALS SETTING METHODS

We included women who had at least one singleton livebirth resulting from IVF/ICSI fresh embryo treatment, using their own eggs and partner's sperm. A linked HFEA dataset was analysed using a multilevel framework, which accommodated repeated IVF cycles resulting in livebirths in the same woman. A population-averaged robust Poisson model was used for binary outcomes and a multinomial logistic regression model was used for categorical outcomes. Unadjusted and adjusted risk ratios (aRRs) (95% CI) were calculated.

MAIN RESULTS AND THE ROLE OF CHANCE

There were 130 516 livebirths in 103 062 women, including 86 630 singletons, 43 886 twin births, and 5384 pairs of singleton siblings. In comparison with fresh cleavage stage ET, fresh blastocyst stage transfer in singletons was associated with a lower risk of low birthweight (aRR = 0.92; 95% CI 0.86, 0.99), lower risk of being SGA (0.83; 0.78, 0.89), and lower risk of congenital anomaly (0.79; 0.71, 0.89). This analysis did not show an increase in risk associated with preterm birth (1.00; 0.94, 1.06), high birthweight (0.99; 0.93, 1.06), LGA (0.99; 0.93, 1.05), and the chance of healthy singleton baby (1.00; 1.00, 1.02). Twins resulting from fresh blastocyst stage ET were at slightly higher risk of preterm birth (1.05; 1.02, 1.10) compared with twins conceived following fresh cleavage stage ET. There was insufficient evidence for an association with the other perinatal outcomes. Singleton siblings born following fresh blastocyst stage ET were at a higher risk of being LGA (1.57; 1.01, 2.46) and at lower risk of having a congenital anomaly (0.52; 0.28, 0.97) compared to their singleton siblings born following cleavage stage ET. There was some evidence of excess risk of preterm birth (1.42; 0.97, 2.23) associated with blastocyst stage transfer. However, we could not confirm an association between blastocyst stage ET and low birthweight (1.35; 0.81, 2.27), high birthweight (1.19; 0.80, 1.77), and the chance of being a healthy baby (0.97; 0.86, 1.09).

LIMITATIONS REASONS FOR CAUTION

This was an observational study where we were unable to adjust for some key confounders, such as maternal smoking status and BMI, which may change from one pregnancy to another and are not recorded in the HFEA dataset.

WIDER IMPLICATIONS OF THE FINDINGS

In the largest study of its kind, our analysis of singleton siblings, corrected for unmeasured, non-time varying maternal factors, confirms the previously reported association between blastocyst transfer and LGA babies, and shows a reduced risk of congenital anomaly following blastocyst transfer. Our sibling analysis did not confirm a decreased risk of low birthweight following blastocyst transfer. Overall, absolute risks are low and there is insufficient evidence to challenge the practice of extended culture of embryos.

STUDY FUNDING/COMPETING INTERESTS

This project is financed by an NHS Grampian Endowment Research Grant, project number 17/052. One of the authors, S.B., was the Editor in Chief of HROpen until 31 December 2022 and would have been in that role when the paper was first submitted. As an invited speaker, S.B. has received travel expenses, accommodation and honoraria from Merck, Organon, and Ferring. A.M. has received travel expenses, accommodation, and honoraria from Merck Serono, Cook Medical, Pharmasure, Gedeon Richter, and Ferring. D.J.M. is currently a HROpen Associate Editor.

TRIAL REGISTRATION NUMBER

N/A.

Perinatal outcomes of 221,709 singleton and twin pregnancies after the use of donor versus partner sperm

OBJECTIVE

To study the association of donor sperm on perinatal outcomes of livebirths conceived via in vitro fertilization (IVF) when compared with partner sperm.

DESIGN

Retrospective cohort study SETTING: National Human Fertilisation and Embryology Authority assisted reproductive technology registry PATIENTS: All live born singletons and twins conceived through IVF with or without intracytoplasmic sperm injection in the United Kingdom between 1991 and 2016 INTERVENTION(S): Donor sperm compared to partner sperm MAIN OUTCOME MEASURE(S): Perinatal outcomes were assessed. The primary outcomes were preterm and very preterm birth; low, very low, high, and very high birthweight; Secondary outcomes were congenital anomaly and health baby. These were assessed for singletons and twins separately.

RESULTS

For singleton livebirths, compared to partner sperm, those conceived with donor sperm were at reduced odds of very preterm (odds ratio [OR], 0.76; 95% confidence interval [CI], 0.63-0.91; adjusted OR [aOR], 0.80; 95% CI, 0.66-0.96), and preterm (OR, 0.90; 95% CI, 0.83-0.98; aOR, 0.93; 95% CI, 0.85-1.01) birth. For birthweight outcomes, donor sperm showed a reduced odds of low (OR, 0.83; 95% CI, 0.76-0.91; aOR, 0.86; 95% CI, 0.78-0.94) and an increased odds of high (OR, 1.15; 95% CI, 1.07-1.23; aOR, 1.09; 95% CI, 1.01-1.17) birthweight. There was no confirmed difference in the odds ratios of very low (OR, 0.88; 95% CI, 0.74-1.06; aOR, 0.94; 95% CI, 0.78-1.13) or very high (OR, 1.21; 95% CI, 1.04-1.40; aOR, 1.15; 95% CI, 0.98-1.34) birthweight. Liveborn twins conceived with donor sperm, compared to partner sperm, were at reduced odds of very low (OR, 0.76; 95% CI, 0.66-0.88; aOR, 0.83; 95% CI, 0.72-0.96) and low (OR, 0.87; 95% CI, 0.81-0.93; aOR, 0.91; 95% CI, 0.85-0.98) birthweight. There was a suggestion of a reduced odds of very preterm (OR, 0.81; 95% CI, 0.70-0.95; aOR, 0.86; 95% CI, 0.74-1.01) and preterm (OR, 0.93; 95% CI, 0.86-1.01; aOR, 0.96; 95% CI, 0.88-1.04) birth. There was considerable uncertainty around the ORs for high (OR, 0.73; 95% CI, 0.31-1.72; aOR, 0.72; 95% CI, 0.29-1.80) and very high (OR, 1.02; 95% CI, 0.39-2.67; aOR, 1.34; 95% CI, 0.50-3.60) birthweight.

CONCLUSION

Although unmeasured confounding remains a possibility, as paternal age, body mass index, and smoking status were unavailable for analysis, women, couples, service providers can be reassured that IVF livebirths conceived with donor sperm have no greater chance of adverse outcomes when compared to partner sperm.

Should we adopt a prognosis-based approach to unexplained infertility?

The treatment of unexplained infertility is a contentious topic that continues to attract a great deal of interest amongst clinicians, patients and policy makers. The inability to identify an underlying pathology makes it difficult to devise effective treatments for this condition. Couples with unexplained infertility can conceive on their own and any proposed intervention needs to offer a better chance of having a baby. Over the years, several prognostic and prediction models based on routinely collected clinical data have been developed, but these are not widely used by clinicians and patients. In this opinion paper, we propose a prognosis-based approach such that a decision to access treatment is based on the estimated chances of natural and treatment-related conception, which, in the same couple, can change over time. This approach avoids treating all couples as a homogeneous group and minimizes unnecessary treatment whilst ensuring access to those who need it early.

Predicting cumulative live birth for couples beginning their second complete cycle of in vitro fertilization treatment

STUDY QUESTION

Can we develop an IVF prediction model to estimate individualized chances of a live birth over multiple complete cycles of IVF in couples embarking on their second complete cycle of treatment?

SUMMARY ANSWER

Yes, our prediction model can estimate individualized chances of cumulative live birth over three additional complete cycles of IVF.

WHAT IS KNOWN ALREADY

After the completion of a first complete cycle of IVF, couples who are unsuccessful may choose to undergo further treatment to have their first child, while those who have had a live birth may decide to have more children. Existing prediction models can estimate the overall chances of success in couples before commencing IVF but are unable to revise these chances on the basis of the couple’s response to a first treatment cycle in terms of the number of eggs retrieved and pregnancy outcome. This makes it difficult for couples to plan and prepare emotionally and financially for the next step in their treatment.

STUDY DESIGN, SIZE, DURATION

For model development, a population-based cohort was used of 49 314 women who started their second cycle of IVF including ICSI in the UK from 1999 to 2008 using their own oocytes and their partners’ sperm. External validation was performed on data from 39 442 women who underwent their second cycle from 2010 to 2016.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Data about all UK IVF treatments were obtained from the Human Fertilisation and Embryology Authority (HFEA) database. Using a discrete time logistic regression model, we predicted the cumulative probability of live birth from the second up to and including the fourth complete cycles of IVF. Inverse probability weighting was used to account for treatment discontinuation. Discrimination was assessed using c-statistic and calibration was assessed using calibration-in-the-large and calibration slope.

MAIN RESULTS AND THE ROLE OF CHANCE

Following exclusions, 49 314 women with 73 053 complete cycles were included. 12 408 (25.2%) had a live birth resulting from their second complete cycle. Cumulatively, 17 394 (35.3%) had a live birth over complete cycles two to four. The model showed moderate discriminative ability (c-statistic: 0.65, 95% CI: 0.64 to 0.65) and evidence of overprediction (calibration-in-the-large = −0.08) and overfitting (calibration slope 0.85, 95% CI: 0.81 to 0.88) in the validation cohort. However, after recalibration the fit was much improved. The recalibrated model identified the following key predictors of live birth: female age (38 versus 32 years—adjusted odds ratio: 0.59, 95% CI: 0.57 to 0.62), number of eggs retrieved in the first complete cycle (12 versus 4 eggs; 1.34, 1.30 to 1.37) and outcome of the first complete cycle (live birth versus no pregnancy; 1.78, 1.66 to 1.91; live birth versus pregnancy loss; 1.29, 1.23 to 1.36). As an example, a 32-year-old with 2 years of non-tubal infertility who had 12 eggs retrieved from her first stimulation and had a live birth during her first complete cycle has a 46% chance of having a further live birth from the second complete cycle of IVF and an 81% chance over a further three cycles.

LIMITATIONS, REASONS FOR CAUTION

The developed model was updated using validation data that was 6 to 12 years old. IVF practice continues to evolve over time, which may affect the accuracy of predictions from the model. We were unable to adjust for some potentially important predictors, e.g. BMI, smoking and alcohol intake in women, as well as measures of ovarian reserve such as antral follicle count. These were not available in the linked HFEA dataset.

WIDER IMPLICATIONS OF THE FINDINGS

By appropriately adjusting for couples who discontinue treatment, our novel prediction model will provide more realistic chances of live birth in couples starting a second complete cycle of IVF. Clinicians can use these predictions to inform discussion with couples who wish to plan ahead. This prediction tool will enable couples to prepare emotionally, financially and logistically for IVF treatment.

STUDY FUNDING/COMPETING INTEREST(S)

This study was supported by an Elphinstone scholarship scheme at the University of Aberdeen and Aberdeen Fertility Centre, University of Aberdeen. The authors have no conflict of interest.

TRIAL REGISTRATION NUMBER

N/A.

Individual participant data meta-analysis of trials comparing frozen versus fresh embryo transfer strategy (INFORM): a protocol

INTRODUCTION

Existing randomised controlled trials (RCTs) comparing a freeze-all embryo transfer strategy and a fresh embryo transfer strategy have shown conflicting results. A freeze-all or a fresh transfer policy may be preferable for some couples undergoing in-vitro fertilisation (IVF), but it is unclear which couples would benefit most from each policy, how and under which protocols. Therefore, we plan a systematic review and individual participant data meta-analysis of RCTs comparing a freeze-all and a fresh transfer policy.

METHODS AND ANALYSIS

We will search electronic databases (Medline, Embase, PsycINFO and CENTRAL) and trial registries (ClinicalTrials.gov and the International Clinical Trials Registry Platform) from their inception to present to identify eligible RCTs. We will also check reference lists of relevant papers. The search was performed on 23 September 2020 and will be updated. We will include RCTs comparing a freeze-all embryo transfer strategy and a fresh embryo transfer strategy in couples undergoing IVF. The primary outcome will be live birth resulting from the first embryo transfer. All outcomes listed in the core outcome set for infertility research will be reported. We will invite the lead investigators of eligible trials to join the Individual participant data meta-analysis of trials comparing frozen versus fresh embryo transfer strategy (INFORM) collaboration and share the deidentified individual participant data (IPD) of their trials. We will harmonise the IPD and perform a two-stage meta-analysis and examine treatment-covariate interactions for important baseline characteristics.

ETHICS AND DISSEMINATION

The study ethics have been granted by the Monash University Human Research Ethics Committee (Project ID: 30391). The findings will be disseminated via presentations at international conferences and publication in peer-reviewed journals.

PROSPERO REGISTRATION NUMBER

CRD42021296566.

Comparison of perinatal outcomes after frozen or fresh embryo transfer: separate analyses of singleton, twin, and sibling live births from a linked national in vitro fertilization registry

OBJECTIVE

To determine whether perinatal outcomes following frozen vs. fresh embryo transfer (ET) differ within singletons, within sets of twins, and between siblings.

DESIGN

Population-based retrospective cohort study.

SETTING

Academic Medical School PATIENT(S): 200,075 live births in 151,561 women who underwent in vitro fertilization with frozen or fresh ET between 1992 and 2017.

MAIN OUTCOME MEASURE(S)

Gestational age at birth, birthweight, congenital anomaly, and healthy baby (≥37 weeks of gestation, birthweight 2,500-4,000 g, no congenital malformations).

RESULT(S)

There were 200,075 live births in 151,561 women including 132,679 singletons, 33,698 sets of twins, and 5,723 pairs of singleton siblings. In singletons, frozen ET was associated with a lower risk of very preterm birth (adjusted relative risk [aRR], 0.83; 95% confidence interval [CI], 0.73, 0.94), preterm birth (aRR, 0.93; 95% CI, 0.88, 0.97), low birthweight (<2,500 g) (aRR, 0.72; 95% CI, 0.68, 0.77), small for gestational age (aRR, 0.66; 95% CI, 0.62, 0.70) and congenital anomaly (aRR, 0.85; 95% CI, 0.78, 0.94), but higher risk of high birthweight (>4,000 g) (aRR, 1.64; 95% CI, 1.58, 1.72) and large for gestational age (aRR, 1.62; 95% CI, 1.55, 1.70) in comparison with fresh ET. In twins, frozen ET was associated with lower risk of very preterm birth (aRR, 0.84; 95% CI, 0.73, 0.97), and low birthweight (aRR, 0.72; 95% CI, 0.68, 0.77), but with a higher chance of a healthy baby (aRR, 1.11; 95% CI, 1.06, 1.16) compared to fresh ET. Singletons conceived following frozen ET had a lower risk of low birthweight (aRR, 0.56; 95% CI, 0.44, 0.74) and being small for gestational age (aRR, 0.54; 95% CI, 0.42, 0.68) than a singleton sibling born after a fresh ET. Frozen ET also was associated with higher risk of high birthweight (aRR, 1.85; 95% CI, 1.54, 2.24) and being large for gestational age (aRR, 1.81; 95% CI, 1.50, 2.20), and also were less likely to be preterm (aRR, 0.81; 95% CI, 0.67, 0.99).

CONCLUSION(S)

Our key finding is that singletons born following a frozen ET are less likely to be small for gestational age than a singleton sibling born following fresh ET but are more likely to be large for gestational age.

Outcomes following Notched Ruthenium-106 Plaque Brachytherapy for Juxtapapillary Choroidal Melanomas

Purpose

This study aimed to evaluate the outcomes of juxtapapillary choroidal melanomas treated with notched ruthenium-106 plaques.

Methods

Juxtapapillary choroidal melanomas (tumours within 2 disc diameters from the optic disc) treated with notched ruthenium-106 plaques (Eckert & Ziegler, BEBIG, Berlin, Germany) at the Scottish Ocular Oncology Service between 2009 and 2015 were retrospectively reviewed. The data were analysed with respect to various outcome measures including recurrence, complications, vision, and eye preservation.

Results

We reviewed 40 patients with a median tumour diameter of 8.4 mm (range 5-17 mm) and a median thickness of 2.5 mm (range 1.1-6 mm). AJCC tumour category distribution was 62.5% T1, 32.5% T2, and 5% T3 tumours. The mean presenting vision was 0.3 logMAR, and the mean final vision was 0.7 logMAR, with 62.5% retaining >1.0 logMAR and 50% retaining >0.3 logMAR at the final follow-up. The median follow-up was 51 months (14-100 months). Over the maximum follow-up time, 13 tumours (32.5%) recurred. Six of these were treated with salvage proton beam therapy (PBT), 2 with transpupillary thermotherapy followed by PBT, and 5 with enucleation. The final eye retention rate was 87.5%. Complications included maculopathy (10%), retinal detachment (5%), neovascular glaucoma (2.5%), and diplopia (2.5%). The observed risk of recurrence over 5 years was 31% (95% CI: 14.1%, 47.8%), and the risk of enucleation over 5 years was 11.5% (95% CI: 0.9%, 21.8%).

Conclusion

Juxtapapillary choroidal melanomas treated with notched ruthenium plaques have a high recurrence rate and frequently need salvage treatment with PBT for tumour control. This has led to a change in our practice toward offering PBT as the first-line treatment for these patients.

Predicting personalized cumulative live birth following in vitro fertilization

OBJECTIVE

To develop in vitro fertilization (IVF) prediction models to estimate the individualized chance of cumulative live birth at two time points: pretreatment (i.e., before starting the first complete cycle of IVF) and posttreatment (i.e., before starting the second complete cycle of IVF in those couples whose first complete cycle was unsuccessful).

DESIGN

Population-based cohort study.

SETTING

National data from the Society for Assisted Reproductive Technology (SART) Clinic Outcome Reporting System.

PATIENT(S)

Based on 88,614 women who commenced IVF treatment using their own eggs and partner's sperm in SART member clinics.

INTERVENTION(S)

Not applicable.

MAIN OUTCOME MEASURE(S)

The pretreatment model estimated the cumulative chance of a live birth over a maximum of three complete cycles of IVF, whereas the posttreatment model did so over the second and third complete cycles. One complete cycle included all fresh and frozen embryo transfers resulting from one episode of ovarian stimulation. We considered the first live birth episode, including singletons and multiple births.

RESULT(S)

Pretreatment predictors included woman's age (35 years vs. 25 years, adjusted odds ratio 0.69, 95% confidence interval 0.66-0.73) and body mass index (35 kg/m² vs. 25 kg/m², adjusted odds ratio 0.75, 95% confidence interval 0.72-0.78). The posttreatment model additionally included the number of eggs from the first complete cycle (15 vs. 9 eggs, adjusted odds ratio 1.10, 95% confidence interval 1.03-1.18). According to the pretreatment model, a nulliparous woman aged 34 years with a body mass index of 23.3 kg/m², male partner infertility, and an antimüllerian hormone level of 3 ng/mL has a 61.7% chance of having a live birth over her first complete cycle of IVF (and a cumulative chance over three complete cycles of 88.8%). If a live birth is not achieved, according to the posttreatment model, her chance of having a live birth over the second complete cycle 1 year later (age 35 years, number of eggs 7) is 42.9%. The C-statistic for all models was between 0.71 and 0.73.

CONCLUSION(S)

The focus of previous IVF prediction models based on US data has been cumulative live birth excluding cycles involving frozen embryos. These novel prediction models provide clinically relevant estimates that could help clinicians and couples plan IVF treatment at different points in time.

Prevalence of PErioperAtive CHildhood obesitY in children undergoing general anaesthesia in the UK: a prospective, multicentre, observational cohort study

BACKGROUND

Childhood obesity has become a serious global healthcare challenge. No UK data currently define its anaesthetic and perioperative implications. We aimed to determine obesity prevalence amongst UK children undergoing general anaesthesia and the incidence of predefined adverse perioperative events, and to compare perioperative obesity rates with National Child Measurement Programme (NCMP) data.

METHODS

During a site-selected consecutive 7-day study period, all children (2-16 yr) undergoing general anaesthesia were included. Anonymised hospital, surgical, and procedural details; demographic data; and adverse perioperative events were collected prospectively by Paediatric Anaesthesia Trainee Research Network (PATRN) collaborators.

RESULTS

For this study, 102 UK hospitals participated and 4232 cases were included in the final analysis; 76% of hospitals did not routinely calculate BMI. In addition, 3030 (71.6%; 95% confidence interval [CI]: 70.2-73.0%) children of healthy weight were compared with 537 (12.7%; 11.7-13.7%) children who were overweight and 478 (11.3%; 10.3-12.2%) children with obesity. Children with obesity (n=71; 14.9%) more commonly underwent (adeno)tonsillectomy than children of healthy weight (n=282; 9.3%; P<0.001; odds ratio [OR] 2.15; 95% CI: 1.58-2.92). Fewer children with obesity (n=365; 77% vs n=2552; 85%) were anaesthetised by consultant anaesthetists (OR 0.62; 95% CI: 0.48-0.79). Mask ventilation was difficult for 3.7% of children with obesity vs 0.6% of children of healthy weight (difference 3.0%; 95% CI: 1.3-4.7%; P<0.001). Comparison with NCMP data demonstrated an over-representation of obesity amongst the paediatric surgical population.

CONCLUSIONS

This large multicentre cohort study suggests a concerning prevalence of children with obesity presenting for anaesthesia. These results should be used to inform optimal provision of care for this population and support perioperative healthcare initiatives to address the burden of childhood obesity.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03994419.

O40 Predictive models of individual risk of elective caesarean section complications: a systematic review

Introduction

With increasing caesarean section (c-section) rates, personalised communication of risk has become paramount. A reliable tool to predict complications would support evidence-based discussion around planned mode of birth.

Method

MEDLINE, Embase, Web of Science, CINAHL, and the Cochrane Library were searched on 27th January with the terms relating to c-section, prognostic models, and complications such as infection. Any study developing and/or validating a prognostic model for maternal complications of c-section in the English language after January 1995 was included. Data extracted encompassed: source of data, participant criteria, outcome to be predicted, candidate predictors, actual predictors, sample size, model development, and model performance. PROBAST (Prediction model Risk Of Bias Assessment Tool) was utilised for risk of bias analysis and applicability concern in the prognostic model studies.

Result

7,752 studies were identified, of which 16 were reviewed producing 3 studies where 3 prognostic models were identified which predicted risk of: blood transfusion, spinal hypotension, and postpartum haemorrhage. From the 3 studies, a total of 29 unique candidate predictors were identified and 15 predictors in the final model. Study authors deemed their studies to be exploratory, exploratory, and confirmatory respectively. None were externally validated and all had a high risk of bias due to analysis technique.

Conclusion

Few models have been developed to predict complications of elective c-section. Existing models predicting blood transfusion, spinal hypotension, and postpartum haemorrhage cannot be recommended for clinical practice. Future research should focus on identifying predictors known before surgery and validating resulting models.

Take-home Message

Systematic review of prediction models for planned C-section complications found none suitable for practice.

Cumulative live birth rates following blastocyst- versus cleavage-stage embryo transfer in the first complete cycle of IVF: a population-based retrospective cohort study

STUDY QUESTION

Is there a difference in the odds of a live birth following blastocyst- versus cleavage-stage embryo transfer in the first complete cycle of IVF?

SUMMARY ANSWER

After adjusting for indication bias, there was not enough evidence to suggest a difference in the odds of live birth following blastocyst- versus cleavage-stage embryo transfer in the first complete cycle of IVF.

WHAT IS KNOWN ALREADY

Replacement of blastocyst-stage embryos has become the dominant practice in IVF but there is uncertainty about whether this technique offers an improved chance of cumulative live birth over all fresh and frozen-thawed embryo transfer attempts associated with a single oocyte retrieval.

STUDY DESIGN, SIZE, DURATION

National population-based retrospective cohort study of 100 610 couples who began their first IVF/ICSI treatment at a licenced UK clinic between 1 January 1999 and 30 July 2010.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Data from the Human Fertilisation and Embryology Authority (HFEA) register on IVF/ICSI treatments using autologous gametes between 1999 and 2010 were analysed. The primary outcome was the live birth rate over the first complete cycle of IVF. Cumulative live birth rates (CLBR) were compared for couples who underwent blastocyst and cleavage transfer, and the adjusted odds of live birth over the first complete cycle were estimated for each group using binary logistic regression. This analysis was repeated within groups of female age, oocytes collected and primary versus secondary infertility. Inverse probability of treatment weighting was used to account for the imbalance in couple characteristics between treatment groups.

MAIN RESULTS AND THE ROLE OF CHANCE

In total, 94 294 (93.7%) couples had a cleavage-stage embryo transfer while 6316 (6.3%) received blastocysts. Over the first complete cycle of IVF/ICSI (incorporating all fresh and frozen-thawed embryo transfers associated with the first oocyte retrieval), the CLBR was increased in those who underwent blastocyst transfer (56.5%) compared to cleavage-stage embryo transfer (34.8%). However, after accounting for the imbalance between exposures, blastocyst transfer did not significantly influence the odds of live birth over the first complete cycle (adjusted odds ratio: 1.03 (0.96, 1.10)).

LIMITATIONS, REASONS FOR CAUTION

Limitations of our study include the retrospective nature of the HFEA dataset and availability of linked data up until 2010. We were unable to adjust for some confounders, such as smoking status, BMI and embryo quality, as these data are not collected at national level by the HFEA. Similarly, there may be unknown couple, treatment or clinic variables that may influence our results. We were unable to assess the intended stage of embryo transfer for women who did not have an embryo replaced, and therefore excluded them from our study. Perinatal outcomes were not included in our analyses and would be a useful basis for future study.

WIDER IMPLICATIONS OF THE FINDINGS

Our findings show that blastocyst-stage embryo transfer may offer an improved chance of live birth in both the first fresh and the first complete cycle of IVF/ICSI compared to cleavage-stage transfer, even in couples with typically poorer prognoses. Where possible, offering blastocyst transfer to a wider range of couples may increase cumulative success rates.

STUDY FUNDING/COMPETING INTEREST(S)

N.J.C. received a Wolfson Foundation Intercalated Degree Research Fellowship funded by the Wolfson Foundation, through the Royal College of Physicians. This work was supported by a Chief Scientist Office Postdoctoral Training Fellowship in Health Services Research and Health of the Public Research (Ref PDF/12/06) held by D.J.M. The views expressed here are those of the authors and not necessarily those of the Chief Scientist Office or the Wolfson Foundation. The funders did not have any role in the study design; in the collection, analysis and interpretation of data; in the writing of the report; nor in the decision to submit the paper for publication. None of the authors has any conflicts of interest to declare.

TRIAL REGISTRATION NUMBER

N/A.

A systematic review of the quality of clinical prediction models in in vitro fertilisation

STUDY QUESTION

What are the best-quality clinical prediction models in IVF (including ICSI) treatment to inform clinicians and their patients of their chance of success?

SUMMARY ANSWER

The review recommends the McLernon post-treatment model for predicting the cumulative chance of live birth over and up to six complete cycles of IVF.

WHAT IS KNOWN ALREADY

Prediction models in IVF have not found widespread use in routine clinical practice. This could be due to their limited predictive accuracy and clinical utility. A previous systematic review of IVF prediction models, published a decade ago and which has never been updated, did not assess the methodological quality of existing models nor provided recommendations for the best-quality models for use in clinical practice.

STUDY DESIGN, SIZE, DURATION

The electronic databases OVID MEDLINE, OVID EMBASE and Cochrane library were searched systematically for primary articles published from 1978 to January 2019 using search terms on the development and/or validation (internal and external) of models in predicting pregnancy or live birth. No language or any other restrictions were applied.

PARTICIPANTS/MATERIALS, SETTING, METHODS

The PRISMA flowchart was used for the inclusion of studies after screening. All studies reporting on the development and/or validation of IVF prediction models were included. Articles reporting on women who had any treatment elements involving donor eggs or sperm and surrogacy were excluded. The CHARMS checklist was used to extract and critically appraise the methodological quality of the included articles. We evaluated models' performance by assessing their c-statistics and plots of calibration in studies and assessed correct reporting by calculating the percentage of the TRIPOD 22 checklist items met in each study.

MAIN RESULTS AND THE ROLE OF CHANCE

We identified 33 publications reporting on 35 prediction models. Seventeen articles had been published since the last systematic review. The quality of models has improved over time with regard to clinical relevance, methodological rigour and utility. The percentage of TRIPOD score for all included studies ranged from 29 to 95%, and the c-statistics of all externally validated studies ranged between 0.55 and 0.77. Most of the models predicted the chance of pregnancy/live birth for a single fresh cycle. Six models aimed to predict the chance of pregnancy/live birth per individual treatment cycle, and three predicted more clinically relevant outcomes such as cumulative pregnancy/live birth. The McLernon (pre- and post-treatment) models predict the cumulative chance of live birth over multiple complete cycles of IVF per woman where a complete cycle includes all fresh and frozen embryo transfers from the same episode of ovarian stimulation. McLernon models were developed using national UK data and had the highest TRIPOD score, and the post-treatment model performed best on external validation.

LIMITATIONS, REASONS FOR CAUTION

To assess the reporting quality of all included studies, we used the TRIPOD checklist, but many of the earlier IVF prediction models were developed and validated before the formal TRIPOD reporting was published in 2015. It should also be noted that two of the authors of this systematic review are authors of the McLernon model article. However, we feel we have conducted our review and made our recommendations using a fair and transparent systematic approach.

WIDER IMPLICATIONS OF THE FINDINGS

This study provides a comprehensive picture of the evolving quality of IVF prediction models. Clinicians should use the most appropriate model to suit their patients' needs. We recommend the McLernon post-treatment model as a counselling tool to inform couples of their predicted chance of success over and up to six complete cycles. However, it requires further external validation to assess applicability in countries with different IVF practices and policies.

STUDY FUNDING/COMPETING INTEREST(S)

The study was funded by the Elphinstone Scholarship Scheme and the Assisted Reproduction Unit, University of Aberdeen. Both D.J.M. and S.B. are authors of the McLernon model article and S.B. is Editor in Chief of Human Reproduction Open. They have completed and submitted the ICMJE forms for Disclosure of potential Conflicts of Interest. The other co-authors have no conflicts of interest to declare.

REGISTRATION NUMBER

N/A.

Prioritizing IVF treatment in the post-COVID 19 era: a predictive modelling study based on UK national data

STUDY QUESTION

Can we use prediction modelling to estimate the impact of coronavirus disease 2019 (COVID 19) related delay in starting IVF or ICSI in different groups of women?

SUMMARY ANSWER

Yes, using a combination of three different models we can predict the impact of delaying access to treatment by 6 and 12 months on the probability of conception leading to live birth in women of different age groups with different categories of infertility.

WHAT IS KNOWN ALREADY

Increased age and duration of infertility can prejudice the chances of success following IVF, but couples with unexplained infertility have a chance of conceiving naturally without treatment whilst waiting for IVF. The worldwide suspension of IVF could lead to worse outcomes in couples awaiting treatment, but it is unclear to what extent this could affect individual couples based on age and cause of infertility.

STUDY DESIGN, SIZE, DURATION

A population based cohort study based on national data from all licensed clinics in the UK obtained from the Human Fertilisation and Embryology Authority Register. Linked data from 9589 women who underwent their first IVF or ICSI treatment in 2017 and consented to the use of their data for research were used to predict livebirth numbers.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Three prediction models were used to estimate the chances of livebirth associated with immediate treatment versus a delay of 6 and 12 months in couples about to embark on IVF or ICSI.

MAIN RESULTS AND THE ROLE OF CHANCE

We estimated that a 6-month delay would reduce livebirths by 0.4%, 2.4%, 5.7%, 9.5% and 11.8% in women aged <30, 30-35, 36-37, 38-39 and 40-42 years, respectively, while corresponding values associated with a delay of 12 months were 0.9%, 4.9%, 11.9%, 18.8% and 22.4%, respectively. In women with known causes of infertility, worst case (best case) predicted chances of livebirth after a delay of 6 months in women aged <30, 30-35, 36-37, 38-39 and 40-42 years varied between 31.6% (35.0%), 29.0% (31.6%), 23.1% (25.2%), 17.2% (19.4%) and 10.3% (12.3%) for tubal infertility and 34.3% (39.2%), 31.6% (35.3%) 25.2%(28.5%) 18.3% (21.3%), and 11.3% (14.1%) for male factor infertility. The corresponding values in those treated immediately were 31.7%, 29.8%, 24.5%, 19.0% and 11.7% for tubal factor and 34.4%, 32.4%, 26.7%, 20.2% and 12.8% in male factor infertility. In women with unexplained infertility the predicted chances of livebirth after a delay of 6 months followed by one complete IVF cycle were 41.0%, 36.6%, 29.4%, 22.4% and 15.1% in women aged <30, 30-35, 36-37, 38-39 and 40-42 years, respectively, compared to 34.9%, 32.5%, 26.9%, 20.7% and 13.2% in similar groups of women treated without any delay. The additional waiting period, which provided more time for spontaneous conception, was predicted to increase the relative number of babies born by 17.5%, 12.6%, 9.1%, 8.4% and 13.8%, in women aged <30, 30-35, 36-37, 38-39 and 40-42 years, respectively. A 12-month delay showed a similar pattern in all subgroups.

LIMITATIONS, REASONS FOR CAUTION

Major sources of uncertainty include the use of prediction models generated in different populations and the need for a number of assumptions. Although the models are validated and the bases for the assumptions are robust, it is impossible to eliminate the possibility of imprecision in our predictions. Therefore, our predicted live birth rates need to be validated in prospective studies to confirm their accuracy.

WIDER IMPLICATIONS OF THE FINDINGS

A delay in starting IVF reduces success rates in all couples. For the first time, we have shown that while this results in fewer babies in older women and those with a known cause of infertility, it has a less detrimental effect on couples with unexplained infertility, some of whom conceive naturally whilst waiting for treatment. Post COVID 19, clinics planning a phased return to normal clinical services should prioritise older women and those with a known cause of infertility.

STUDY FUNDING/COMPETING INTEREST(S)

No external funding was received for this study. B.W.M. is supported by an NHMRC Practitioner Fellowship (GNT1082548) and reports consultancy work for ObsEva, Merck, Merck KGaA, Guerbet and iGenomics. SB is Editor-in-Chief of Human Reproduction Open. None of the other authors declare any conflicts of interest.

Women's perspectives on smartphone apps for fertility tracking and predicting conception: a mixed methods study

BACKGROUND

Women use fertility tracking apps (FTAs) for conception purposes, but user perspectives on FTA use for conception are largely unknown. In collaboration with SPD Clearblue, this study explored: how women trying to conceive use FTAs; women's knowledge of their conception chances; and women's feelings towards a potential natural conception prediction app (NCPA).

METHODS

A mixed methods design was used (online survey and phone interviews). Participants were women 18-40 years old actively trying to conceive.

RESULTS

The survey received 154 responses and 24 interviews were conducted. Thematic analysis of interviews found that women consider several factors before trying to conceive (ex. age, financial and job security, stability of relationship, etc.) and may adopt lifestyle and behaviour changes when trying (ex. increasing exercise, smoking cessation, diet changes, etc.). Survey results indicated that nearly all respondents were aware of FTAs (n = 146, 94.8%), however, several other fertility and conception information sources were also used (ex. health care providers, online sources, family and friends, etc.). Nearly all respondents reported they would use an NCPA (n = 153, 99.4%). During interviews women had positive feelings towards such an app due to it offering new and individualised information, but worried the app could provide upsetting information.

CONCLUSION

This research elaborates on women's uses of and interest in FTAs. Stakeholders should use this research to reflect on current conception experiences and possibilities for improvement through development of an NCPA. Future research should seek opinions from a more diverse sample of women to inform the development of an inclusive NCPA.

Country-level determinants of the severity of the first global wave of the COVID-19 pandemic: an ecological study

OBJECTIVE

We aimed to identify the country-level determinants of the severity of the first wave of the COVID-19 pandemic.

DESIGN

Ecological study of publicly available data. Countries reporting >25 COVID-19 related deaths until 8 June 2020 were included. The outcome was log mean mortality rate from COVID-19, an estimate of the country-level daily increase in reported deaths during the ascending phase of the epidemic curve. Potential determinants assessed were most recently published demographic parameters (population and population density, percentage population living in urban areas, population >65 years, average body mass index and smoking prevalence); economic parameters (gross domestic product per capita); environmental parameters (pollution levels and mean temperature (January-May); comorbidities (prevalence of diabetes, hypertension and cancer); health system parameters (WHO Health Index and hospital beds per 10 000 population); international arrivals; the stringency index, as a measure of country-level response to COVID-19; BCG vaccination coverage; UV radiation exposure; and testing capacity. Multivariable linear regression was used to analyse the data.

PRIMARY OUTCOME

Country-level mean mortality rate: the mean slope of the COVID-19 mortality curve during its ascending phase.

PARTICIPANTS

Thirty-seven countries were included: Algeria, Argentina, Austria, Belgium, Brazil, Canada, Chile, Colombia, the Dominican Republic, Ecuador, Egypt, Finland, France, Germany, Hungary, India, Indonesia, Ireland, Italy, Japan, Mexico, the Netherlands, Peru, the Philippines, Poland, Portugal, Romania, the Russian Federation, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, Ukraine, the UK and the USA.

RESULTS

Of all country-level determinants included in the multivariable model, total number of international arrivals (beta 0.033 (95% CI 0.012 to 0.054)) and BCG vaccination coverage (-0.018 (95% CI -0.034 to -0.002)), were significantly associated with the natural logarithm of the mean death rate.

CONCLUSIONS

International travel was directly associated with the mortality slope and thus potentially the spread of COVID-19. Very early restrictions on international travel should be considered to control COVID-19 outbreaks and prevent related deaths.

Predicting kidney failure risk after acute kidney injury among people receiving nephrology clinic care

Background

Outcomes after acute kidney injury (AKI) are well described, but not for those already under nephrology clinic care. This is where discussions about kidney failure risk are commonplace. We evaluated whether the established kidney failure risk equation (KFRE) should account for previous AKI episodes when used in this setting.

Methods

This observational cohort study included 7491 people referred for nephrology clinic care in British Columbia in 2003–09 followed to 2016. Predictors were previous Kidney Disease: Improving Global Outcomes–based AKI, age, sex, proteinuria, estimated glomerular filtration rate (eGFR) and renal diagnosis. Outcomes were 5-year kidney failure and death. We developed cause-specific Cox models (AKI versus no AKI) for kidney failure and death, stratified by eGFR (</≥30 mL/min/1.73 m²). We also compared prediction models comparing the 5-year KFRE with two refitted models, one with and one without AKI as a predictor.

Results

AKI was associated with increased kidney failure (33.1% versus 26.3%) and death (23.8% versus 16.8%) (P  < 0.001). In Cox models, AKI was independently associated with increased kidney failure in those with an eGFR ≥30 mL/min/1.73 m² {hazard ratio [HR] 1.35 [95% confidence interval (CI) 1.07–1.70]}, no increase in those with eGFR <30 mL/min/1.73 m² ([HR 1.05 95% CI 0.91–1.21)] and increased mortality in both subgroups [respective HRs 1.89 (95% CI 1.56–2.30) and 1.43 (1.16–1.75)]. Incorporating AKI into a refitted kidney failure prediction model did not improve predictions on comparison of receiver operating characteristics (P = 0.16) or decision curve analysis. The original KFRE calibrated poorly in this setting, underpredicting risk.

Conclusions

AKI carries a poorer long-term prognosis among those already under nephrology care. AKI may not alter kidney failure risk predictions, but the use of prediction models without appreciating the full impact of AKI, including increased mortality, would be simplistic. People with kidney diseases have risks beyond simply kidney failure. This complexity and variability of outcomes of individuals is important.

Outcomes of pregnancies using donor sperm compared with those using partner sperm: systematic review and meta-analysis

BACKGROUND

Registry data from the Human Fertilisation and Embryology Authority (HFEA) show an increase of 40% in IUI and 377% in IVF cases using donor sperm between 2006 and 2016.

OBJECTIVE AND RATIONALE

The objective of this study was to establish whether pregnancies conceived using donor sperm are at higher risk of obstetric and perinatal complications than those conceived with partner sperm. As more treatments are being carried out using donor sperm, attention is being given to obstetric and perinatal outcomes, as events in utero and at delivery have implications for long-term health. There is a need to know if there is any difference in the outcomes of pregnancies between those conceived using donor versus partner sperm in order to adequately inform and counsel couples.

SEARCH METHODS

We performed a systematic review and meta-analysis of the outcomes of pregnancies conceived using donor sperm compared with partner sperm. Searches were performed in the OVID MEDLINE, OVID Embase, CENTRAL and CINAHL databases, including all studies published before 11 February 2019. The search strategy involved search terms for pregnancy, infant, donor sperm, heterologous artificial insemination, donor gametes, pregnancy outcomes and perinatal outcomes. Studies were included if they assessed pregnancies conceived by any method using, or infants born from, donor sperm compared with partner sperm and described early pregnancy, obstetric or perinatal outcomes. The Downs and Black tool was used for quality and bias assessment of studies.

OUTCOMES

Of 3391 studies identified from the search, 37 studies were included in the review and 36 were included in the meta-analysis. For pregnancies conceived with donor sperm, versus partner sperm, there was an increase in the relative risk (RR) (95% CI) of combined hypertensive disorders of pregnancy: 1.44 (1.17-1.78), pre-eclampsia: 1.49 (1.05-2.09) and small for gestational age (SGA): 1.42 (1.17-1.79) but a reduced risk of ectopic pregnancy: 0.69 (0.48-0.98). There was no difference in the overall RR (95% CI) of miscarriage: 0.94 (0.80-1.11), gestational diabetes: 1.49 (0.62-3.59), pregnancy-induced hypertension (PIH): 1.24 (0.87-1.76), placental abruption: 0.65 (0.04-10.37), placenta praevia: 1.19 (0.64-2.21), preterm birth: 0.98 (0.88-1.08), low birth weight: 0.97 (0.82-1.15), high birthweight: 1.28 (0.94-1.73): large for gestational age (LGA): 1.01 (0.84-1.22), stillbirth: 1.23 (0.97-1.57), neonatal death: 0.79 (0.36-1.73) and congenital anomaly: 1.15 (0.86-1.53).

WIDER IMPLICATIONS

The majority of our findings are reassuring, except for the mild increased risk of hypertensive disorders of pregnancy and SGA in pregnancies resulting from donor sperm. However, the evidence for this is limited and should be interpreted with caution because the evidence was based on observational studies which varied in their quality and risk of bias. Further high-quality population-based studies reporting obstetric outcomes in detail are required to confirm these findings.

Treatment-independent live birth after in-vitro fertilisation: a retrospective cohort study of 2,133 women

STUDY QUESTION

What is the chance of a treatment-independent live birth following IVF (including ICSI) treatment?

SUMMARY ANSWER

Over 5 years of follow-up, the treatment-independent live birth rate was 17% in unsuccessfully treated women and 15% in those who had a live birth after IVF.

WHAT IS KNOWN ALREADY

A limited number of studies have investigated the chance of treatment-independent conception following completion of IVF, but most of them have been based on surveys with poor response rates and limited sample sizes.

STUDY DESIGN, SIZE, DURATION

This is a population-based, retrospective cohort study of 2133 women who received IVF treatment between 1998 and 2011 at a single regional IVF Unit and were followed for a minimum of 1 year and maximum of 15 years after their last IVF or ICSI treatment cycle.

PARTICIPANTS/MATERIALS, SETTING, METHODS

This study included all women, residing in the north-east of the UK, who attended the Aberdeen Fertility Clinic and received IVF treatment between 1998 and 2011. Clinical and diagnostic information of all women was linked with treatment and pregnancy outcome data. A total of 2133 women were divided into two groups: (i) those who achieved a live birth following successful IVF or ICSI treatment (n = 1060) and (ii) those in whom treatment was unsuccessful i.e. resulted in either no pregnancy or pregnancy loss (n = 1073). The two groups were followed from the date of the last embryo transfer until the first treatment-independent live birth or 31 December 2012, whichever came first. The primary outcome was the treatment-independent live birth rate at 1, 2.5, 5 and 10 years of follow-up. Cox regression was used to determine factors associated with treatment-independent live birth in each group.

MAIN RESULTS AND THE ROLE OF CHANCE

Within 5 years of follow-up, the treatment-independent live birth rate was 17% (95% CI, 15-19%) among women whose IVF or ICSI treatment was unsuccessful and 15% (95% CI, 12-17%) among women whose treatment resulted in live birth. In both groups, shorter duration of infertility, younger female age and IVF as compared to ICSI were associated with a higher chance of achieving treatment-independent live birth. Among unsuccessfully treated women, the chance of post-IVF live birth was reduced in those with tubal factor infertility. Three or more previous IVF or ICSI embryo transfers were associated with a lower chance of treatment-independent live birth among successfully treated women.

LIMITATIONS, REASONS FOR CAUTION

The study was conducted in a single fertility centre, which could compromise the generalizability of the findings. Moreover, data were unavailable on the women's use of contraception or active attempts to get pregnant, both of which could influence treatment-independent live birth rates.

WIDER IMPLICATIONS OF THE FINDINGS

This study provides a better understanding of the long-term prognosis for treatment-independent live birth after completion of IVF or ICSI treatment. The results will inform women of their chances of a treatment-independent live birth following failed or successful treatment and the factors that are associated with it.

STUDY FUNDING/COMPETING INTEREST(S)

This work was funded by a Chief Scientist Office Postdoctoral Training Fellowship in Health Services Research and Health of the Public Research (Ref PDF/12/06). The views expressed here are those of the authors and not necessarily those of the Chief Scientist Office. The authors have no competing interests.

TRIAL REGISTRATION NUMBER

Not applicable.

Age-related natural fertility outcomes in women over 35 years: a systematic review and individual participant data meta-analysis

STUDY QUESTION

What is the rate of natural conception leading to ongoing pregnancy or livebirth over 6–12 months for infertile women of age ≥35 years?

SUMMARY ANSWER

Natural conception rates were still clinically relevant in women aged 35 years and above and were significantly higher in women with unexplained infertility compared to those with other diagnoses.

WHAT IS KNOWN ALREADY

In recent years, increasing numbers of women have attempted to conceive at a later age, resulting in a commensurate increase in the need for ART. However, there is a lack of data on natural fertility outcomes (i.e. no interventions) in women with increasing age.

STUDY DESIGN, SIZE, DURATION

A systematic review with individual participant data (IPD) meta-analysis was carried out. PubMed, MEDLINE, EMBASE, the Cochrane Library, clinicaltrials.gov were searched until 1 July 2018 including search terms ‘fertility service’, ‘waiting list’, ‘treatment-independent’ and ‘spontaneous conception’. Language restrictions were not imposed.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Inclusion criteria were studies (at least partly) reporting on infertile couples with female partner of age ≥35 years who attended fertility services, underwent fertility workup (e.g. history, semen analysis, tubal status and ovulation status) and were exposed to natural conception (e.g. independent of treatment such as IVF, ovulation induction and tubal surgery). Studies that exclusively studied only one infertility diagnosis, without including other women presenting to infertility services for other causes of infertility, were excluded. For studies that met the inclusion criteria, study authors were contacted to provide IPD, after which fertility outcomes for women of age ≥35 years were retrieved. Time to pregnancy or livebirth and the effect of increasing age on fertility outcomes after adjustment for other prognostic factors were analysed. Quality of studies was graded with the Newcastle–Ottawa Scale (non-randomised controlled trials (RCTs)) or the Cochrane Risk of Bias tool (for RCTs).

MAIN RESULTS AND THE ROLE OF CHANCE

We included nine studies (seven cohort studies and two RCTs) (n = 4379 women of at least age 35 years), with the observed composite primary outcome of ongoing pregnancy or livebirth occurring in 429 women (9.8%) over a median follow-up of 5 months (25th to 75th percentile: 2.5–8.5 months). Studies were of moderate to high quality. The probability of natural conception significantly decreased with any diagnosis of infertility, when compared with unexplained infertility. We found non-linear effects of female age and duration of infertility on ongoing pregnancy and tabulated the predicted probabilities for unexplained infertile women aged 35–42 years with either primary or secondary infertility and with a duration of infertility from 1 to 6 years. For a 35-year-old woman with 2 years of primary unexplained infertility, the predicted probability of natural conception leading to ongoing pregnancy or livebirth was 0.15 (95% CI 0.11–0.19) after 6 months and 0.24 (95% CI 0.17–0.30) after 12 months. For a 42-year-old woman, this decreased to 0.08 (95% CI 0.04–0.11) after 6 months and 0.13 (95% CI 0.07–0.18) after 12 months.

LIMITATIONS, REASONS FOR CAUTION

In the studies selected, there were different study designs, recruitment strategies in different centres, protocols and countries and different methods of assessment of infertility. Data were limited for women above the age of 40 years.

WIDER IMPLICATIONS OF THE FINDINGS

Women attending fertility services should be encouraged to pursue natural conception while waiting for treatment to commence and after treatment if it is unsuccessful. Our results may aid in counselling women, and, in particular, for those with unexplained infertility.

STUDY FUNDING/COMPETING INTEREST(S)

S.J.C. received funding from the University of Adelaide Summer Research Scholarship. B.W.M. is supported by a NHMRC Investigator grant (GNT1176437), B.W.M. reports consultancy for ObsEva, Merck, Merck KGaA, iGenomix and Guerbet. B.W.M. reports research support by Merck and Guerbet.

PROSPERO REGISTRATION NUMBER

CRD42018096552.

Predicting the chances of having a baby with or without treatment at different time points in couples with unexplained subfertility

STUDY QUESTION

Can we develop a prediction model that can estimate the chances of conception leading to live birth with and without treatment at different points in time in couples with unexplained subfertility?

SUMMARY ANSWER

Yes, a dynamic model was developed that predicted the probability of conceiving under expectant management and following active treatments (in vitro fertilisation (IVF), intrauterine insemination with ovarian stimulation (IUI + SO), clomiphene) at different points in time since diagnosis.

WHAT IS KNOWN ALREADY

Couples with no identified cause for their subfertility continue to have a realistic chance of conceiving naturally, which makes it difficult for clinicians to decide when to intervene. Previous fertility prediction models have attempted to address this by separately estimating either the chances of natural conception or the chances of conception following certain treatments. These models only make predictions at a single point in time and are therefore inadequate for informing continued decision-making at subsequent consultations.

STUDY DESIGN, SIZE, DURATION

A population-based study of 1316 couples with unexplained subfertility attending a regional clinic between 1998 and 2011.

PARTICIPANTS/MATERIALS, SETTING, METHODS

A dynamic prediction model was developed that estimates the chances of conception within 6 months from the point when a diagnosis of unexplained subfertility was made. These predictions were recomputed each month to provide a dynamic assessment of the individualised chances of conception while taking account of treatment status in each month. Conception must have led to live birth and treatments included clomiphene, IUI + SO, and IVF. Predictions for natural conception were externally validated using a prospective cohort from The Netherlands.

MAIN RESULTS AND THE ROLE OF CHANCE

A total of 554 (42%) couples started fertility treatment within 2 years of their first fertility consultation. The natural conception leading to live birth rate was 0.24 natural conceptions per couple per year. Active treatment had a higher chance of conception compared to those who remained under expectant management. This association ranged from weak with clomiphene to strong with IVF [clomiphene, hazard ratio (HR) = 1.42 (95% confidence interval, 1.05 to 1.91); IUI + SO, HR = 2.90 (2.06 to 4.08); IVF, HR = 5.09 (4.04 to 6.40)]. Female age and duration of subfertility were significant predictors, without clear interaction with the relative effect of treatment.

LIMITATIONS, REASONS FOR CAUTION

We were unable to adjust for other potentially important predictors, e.g. measures of ovarian reserve, which were not available in the linked Grampian dataset that may have made predictions more specific. This study was conducted using single centre data meaning that it may not be generalizable to other centres. However, the model performed as well as previous models in reproductive medicine when externally validated using the Dutch cohort.

WIDER IMPLICATIONS OF THE FINDINGS

For the first time, it is possible to estimate the chances of conception following expectant management and different fertility treatments over time in couples with unexplained subfertility. This information will help inform couples and their clinicians of their likely chances of success, which may help manage expectations, not only at diagnostic workup completion but also throughout their fertility journey.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by a Chief Scientist Office postdoctoral training fellowship in health services research and health of the public research (ref PDF/12/06). B.W.M. is supported by an NHMRC Practitioner Fellowship (GNT1082548). B.W.M. reports consultancy for ObsEva, Merck, and Guerbet. None of the other authors declare any conflicts of interest.

Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal

OBJECTIVE

To review and appraise the validity and usefulness of published and preprint reports of prediction models for diagnosing coronavirus disease 2019 (covid-19) in patients with suspected infection, for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19 infection or being admitted to hospital with the disease.

DESIGN

Living systematic review and critical appraisal by the COVID-PRECISE (Precise Risk Estimation to optimise covid-19 Care for Infected or Suspected patients in diverse sEttings) group.

DATA SOURCES

PubMed and Embase through Ovid, up to 1 July 2020, supplemented with arXiv, medRxiv, and bioRxiv up to 5 May 2020.

STUDY SELECTION

Studies that developed or validated a multivariable covid-19 related prediction model.

DATA EXTRACTION

At least two authors independently extracted data using the CHARMS (critical appraisal and data extraction for systematic reviews of prediction modelling studies) checklist; risk of bias was assessed using PROBAST (prediction model risk of bias assessment tool).

RESULTS

37 421 titles were screened, and 169 studies describing 232 prediction models were included. The review identified seven models for identifying people at risk in the general population; 118 diagnostic models for detecting covid-19 (75 were based on medical imaging, 10 to diagnose disease severity); and 107 prognostic models for predicting mortality risk, progression to severe disease, intensive care unit admission, ventilation, intubation, or length of hospital stay. The most frequent types of predictors included in the covid-19 prediction models are vital signs, age, comorbidities, and image features. Flu-like symptoms are frequently predictive in diagnostic models, while sex, C reactive protein, and lymphocyte counts are frequent prognostic factors. Reported C index estimates from the strongest form of validation available per model ranged from 0.71 to 0.99 in prediction models for the general population, from 0.65 to more than 0.99 in diagnostic models, and from 0.54 to 0.99 in prognostic models. All models were rated at high or unclear risk of bias, mostly because of non-representative selection of control patients, exclusion of patients who had not experienced the event of interest by the end of the study, high risk of model overfitting, and unclear reporting. Many models did not include a description of the target population (n=27, 12%) or care setting (n=75, 32%), and only 11 (5%) were externally validated by a calibration plot. The Jehi diagnostic model and the 4C mortality score were identified as promising models.

CONCLUSION

Prediction models for covid-19 are quickly entering the academic literature to support medical decision making at a time when they are urgently needed. This review indicates that almost all pubished prediction models are poorly reported, and at high risk of bias such that their reported predictive performance is probably optimistic. However, we have identified two (one diagnostic and one prognostic) promising models that should soon be validated in multiple cohorts, preferably through collaborative efforts and data sharing to also allow an investigation of the stability and heterogeneity in their performance across populations and settings. Details on all reviewed models are publicly available at https://www.covprecise.org/. Methodological guidance as provided in this paper should be followed because unreliable predictions could cause more harm than benefit in guiding clinical decisions. Finally, prediction model authors should adhere to the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) reporting guideline.

SYSTEMATIC REVIEW REGISTRATION

Protocol https://osf.io/ehc47/, registration https://osf.io/wy245.

READERS' NOTE

This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This version is update 3 of the original article published on 7 April 2020 (BMJ 2020;369:m1328). Previous updates can be found as data supplements (https://www.bmj.com/content/369/bmj.m1328/related#datasupp). When citing this paper please consider adding the update number and date of access for clarity.

Incidence of paediatric unplanned day-case admissions in the UK and Ireland: a prospective multicentre observational study

BACKGROUND

Failure to discharge home after day-case procedures has a negative impact on patients, families, and hospital finances. There are currently no national paediatric data on the incidence and causes of unplanned admission. We determined the incidence of unplanned admissions after paediatric day-case anaesthesia, and identified risk factors leading to unplanned admission.

METHODS

During a 6 week period (in October and November 2017), all children aged 16 yr or under receiving general anaesthesia without an inpatient bed on arrival were included. Hospital, surgical, and procedural details; anonymised patient characteristic data; and anaesthetic and surgical experience were collected by local Paediatric Anaesthesia Trainee Research Network coordinators. A mixed-effects binary logistic regression model with backward selection was used to determine variables associated with unplanned admission.

RESULTS

Ninety three hospitals across the UK and Ireland participated. There were 25 986 cases, of which 640 were unplanned admissions. The independent risk factors for unplanned admission were ASA-physical status (PS) (ASA-PS 3/4 vs ASA-PS 1; odds ratio [OR]: 2.80 [95% confidence interval {CI}: 2.07-3.77]), duration of procedure (OR: 1.04 [95% CI: 1.03-1.05]), and surgical specialty (vs ear, nose, and throat [highest caseload specialty]: cardiology OR: 1.89 [95% CI: 1.15-3.06], orthopaedics/trauma OR: 0.91 [95% CI: 0.69-1.18], and general surgery OR: 0.59 [95% CI: 0.46-0.77]). The commonest reasons for admission were unexpected surgical complexity, pain, postoperative nausea and vomiting, and late finish.

CONCLUSIONS

Paediatric patient physical status, some types of surgery and duration of procedure were associated with unplanned day-surgery admissions. Unexpected surgical complexity and patient discomfort in recovery were common factors.

A comparison of the beta-geometric model with landmarking for dynamic prediction of time to pregnancy

We conducted a simulation study to compare two methods that have been recently used in clinical literature for the dynamic prediction of time to pregnancy. The first is landmarking, a semi-parametric method where predictions are updated as time progresses using the patient subset still at risk at that time point. The second is the beta-geometric model that updates predictions over time from a parametric model estimated on all data and is specific to applications with a discrete time to event outcome. The beta-geometric model introduces unobserved heterogeneity by modelling the chance of an event per discrete time unit according to a beta distribution. Due to selection of patients with lower chances as time progresses, the predicted probability of an event decreases over time. Both methods were recently used to develop models predicting the chance to conceive naturally. The advantages, disadvantages and accuracy of these two methods are unknown. We simulated time-to-pregnancy data according to different scenarios. We then compared the two methods by the following out-of-sample metrics: bias and root mean squared error in the average prediction, root mean squared error in individual predictions, Brier score and c statistic. We consider different scenarios including data-generating mechanisms for which the models are misspecified. We applied the two methods on a clinical dataset comprising 4999 couples. Finally, we discuss the pros and cons of the two methods based on our results and present recommendations for use of either of the methods in different settings and (effective) sample sizes.

Calibration: the Achilles heel of predictive analytics

BACKGROUND

The assessment of calibration performance of risk prediction models based on regression or more flexible machine learning algorithms receives little attention.

MAIN TEXT

Herein, we argue that this needs to change immediately because poorly calibrated algorithms can be misleading and potentially harmful for clinical decision-making. We summarize how to avoid poor calibration at algorithm development and how to assess calibration at algorithm validation, emphasizing balance between model complexity and the available sample size. At external validation, calibration curves require sufficiently large samples. Algorithm updating should be considered for appropriate support of clinical practice.

CONCLUSION

Efforts are required to avoid poor calibration when developing prediction models, to evaluate calibration when validating models, and to update models when indicated. The ultimate aim is to optimize the utility of predictive analytics for shared decision-making and patient counseling.

Three myths about risk thresholds for prediction models

BACKGROUND

Clinical prediction models are useful in estimating a patient's risk of having a certain disease or experiencing an event in the future based on their current characteristics. Defining an appropriate risk threshold to recommend intervention is a key challenge in bringing a risk prediction model to clinical application; such risk thresholds are often defined in an ad hoc way. This is problematic because tacitly assumed costs of false positive and false negative classifications may not be clinically sensible. For example, when choosing the risk threshold that maximizes the proportion of patients correctly classified, false positives and false negatives are assumed equally costly. Furthermore, small to moderate sample sizes may lead to unstable optimal thresholds, which requires a particularly cautious interpretation of results.

MAIN TEXT

We discuss how three common myths about risk thresholds often lead to inappropriate risk stratification of patients. First, we point out the contexts of counseling and shared decision-making in which a continuous risk estimate is more useful than risk stratification. Second, we argue that threshold selection should reflect the consequences of the decisions made following risk stratification. Third, we emphasize that there is usually no universally optimal threshold but rather that a plausible risk threshold depends on the clinical context. Consequently, we recommend to present results for multiple risk thresholds when developing or validating a prediction model.

CONCLUSION

Bearing in mind these three considerations can avoid inappropriate allocation (and non-allocation) of interventions. Using discriminating and well-calibrated models will generate better clinical outcomes if context-dependent thresholds are used.

Myocardial infarction after acute ischaemic stroke: Incidence, mortality and risk factors

OBJECTIVES

To determine the risk factor profiles associated with post-acute ischaemic stroke (AIS) myocardial infarction (MI) over long-term follow-up.

METHODS

This observational study includes prospectively identified AIS patients (n = 9840) admitted to a UK regional centre between January 2003 and December 2016 (median follow-up: 4.72 years). Predictors of post-stroke MI during follow-up were examined using logistic and Cox regression models for in-hospital and post-discharge events, respectively. MI incidence was determined using a competing risk non-parametric estimator. The influence of post-stroke MI on mortality was examined using Cox regressions.

RESULTS

Mean age (SD) of study participants was 77.3 (12.2) years (48% males). Factors associated with in-hospital MI (OR [95% CI]) were increasing blood glucose (1.80 [1.17-2.77] per 10 mmol/L), total leucocyte count (1.25 [1.01-1.54] per 10 × 10⁹ /L) and CRP (1.05 [1.02-1.08] per 10 mg/L increase). Age (HR [95% CI] = 1.03 [1.01-1.06]), coronary heart disease (1.59 [1.01-2.50]), chronic kidney disease (2.58 [1.44-4.63]) and cancers (1.76 [1.08-2.89]) were associated with incident MI between discharge and one-year follow-up. Age (1.02 [1.00-1.03]), diabetes (1.96 [1.38-2.65]), congestive heart failure (2.07 [1.44-2.99]), coronary heart disease (1.81 [1.31-2.50]), hypertension [1.86 (1.24-2.79)] and peripheral vascular disease (2.25 [1.40-3.63]) were associated with incident MI between 1 and 5 years after discharge. Diabetes (2.01 [1.09-3.72]), hypertension (3.69 [1.44-9.45]) and peripheral vascular disease (2.46 [1.02-5.98]) were associated with incident MI between 5 and 10 years after discharge. Cumulative MI incidence over 10 years was 5.4%. MI during all follow-up periods (discharge-1, 1-5, 5-10 years) was associated with increased risk of death (respective HR [95% CI] = 3.26 [2.51-4.15], 1.96 [1.58-2.42] and 1.92 [1.26-2.93]).

CONCLUSIONS

In conclusion, prognosis is poor in post-stroke MI. We highlight a range of potential areas to focus preventative efforts.

Hospital-Level Variations in Rates of Inpatient Urinary Tract Infections in Stroke

Background and purpose: Urinary tract infection (UTI) is one of the most common complications following stroke and has prognostic significance. UTI rates have been shown to vary between hospitals, but it is unclear whether this is due to case-mix differences or heterogeneities in care among hospitals.

Methods: A prospective multi-center cohort study of acute stroke patients admitted to eight National Health Service (NHS) acute hospital trusts within the Anglia Stroke & Heart Clinical Network between 2009 and 2011 was conducted. We modeled the association between hospital (as a fixed-effect) and inpatient UTI using a multivariable logistic regression model, adjusting for established patient-level risk factors. We graphically and descriptively analyzed heterogeneities in hospital-level characteristics.

Results: We included 2,241 stroke admissions in our analysis; 171 (7.6%) acquired UTI as an inpatient. UTI rates varied significantly between the eight hospitals, ranging from 3 to 11%. The hospital that had the lowest odds of UTI [odds ratio (OR) = 0.50 (95% confidence interval (CI) 0.22–.11)] in adjusted analysis, had the highest number of junior doctors and occupational therapists per five beds of all hospitals. The hospital with the highest adjusted UTI rate [OR=2.69 (1.56–4.64)] was tertiary, the largest and had the highest volume of stroke patients, lowest number of stroke unit beds per 100 admissions, and the highest number of hospital beds per CT scanner.

Conclusions: There is hospital-level variation in post-stroke UTI. Our results suggest the potential influence of service characteristics independently of patient-level factors which may be amenable to be addressed to improve the ultimate stroke outcome.

Is IUI with ovarian stimulation effective in couples with unexplained subfertility?

STUDY QUESTION

Does starting IUI with ovarian stimulation (IUI-OS) within 1.5 years after completion of the fertility workup increase ongoing pregnancy rates compared to expectant management in couples with unexplained subfertility?

SUMMARY ANSWER

IUI-OS is associated with higher chances of ongoing pregnancy compared to expectant management in unexplained subfertile couples, specifically those with poor prognoses of natural conception, i.e. <15% over 6 months or <25% over 1 year.

WHAT IS KNOWN ALREADY

IUI-OS is often the first-line treatment for couples with unexplained subfertility. Two randomized controlled trials compared IUI-OS to expectant management using different thresholds for the prognosis of natural conception as inclusion criteria and found conflicting results. A cohort of couples with unexplained subfertility exposed to expectant management and IUI-OS offers an opportunity to determine the chances of conception after both strategies and to evaluate whether the effect of IUI-OS depends on a couple's prognosis of natural conception.

STUDY DESIGN, SIZE, DURATION

A prospective cohort study on couples with unexplained or mild male subfertility who could start IUI-OS at any point after completion of the fertility workup, recruited in seven Dutch centres between January 2002 and February 2004. Decisions regarding treatment were subject to local protocols, the judgement of the clinician and the wishes of the couple. Couples with bilateral tubal occlusion, anovulation or a total motile sperm count <1 × 106 were excluded. Follow up was censored at the start of IVF, after the last IUI cycle or at last contact and truncated at a maximum of 1.5 years after the fertility workup.

PARTICIPANTS/MATERIALS, SETTING, METHODS

The endpoint was time to conception leading to an ongoing pregnancy. We used the sequential Cox approach comparing in each month ongoing pregnancy rates over the next 6 months of couples who started IUI-OS to couples who did not. We calculated the prognosis of natural conception for individual couples, updated this over consecutive failed cycles and evaluated whether prognosis modified the effect of starting IUI-OS. We corrected for known predictors of conception using inverse probability weighting.

MAIN RESULTS AND THE ROLE OF CHANCE

Data from 1896 couples were available. There were 800 couples whom had at least one IUI-OS cycle within 1.5 years post fertility workup of whom 142 couples conceived (rate: 0.50 per couple per year, median follow up 4 months). The median period between fertility workup completion and starting IUI-OS was 6.5 months. Out of 1096 untreated couples, 386 conceived naturally (rate: 0.31 per couple per year, median follow up 7 months). Starting IUI-OS was associated with a higher chance of ongoing pregnancy by a pooled, overall hazard ratio of 1.96 (95% CI: 1.47-2.62) compared to expectant management. The effect of treatment was modified by a couple's prognosis of achieving natural conception (P = 0.01), with poorer prognoses or additional failed natural cycles being associated with a stronger effect of treatment. The predicted 6-month ongoing pregnancy rate for a couple with a prognosis of 25% at completion of the fertility workup over the next six cycles (~40% over 1 year) was 25% (95% CI: 21-28%) for expectant management and 24% (95% CI: 9-36%) when starting IUI-OS directly. For a couple with a prognosis of 15% (25% over 1 year), these predicted rates were 17% (95% CI: 15-19%) for expectant management and 24% (95% CI: 15-32%) for starting IUI-OS.

LIMITATIONS, REASONS FOR CAUTION

The effect estimates are based on a prospective cohort followed up for 1.5 years after completion of the fertility workup. Although we balanced the known predictors of conception between treated and untreated couples using inverse probability weighting, observational data may be subject to residual confounding. The results need to be confirmed in external datasets.

WIDER IMPLICATIONS OF THE FINDINGS

These results explain the discrepancies between previous trials that compared IUI-OS to expectant management, but further studies are required to establish the threshold at which IUI-OS is (cost-)effective.

STUDY FUNDING/COMPETING INTEREST(S)

This study was facilitated by (Grant 945/12/002) from ZonMW, The Netherlands Organization for Health Research and Development, The Hague, The Netherlands. B.W.M. is supported by a NHMRC Practitioner Fellowship (GNT1082548). B.W.M. reports consultancy for ObsEva, Merck and Guerbet. S.B. reports acting as Editor-in-Chief of HROpen. The other authors have no conflicts of interest.

External validation of a dynamic prediction model for repeated predictions of natural conception over time

STUDY QUESTION

How well does a previously developed dynamic prediction model perform in an external, geographical validation in terms of predicting the chances of natural conception at various points in time?

SUMMARY ANSWER

The dynamic prediction model performs well in an external validation on a Scottish cohort.

WHAT IS KNOWN ALREADY

Prediction models provide information that can aid evidence-based management of unexplained subfertile couples. We developed a dynamic prediction model for natural conception (van Eekelen model) that is able to update predictions of natural conception when couples return to their clinician after a period of unsuccessful expectant management. It is not known how well this model performs in an external population.

STUDY DESIGN, SIZE, DURATION

A record-linked registry study including the long-term follow-up of all couples who were considered unexplained subfertile following a fertility workup at a Scottish fertility clinic between 1998 and 2011. Couples with anovulation, uni/bilateral tubal occlusion, mild/severe endometriosis or impaired semen quality according to World Health Organization criteria were excluded.

PARTICIPANTS/MATERIALS, SETTING, METHODS

The endpoint was time to natural conception, leading to an ongoing pregnancy (defined as reaching a gestational age of at least 12 weeks). Follow-up was censored at the start of treatment, at the change of partner or at the end of study (31 March 2012). The performance of the van Eekelen model was evaluated in terms of calibration and discrimination at various points in time. Additionally, we assessed the clinical utility of the model in terms of the range of the calculated predictions.

MAIN RESULTS AND THE ROLE OF CHANCE

Of a total of 1203 couples with a median follow-up of 1 year and 3 months after the fertility workup, 398 (33%) couples conceived naturally leading to an ongoing pregnancy. Using the dynamic prediction model, the mean probability of natural conception over the course of the first year after the fertility workup was estimated at 25% (observed: 23%). After 0.5, 1 and 1.5 years of expectant management after the completion of the fertility workup, the average probability of conceiving naturally over the next year was estimated at 18% (observed: 15%), 14% (observed: 14%) and 12% (observed: 12%). Calibration plots showed good agreement between predicted chances and the observed fraction of ongoing pregnancy within risk groups. Discrimination was moderate with c statistics similar to those in the internal validation, ranging from 0.60 to 0.64. The range of predicted chances was sufficiently wide to distinguish between couples having a good and poor prognosis with a minimum of zero at all times and a maximum of 55% over the first year after the workup, which decreased to maxima of 43% after 0.5 years, 34% after 1 year and 29% after 1.5 years after the fertility workup.

LIMITATIONS, REASONS FOR CAUTION

The model slightly overestimated the chances of conception by ~2-3% points on group level in the first-year post-fertility workup and after 0.5 years of expectant management, respectively. This is likely attributable to the fact that the exact dates of completion of the fertility workup for couples were missing and had to be estimated.

WIDER IMPLICATIONS OF THE FINDINGS

The van Eekelen model is a valid and robust tool that is ready to use in clinical practice to counsel couples with unexplained subfertility on their individualized chances of natural conception at various points in time, notably when couples return to the clinic after a period of unsuccessful expectant management.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by a Chief Scientist Office postdoctoral training fellowship in health services research and health of the public research (ref PDF/12/06). There are no conflicts of interest.

IVF for unexplained subfertility; whom should we treat?

STUDY QUESTION

Which couples with unexplained subfertility can expect increased chances of ongoing pregnancy with IVF compared to expectant management?

SUMMARY ANSWER

For couples in which the woman is under 40 years of age, IVF is associated with higher chances of conception than expectant management.

WHAT IS KNOWN ALREADY

The clinical indications for IVF have expanded over time from bilateral tubal blockage to include unexplained subfertility in which there is no identifiable barrier to conception. Yet, there is little evidence from randomized controlled trials that IVF is effective in these couples.

STUDY DESIGN, SIZE, DURATION

We compared outcomes in British couples with unexplained subfertility undergoing IVF (n = 40 921) from registry data to couples with the same type of subfertility on expectant management. Those couples on expectant management (defined as no intervention aside from the advice to have intercourse) comprised a prospective nation-wide Dutch cohort (n = 4875) and a retrospective regional cohort from Aberdeen, Scotland (n = 975). We excluded couples who had tried for <1 year to conceive and also those with anovulation, uni- or bilateral tubal occlusion, mild or severe endometriosis or male subfertility i.e. impaired semen quality according to World Health Organization criteria.

PARTICIPANTS/MATERIALS, SETTING, METHODS

We matched couples who received IVF and couples on expectant management based on their characteristics to control for confounding. We fitted a Cox proportional hazards model including patient characteristics, IVF treatment and their interactions to estimate the individualized chance of conception over 1 year—either following IVF or expectant management for all combinations of patient characteristics. The endpoint was conception leading to ongoing pregnancy, defined as a foetus reaching a gestational age of at least 12 weeks.

MAIN RESULTS AND THE ROLE OF CHANCE

The adjusted 1-year chance of conception was 47.9% (95% CI: 45.0–50.9) after IVF and 26.1% (95% CI: 24.2–28.0) after expectant management. The absolute difference in the average adjusted 1-year chances of conception was 21.8% (95%CI: 18.3–25.3) in favour of IVF. The effectiveness of IVF was influenced by female age, duration of subfertility and previous pregnancy. IVF was effective in women under 40 years, but the 1-year chance of an IVF conception declined sharply in women over 34 years. In contrast, in woman over 40 years of age, IVF was less effective, with an absolute difference in chance compared to expectant management of 10% or lower. Regardless of female age, IVF was also less effective in couples with a short period of secondary subfertility (1 year) who had chances of natural conception of 30% or above.

LIMITATIONS, REASONS FOR CAUTION

The 1-year chances of conception were based on three cohorts with different sampling mechanisms. Despite adjustment for the three most important prognostic patient characteristics, namely female age, duration of subfertility and primary or secondary subfertility, our estimates might not be free from residual confounding.

WIDER IMPLICATIONS OF THE FINDINGS

IVF should be used selectively based on judgements on gain compared to continuing expectant management for a given couple. Our results can be used by clinicians to counsel couples with unexplained subfertility, to inform their expectations and facilitate evidence-based, shared decision making.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by Tenovus Scotland [grant G17.04]. Travel for RvE was supported by the Amsterdam Reproduction & Development Research Group [grant V.000296]. SB reports acting as editor-in-chief of HROpen. Other authors have no conflicts.

Individual and Combined Impact of Heart Failure and Atrial Fibrillation on Ischemic Stroke Outcomes

Background and Purpose- We aimed to determine individual and combined effects of atrial fibrillation (AF) and heart failure (HF) on acute ischemic stroke outcomes: in-hospital mortality, length-of-stay, and poststroke disability; long-term mortality and stroke recurrence. Methods- Prospective cohort study of patients with acute ischemic stroke admitted to a UK center with a catchment population of ≈900 000 between 2004 and 2016. Exposure groups were patients with neither AF nor HF (reference group), those with AF but without HF, those with HF but without AF, and those with AF+HF. Logistic and Cox regressions were used to model in-hospital and long-term outcomes, respectively. Results- A total of 10 816 patients with a mean age±SD =77.9±12.1 years, 48% male were included. Only 30 (4.9%) of the patients with HF but not AF were anticoagulated at discharge. Both AF (odds ratio, 1.24 [95% CI, 1.07-1.43]), HF (odds ratio, 1.40 [1.10-1.79]), and their combination (odds ratio, 2.23 [1.83-2.72]) were associated with increased odds of in-hospital mortality. All 3 exposure groups were associated with increased length-of-stay, while only AF predicted increased disability (1.36 [1.12-1.64]). Patients were followed for a median of 5.5 and 3.7 years for mortality and recurrence, respectively. Long-term mortality was associated with AF (hazard ratio, 1.45 [95% CI, 1.33-1.59]), HF (2.07 [1.83-2.36]), and their combination (2.20 [1.96-2.46]). Recurrent stroke was associated with AF 1.50 (1.26-1.78), HF (1.33 [1.01-1.75]), and AF with HF (1.62 [1.28-2.07]). Conclusions- The AF-associated excess risk of stroke recurrence was independent of comorbid HF. HF without AF was also associated with a significant risk of recurrence. Anticoagulation for secondary stroke prevention in patients with HF without AF may require further evaluation in a clinical trial setting.

Predicting the cumulative chance of live birth over multiple complete cycles of in vitro fertilization: an external validation study

STUDY QUESTION

Are the published pre-treatment and post-treatment McLernon models, predicting cumulative live birth rates (LBR) over multiple complete IVF cycles, valid in a different context?

SUMMARY ANSWER

With minor recalibration of the pre-treatment model, both McLernon models accurately predict cumulative LBR in a different geographical context and a more recent time period.

WHAT IS KNOWN ALREADY

Previous IVF prediction models have estimated the chance of a live birth after a single fresh embryo transfer, thereby excluding the important contribution of embryo cryopreservation and subsequent IVF cycles to cumulative LBR. In contrast, the recently developed McLernon models predict the cumulative chance of a live birth over multiple complete IVF cycles at two certain time points: (i) before initiating treatment using baseline characteristics (pre-treatment model) and (ii) after the first IVF cycle adding treatment related information to update predictions (post-treatment model). Before implementation of these models in clinical practice, their predictive performance needs to be validated in an independent cohort.

STUDY DESIGN, SIZE, DURATION

External validation study in an independent prospective cohort of 1515 Dutch women who participated in the OPTIMIST study (NTR2657) and underwent their first IVF treatment between 2011 and 2014. Participants underwent a total of 2881 complete treatment cycles, with a complete cycle defined as all fresh and frozen thawed embryo transfers resulting from one episode of ovarian stimulation. The follow up duration was 18 months after inclusion, and the primary outcome was ongoing pregnancy leading to live birth.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Model performance was externally validated up to three complete treatment cycles, using the linear predictor as described by McLernon et al. to calculate the probability of a live birth. Discrimination was expressed by the c-statistic and calibration was depicted graphically in a calibration plot. In contrast to the original model development cohort, anti-Müllerian hormone (AMH), antral follicle count (AFC) and body weight were available in the OPTIMIST cohort, and evaluated as potential additional predictors for model improvement.

MAIN RESULTS AND THE ROLE OF CHANCE

Applying the McLernon models to the OPTIMIST cohort, the c-statistic of the pre-treatment model was 0.62 (95% CI: 0.59-0.64) and of the post-treatment model 0.71 (95% CI: 0.69-0.74). The calibration plot of the pre-treatment model indicated a slight overestimation of the cumulative LBR. To improve calibration, the pre-treatment model was recalibrated by subtracting 0.35 from the intercept. The post-treatment model calibration plot revealed accurate cumulative LBR predictions. After addition of AMH, AFC and body weight to the McLernon models, the c-statistic of the updated pre-treatment model improved slightly to 0.66 (95% CI: 0.64-0.68), and of the updated post-treatment model remained at the previous level of 0.71 (95% CI: 0.69-0.73). Using the recalibrated pre-treatment model, a woman aged 30 years with 2 years of primary infertility who starts ICSI treatment for male factor infertility has a chance of 40% of a live birth from the first complete cycle, increasing to 72% over three complete cycles. If this woman weighs 70 kg, has an AMH of 1.5 ng/mL and an AFC of 10 measured at the beginning of her treatment, the updated pre-treatment model revises the estimated chance of a live birth to 30% in the first complete cycle and 59% over three complete cycles. If this woman then has five retrieved oocytes, no embryos cryopreserved and a single fresh cleavage stage embryo transfer in her first ICSI cycle, the post-treatment model estimates the chances of a live birth at 28 and 58%, respectively.

LIMITATIONS, REASONS FOR CAUTION

Two randomized controlled trials (RCT) evaluating the effectiveness of gonadotropin dose individualization on basis of the AFC were nested within the OPTIMIST study. The strict dosing regimens, the RCT in- and exclusion criteria and the limited follow up time of 18 months might have influenced model performance in this independent cohort. Also, consistent with the original model development study, external validation was performed using the optimistic assumption that the cumulative LBR in couples who discontinue treatment without a live birth would have been equal to that of those who continue treatment.

WIDER IMPLICATIONS OF THE FINDINGS

After national recalibration to account for geographical differences in IVF treatment, the McLernon prediction models can be introduced as new counselling tools in clinical practice to inform patients and to complement clinical reasoning. These models are the first to offer an objective and personalized estimate of the cumulative probability of a live birth over multiple complete IVF cycles.

STUDY FUNDING/COMPETING INTEREST(S)

No external funds were obtained for this study. M.J.C.E., D.J.M. and S.B. have nothing to disclose. J.A.L, S.C.O, T.C.v.T. and H.LT. received an unrestricted personal grant from Merck BV. B.W.M. is supported by a NHMRC Practitioner Fellowship (GNT1082548) and reports consultancy for ObsEva, Merck and Guerbet. F.J.M.B. receives monetary compensation as a member of the external advisory board for Merck BV (the Netherlands) and Ferring pharmaceutics BV (the Netherlands), for consultancy work for Gedeon Richter (Belgium) and Roche Diagnostics on automated AMH assay development, and for a research cooperation with Ansh Labs (USA).

TRIAL REGISTRATION NUMBER

Not applicable.

A mixed methods exploratory study of women's relationships with and uses of fertility tracking apps

Digital self-tracking is rising, including tracking of menstrual cycles by women using fertility tracking apps (FTAs). However, little is known about users’ experiences of FTAs and their relationships with them. The aim of this study was to explore women’s uses of and relationships with FTAs. This exploratory study employed a mixed methods approach, involving the collection and analysis of an online survey and follow-up interviews. Qualitative analysis of survey and interview data informed hypothesis development. Online surveys yielded 241 responses and 11 follow-up interviews were conducted. Just over a third of women surveyed had experience of using FTAs (89/241) and follow-up interviews were conducted with a proportion of respondents (11/241). Four main motivations to use FTAs were identified: (a) to observe cycle (72%); (b) to conceive (34%); (c) to inform fertility treatment (12%); and (d) as contraception (4%). Analysis of the free-text survey questions and interviews using grounded theory methodology highlighted four themes underpinning women’s relationships with FTAs: (a) medical grounding; (b) health trackers versus non-trackers; (c) design; and (d) social and ethical aspects. Participants who used other health apps were more likely to use FTAs (p = 0.001). Respondents who used contraception were less likely to use FTAs compared with respondents who did not use contraception (p = 0.002). FTA usage also decreases (p = 0.001) as age increases. There was no association between FTA usage and menstrual status (p = 0.259). This research emphasises the differing motivations for FTA use. Future research should further explore the diverse relationships between different subgroups of women and FTAs.

Distinguishing variation in referral accuracy from referral threshold: analysis of a national dataset of referrals for suspected cancer

OBJECTIVES

To distinguish between variation in referral threshold and variation in accurate selection of patients for referral in fast-track referrals for possible cancer. To examine factors associated with threshold and accuracy and model the effects of changing thresholds.

DESIGN

Analysis of national data on cancer referrals from general practices in England over a 5-year period. We developed a new method to estimate specificity of referral to complement existing sensitivity. We used bivariate meta-analysis to produce summary measures and described practices in relation to these.

SETTING

5479 general practitioner (GP) practices with data relating to more than 50 cancer cases diagnosed over the 5 years.

OUTCOMES

Number of practices whose 95% confidence regions for sensitivity and specificity indicated that they were outliers in terms of either referral threshold or decision accuracy.

RESULTS

2019 practices (36.8%) were outliers in relation to referral threshold compared with 1205 practices (22%) in relation to decision accuracy. Practice age profile, cancer incidence and deprivation showed a modest association with decision accuracy but not with thresholds. If all practices shared the referral behaviour of those in the highest quintile of age-standardised referral rate, there would be a 3.3% increase in cancers detected through fast-track pathways at the cost of a 36.9% increase in urgent referrals.

CONCLUSION

This new method permits variation in referral to be described more precisely and quality improvement activities to be targeted. Changing referral thresholds without increasing accuracy will result in modest effects on detection rates and a large increase in demand on diagnostic services.

Brief Report: Predicting Functional Disability: One-Year Results From the Scottish Early Rheumatoid Arthritis Inception Cohort

OBJECTIVE

To identify baseline prognostic indicators of disability at 1 year within a contemporary early inflammatory arthritis inception cohort and then develop a clinically useful tool to support early patient education and decision-making.

METHODS

The Scottish Early Rheumatoid Arthritis (SERA) inception cohort is a multicenter, prospective study of patients with newly presenting RA or undifferentiated arthritis. SERA data were analyzed to determine baseline predictors of disability (defined as a Health Assessment Questionnaire [HAQ] score of ≥1) at 1 year. Clinical and psychosocial baseline exposures were entered into a forward stepwise logistic regression model. The model was externally validated using newly accrued SERA data and subsequently converted into a prediction tool.

RESULTS

Of the 578 participants (64.5% female), 36.7% (n = 212) reported functional disability at 1 year. Functional disability was independently predicted by baseline disability (odds ratio [OR] 2.67 [95% confidence interval (95% CI) 1.98, 3.59]), depression (OR 2.52 [95% CI 1.18, 5.37]), anxiety (OR 2.37 [95% CI 1.33, 4.21]), being in paid employment with absenteeism during the last week (OR 1.19 [95% CI 0.63, 2.23]), not being in paid employment (OR 2.36 [95% CI 1.38, 4.03]), and being overweight (OR 1.61 [95% CI 1.04, 2.50]). External validation (using 113 newly acquired patients) evidenced good discriminative performance with a C statistic of 0.74, and the calibration slope showed no evidence of model overfit (P = 0.31).

CONCLUSION

In the context of modern early inflammatory arthritis treatment paradigms, predictors of disability at 1 year appear to be dominated by psychosocial rather than more traditional clinical measures. This indicates the potential benefit of early access to nonpharmacologic interventions targeting key psychosocial factors, such as mental health and work disability.

Socioeconomic Deprivation as Measured by the Index of Multiple Deprivation and Its Association with Low Sex Hormone Binding Globulin in Women

Objective:

Sex hormone binding globulin (SHBG) is a marker of insulin resistance. Given established links between BMI and socioeconomic disadvantage, we investigated how SHBG varies by index of multiple deprivation (IMD).

Research Design and Methods:

Using laboratory data from a Midlands UK population of mixed ethnicity, we examined the relation between blood concentrations of SHBG and IMD in 1160 women aged between 17 and 71 years. Women with a serum SHBG >250 nmol/L were excluded.

Results:

Mean age was 28.7 (95% confidence interval (CI) 28.2–29.1) years. 48.2% of women were of Caucasian origin, 15.5% of Southern Asian ethnicity and 2.6% were of African or other origin (33.7% were of unknown origin).

SHBG increased with age (Spearman’s ρ=0.195; p<0.001). A higher proportion of women of South Asian origin versus other ethnic groups had an SHBG <30 nmol/L (OR 1.93 (95% CI 1.37–2.71)).

SHBG level was lower in individuals with greater socioeconomic disadvantage as measured by IMD (Spearman's ρ= -0.09; p=0.004 for SHBG versus IMD).

In multivariate logistic regression, IMD women in the quartiles 2–5 (higher socioeconomic disadvantage) were more likely to have an SHBG <30 nmol/L (compatible with significant insulin resistance) versus quartile 1 (odds ratio (OR) 1.71 (95% confidence interval (CI) 1.17–2.53), adjusted for age (OR=0.97 (95% CI 0.95–0.98)) and ethnicity (for South Asian ethnicity OR=2.00 (95% CI 1.42–2.81) versus the rest).

Conclusion:

Lower SHBG levels in women are associated with a higher level of socioeconomic disadvantage. Given the known association between lower SHBG and higher plasma glucose, our findings suggest a link between socioeconomic disadvantage and future risk of type 2 diabetes.

Acute kidney injury as an independent risk factor for unplanned 90-day hospital readmissions

Background

Reducing readmissions is an international priority in healthcare. Acute kidney injury (AKI) is common, serious and also a global concern. This analysis evaluates AKI as a candidate risk factor for unplanned readmissions and determines the reasons for readmissions.

Methods

GLOMMS-II is a large population cohort from one health authority in Scotland, combining hospital episode data and complete serial biochemistry results through data-linkage. 16453 people (2623 with AKI and 13830 without AKI) from GLOMMS-II who survived an index hospital admission in 2003 were used to identify the causes of and predict readmissions. The main outcome was “unplanned readmission or death” within 90 days of discharge. In a secondary analysis, the outcome was limited to readmissions with acute pulmonary oedema. 26 candidate predictors during the index admission included AKI (defined and staged 1–3 using an automated e-alert algorithm), prior AKI episodes, baseline kidney function, index admission circumstances and comorbidities. Prediction models were developed and assessed using multivariable logistic regression (stepwise variable selection), C statistics, bootstrap validation and decision curve analysis.

Results

Three thousand sixty-five (18.6%) patients had the main outcome (2702 readmitted, 363 died without readmission). The outcome was strongly predicted by AKI. Multivariable odds ratios for AKI stage 3; 2 and 1 (vs no AKI) were 2.80 (2.22–3.53); 2.23 (1.85–2.68) and 1.50 (1.33–1.70). Acute pulmonary oedema was the reason for readmission in 26.6% with AKI and eGFR < 60; and 4.0% with no AKI and eGFR ≥ 60. The best stepwise model from all candidate predictors had a C statistic of 0.698 for the main outcome. In a secondary analysis, a model for readmission with acute pulmonary oedema had a C statistic of 0.853. In decision curve analysis, AKI improved clinical utility when added to any model, although the incremental benefit was small when predicting the main outcome.

Conclusions

AKI is a strong, consistent and independent risk factor for unplanned readmissions – particularly readmissions with acute pulmonary oedema. Pre-emptive planning at discharge should be considered to minimise avoidable readmissions in this high risk group.

Electronic supplementary material

The online version of this article (doi:10.1186/s12882-016-0430-4) contains supplementary material, which is available to authorized users.

Predicting the chances of a live birth after one or more complete cycles of in vitro fertilisation: population based study of linked cycle data from 113 873 women

OBJECTIVE

 To develop a prediction model to estimate the chances of a live birth over multiple complete cycles of in vitro fertilisation (IVF) based on a couple's specific characteristics and treatment information.

DESIGN

 Population based cohort study.

SETTING

 All licensed IVF clinics in the UK. National data from the Human Fertilisation and Embryology Authority register.

PARTICIPANTS

 All 253 417 women who started IVF (including intracytoplasmic sperm injection) treatment in the UK from 1999 to 2008 using their own eggs and partner's sperm.

MAIN OUTCOME MEASURE

 Two clinical prediction models were developed to estimate the individualised cumulative chance of a first live birth over a maximum of six complete cycles of IVF-one model using information available before starting treatment and the other based on additional information collected during the first IVF attempt. A complete cycle is defined as all fresh and frozen-thawed embryo transfers arising from one episode of ovarian stimulation.

RESULTS

 After exclusions, 113 873 women with 184 269 complete cycles were included, of whom 33 154 (29.1%) had a live birth after their first complete cycle and 48 925 (43.0%) after six complete cycles. Key pretreatment predictors of live birth were the woman's age (31 v 37 years; adjusted odds ratio 1.66, 95% confidence interval 1.62 to 1.71) and duration of infertility (3 v 6 years; 1.09, 1.08 to 1.10). Post-treatment predictors included number of eggs collected (13 v 5 eggs; 1.29, 1.27 to 1.32), cryopreservation of embryos (1.91, 1.86 to 1.96), the woman's age (1.53, 1.49 to 1.58), and stage of embryos transferred (eg, double blastocyst v double cleavage; 1.79, 1.67 to 1.91). Pretreatment, a 30 year old woman with two years of unexplained primary infertility has a 46% chance of having a live birth from the first complete cycle of IVF and a 79% chance over three complete cycles. If she then has five eggs collected in her first complete cycle followed by a single cleavage stage embryo transfer (with no embryos left for freezing) her chances change to 28% and 56%, respectively.

CONCLUSIONS

 This study provides an individualised estimate of a couple's cumulative chances of having a baby over a complete package of IVF both before treatment and after the first fresh embryo transfer. This novel resource may help couples plan their treatment and prepare emotionally and financially for their IVF journey.

Receiver operating characteristics of the prostate specific antigen test in an unselected population

Objectives: To determine the operating characteristics of prostate-specific antigen (PSA) testing and prostate cancer diagnosis rates in men who have had an initial PSA test in Tayside.

Setting: A retrospective cohort study in Tayside, Scotland from 1992 to 2001.

Methods: In total, 20,623 men were PSA tested during the period 1992–2001. After exclusions, 19,660 were studied. Sensitivity and specificity were calculated for various PSA cut-off values by age group using logistic regression weighted for verification bias (biopsy). Cox regression analysis was performed using six test pattern cohorts.

Results: The annual rate of PSA testing increased from 5.1 per 1000 man years in 1992 to 21.3 per 1000 man years in 2001. The average number of PSA tests per patient increased from 1.11 in 1992 to 2.57 in 2001. Prostate cancer diagnosis and death rates remained constant from 1995 onward. The PSA test had generally inadequate sensitivity and specificity values, so a unique cut-off could not be found for the two older age groups which could be used as a recommendation for biopsy. The commonly used 4 ng/mL cut-off was reasonably sensitive and specific only for the under 60 age group with values of 92.4% and 90.7%, respectively. For prostate cancer diagnosis, the hazard ratios (HR) were reported relative to those with a series of all normal tests. For those with an initially normal PSA test who had at least one abnormal retest result the HR for diagnosis was 10.43 (95% confidence interval [CI] 6.17–17.63). For those with initially abnormal tests with normal retests HR = 1.63 (95% CI 0.65–4.07).

Conclusions: There are no optimal PSA cut-off values for older age groups with which to make a confident referral for biopsy. The increase in PSA testing and the questionable cut-off values of the test calls for the development of an alternative screening strategy.