Prognosis research strategy (PROGRESS) 4: stratified medicine research

Evaluating the STarTBack stratified treatment approach for low back pain: exploring study-level factors potentially explaining differences in results of studies - a literature review

OBJECTIVE

To explore if there are differences in the design and/or conduct of studies that have tested the STarTBack treatment approach for the management of low back pain (LBP), potentially explaining differences in study results.

DESIGN

A literature review.

DATA SOURCES

MEDLINE, CINAHL and EMBASE were searched from inception to 26 July 2023.

ELIGIBILITY CRITERIA

We included studies that included (1) participants with LBP and/or leg pain, (2) randomised controlled trials, controlled clinical trials and interrupted time series designs, (3) used the STarTBack Tool to stratify participants into subgroups and (4) studies provided matched treatments according to participants STarTBack score.

DATA EXTRACTION AND SYNTHESIS

Two review authors independently reviewed the search results and extracted data into the data extraction form. Due to the exploratory nature of this study, results are presented descriptively.

RESULTS

11 studies conducted across 5 countries were included. There were substantial differences in the proportion of participants allocated to the different risk groups; low-risk group (range: 19%-58%), medium risk group (range: 31%-52%) and high-risk group (range: 6%-38%). There were large differences between studies in the implementation of the STarTBack approach. The original STarTBack trial (Hill et al, 2011) had a more explanatory design while in many subsequent studies, the design was more pragmatic/real world. Only the two original studies provided clear evidence that the implementation of the STarTBack tool led to a higher proportion of participants receiving matched treatment. In the other studies, there was no evidence of a difference, or it was unclear. In two studies, a researcher made the decision about which matched treatment participants received based on the STartTback Tool, while in nine studies, this was done by a clinician. Most studies recommended the same matched treatment for each risk group as per the original study except for a small number of studies. Only three studies reported whether the clinician delivering matched treatment followed the recommended treatment as per the tool. There was substantial variability in the training clinicians received.

CONCLUSIONS

Reporting of important study-level factors (eg, differences in study design, whether clinicians were trained and how the tool was used in each study) in how the STarTBack approach was implemented was unclear. There is some suggestion that key factors may include the individual who implemented the STarTBack tool, whether the recommendations of the tool were followed, the amount of training the clinician delivering the matched treatment received, and whether clinicians actually delivered the matched treatment.

A brief step-by-step guide on conducting a systematic review and meta-analysis of prognostic model studies

Prognostic models provide an avenue to predict the risk of individual patients and support shared-decision making. Many prognostic models are published annually, and systematic reviews provide an avenue to collate the existing evidence behind prognostic models to determine whether a model demonstrates adequate predictive performance and is ready for real-world use. This article provides a brief step-by-step guide on how to conduct a systematic review and meta-analysis of prognostic model studies and how these reviews differ from systematic reviews of therapy and diagnosis.

Clinical Risk Assessment and Prediction in Congenital Heart Disease Across the Lifespan: JACC Scientific Statement

Congenital heart disease (CHD) comprises a range of structural anomalies, each with a unique natural history, evolving treatment strategies, and distinct long-term consequences. Current prediction models are challenged by generalizability, limited validation, and questionable application to extended follow-up periods. In this JACC Scientific Statement, we tackle the difficulty of risk measurement across the lifespan. We appraise current and future risk measurement frameworks and describe domains of risk specific to CHD. Risk of adverse outcomes varies with age, sex, genetics, era, socioeconomic status, behavior, and comorbidities as they evolve through the lifespan and across care settings. Emerging technologies and approaches promise to improve risk assessment, but there is also need for large, longitudinal, representative, prospective CHD cohorts with multidimensional data and consensus-driven methodologies to provide insight into time-varying risk. Communication of risk, particularly with patients and their families, poses a separate and equally important challenge, and best practices are reviewed.

Development of a Secure Web-Based Medical Imaging Analysis Platform: The AWESOMME Project

Precision medicine research benefits from machine learning in the creation of robust models adapted to the processing of patient data. This applies both to pathology identification in images, i.e., annotation or segmentation, and to computer-aided diagnostic for classification or prediction. It comes with the strong need to exploit and visualize large volumes of images and associated medical data. The work carried out in this paper follows on from a main case study piloted in a cancer center. It proposes an analysis pipeline for patients with osteosarcoma through segmentation, feature extraction and application of a deep learning model to predict response to treatment. The main aim of the AWESOMME project is to leverage this work and implement the pipeline on an easy-to-access, secure web platform. The proposed WEB application is based on a three-component architecture: a data server, a heavy computation and authentication server and a medical imaging web-framework with a user interface. These existing components have been enhanced to meet the needs of security and traceability for the continuous production of expert data. It innovates by covering all steps of medical imaging processing (visualization and segmentation, feature extraction and aided diagnostic) and enables the test and use of machine learning models. The infrastructure is operational, deployed in internal production and is currently being installed in the hospital environment. The extension of the case study and user feedback enabled us to fine-tune functionalities and proved that AWESOMME is a modular solution capable to analyze medical data and share research algorithms with in-house clinicians.

Competing Benefits and Competing Hazards: The Benefit to Harm Balance in Individual Patients in Rational Therapeutics

For any therapeutic intervention in an individual, there is a balance between the potential benefits and the possible harms. The extent to which the benefits are desirable in a given condition depends on the efficacy of the intervention, the chance of obtaining it and the seriousness and intensity of the condition. The extent to which the harms are undesirable depends on the nature of the hazard that can lead to harm, the chance that the harm will occur and its seriousness and intensity. Rational therapeutic decisions require clinicians to consider competing courses of action, with potential benefits of different desirability and potential harms of different undesirability. They also have a duty to explain to the patient, for the contemplated interventions, both the possible benefits and the potential harms that the patient may consider significant. In an individual patient, it is necessary to consider (a) the probabilities of benefit from both intervention and non-intervention and (b) the probabilities of harm from both intervention and non-intervention. However, there are several potential problems. Here, we consider how failure to distinguish maximum benefits from probable benefits, or hazards (potential harms) from probable harms, and failure to consider all the competing probabilities may lead to imperfect therapeutic decisions. We also briefly discuss methods to assess the benefit to harm balance.

[DemStepCare: Risk-stratified support for primary care-based dementia care - evaluation from general practitioner's view]

OBJECTIVE

The innovation fund project DemStepCare aimed to optimize multi-professional care through case management, risk stratification, and crisis outpatient clinic. Here, the evaluation results from the perspective of the general practitioners are presented.

METHODS

A quantitative survey was carried out at three time points regarding acceptance, benefit assessment and sensitivity to dementia of the general practitioners. In addition, qualitative interviews were conducted.

RESULTS

Satisfaction with the overall project was high. Added value and relief factors were perceived and more effective and stable dementia care was achieved through collaboration with case management. Physicians reported increased subjective competence in diagnostics and disease management.

CONCLUSIONS

The results confirm the benefit and effectiveness of DemStepCare from general practitioner's perspective.

Identification of heart failure hospitalization from NHS Digital data: comparison with expert adjudication

AIMS

Population-wide, person-level, linked electronic health record data are increasingly used to estimate epidemiology, guide resource allocation, and identify events in clinical trials. The accuracy of data from NHS Digital (now part of NHS England) for identifying hospitalization for heart failure (HHF), a key HF standard, is not clear. This study aimed to evaluate the accuracy of NHS Digital data for identifying HHF.

METHODS AND RESULTS

Patients experiencing at least one HHF, as determined by NHS Digital data, and age- and sex-matched patients not experiencing HHF, were identified from a prospective cohort study and underwent expert adjudication. Three code sets commonly used to identify HHF were applied to the data and compared with expert adjudication (I50: International Classification of Diseases-10 codes beginning I50; OIS: Clinical Commissioning Groups Outcomes Indicator Set; and NICOR: National Institute for Cardiovascular Outcomes Research, used as the basis for the National Heart Failure Audit in England and Wales). Five hundred four patients underwent expert adjudication, of which 10 (2%) were adjudicated to have experienced HHF. Specificity was high across all three code sets in the first diagnosis position {I50: 96.2% [95% confidence interval (CI) 94.1-97.7%]; NICOR: 93.3% [CI 90.8-95.4%]; OIS: 95.6% [CI 93.3-97.2%]} but decreased substantially as the number of diagnosis positions expanded. Sensitivity [40.0% (CI 12.2-73.8%)] and positive predictive value (PPV) [highest with I50: 17.4% (CI 8.1-33.6%)] were low in the first diagnosis position for all coding sets. PPV was higher for the National Heart Failure Audit criteria, albeit modestly [36.4% (CI 16.6-62.2%)].

CONCLUSIONS

NHS Digital data were not able to accurately identify HHF and should not be used in isolation for this purpose.

Prospective study validating a multidimensional treatment decision score predicting the 24-month outcome in untreated patients with clinically isolated syndrome and early relapsing-remitting multiple sclerosis, the ProVal-MS study

INTRODUCTION

In Multiple Sclerosis (MS), patients´ characteristics and (bio)markers that reliably predict the individual disease prognosis at disease onset are lacking. Cohort studies allow a close follow-up of MS histories and a thorough phenotyping of patients. Therefore, a multicenter cohort study was initiated to implement a wide spectrum of data and (bio)markers in newly diagnosed patients.

METHODS

ProVal-MS (Prospective study to validate a multidimensional decision score that predicts treatment outcome at 24 months in untreated patients with clinically isolated syndrome or early Relapsing-Remitting-MS) is a prospective cohort study in patients with clinically isolated syndrome (CIS) or Relapsing-Remitting (RR)-MS (McDonald 2017 criteria), diagnosed within the last two years, conducted at five academic centers in Southern Germany. The collection of clinical, laboratory, imaging, and paraclinical data as well as biosamples is harmonized across centers. The primary goal is to validate (discrimination and calibration) the previously published DIFUTURE MS-Treatment Decision score (MS-TDS). The score supports clinical decision-making regarding the options of early (within 6 months after study baseline) platform medication (Interferon beta, glatiramer acetate, dimethyl/diroximel fumarate, teriflunomide), or no immediate treatment (> 6 months after baseline) of patients with early RR-MS and CIS by predicting the probability of new or enlarging lesions in cerebral magnetic resonance images (MRIs) between 6 and 24 months. Further objectives are refining the MS-TDS score and providing data to identify new markers reflecting disease course and severity. The project also provides a technical evaluation of the ProVal-MS cohort within the IT-infrastructure of the DIFUTURE consortium (Data Integration for Future Medicine) and assesses the efficacy of the data sharing techniques developed.

PERSPECTIVE

Clinical cohorts provide the infrastructure to discover and to validate relevant disease-specific findings. A successful validation of the MS-TDS will add a new clinical decision tool to the armamentarium of practicing MS neurologists from which newly diagnosed MS patients may take advantage. Trial registration ProVal-MS has been registered in the German Clinical Trials Register, `Deutsches Register Klinischer Studien` (DRKS)-ID: DRKS00014034, date of registration: 21 December 2018; https://drks.de/search/en/trial/DRKS00014034.

Blood levels of glial fibrillary acidic protein for predicting clinical progression to Alzheimer's disease in adults without dementia: a systematic review and meta-analysis protocol

BACKGROUND

There is urgent clinical need to identify reliable prognostic biomarkers that predict the progression of dementia symptoms in individuals with early-phase Alzheimer's disease (AD) especially given the research on and predicted applications of amyloid-beta (Aβ)-directed immunotherapies to remove Aβ from the brain. Cross-sectional studies have reported higher levels of cerebrospinal fluid and blood glial fibrillary acidic protein (GFAP) in individuals with AD-associated dementia than in cognitively unimpaired individuals. Further, recent longitudinal studies have assessed the prognostic potential of baseline blood GFAP levels as a predictor of future cognitive decline in cognitively unimpaired individuals and in those with mild cognitive impairment (MCI) due to AD. In this systematic review and meta-analysis, we propose analyzing longitudinal studies on blood GFAP levels to predict future cognitive decline.

METHODS

This study will include prospective and retrospective cohort studies that assessed blood GFAP levels as a prognostic factor and any prediction models that incorporated blood GFAP levels in cognitively unimpaired individuals or those with MCI. The primary outcome will be conversion to MCI or AD in cognitively unimpaired individuals or conversion to AD in individuals with MCI. Articles from PubMed and Embase will be extracted up to December 31, 2023, without language restrictions. An independent dual screening of abstracts and potentially eligible full-text reports will be conducted. Data will be dual-extracted using the CHeck list for critical appraisal, data extraction for systematic Reviews of prediction Modeling Studies (CHARMS)-prognostic factor, and CHARMS checklists, and we will dual-rate the risk of bias and applicability using the Quality In Prognosis Studies and Prediction Study Risk-of-Bias Assessment tools. We will qualitatively synthesize the study data, participants, index biomarkers, predictive model characteristics, and clinical outcomes. If appropriate, random-effects meta-analyses will be performed to obtain summary estimates. Finally, we will assess the body of evidence using the Grading of Recommendation, Assessment, Development, and Evaluation Approach.

DISCUSSION

This systematic review and meta-analysis will comprehensively evaluate and synthesize existing evidence on blood GFAP levels for prognosticating presymptomatic individuals and those with MCI to help advance risk-stratified treatment strategies for early-phase AD.

TRIAL REGISTRATION

PROSPERO CRD42023481200.

Prognostic factors associated with risk of stroke following blunt cerebrovascular injury: A systematic review and meta-analysis

BACKGROUND & OBJECTIVES

Blunt cerebrovascular injury (BCVI) includes carotid and/or vertebral artery injury following trauma, and conveys an increased stroke risk. We conducted a systematic review and meta-analysis to provide a comprehensive summary of prognostic factors associated with risk of stroke following BCVI.

METHODS

We searched the EMBASE and MEDLINE databases from January 1946 to June 2023. We identified studies reporting associations between patient or injury factors and risk of stroke following BCVI. We performed meta-analyses of odds ratios (ORs) using the random effects method and assessed individual study risk of bias using the QUIPS tool. We separately pooled adjusted and unadjusted analyses, highlighting the estimate with the higher certainty.

RESULTS

We included 26 cohort studies, involving 20,458 patients with blunt trauma. The overall incidence of stroke following BCVI was 7.7 %. Studies were predominantly retrospective cohorts from North America and included both carotid and vertebral artery injuries. Diagnosis of BCVI was most commonly confirmed with CT angiography. We demonstrated with moderate to high certainty that factors associated with increased risk of stroke included carotid artery injury (as compared to vertebral artery injury, unadjusted odds ratio [uOR] 1.94, 95 % CI 1.62 to 2.32), Grade III Injury (as compared to grade I or II) (uOR 2.45, 95 % CI 1.88 to 3.20), Grade IV injury (uOR 3.09, 95 % CI 2.20 to 4.35), polyarterial injury (uOR 3.11 (95 % CI 2.05 to 4.72), occurrence of hypotension at the time of hospital admission (adjusted odds ratio [aOR] 1.32, 95 % CI 0.87 to 2.03) and higher total body injury severity (aOR 5.91, 95 % CI 1.90 to 18.39).

CONCLUSION

Local anatomical injury pattern, overall burden of injury and flow dynamics contribute to BCVI-related stroke risk. These findings provide the foundational evidence base for risk stratification to support clinical decision making and further research.

Association between Controlling Nutritional Status (CONUT) Score and Body Composition, Inflammation and Frailty in Hospitalized Elderly Patients

The Controlling Nutritional Status (CONUT) score has demonstrated its ability to identify patients with poor nutritional status and predict various clinical outcomes. Our objective was to assess the association between the CONUT score, inflammatory status, and body composition, as well as its ability to identify patients at risk of frailty in hospitalized elderly patients.

METHODS

a total of 361 patients were retrospectively recruited and divided into three groups based on the CONUT score.

RESULTS

patients with a score ≥5 exhibited significantly higher levels of inflammatory markers, such as erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), Neutrophil/Lymphocytes ratio (NLR), main platelet volume (MPV), and ferritin, compared to those with a lower score. Furthermore, these patients showed unfavorable changes in body composition, including a lower percentage of skeletal muscle mass (MM) and fat-free mass (FFM) and a higher percentage of fatty mass (FM). A positive correlation was found between the CONUT score and inflammatory markers, Geriatric Depression Scale Short Form (GDS-SF), and FM. Conversely, the Mini Nutritional Assessment (MNA), Mini-Mental Status Examination, activity daily living (ADL), instrumental activity daily living (IADL), Barthel index, FFM, and MM showed a negative correlation. Frailty was highly prevalent among patients with a higher CONUT score. The receiver operating characteristic (ROC) curve demonstrated high accuracy in identifying frail patients (sensitivity).

CONCLUSIONS

a high CONUT score is associated with a pro-inflammatory status as well as with unfavorable body composition. Additionally, it is a good tool to identify frailty among hospitalized elderly patients.

Glycemic Variability As a Prognostic Factor for Mortality in Patients With Critical Illness: A Systematic Review and Meta-Analysis

OBJECTIVES

To perform a systematic review and meta-analysis to evaluate the association of various measures of glycemic variability, including time-domain and complexity-domain, with short-term mortality in patients with critical illness.

DATA SOURCES

We searched Embase Classic +, MEDLINE, and the Cochrane Database of Systematic Reviews from inception to November 3, 2023.

STUDY SELECTION

We included English language studies that assessed metrics of glycemic variation or complexity and short-term mortality in patients admitted to the ICU.

DATA EXTRACTION

Two authors performed independent data abstraction and risk-of-bias assessments. We used a random-effects model to pool binary and continuous data and summarized estimates of effect using odds ratios and mean difference. We used the Quality in Prognosis Studies tool to assess risk of bias and the Grading of Recommendations, Assessment, Development and Evaluations to assess certainty of pooled estimates.

DATA SYNTHESIS

We included 41 studies (n = 162,259). We demonstrate that increased sd, coefficient of variance, glycemic lability index, and decreased time in range are probably associated with increased mortality in critically ill patients (moderate certainty) and that increased mean absolute glucose, mean amplitude of glycemic excursion, and detrended fluctuation analysis may be associated with increased mortality (low certainty).

CONCLUSIONS

We found a consistent association between increased measures of glycemic variability and higher short-term mortality in patient with critical illness. Further research should focus on standardized measurements of glycemic variation and complexity, along with their utility as therapeutic targets and prognostic markers.

Establishing the prognostic profile of patients with work-related musculoskeletal disorders: Development and acceptability of the MAPS questionnaire

PURPOSE

Work-related musculoskeletal disorders (WRMD) are the most common causes of disability worldwide and are associated with significant use of healthcare. One way to optimize the clinical outcomes of injured workers receiving rehabilitation is to identify and address individual prognostic factors (PF), which can facilitate the personalization of the treatment plan. As there is no pragmatic and systematic method to collect prognostic-related data, the purpose of the study was to develop and assess the acceptability of a set of questionnaires to establish the "prognostic profile" of workers with WRMD.

METHODS

We utilized a multistep process to inform the acceptability of the Measures Associated to PrognoStic (MAPS) questionnaire. During STEP-1, a preliminary version of the was developed through a literature search followed by an expert consensus including a patient-advisor. During STEP-2, future users (rehabilitation professionals, healthcare administrators and compensation officers) were consulted through an online survey and were asked to rate the relevance of each content item; items that obtained ≥80% of "totally agree" answers were included. They were also asked to prioritize PF according to their usefulness for clinical decision-making, as well as perceived efficacy to enhance the treatment plan.

RESULTS

The questionnaire was developed with three categories: the outcome predicted, the unique PF, and prognostic tools. Personal PF (i.e.: coping strategies, fear-avoidance beliefs), pain related PF (i.e.: pain intensity/severity, duration of pain), and work-related PF (i.e.: work physical demands, work accommodations) were identified to be totally relevant and included in the questionnaire. 84% of the respondents agreed that their patients could complete the MAPS questionnaire in their clinical setting, while 75% totally agreed that the questionnaire is useful to personalize rehabilitation interventions.

CONCLUSION

The MAPS questionnaire was deemed acceptable to establish the "prognostic profile" of injured workers and help the clinicians in the treatment decision-making process.

Prognostic models for clinical outcomes in patients with venous leg ulcers: A systematic review

OBJECTIVE

The purpose of this review was to identify prognostic models for clinical application in patients with venous leg ulcers (VLUs).

METHODS

Literature searches were conducted in Embase, Medline, Cochrane, and CINAHL databases from inception to December 22, 2021. Eligible studies reported prognostic models aimed at developing, validating, and adjusting multivariable prognostic models that include multiple prognostic factors combined, and that predicted clinical outcomes. Methodological quality was assessed using the CHARMS checklist and PROBAST short form questionnaire.

RESULTS

Thirteen studies were identified, of which three were validation studies of previously published models, four reported derivation and validation of models, and the remainder reported derivation models only. There was substantial heterogeneity in the model characteristics, including 11 studies focused on wound healing outcomes reporting 91 different predictors. Three studies shared similar predicted outcomes, follow-up timepoint and used a Cox proportional hazards model. However, these models reported different predictor selection methods and different predictors and it was therefore not feasible to summarize performance, such as discriminative ability.

CONCLUSIONS

There are no standout risk prediction models in the literature with promising clinical application for patients with VLUs. Future research should focus on developing and validating high-performing models in wider VLU populations.

Prognostic factors associated with changes in knee pain outcomes, identified from initial primary care consultation data. A systematic literature review

BACKGROUND

Data collected during initial primary care consultations could be a source of baseline prognostic factors associated with changes in outcome measures for patients with knee pain.

OBJECTIVES

To identify, appraise and synthesize studies investigating prognostic factors associated with changes in outcome for people presenting with knee pain in primary care.

METHODS

EMBASE, CINAHL, AMED, MEDLINE and MedRxiv electronic databases were searched from inception to March 2021 and repeated in August 2022. Prospective cohort studies of adult participants with musculoskeletal knee pain assessing the association between putative prognostic factors and outcomes in primary care were included. The Quality in Prognostic Studies (QUIPS) tool and The Modified Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework, specific to prognostic reviews were used to appraise and synthesize the evidence respectively.

RESULTS

Eight studies were included. Eight knee pain outcomes were identified. Methodological and statistical heterogeneity resulted in qualitative analysis. All evidence was judged to be of low to very low quality. Bilateral knee pain (multivariable odds ratio (OR) range 2.60-2.74; 95%CI range 0.90-8.10, p value = 0.09) and a lower educational level (multivariable (OR) range 1.74-5.6; 95%CI range 1.16-16.20, p value = <0.001) were synonymously associated with persisting knee pain at 12-month follow up. A total of 37 univariable and 63 multivariable prognostic factors were statistically associated with outcomes (p ≤ 0.05) in single studies.

CONCLUSIONS

There was consensus from two independent studies that bilateral knee pain and lower educational level were associated with persistent knee pain. Many baseline factors were associated with outcome in individual studies but not consistently between studies. The current understanding, accuracy and reliability of the prognostic value of initial primary care consultation data for knee pain outcomes are limited. This review will provide an essential guide for candidate variable selection in future primary care prognostic confirmatory studies.Key messagesBilateral knee pain and lower educational level were associated with persistent knee pain.Many baseline factors were associated with outcome in individual studies but not consistently between studies.The current understanding, accuracy and reliability of the prognostic value of initial primary care consultation data for knee pain outcomes are limited.

The design of studies testing the effectiveness of risk-guided care has many challenges: a scoping review addressing key considerations

OBJECTIVES

Studies evaluating the effectiveness of care based on patients' risk of adverse outcomes (risk-guided care) use a variety of study designs. In this scoping review, using examples, we review characteristics of relevant studies and present key design features to optimize the trustworthiness of results.

STUDY DESIGN AND SETTING

We searched five online databases for studies evaluating the effect of risk-guided care among adults on clinical outcomes, process, or cost. Pairs of reviewers independently performed screening and data abstraction. We descriptively summarized the study design and characteristics.

RESULTS

Among 14,561 hits, we identified 116 eligible studies. Study designs included randomized controlled trials (RCTs), post hoc analysis of RCTs, and retrospective or prospective cohort studies. Challenges and sources of bias in the design included limited performance of predictive models, contamination, inadequacy to address the credibility of subgroup effects, absence of differences in care across risk strata, reporting only process measures as opposed to clinical outcomes, and failure to report benefits and harms.

CONCLUSION

To assess the benefit of risk-guided care, RCTs provide the most trustworthy evidence. Observational studies offer an alternative but are hampered by confounding and other limitations. Reaching valid conclusions when testing risk-guided care requires addressing the challenges identified in our review.

Prognostic factors associated with favourable functional outcome among adult patients requiring extracorporeal cardiopulmonary resuscitation for out-of-hospital cardiac arrest: A systematic review and meta-analysis

BACKGROUND

Extracorporeal cardiopulmonary resuscitation (ECPR), has demonstrated promise in the management of refractory out-of-hospital cardiac arrest (OHCA). However, evidence from observational studies and clinical trials are conflicting and the factors influencing outcome have not been well established.

METHODS

We conducted a systematic review and meta-analysis summarizing the association between pre-ECPR prognostic factors and likelihood of good functional outcome among adult patients requiring ECPR for OHCA. We searched Medline and Embase databases from inception to February 28, 2023 and screened studies with two independent reviewers. We performed meta-analyses of unadjusted and adjusted odds ratios, adjusted hazard ratios and mean differences separately. We assessed risk of bias using the QUIPS tool and certainty of evidence using the GRADE approach.

FINDINGS

We included 29 observational and randomized studies involving 7,397 patients. Factors with moderate or high certainty of association with increased survival with favourable functional outcome include pre-arrest patient factors, such as younger age (odds ratio (OR) 2.13, 95% CI 1.52 to 2.99) and female sex (OR 1.37, 95% CI 1.11 to 1.70), as well as intra-arrest factors, such as shockable rhythm (OR 2.79, 95% CI 2.04 to 3.80), witnessed arrest (OR 1.68 (95% CI 1.16 to 2.42), bystander CPR (OR 1.55, 95% CI 1.19 to 2.01), return of spontaneous circulation (OR 2.81, 95% CI 2.19 to 3.61) and shorter time to cannulation (OR 1.14, 95% CI 1.17 to 1.69 per 10 minutes).

INTERPRETATION

The findings of this review confirm several clinical concepts wellestablished in the cardiac arrest literature and their applicability to the patient for whom ECPR is considered - that is, the impact of pre-existing patient factors, the benefit of timely and effective CPR, as well as the prognostic importance of minimizing low-flow time. We advocate for the thoughtful consideration of these prognostic factors as part of a risk stratification framework when evaluating a patient's potential candidacy for ECPR.

Progress of the application clinical prediction model in polycystic ovary syndrome

Clinical prediction models play an important role in the field of medicine. These can help predict the probability of an individual suffering from disease, complications, and treatment outcomes by applying specific methodologies. Polycystic ovary syndrome (PCOS) is a common disease with a high incidence rate, huge heterogeneity, short- and long-term complications, and complex treatments. In this systematic review study, we reviewed the progress of clinical prediction models in PCOS patients, including diagnosis and prediction models for PCOS complications and treatment outcomes. We aimed to provide ideas for medical researchers and clues for the management of PCOS. In the future, models with poor accuracy can be greatly improved by adding well-known parameters and validations, which will further expand our understanding of PCOS in terms of precision medicine. By developing a series of predictive models, we can make the definition of PCOS more accurate, which can improve the diagnosis of PCOS and reduce the likelihood of false positives and false negatives. It will also help discover complications earlier and treatment outcomes being known earlier, which can result in better outcomes for women with PCOS.

Performance of polygenic risk scores in screening, prediction, and risk stratification: secondary analysis of data in the Polygenic Score Catalog

Objective

To clarify the performance of polygenic risk scores in population screening, individual risk prediction, and population risk stratification.

Design

Secondary analysis of data in the Polygenic Score Catalog.

Setting

Polygenic Score Catalog, April 2022. Secondary analysis of 3915 performance metric estimates for 926 polygenic risk scores for 310 diseases to generate estimates of performance in population screening, individual risk, and population risk stratification.

Participants

Individuals contributing to the published studies in the Polygenic Score Catalog.

Main outcome measures

Detection rate for a 5% false positive rate (DR5) and the population odds of becoming affected given a positive result; individual odds of becoming affected for a person with a particular polygenic score; and odds of becoming affected for groups of individuals in different portions of a polygenic risk score distribution. Coronary artery disease and breast cancer were used as illustrative examples.

Results

For performance in population screening, median DR5 for all polygenic risk scores and all diseases studied was 11% (interquartile range 8-18%). Median DR5 was 12% (9-19%) for polygenic risk scores for coronary artery disease and 10% (9-12%) for breast cancer. The population odds of becoming affected given a positive results were 1:8 for coronary artery disease and 1:21 for breast cancer, with background 10 year odds of 1:19 and 1:41, respectively, which are typical for these diseases at age 50. For individual risk prediction, the corresponding 10 year odds of becoming affected for individuals aged 50 with a polygenic risk score at the 2.5th, 25th, 75th, and 97.5th centiles were 1:54, 1:29, 1:15, and 1:8 for coronary artery disease and 1:91, 1:56, 1:34, and 1:21 for breast cancer. In terms of population risk stratification, at age 50, the risk of coronary artery disease was divided into five groups, with 10 year odds of 1:41 and 1:11 for the lowest and highest quintile groups, respectively. The 10 year odds was 1:7 for the upper 2.5% of the polygenic risk score distribution for coronary artery disease, a group that contributed 7% of cases. The corresponding estimates for breast cancer were 1:72 and 1:26 for the lowest and highest quintile groups, and 1:19 for the upper 2.5% of the distribution, which contributed 6% of cases.

Conclusion

Polygenic risk scores performed poorly in population screening, individual risk prediction, and population risk stratification. Strong claims about the effect of polygenic risk scores on healthcare seem to be disproportionate to their performance.

Effectiveness of Exercise Interventions for Preventing Neck Pain: A Systematic Review With Meta-analysis of Randomized Controlled Trials

OBJECTIVE: To update the evidence on the effectiveness of exercise interventions to prevent episodes of neck pain. DESIGN: Systematic review with meta-analysis. LITERATURE SEARCH: MEDLINE, Embase, CENTRAL, CINAHL, SPORTDiscus, PEDro, and trial registries from inception to December 2, 2022. Forward and backward citation searches. STUDY SELECTION CRITERIA: Randomized controlled trials (RCTs) that enrolled adults without neck pain at baseline and compared exercise interventions to no intervention, placebo/sham, attention control, or minimal intervention. Military populations and astronauts were excluded. DATA SYNTHESIS: Random-effects meta-analysis. Risk of bias was assessed using the Cochrane RoB 2 tool. The certainty of evidence was judged according to the GRADE approach. RESULTS: Of 4703 records screened, 5 trials (1722 participants at baseline) were included and eligible for meta-analysis. Most (80%) participants were office workers. Risk of bias was rated as some concerns for 2 trials and high for 3 trials. There was moderate-certainty evidence that exercise interventions probably reduce the risk of a new episode of neck pain (OR, 0.49; 95% confidence interval: 0.31, 0.76) compared to no or minimal intervention in the short-term (≤12 months). The results were not robust to sensitivity analyses for missing outcome data. CONCLUSION: There was moderate-certainty evidence supporting exercise interventions for reducing the risk for an episode of neck pain in the next 12 months. The clinical significance of the effect is unclear. J Orthop Sports Phys Ther 2023;53(10):1-16. Epub: 8 September 2023. doi:10.2519/jospt.2023.12063.

Increasing transparency in indirect treatment comparisons: is selecting effect modifiers the missing part of the puzzle? A review of methodological approaches and critical considerations

Failure to adjust for effect modifiers (EMs) in indirect treatment comparisons (ITCs) can produce biased and uncertain effect estimates. This is particularly important for health technology assessments (HTAs), where the availability of new treatments is based on comparative effectiveness results. Much emphasis has been placed on advancing ITC methods to adjust for EMs, yet whether EMs are appropriately identified for the conduct of ITCs in the first place is unclear. To understand the extent of guidance and requirements for the selection of EMs for ITCs currently available and if and how this guidance is applied in practice, a series of pragmatic reviews of guidance documents from HTA and non-payer organizations, primary published ITC analyses, and prior HTA submissions in two indications (non-small cell lung cancer and psoriasis) was conducted. The reviews showed that current ITC guidance mainly focused on developing analytical methods to adjust for EMs. Some organizations, such as HTA bodies in the UK, France and Germany, recommended the use of literature reviews, expert opinion and statistical methods to identify EMs. No detailed guidance on the selection process or the appropriate literature review approach was found. Similar trends were identified through the database search and review of prior HTA submissions; only few published ITCs and submissions included information on the EM selection process which was either based on findings from the literature, trial subgroup analyses, or clinical input. No reference to a systematic selection approach was found. There is an urgent need to fill the guidance gap identified across the reviews by including a step in ITC guidelines on how EMs should be identified through systematic reviews, formal expert elicitation, and a quantitative assessment of the EM distribution. Researchers and manufacturers are also encouraged to improve transparent reporting and justification of their selection of EMs to allow for an independent review of the set of factors being considered for adjustment. Both will contribute toward reducing bias in the ITC results and ultimately increase confidence in decision-making.

Probiotics and the Potential of Genetic Modification as a Possible Treatment for Food Allergy

Food allergy is a common condition that affects millions of people worldwide. It is caused by an abnormal immune response to harmless food antigens, which is influenced by genetics and environmental factors. Modulating the gut microbiota and immune system with probiotics or genetically modified probiotics confers health benefits to the host and offers a novel strategy for preventing and treating food allergy. This systematic review aims to summarize the current proof of the role of probiotics in food allergy and propose a promising future research direction of using probiotics as a possible strategy of treatment for food allergy.

Large Language Models for Epidemiological Research via Automated Machine Learning: Case Study Using Data From the British National Child Development Study

Background

Large language models have had a huge impact on natural language processing (NLP) in recent years. However, their application in epidemiological research is still limited to the analysis of electronic health records and social media data.

objectives

To demonstrate the potential of NLP beyond these domains, we aimed to develop prediction models based on texts collected from an epidemiological cohort and compare their performance to classical regression methods.

Methods

We used data from the British National Child Development Study, where 10,567 children aged 11 years wrote essays about how they imagined themselves as 25-year-olds. Overall, 15% of the data set was set aside as a test set for performance evaluation. Pretrained language models were fine-tuned using AutoTrain (Hugging Face) to predict current reading comprehension score (range: 0-35) and future BMI and physical activity (active vs inactive) at the age of 33 years. We then compared their predictive performance (accuracy or discrimination) with linear and logistic regression models, including demographic and lifestyle factors of the parents and children from birth to the age of 11 years as predictors.

Results

NLP clearly outperformed linear regression when predicting reading comprehension scores (root mean square error: 3.89, 95% CI 3.74-4.05 for NLP vs 4.14, 95% CI 3.98-4.30 and 5.41, 95% CI 5.23-5.58 for regression models with and without general ability score as a predictor, respectively). Predictive performance for physical activity was similarly poor for the 2 methods (area under the receiver operating characteristic curve: 0.55, 95% CI 0.52-0.60 for both) but was slightly better than random assignment, whereas linear regression clearly outperformed the NLP approach when predicting BMI (root mean square error: 4.38, 95% CI 4.02-4.74 for NLP vs 3.85, 95% CI 3.54-4.16 for regression). The NLP approach did not perform better than simply assigning the mean BMI from the training set as a predictor.

Conclusions

Our study demonstrated the potential of using large language models on text collected from epidemiological studies. The performance of the approach appeared to depend on how directly the topic of the text was related to the outcome. Open-ended questions specifically designed to capture certain health concepts and lived experiences in combination with NLP methods should receive more attention in future epidemiological studies.

Overview of systematic reviews of risk factors for prosthetic joint infection

BACKGROUND

Prosthetic joint infection is one of the most serious complications in orthopedics. Prognostic systematic reviews (SR) detecting and assessing factors related to prosthetic joint infection, allow better prediction of risk and implementation of preventive measures. Although prognostic SR are increasingly frequent, their methodological field presents some knowledge gaps.

PURPOSE

To carry out an overview of SR assessing risk factors for prosthetic joint infection, describing and synthesizing their evidence. Secondarily, to assess the risk of bias and methodological quality.

MATERIAL AND METHODS

We conducted a bibliographic search in 4databases (May 2021) to identify prognostic SR evaluating any risk factor for prosthetic joint infection. We evaluated risk of bias with the ROBIS tool, and methodological quality with a modified AMSTAR-2 tool. We computed the overlap degree study between included SR.

RESULTS

Twenty-three SR were included, studying 15 factors for prosthetic joint infection, of which, 13 had significant association. The most frequently studied risk factors were obesity, intra-articular corticosteroids, smoking and uncontrolled diabetes. Overlapping between SR was high for obesity and very high for intra-articular corticoid injection, smoking and uncontrolled diabetes. Risk of bias was considered low in 8SRs (34.7%). The modified AMSTAR-2 tool showed important methodological gaps.

CONCLUSIONS

Identification of procedural-modifiable factors, such as intra-articular corticoids use, can give patients better results. Overlapping between SR was very high, meaning that some SR are redundant. The evidence on risk factors for prosthetic joint infection is weak due to high risk of bias and limited methodological quality.

[Translated article] Overview of systematic reviews of risk factors for prosthetic joint infection

BACKGROUND

Prosthetic joint infection is one of the most serious complications in orthopedics. Prognostic systematic reviews (SRs) detecting and assessing factors related to prosthetic joint infection, allow better prediction of risk and implementation of preventive measures. Although prognostic SRs are increasingly frequent, their methodological field presents some knowledge gaps.

PURPOSE

To carry out an overview of SR assessing risk factors for prosthetic joint infection, describing and synthesizing their evidence. Secondarily, to assess the risk of bias and methodological quality.

MATERIAL AND METHODS

We conducted a bibliographic search in 4 databases (May 2021) to identify prognostic SR evaluating any risk factor for prosthetic joint infection. We evaluated risk of bias with the ROBIS tool, and methodological quality with a modified AMSTAR-2 tool. We computed the overlap degree study between included SR.

RESULTS

Twenty-three SRs were included, studying 15 factors for prosthetic joint infection, of which, 13 had significant association. The most frequently studied risk factors were obesity, intra-articular corticosteroids, smoking and uncontrolled diabetes. Overlapping between SR was high for obesity and very high for intra-articular corticoid injection, smoking and uncontrolled diabetes. Risk of bias was considered low in 8 SRs (34.7%). The modified AMSTAR-2 tool showed important methodological gaps.

CONCLUSIONS

Identification of procedural-modifiable factors, such as intra-articular corticoids use, can give patients better results. Overlapping between SR was very high, meaning that some SRs are redundant. The evidence on risk factors for prosthetic joint infection is weak due to high risk of bias and limited methodological quality.

Prognostic factors associated with failure of total elbow replacement: a protocol for a systematic review

INTRODUCTION

Total elbow replacement (TER) has higher failure rates requiring revision surgery compared with the replacement of other joints. Understanding the factors associated with failure is essential for informed decision-making between patients and clinicians, and for reducing the failure rate. This review aims to identify, describe and appraise the literature examining prognostic factors for failure of TER.

METHODS AND ANALYSIS

This systematic review will be conducted and reported in line with the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols guidelines. Electronic literature searches will be conducted using Medline, EMBASE, PubMed and Cochrane. The search strategy will be broad, including a combination of subject headings (MESH) and free text search. This search will be supplemented with a screening of reference lists of the included studies and relevant reviews. Two independent reviewers will screen all search results in two stages (title and abstract, and full text) based on the Population, Index prognostic factor, Comparator prognostic factor, Outcome, Time and Setting criteria. The types of evidence included will be randomised trials, non-randomised trials, prospective and retrospective cohort studies, registry studies and case-control studies. If the literature lacks enough studies, then case series with 50 or more TERs will be considered for inclusion. Data extraction and risk of bias assessment for included studies will be performed by two independent reviewers using the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies for Prognostic Factors and Quality In Prognostic Studies tools.Meta-analyses of prognostic estimates for each factor will be undertaken for studies that are deemed to be sufficiently robust and comparable. Several challenges are likely to arise due to heterogeneity between studies, therefore, subgroup and sensitivity analyses will be performed to account for the differences between studies. Heterogeneity will be assessed using Q and I2 statistics. If I2>40% then pooled estimates will not be reported. When quantitative synthesis is not possible, a narrative synthesis will be undertaken. The quality of the evidence for each prognostic factor will be assessed using the Grades of Recommendation Assessment, Development and Evaluation tool.

PROSPERO REGISTRATION NUMBER

CRD42023384756.

Stratified care in hip arthroscopy: can we predict successful and unsuccessful outcomes? Development and external temporal validation of multivariable prediction models

OBJECTIVE

Although hip arthroscopy is a widely adopted treatment option for hip-related pain, it is unknown whether preoperative clinical information can be used to assist surgical decision-making to avoid offering surgery to patients with limited potential for a successful outcome. We aimed to develop and validate clinical prediction models to identify patients more likely to have an unsuccessful or successful outcome 1 year post hip arthroscopy based on the patient acceptable symptom state.

METHODS

Patient records were extracted from the Danish Hip Arthroscopy Registry (DHAR). A priori, 26 common clinical variables from DHAR were selected as prognostic factors, including demographics, radiographic parameters of hip morphology and self-reported measures. We used 1082 hip arthroscopy patients (surgery performed 25 April 2012 to 4 October 2017) to develop the clinical prediction models based on logistic regression analyses. The development models were internally validated using bootstrapping and shrinkage before temporal external validation was performed using 464 hip arthroscopy patients (surgery performed 5 October 2017 to 13 May 2019).

RESULTS

The prediction model for unsuccessful outcomes showed best and acceptable predictive performance on the external validation dataset for all multiple imputations (Nagelkerke R2 range: 0.25-0.26) and calibration (intercept range: -0.10 to -0.11; slope range: 1.06-1.09), and acceptable discrimination (area under the curve range: 0.76-0.77). The prediction model for successful outcomes did not calibrate well, while also showing poor discrimination.

CONCLUSION

Common clinical variables including demographics, radiographic parameters of hip morphology and self-reported measures were able to predict the probability of having an unsuccessful outcome 1 year after hip arthroscopy, while the model for successful outcome showed unacceptable accuracy. The externally validated prediction model can be used to support clinical evaluation and shared decision making by informing the orthopaedic surgeon and patient about the risk of an unsuccessful outcome, and thus when surgery may not be appropriate.

Evaluation of a blended learning approach on stratified care for physiotherapy bachelor students

BACKGROUND

Stratified models of care are valuable for addressing psychosocial factors which influence the outcome of patients with musculoskeletal disorders. Introducing such models in undergraduate training has the potential to propagate this knowledge with evidence and foster its implementation. The objective of this paper is to explore the perception and changes in the fear-avoidance beliefs of physiotherapy students participating in a developed blended learning course on stratified care.

METHODOLOGY

A mixed-methods with a convenient sample of two consecutive cohorts were given a blended learning course on stratified care for patients with low back pain. The blended learning course comprised scientific rudiments and application of stratified care in clinical practice conceptualised using the KERN' 6-step approach. The exam scores, perceptions, performance on self-reflection-tests and pre- and post-scores on The Tampa Scale for Kinesiophobia for Physiotherapists' (TSK-PT) were obtained. After gaining clinical experience, participants were invited to discuss their clinical experiences and perceptions in workshops. The quantitative data was analysed explorative-descriptively. The qualitative data was analysed following an inductive coding system with constant comparisons.

RESULTS

Ninety-one participants consented to the evaluation (mean age = 22.9 ± 1.6 years), 66% were female. Exam scores correlated with time spent in training (r = 0.30) and scores on self-reflection-tests 1 and 2 (r = 0.40 and r = 0.41). Participants in both cohorts described the learning resources as promoting their interest in the subject (72% and 94%), up-to-date (91% and 93%) and helpful (91% and 97%). The fear-avoidance scores for participants decreased from 53.5 (± 9.96) to 40.1 (± 12.4) with a large effect size (d = 1.18). The regression model [F (2, 49) = 1151.2, p < 0.001] suggests that pre-TSK-PT and the interest of participants in the training predicted post-TSK-PT. The workshop participants (n = 62) all worked in clinical practice. Emerging from the analysis were 4 categories (evolving to maturity in practice, perceiving determinants of stratified care, strategising for implementation and adopting an outlook for future practice).

CONCLUSION

The quality of engagement in learning, training strategy and interest in the subject contributes immensely to learning outcomes. This blended learning course was successful in reducing kinesiophobia and influencing the participants' attitude towards care with the potential of being translated into long-term practice.

Individual participant data systematic review and meta-analysis of randomised controlled trials assessing adult mindfulness-based programmes for mental health promotion in non-clinical settings

Introduction

Mindfulness-based programmes (MBPs) are widely used to prevent mental ill-health that is becoming the leading global cause of morbidity. Evidence suggests beneficial average effects but wide variability. We aimed to confirm the effect of MBPs on psychological distress, and to understand whether and how baseline distress, gender, age, education, and dispositional mindfulness modify the effect of MBPs on distress among adults in non-clinical settings.

Methods

We conducted a pre-registered systematic review and individual participant data (IPD) meta-analysis (PROSPERO CRD42020200117). Thirteen databases were searched in December 2020 for randomised controlled trials satisfying a quality threshold and comparing in-person, expert-defined MBPs in non-clinical settings with passive control groups. Two researchers independently selected, extracted, and appraised trials using the revised Cochrane Risk-of-Bias Tool (RoB2). Anonymised IPD of eligible trials were sought from collaborating authors. The primary outcome was psychological distress (unpleasant mental or emotional experiences including anxiety and depression) at 1 to 6 months after programme completion. Data were checked and imputed if missing. Pairwise, random-effects, two-stage IPD meta-analyses were conducted. Effect modification analyses followed a within-studies approach. Public and professional stakeholders were involved in the planning, conduct and dissemination of this study.

Results

Fifteen trials were eligible, 13 trialists shared IPD (2,371 participants representing 8 countries, median age 34 years-old, 71% women, moderately distressed on average, 20% missing outcome data). In comparison with passive control groups, MBPs reduced average distress between one- and six-months post-intervention with a small to moderate effect size (standardised mean difference (SMD) -0.32; 95% confidence interval (CI) -0.41 to -0.24; p-value < 0.001; 95% prediction interval (PI) -0.41 to -0.24 (no heterogeneity)). Results were robust to sensitivity analyses, and similar for the other psychological distress time point ranges. Confidence in the primary outcome result is high. We found no clear indication that this effect is modified by baseline psychological distress, gender, age, education level, or dispositional mindfulness.

Conclusions

Group-based teacher-led MBPs generally reduce psychological distress among community adults who volunteer to receive this type of intervention. More research is needed to identify sources of variability in outcomes at an individual level.

Predictors of Noninvasive Ventilation Failure in the Post-Extubation Period: A Systematic Review and Meta-Analysis

OBJECTIVES

To identify factors associated with failure of noninvasive ventilation (NIV) in the post-extubation period.

DATA SOURCES

We searched Embase Classic +, MEDLINE, and the Cochrane Database of Systematic Reviews from inception to February 28, 2022.

STUDY SELECTION

We included English language studies that provided predictors of post-extubation NIV failure necessitating reintubation.

DATA EXTRACTION

Two authors conducted data abstraction and risk-of-bias assessments independently. We used a random-effects model to pool binary and continuous data and summarized estimates of effect using odds ratios (ORs) mean difference (MD), respectively. We used the Quality in Prognosis Studies tool to assess risk of bias and the Grading of Recommendations, Assessment, Development and Evaluations to assess certainty.

DATA SYNTHESIS

We included 25 studies ( n = 2,327). Illness-related factors associated with increased odds of post-extubation NIV failure were higher critical illness severity (OR, 3.56; 95% CI, 1.96-6.45; high certainty) and a diagnosis of pneumonia (OR, 6.16; 95% CI, 2.59-14.66; moderate certainty). Clinical and biochemical factors associated with moderate certainty of increased risk of NIV failure post-extubation include higher respiratory rate (MD, 1.54; 95% CI, 0.61-2.47), higher heart rate (MD, 4.46; 95% CI, 1.67-7.25), lower Pa o2 :F io2 (MD, -30.78; 95% CI, -50.02 to -11.54) 1-hour after NIV initiation, and higher rapid shallow breathing index (MD, 15.21; 95% CI, 12.04-18.38) prior to NIV start. Elevated body mass index was the only patient-related factor that may be associated with a protective effect (OR, 0.21; 95% CI, 0.09-0.52; moderate certainty) on post-extubation NIV failure.

CONCLUSIONS

We identified several prognostic factors before and 1 hour after NIV initiation associated with increased risk of NIV failure in the post-extubation period. Well-designed prospective studies are required to confirm the prognostic importance of these factors to help further guide clinical decision-making.

Individualized Risk Prediction for Improved Chronic Wound Management

Significance: Chronic wounds are associated with significant morbidity, marked loss of quality of life, and considerable economic burden. Evidence-based risk prediction to guide improved wound prevention and treatment is limited by the complexity in their etiology, clinical underreporting, and a lack of studies using large high-quality datasets. Recent Advancements: The objective of this review is to summarize key components and challenges in the development of personalized risk prediction tools for both prevention and management of chronic wounds, while highlighting several innovations in the development of better risk stratification. Critical Issues: Regression-based risk prediction approaches remain important for assessment of prognosis and risk stratification in chronic wound management. Advances in statistical computing have boosted the development of several promising machine learning (ML) and other semiautomated classification tools. These methods may be better placed to handle large number of wound healing risk factors from large datasets, potentially resulting in better risk prediction when combined with conventional methods and clinical experience and expertise. Future Directions: Where the number of predictors is large and heterogenous, the correlations between various risk factors complex, and very large data sets are available, ML may prove a powerful adjuvant for risk stratifying patients predisposed to chronic wounds. Conventional regression-based approaches remain important, particularly where the number of predictors is relatively small. Translating estimated risk derived from ML algorithms into practical prediction tools for use in clinical practice remains challenging.

Systematic metareview of prediction studies demonstrates stable trends in bias and low PROBAST inter-rater agreement

OBJECTIVES

To (1) explore trends of risk of bias (ROB) in prediction research over time following key methodological publications, using the Prediction model Risk Of Bias ASsessment Tool (PROBAST) and (2) assess the inter-rater agreement of the PROBAST.

STUDY DESIGN AND SETTING

PubMed and Web of Science were searched for reviews with extractable PROBAST scores on domain and signaling question (SQ) level. ROB trends were visually correlated with yearly citations of key publications. Inter-rater agreement was assessed using Cohen's Kappa.

RESULTS

One hundred and thirty nine systematic reviews were included, of which 85 reviews (containing 2,477 single studies) on domain level and 54 reviews (containing 2,458 single studies) on SQ level. High ROB was prevalent, especially in the Analysis domain, and overall trends of ROB remained relatively stable over time. The inter-rater agreement was low, both on domain (Kappa 0.04-0.26) and SQ level (Kappa -0.14 to 0.49).

CONCLUSION

Prediction model studies are at high ROB and time trends in ROB as assessed with the PROBAST remain relatively stable. These results might be explained by key publications having no influence on ROB or recency of key publications. Moreover, the trend may suffer from the low inter-rater agreement and ceiling effect of the PROBAST. The inter-rater agreement could potentially be improved by altering the PROBAST or providing training on how to apply the PROBAST.

Diagnosis or prognosis? An umbrella review of mid-trimester cervical length and spontaneous preterm birth

BACKGROUND

Cervical length is widely used to assess a woman's risk of spontaneous preterm birth (SPTB).

OBJECTIVES

To summarise and critically appraise the evidence from systematic reviews on the prognostic capacity of transvaginal sonographic cervical length in the second trimester in asymptomatic women with singleton or twin pregnancy.

SEARCH STRATEGY

Searches were performed in Medline, Embase, CINAHL and grey literature from 1 January 1995 to 6 July 2021, including keywords 'cervical length', 'preterm birth', 'obstetric labour, premature', 'review' and others, without language restriction.

SELECTION CRITERIA

We included systematic reviews including women who did not receive treatments to reduce SPTB risk.

DATA COLLECTION AND ANALYSIS

From 2472 articles, 14 systematic reviews were included. Summary statistics were independently extracted by two reviewers, tabulated and analysed descriptively. The ROBIS tool was used to evaluate risk of bias of included systematic reviews.

MAIN RESULTS

Twelve reviews performed meta-analyses: two were reported as systematic reviews of prognostic factor studies, ten used diagnostic test accuracy methodology. Ten systematic reviews were at high or unclear risk of bias. Meta-analyses reported up to 80 combinations of cervical length, gestational age at measurement and definition of preterm birth. Cervical length was consistently associated with SPTB, with a likelihood ratio for a positive test of 1.70-142.

CONCLUSIONS

The ability of cervical length to predict SPTB is a prognostic research question; systematic reviews typically analysed diagnostic test accuracy. Individual participant data meta-analysis using prognostic factor research methods is recommended to better quantify how well transvaginal ultrasonographic cervical length can predict SPTB.

Cardiovascular and Renal Benefits of Novel Diabetes Drugs by Baseline Cardiovascular Risk: A Systematic Review, Meta-analysis, and Meta-regression

BACKGROUND

Eligibility for glucagon-like peptide 1 receptor agonists (GLP-1RA) and sodium-glucose cotransporter 2 inhibitors (SGLT2i) has been expanded to patients with diabetes at lower cardiovascular risk, but whether treatment benefits differ by risk levels is not clear.

PURPOSE

To investigate whether patients with varying risks differ in cardiovascular and renal benefits from GLP-1RA and SGLT2i with use of meta-analysis and meta-regression.

DATA SOURCES

We performed a systematic review using PubMed through 7 November 2022.

STUDY SELECTION

We included reports of GLP-1RA and SGLT2i confirmatory randomized trials in adult patients with safety or efficacy end point data.

DATA EXTRACTION

Hazard ratio (HR) and event rate data were extracted for mortality, cardiovascular, and renal outcomes.

DATA SYNTHESIS

We analyzed 9 GLP-1RA and 13 SGLT2i trials comprising 154,649 patients. Summary HRs were significant for cardiovascular mortality (GLP-1RA 0.87 and SGLT2i 0.86), major adverse cardiovascular events (0.87 and 0.88), heart failure (0.89 and 0.70), and renal (0.84 and 0.65) outcomes. For stroke, efficacy was significant for GLP-1RA (0.84) but not for SGLT2i (0.92). Associations between control arm cardiovascular mortality rates and HRs were nonsignificant. Five-year absolute risk reductions (0.80-4.25%) increased to 11.6% for heart failure in SGLT2i trials in patients with high risk (Pslope < 0.001). For GLP1-RAs, associations were nonsignificant.

LIMITATIONS

Analyses were limited by lack of patient-level data, consistency in end point definitions, and variation in cardiovascular mortality rates for GLP-1RA trials.

CONCLUSIONS

Relative effects of novel diabetes drugs are preserved across baseline cardiovascular risk, whereas absolute benefits increase at higher risks, particularly regarding heart failure. Our findings suggest a need for baseline risk assessment tools to identify variation in absolute treatment benefits and improve decision-making.

Effect of a Nurse Navigation Intervention on Mental Symptoms in Patients With Psychological Vulnerability and Breast Cancer: The REBECCA Randomized Clinical Trial

Importance

The unmet needs regarding symptom management of psychological distress among patients with breast cancer must be addressed. However, little evidence exists on effective interventions, such as nurse navigation.

Objective

To compare the long-term effects of the REBECCA (Rehabilitation After Breast Cancer) nurse navigation intervention vs usual care in patients with breast cancer who were psychologically vulnerable.

Design, Setting, and Participants

This parallel randomized clinical trial recruited and evaluated for eligibility adult female patients with newly diagnosed breast cancer and symptoms of psychological distress (distress score of ≥7 points on Distress Thermometer) at Rigshospitalet in Copenhagen, Denmark, from August 2017 to October 2019. This study continued the work of a pilot study, extending the follow-up to 18 months. Patients who met the inclusion criteria were randomized to either standard care or the REBECCA intervention. Intention-to-treat analyses were performed from June 2021 to October 2022.

Interventions

Patients who were randomized to the REBECCA intervention received nurse navigation and symptom screening as well as standard care. Standard care included regular treatment, nurse support at chemotherapy and radiotherapy appointments, and municipality-based rehabilitation.

Main Outcomes and Measures

The primary outcome was distress, as measured using the Distress Thermometer. The secondary outcomes included symptoms of anxiety, symptoms of depression, breast cancer-specific health-related quality of life, fear of recurrence, sleep, cognitive function, patient activation, pain, health behavior, body mass index, and need for support. Long-term effects at 6, 12, and 18 months were examined using mixed-effect models, adjusting for randomization strata of age and treatment modality.

Results

A total of 309 female patients were included in the analysis, with 153 patients randomized to the standard care group and 156 patients randomized to the REBECCA intervention group. Mean (SD) age was 56 (11) years with only small between-group differences. Patients receiving the REBECCA intervention compared with standard care had reduced (although not significant) symptoms of distress, especially at the 12-month follow-up (estimated effect = -0.51 [95% CI, -1.05 to 0.04]; effect size [ES] = -0.49). Significant effects were seen for symptoms of depression at 6 months (estimated effect = -1.39 [95% CI, -2.33 to -0.44]; ES = -0.27), and breast cancer-specific health-related quality of life at 12 months (estimated effect = 4.03 [95% CI, 1.28- 6.77]; ES = 0.31). Nonsignificant reductions were seen for symptoms of anxiety at 6 months (estimated effect = -1.00 [95% CI, -1.95 to -0.06]; ES = -0.21) and 12 months (estimated effect = -1.01 [95% CI, -1.97 to -0.04]; ES = -0.21), and a nonsignificant increase was seen for patient activation at 18 months (estimated effect = 3.52 [95% CI, -0.09 to 7.12]; ES = 0.25). Stronger intervention effects were observed for younger age, low patient activation, less education, and low social support.

Conclusions and Relevance

Results of this study indicate that patients with breast cancer who were psychologically vulnerable (ie, having moderate to high psychological distress) did not experience significant reduction in distress with nurse navigation. Further research is needed to develop the intervention's framework and investigate its potential use in clinical practice.

Trial Registration

ClinicalTrials.gov Identifier: NCT03254875.

Cytokine Patterns as Predictors of Antibiotic Treatment Effect in Chronic Low Back Pain with Modic Changes: Subgroup Analyses of a Randomized Trial (AIM Study)

Objective

Randomized trials testing the effect of antibiotics for chronic low back pain (LBP) with vertebral bone marrow changes on MRI (Modic changes) report inconsistent results. A proposed explanation is subgroups with low grade discitis where antibiotics are effective, but there is currently no method to identify such subgroups. The objective of the present study was to evaluate whether distinct patterns of serum cytokine levels predict any treatment effect of oral amoxicillin at one-year follow-up in patients with chronic low back pain and Modic changes at the level of a previous lumbar disc herniation.

Design

We used data from an overpowered, randomized, placebo-controlled trial (the AIM study) that tested 100 days of oral 750 mg amoxicillin vs placebo three times daily in hospital outpatients with chronic (>6 months) LBP with pain intensity ≥5 on a 0-10 numerical rating scale and Modic changes type 1 (oedema type) or 2 (fatty type). We measured serum levels of 40 inflammatory cytokines at baseline and analysed six predefined potential predictors of treatment effect based on cytokine patterns in 78 randomized patients; three analyses with recursive partitioning, one based on cluster analysis and two based on principal component analyses. The primary outcome was the Roland-Morris Disability Questionnaire score at one-year follow-up in the intention to treat population. The methodology and overall results of the AIM study were published previously.

Results

The 78 patients were 25-62 years old and 47 (60%) were women. None of the three recursive partitioning analyses resulted in any suggested subgroups. Of all main analyses, the largest effect estimate (mean difference between antibiotic and placebo groups) was seen in a subgroup not predefined as of main interest (Cluster category 3+4; -2.0, 95% CI: -5.2-1.3, RMDQ points; p-value for interaction 0.54).

Conclusion

Patterns of inflammatory serum cytokine levels did not predict treatment effect of amoxicillin in patients with chronic LBP and Modic changes.

Clinical Trial Registration Number

ClinicalTrials.gov (identifier: NCT02323412).

Six Externally Validated Prognostic Models Have Potential Clinical Value to Predict Patient Health Outcomes in the Rehabilitation of Musculoskeletal Conditions: A Systematic Review

OBJECTIVE

The purpose of this systematic review was to identify and appraise externally validated prognostic models to predict a patient's health outcomes relevant to physical rehabilitation of musculoskeletal (MSK) conditions.

METHODS

We systematically reviewed 8 databases and reported our findings according to Preferred Reporting Items for Systematic Reviews and Meta-Analysis 2020. An information specialist designed a search strategy to identify externally validated prognostic models for MSK conditions. Paired reviewers independently screened the title, abstract, and full text and conducted data extraction. We extracted characteristics of included studies (eg, country and study design), prognostic models (eg, performance measures and type of model) and predicted clinical outcomes (eg, pain and disability). We assessed the risk of bias and concerns of applicability using the prediction model risk of bias assessment tool. We proposed and used a 5-step method to determine which prognostic models were clinically valuable.

RESULTS

We found 4896 citations, read 300 full-text articles, and included 46 papers (37 distinct models). Prognostic models were externally validated for the spine, upper limb, lower limb conditions, and MSK trauma, injuries, and pain. All studies presented a high risk of bias. Half of the models showed low concerns for applicability. Reporting of calibration and discrimination performance measures was often lacking. We found 6 externally validated models with adequate measures, which could be deemed clinically valuable [ie, (1) STart Back Screening Tool, (2) Wallis Occupational Rehabilitation RisK model, (3) Da Silva model, (4) PICKUP model, (5) Schellingerhout rule, and (6) Keene model]. Despite having a high risk of bias, which is mostly explained by the very conservative properties of the PROBAST tool, the 6 models remain clinically relevant.

CONCLUSION

We found 6 externally validated prognostic models developed to predict patients' health outcomes that were clinically relevant to the physical rehabilitation of MSK conditions.

IMPACT

Our results provide clinicians with externally validated prognostic models to help them better predict patients' clinical outcomes and facilitate personalized treatment plans. Incorporating clinically valuable prognostic models could inherently improve the value of care provided by physical therapists.

Systematic review and meta-analysis of prediction models used in cervical cancer

BACKGROUND

Cervical cancer is one of the most common cancers in women with an incidence of around 6.5 % of all the cancer in women worldwide. Early detection and adequate treatment according to staging improve the patient's life expectancy. Outcome prediction models might aid treatment decisions, but a systematic review on prediction models for cervical cancer patients is not available.

DESIGN

We performed a systematic review for prediction models in cervical cancer following PRISMA guidelines. Key features that were used for model training and validation, the endpoints were extracted from the article and data were analyzed. Selected articles were grouped based on prediction endpoints i.e. Group1: Overall survival, Group2: progression-free survival; Group3: recurrence or distant metastasis; Group4: treatment response; Group5: toxicity or quality of life. We developed a scoring system to evaluate the manuscript. As per our criteria, studies were divided into four groups based on scores obtained in our scoring system, the Most significant study (Score > 60 %); Significant study (60 % > Score > 50 %); Moderately Significant study (50 % > Score > 40 %); least significant study (score < 40 %). A meta-analysis was performed for all the groups separately.

RESULTS

The first line of search selected 1358 articles and finally 39 articles were selected as eligible for inclusion in the review. As per our assessment criteria, 16, 13 and 10 studies were found to be the most significant, significant and moderately significant respectively. The intra-group pooled correlation coefficient for Group1, Group2, Group3, Group4, and Group5 were 0.76 [0.72, 0.79], 0.80 [0.73, 0.86], 0.87 [0.83, 0.90], 0.85 [0.77, 0.90], 0.88 [0.85, 0.90] respectively. All the models were found to be good (prediction accuracy [c-index/AUC/R²] >0.7) in endpoint prediction.

CONCLUSIONS

Prediction models of cervical cancer toxicity, local or distant recurrence and survival prediction show promising results with reasonable prediction accuracy [c-index/AUC/R² > 0.7]. These models should also be validated on external data and evaluated in prospective clinical studies.

Development of transdiagnostic clinical risk prediction models for 12-month onset and course of eating disorders among adolescents in the community

OBJECTIVE

To develop and internally validate risk prediction models for adolescent onset and persistence of eating disorders.

METHODS

N = 963 Australian adolescents (11-19 years) in the EveryBODY Study cohort completed online surveys in 2018 and 2019. Models were built to predict 12-month risk of (1) onset, and (2) persistence of a DSM-5 eating disorder.

RESULTS

Onset Model. Of the n = 687 adolescents without an eating disorder at baseline, 16.9% were identified with an eating disorder after 12 months. The prediction model was based on evidence-based risk factors for eating disorder onset available within the dataset (sex, body mass index percentile, strict weight loss dieting, history of bullying, psychological distress, weight/shape concerns). This model showed fair discriminative performance (mean AUC = .75). The most important factors were psychological distress, weight and shape concerns, and female sex. Diagnostic Persistence Model. Of the n = 276 adolescents with an eating disorder at baseline, 74.6% were identified as continuing to meet criteria for an eating disorder after 12 months. The prediction model for diagnostic persistence was based on available evidence-based risk factors for eating disorder persistence (purging, distress, social impairment). This model showed poor discriminative performance (mean AUC = .65). The most important factors were psychological distress and self-induced vomiting for weight control.

DISCUSSION

We found preliminary evidence for the utility of a parsimonious model for 12-month onset of an eating disorder among adolescents in the community. Future research should include additional evidence-based risk factors and validate models beyond the original sample.

PUBLIC SIGNIFICANCE

This study demonstrated the feasibility of developing parsimonious and accurate models for the prediction of future onset of an eating disorder among adolescents. The most important predictors in this model included psychological distress and weight and shape concerns. This study has laid the ground work for future research to build and test more accurate prediction models in diverse samples, prior to translation into a clinical tool for use in real world settings to aid decisions about referral to early intervention.

Massive Irreparable Rotator Cuff Tears: Which Patients Will Benefit from Physiotherapy Exercise Programs? A Narrative Review

Massive irreparable rotator cuff tears can cause significant shoulder pain, disability and reduction in quality of life. Treatment approaches can be operative or non-operative. Operative approaches include reverse total shoulder arthroplasty, arthroscopic debridement, partial rotator cuff repair, subacromial balloon spacers, superior capsule reconstruction, and tendon transfer procedures. Non-operative approaches include physiotherapy exercise programs and corticosteroid injections. There are no randomized controlled trials comparing the different treatment approaches. It is therefore challenging for clinicians to advise patients on what is their best treatment pathway. Physiotherapy exercise programs are less expensive and have lower risks for patients than surgical approaches. However, the success of physiotherapy in patients with massive irreparable rotator cuff tears is highly variable with published success rates of 32-96%. Several cohort studies have sought to identify if certain factors are predictive of success with physiotherapy. Several biomechanical factors were identified as possibly being related to a successful or unsuccessful outcome following physiotherapy, with complete tear of subscapularis demonstrating the strongest evidence. However, there were no appropriately designed prognostic studies. There has been a strong emphasis on biomechanical factors. Other domains such as psychosocial factors, which are important in similar patient populations, have not been explored. We recommend that further research is needed in this area and should include randomized controlled trials comparing treatment approaches and longitudinal prospective prognostic studies to identify predictors of treatment success.

Prognostic factors associated with mortality among patients receiving venovenous extracorporeal membrane oxygenation for COVID-19: a systematic review and meta-analysis

BACKGROUND

Venovenous extracorporeal membrane oxygenation (ECMO) can be considered for patients with COVID-19-associated acute respiratory distress syndrome (ARDS) who continue to deteriorate despite evidence-based therapies and lung-protective ventilation. The Extracorporeal Life Support Organization has emphasised the importance of patient selection; however, to better inform these decisions, a comprehensive and evidence-based understanding of the risk factors associated with poor outcomes is necessary. We aimed to summarise the association between pre-cannulation prognostic factors and risk of mortality in adult patients requiring venovenous ECMO for the treatment of COVID-19.

METHODS

In this systematic review and meta-analysis, we searched MEDLINE and Embase from Dec 1, 2019, to April 14, 2022, for randomised controlled trials and observational studies involving adult patients who required ECMO for COVID-19-associated ARDS and for whom pre-cannulation prognostic factors associated with in-hospital mortality were evaluated. We conducted separate meta-analyses of unadjusted and adjusted odds ratios (uORs), adjusted hazard ratios (aHRs), and mean differences, and excluded studies if these data could not be extracted. We assessed the risk of bias using the Quality in Prognosis Studies tool and certainty of evidence using the Grading of Recommendations Assessment, Development and Evaluation approach. Our protocol was registered with the Open Science Framework registry, osf.io/6gcy2.

FINDINGS

Our search identified 2888 studies, of which 42 observational cohort studies involving 17 449 patients were included. Factors that had moderate or high certainty of association with increased mortality included patient factors, such as older age (adjusted hazard ratio [aHR] 2·27 [95% CI 1·63-3·16]), male sex (unadjusted odds ratio [uOR] 1·34 [1·20-1·49]), and chronic lung disease (aHR 1·55 [1·20-2·00]); pre-cannulation disease factors, such as longer duration of symptoms (mean difference 1·51 days [95% CI 0·36-2·65]), longer duration of invasive mechanical ventilation (uOR 1·94 [1·40-2·67]), higher partial pressure of arterial carbon dioxide (mean difference 4·04 mm Hg [1·64-6·44]), and higher driving pressure (aHR 2·36 [1·40-3·97]); and centre factors, such as less previous experience with ECMO (aOR 2·27 [1·28-4·05].

INTERPRETATION

The prognostic factors identified highlight the importance of patient selection, the effect of injurious lung ventilation, and the potential opportunity for greater centralisation and collaboration in the use of ECMO for the treatment of COVID-19-associated ARDS. These factors should be carefully considered as part of a risk stratification framework when evaluating a patient for potential treatment with venovenous ECMO.

FUNDING

None.

Training parameters and longitudinal adaptations that most strongly mediate walking capacity gains from high-intensity interval training post-stroke

Background

Locomotor high-intensity interval training (HIIT) has been shown to improve walking capacity more than moderate-intensity aerobic training (MAT) after stroke, but it is unclear which training parameter(s) should be prioritized (e.g. speed, heart rate, blood lactate, step count) and to what extent walking capacity gains are the result of neuromotor versus cardiorespiratory adaptations.

Objective

Assess which training parameters and longitudinal adaptations most strongly mediate 6-minute walk distance (6MWD) gains from post-stroke HIIT.

Methods

The HIT-Stroke Trial randomized 55 persons with chronic stroke and persistent walking limitations to HIIT or MAT and collected detailed training data. Blinded outcomes included 6MWD, plus measures of neuromotor gait function (e.g. fastest 10-meter gait speed) and aerobic capacity (e.g. ventilatory threshold). This ancillary analysis used structural equation models to compare mediating effects of different training parameters and longitudinal adaptations on 6MWD.

Results

Net gains in 6MWD from HIIT versus MAT were primarily mediated by faster training speeds and longitudinal adaptations in neuromotor gait function. Training step count was also positively associated with 6MWD gains, but was lower with HIIT versus MAT, which decreased the net 6MWD gain. HIIT generated higher training heart rate and lactate than MAT, but aerobic capacity gains were similar between groups, and 6MWD changes were not associated with training heart rate, training lactate, or aerobic adaptations.

Conclusions

To increase walking capacity with post-stroke HIIT, training speed and step count appear to be the most important parameters to prioritize.

Cortical function and sensorimotor plasticity are prognostic factors associated with future low back pain after an acute episode: the Understanding persistent Pain Where it ResiDes prospective cohort study

ABSTRACT

Predicting the development of chronic low back pain (LBP) at the time of an acute episode remains challenging. The Understanding persistent Pain Where it ResiDes study aimed to identify neurobiological and psychological risk factors for chronic LBP. Individuals with acute LBP (N = 120) participated in a prospective cohort study with 6-month follow-up. Candidate predictors were selected from the neurobiological (eg, sensorimotor cortical excitability assessed by sensory and motor-evoked potentials and brain-derived neurotrophic factor genotype), psychological (eg, depression and anxiety), symptom-related (eg, LBP history), and demographic domains. Analyses involved multivariable linear regression models with pain intensity or disability degree as continuous variables. Secondary analyses involved a multivariable logistic model with the presence of LBP at 6 months (thresholding pain intensity and disability degree) as a dichotomous variable. Lower sensory cortex and corticomotor excitability, higher baseline pain intensity, higher depression, stress, and pain catastrophizing were the strongest predictors ( R2 = 0.47) of pain intensity at 6 months. Older age and higher pain catastrophizing were the strongest predictors ( R2 = 0.30) of disability at 6 months. When the LBP outcome was dichotomised, sensory cortex and corticomotor excitability, brain-derived neurotrophic factor genotype, depression and anxiety, LBP history and baseline pain intensity, discriminated between those who did and did not report LBP at 6 months (C-statistic 0.91). This study identifies novel risk factors for the development of future LBP. Neurobiological risk factors, when added to a multivariable linear regression model, explained a further 15% of the variance in the 6-month pain intensity.

Who are likely to benefit from the Good Life with osteoArthritis in Denmark (GLAD) exercise and education program? An effect modifier analysis of a randomised controlled trial

OBJECTIVE

To identify contextual factors that modify the treatment effect of the 'Good Life with osteoArthritis in Denmark' (GLAD) exercise and education programme compared to open-label placebo (OLP) on knee pain in individuals with knee osteoarthritis (OA).

METHODS

Secondary effect modifier analysis of a randomised controlled trial. 206 participants with symptomatic and radiographic knee OA were randomised to either the 8-week GLAD programme (n = 102) or OLP given as 4 intra-articular saline injections over 8 weeks (n = 104). The primary outcome was change from baseline to week 9 in the Knee injury and Osteoarthritis Outcome Score questionnaire (KOOS) pain subscale (range 0 (worst) to 100 (best)). Subgroups were created based on baseline information: BMI, swollen study knee, bilateral radiographic knee OA, sports participation as a young adult, sex, median age, a priori treatment preference, regular use of analgesics (NSAIDs or paracetamol), radiographic disease severity, and presence of constant or intermittent pain.

RESULTS

Participants who reported use of analgesics at baseline seem to benefit from the GLAD programme over OLP (subgroup contrast: 10.3 KOOS pain points (95% CI 3.0 to 17.6)). Participants with constant pain at baseline also seem to benefit from GLAD over OLP (subgroup contrast: 10.0 points (95% CI 2.8 to 17.2)).

CONCLUSIONS

These results imply that patients who take analgesics or report constant knee pain, GLAD seems to yield clinically relevant benefits on knee pain when compared to OLP. The results support a stratified recommendation of GLAD as management of knee OA.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03843931. EudraCT number 2019-000809-71.

Trans-diagnostic determinants of psychotherapeutic treatment response: The pressing need and new opportunities for a more systematic way of selecting psychotherapeutic treatment in the age of virtual service delivery

Numerous forms of psychotherapy have demonstrated effectiveness for individuals with specific mental disorders. It is, therefore, the task of the clinician to choose the most appropriate therapeutic approach for any given client to maximize effectiveness. This can prove to be a difficult task due to at least three considerations: (1) there is no treatment approach, method or model that works well on all patients, even within a particular diagnostic class; (2) several treatments are equally efficacious (i.e., more likely to be effective than no treatment at all) when considered only in terms of the patient's diagnosis; and (3) effectiveness in the real-world therapeutic setting is determined by a host of non-diagnostic factors. Typically, consideration of these latter, trans-diagnostic factors is unmethodical or altogether excluded from treatment planning - often resulting in suboptimal patient care, inappropriate clinic resource utilization, patient dissatisfaction with care, patient demoralization/hopelessness, and treatment failure. In this perspective article, we argue that a more systematic research on and clinical consideration of trans-diagnostic factors determining psychotherapeutic treatment outcome (i.e., treatment moderators) would be beneficial and - with the seismic shift toward online service delivery - is more feasible than it used to be. Such a transition toward more client-centered care - systematically considering variables such as sociodemographic characteristics, patient motivation for change, self-efficacy, illness acuity, character pathology, trauma history when making treatment choices - would result in not only decreased symptom burden and improved quality of life but also better resource utilization in mental health care and improved staff morale reducing staff burnout and turnover.

Development of a core descriptor set for Crohn's anal fistula

AIM

Crohn's anal fistula (CAF) is a complex condition, with no agreement on which patient characteristics should be routinely reported in studies. The aim of this study was to develop a core descriptor set of key patient characteristics for reporting in all CAF research.

METHOD

Candidate descriptors were generated from published literature and stakeholder suggestions. Colorectal surgeons, gastroenterologists and specialist nurses in inflammatory bowel disease took part in three rounds of an international modified Delphi process using nine-point Likert scales to rank the importance of descriptors. Feedback was provided between rounds to allow refinement of the next ratings. Patterns in descriptor voting were assessed using principal component analysis (PCA). Resulting PCA groups were used to organize items in rounds two and three. Consensus descriptors were submitted to a patient panel for feedback. Items meeting predetermined thresholds were included in the final set and ratified at the consensus meeting.

RESULTS

One hundred and thirty three respondents from 22 countries completed round one, of whom 67.0% completed round three. Ninety seven descriptors were rated across three rounds in 11 PCA-based groups. Forty descriptors were shortlisted. The consensus meeting ratified a core descriptor set of 37 descriptors within six domains: fistula anatomy, current disease activity and phenotype, risk factors, medical interventions for CAF, surgical interventions for CAF, and patient symptoms and impact on quality of life.

CONCLUSION

The core descriptor set proposed for all future CAF research reflects characteristics important to gastroenterologists and surgeons. This might aid transparent reporting in future studies.

Service evaluation of telehealth in a physiotherapy musculoskeletal setting: Patient outcomes and results from risk stratification

INTRODUCTION

Due to COVID-19 the ability to see all patients face-to-face (FTF) was removed. Services implemented telehealth to cater for patients requiring musculoskeletal care. A service evaluation was undertaken to assess the effectiveness of a mixed telehealth/FTF approach and identify if stratifying patients could help tailor intervention.

METHODS

Retrospective analysis of data collected from patients who were assessed by Musculoskeletal Physiotherapists in one Scottish health board was undertaken. Patients were divided into low, medium and high risk sub-groups through the Keele STarT MSK tool. Outcome measures for pain and musculoskeletal health were taken at baseline/discharge along with satisfaction/preference. Descriptive and Inferential statistical analysis was conducted to establish whether changes in the outcome measures within and between risk sub-groups were statistically significant.

RESULTS

Pain level difference from baseline to discharge demonstrated clinically and statistically significant improvements across all risk groups (N = 89). Musculoskeletal health demonstrated clinically significant improvements across all risk groups and statistically significant improvements in the medium/high risk groups but not the low risk. Patients with knee osteoarthritis and low back pain in the medium risk group had fewest appointments while patients with chronic shoulder pain had the most. The majority of patients were satisfied with all mediums but preferred FTF or an option between telehealth/FTF in the future.

CONCLUSION

Telehealth is a promising model of care when utilised in combination with FTF for patients with musculoskeletal conditions. Through stratification, identifying specific conditions and shared decision making it may be possible to treat certain patient groups via telehealth.