Accuracy of automated computer-aided risk scoring systems to estimate the risk of COVID-19: a retrospective cohort study

BACKGROUND

In the UK National Health Service (NHS), the patient's vital signs are monitored and summarised into a National Early Warning Score (NEWS) score. A set of computer-aided risk scoring systems (CARSS) was developed and validated for predicting in-hospital mortality and sepsis in unplanned admission to hospital using NEWS and routine blood tests results. We sought to assess the accuracy of these models to predict the risk of COVID-19 in unplanned admissions during the first phase of the pandemic.

METHODS

Adult ( > = 18 years) non-elective admissions discharged (alive/deceased) between 11-March-2020 to 13-June-2020 from two acute hospitals with an index NEWS electronically recorded within ± 24 h of admission. We identified COVID-19 admission based on ICD-10 code 'U071' which was determined by COVID-19 swab test results (hospital or community). We assessed the performance of CARSS (CARS_N, CARS_NB, CARM_N, CARM_NB) for predicting the risk of COVID-19 in terms of discrimination (c-statistic) and calibration (graphically).

RESULTS

The risk of in-hospital mortality following emergency medical admission was 8.4% (500/6444) and 9.6% (620/6444) had a diagnosis of COVID-19. For predicting COVID-19 admissions, the CARS_N model had the highest discrimination 0.73 (0.71 to 0.75) and calibration slope 0.81 (0.72 to 0.89) compared to other CARSS models: CARM_N (discrimination:0.68 (0.66 to 0.70) and calibration slope 0.47 (0.41 to 0.54)), CARM_NB (discrimination:0.68 (0.65 to 0.70) and calibration slope 0.37 (0.31 to 0.43)), and CARS_NB (discrimination:0.68 (0.66 to 0.70) and calibration slope 0.56 (0.47 to 0.64)).

CONCLUSIONS

The CARS_N model is reasonably accurate for predicting the risk of COVID-19. It may be clinically useful as an early warning system at the time of admission especially to triage large numbers of unplanned admissions because it requires no additional data collection and is readily automated.

Evaluating the prospective utility of pharmacogenetics reporting among Canadian Armed Forces personnel receiving pharmacotherapy: a preliminary assessment towards precision psychiatric care

Pharmacological interventions for treating posttraumatic stress disorder in Canadian Armed Forces (CAF) members and Veterans often achieve modest results. The field of pharmacogenetics, or the study of how genes influence an individual's response to different medications, offers insight into how prior knowledge of gene-drug interactions may potentially improve the trial-and-error process of drug selection in pharmacotherapy, thereby improving treatment effects and remission rates. Given the relative recency of pharmacogenetics testing and sparse research in military samples, we used pharmacogenetics testing in a small pilot group (n=23) of CAF members and Veterans who were already engaged in pharmacotherapy for a service-related mental health condition to better understand the associated opportunities and challenges of pharmacogenetics testing in this population. Our preliminary evaluation involved: (1) reporting the prevalence of pharmacogenetics testing 'bin' status according to participants' reports ('green', 'yellow' or 'red'; intending to signal 'go', 'caution' or 'stop', regarding the potential for gene-drug interactions); (2) calculating the percentage of currently prescribed psychotropic medications that were assessed and included in the reports; (3) evaluating whether prescribers used pharmacogenetics testing information according to clinical notes and (4) collecting informal feedback from participating psychiatrists. While pharmacogenetics testing appeared to provide valuable information for a number of clients, a major limitation was the number of commonly prescribed medications not included in the reports.

Are we meeting the standards set for informed consent in spinal surgery?

INTRODUCTION

Informed consent empowers patients to exercise their autonomy and actively participate in their medical care. Guidance published by the British Association of Spine Surgeons (BASS) lists three components of consent: provision of information booklets, patient-centred dialogue and completion of appropriate consent forms. The aim of the study was to review the quality of the spinal surgery consent process against the BASS guidance in a single tertiary neurosurgery centre in London.

METHODS

Retrospective review of clinic letters and consent forms was performed for 100 consecutive cases of elective, non-instrumented spinal decompression surgeries performed in 2019. Documentation was graded for inclusion of the intended benefit (improvement of pain/prevention of neurological deterioration), alternative management options (including no treatment), surgical options and risks (infection, bleeding, paralysis, sphincter disturbances, dural tear and recurrence). Provision of supplementary information booklets was recorded. Two-tailed Fisher exact test was used to calculate statistical significance where appropriate.

RESULTS

Documentation of indications and risks of elective spinal surgery, specifically risk of recurrence (62%) and sphincter disturbance (85%), was suboptimal on the consent forms. Documentation of these risks was also poor in clinic letters (<50%). Alternative treatment options were explained in less than half of the clinic letters, and there was no documentation of information booklet provision prior to elective surgeries.

CONCLUSION

Lack of informed consent plays a major role in medical malpractice claims in spinal surgery. Poor documentation puts the surgeon in a liable position. BASS guidance could be implemented to create a more standardised process of consent in spinal surgery.

Implementation and clinical utility of a Computer-Aided Risk Score for Mortality (CARM): a qualitative study

OBJECTIVES

The Computer-Aided Risk Score for Mortality (CARM) estimates the risk of in-hospital mortality following acute admission to the hospital by automatically amalgamating physiological measures, blood tests, gender, age and COVID-19 status. Our aims were to implement the score with a small group of practitioners and understand their first-hand experience of interacting with the score in situ.

DESIGN

Pilot implementation evaluation study involving qualitative interviews.

SETTING

This study was conducted in one of the two National Health Service hospital trusts in the North of England in which the score was developed.

PARTICIPANTS

Medical, older person and ICU/anaesthetic consultants and specialist grade registrars (n=116) and critical outreach nurses (n=7) were given access to CARM. Nine interviews were conducted in total, with eight doctors and one critical care outreach nurse.

INTERVENTIONS

Participants were given access to the CARM score, visible after login to the patients' electronic record, along with information about the development and intended use of the score.

RESULTS

Four themes and 14 subthemes emerged from reflexive thematic analysis: (1) current use (including support or challenge clinical judgement and decision making, communicating risk of mortality and professional curiosity); (2) barriers and facilitators to use (including litigation, resource needs, perception of the evidence base, strengths and limitations), (3) implementation support needs (including roll-out and integration, access, training and education); and (4) recommendations for development (including presentation and functionality and potential additional data). Barriers and facilitators to use, and recommendations for development featured highly across most interviews.

CONCLUSION

Our in situ evaluation of the pilot implementation of CARM demonstrated its scope in supporting clinical decision making and communicating risk of mortality between clinical colleagues and with service users. It suggested to us barriers to implementation of the score. Our findings may support those seeking to develop, implement or improve the adoption of risk scores.

Methods of policy monitoring in physical activity promotion: a systematic review across different levels of government

Background

Even though the importance of policy monitoring in public health has increased in the last decades, there is still a lack of understanding what different approaches of policy monitoring exist and which methodology they employ. In order to address this research gap, this review attempts to provide a comprehensive overview about the methods of policy monitoring in the field of physical activity promotion.

Methods

A systematic search was conducted in five scientific databases, using the terms “physical activity”, “policy” and “monitoring” and their variations. In total, 12.963 studies were identified and, after the elimination of duplicates, screened independently by two reviewers. During full text analysis, information on the methods applied for policy monitoring was extracted and studies were categorized based on their key characteristics (monitoring tool, policy level, and setting).

Results

The search yielded in a total of 112 studies that were structured into seven categories: Report Cards on Physical Activity for Children and Youth, HEPA Monitoring Framework, HEPA Policy Audit Tool, national policies, subnational policies, school setting, and childcare setting. Across all categories, policy monitoring focused mainly on national level policies in a single country. Differences were identified with regards to the level of government involvement which allowed to differentiate between research-driven approaches (little or no government involvement), government-driven approaches (led by governments), and co-production approaches (strong collaboration between researchers and governments).

Conclusions

Research-driven, government-driven and co-production approaches have different strengths and weaknesses with regards to the monitoring of policies. Awareness needs to be raised regarding the implications of these approaches, and more research is needed to analyse the impact of policy monitoring on policy-making in public health.

Development and validation of automated computer-aided risk scores to predict in-hospital mortality for emergency medical admissions with COVID-19: a retrospective cohort development and validation study

OBJECTIVES

There are no established mortality risk equations specifically for unplanned emergency medical admissions which include patients with SARS-19 (COVID-19). We aim to develop and validate a computer-aided risk score (CARMc19) for predicting mortality risk by combining COVID-19 status, the first electronically recorded blood test results and the National Early Warning Score (NEWS2).

DESIGN

Logistic regression model development and validation study.

SETTING

Two acute hospitals (York Hospital-model development data; Scarborough Hospital-external validation data).

PARTICIPANTS

Adult (aged ≥16 years) medical admissions discharged over a 24-month period with electronic NEWS and blood test results recorded on admission. We used logistic regression modelling to predict the risk of in-hospital mortality using two models: (1) CARMc19_N: age+sex+NEWS2 including subcomponents+COVID19; (2) CARMc19_NB: CARMc19_N in conjunction with seven blood test results and acute kidney injury score. Model performance was evaluated according to discrimination (c-statistic), calibration (graphically) and clinical usefulness at NEWS2 thresholds of 4+, 5+, 6+.

RESULTS

The risk of in-hospital mortality following emergency medical admission was similar in development and validation datasets (8.4% vs 8.2%). The c-statistics for predicting mortality for CARMc19_NB is better than CARMc19_N in the validation dataset (CARMc19_NB=0.88 (95% CI 0.86 to 0.90) vs CARMc19_N=0.86 (95% CI 0.83 to 0.88)). Both models had good calibration (CARMc19_NB=1.01 (95% CI 0.88 to 1.14) and CARMc19_N:0.95 (95% CI 0.83 to 1.06)). At all NEWS2 thresholds (4+, 5+, 6+) model, CARMc19_NB had better sensitivity and similar specificity.

CONCLUSIONS

We have developed a validated CARMc19 scores with good performance characteristics for predicting the risk of in-hospital mortality. Since the CARMc19 scores place no additional data collection burden on clinicians, it may now be carefully introduced and evaluated in hospitals with sufficient informatics infrastructure.

Staffing and Capacity Planning for SARS-CoV-2 Monoclonal Antibody Infusion Facilities: A Performance Estimation Calculator Based on Discrete-Event Simulations

Background

The COVID-19 pandemic has significantly stressed healthcare systems. The addition of monoclonal antibody (mAb) infusions, which prevent severe disease and reduce hospitalizations, to the repertoire of COVID-19 countermeasures offers the opportunity to reduce system stress but requires strategic planning and use of novel approaches. Our objective was to develop a web-based decision-support tool to help existing and future mAb infusion facilities make better and more informed staffing and capacity decisions.

Materials and Methods

Using real-world observations from three medical centers operating with federal field team support, we developed a discrete-event simulation model and performed simulation experiments to assess performance of mAb infusion sites under different conditions.

Results

162,000 scenarios were evaluated by simulations. Our analyses revealed that it was more effective to add check-in staff than to add additional nurses for middle-to-large size sites with ≥2 infusion nurses; that scheduled appointments performed better than walk-ins when patient load was not high; and that reducing infusion time was particularly impactful when load on resources was only slightly above manageable levels.

Discussion

Physical capacity, check-in staff, and infusion time were as important as nurses for mAb sites. Health systems can effectively operate an infusion center under different conditions to provide mAb therapeutics even with relatively low investments in physical resources and staff.

Conclusion

Simulations of mAb infusion sites were used to create a capacity planning tool to optimize resource utility and allocation in constrained pandemic conditions, and more efficiently treat COVID-19 patients at existing and future mAb infusion sites.

Long-term outcome of patients receiving haematopoietic allogeneic stem cell transplantation as first transplant for high-risk Hodgkin lymphoma: a retrospective analysis from the Lymphoma Working Party-EBMT

We analysed long-term outcome of patients receiving haematopoietic allogeneic stem cell transplantation (allo-HSCT) as a first transplant for high-risk Hodgkin lymphoma (HL). One hundred and ninety patients were included in this study, 63% of them had previously received brentuximab vedotin and/or checkpoint inhibitors. Seventy patients (37%) received an unrelated donor allo-HSCT, 99 (51%) had myeloablative conditioning (MAC) and 60% had in vivo T-cell/depleted grafts (TCD). The 100-day cumulative incidence (CI) of grade II-IV acute graft-versus-host disease (GVHD) was 25% and the 3-year CI of chronic GVHD was 38%. The 3-year CI of non-relapse mortality (NRM) and relapse rate were 21% and 38% respectively. After a median follow-up of 58 months, 3-year overall survival (OS) and progression-free survival (PFS) were 58% and 41% respectively. Multivariate analysis showed that, in comparison to reduced-intensity conditioning regimens with or without TCD, MAC using TCD had similar NRM and a lower risk of relapse leading to significantly better OS and PFS. MAC without TCD was associated with higher NRM and worse survival outcomes. These results suggest that in patients with high-risk HL and candidates of allo-HSCT, a MAC strategy with TCD might be the best option.

1536 Neuroanatomy, Not Just for Budding Neurosurgeons. Motivations for Participating in An Extra-Curricular Neuroanatomy Course for Undergraduates

Introduction

Extra-curricular activities form an important part of undergraduate education as they give students the opportunity to explore subjects of interest. There is significant demand within the undergraduate population for further teaching in neuro-related specialities. The aim of this online twelve-week course was to provide neuroanatomy teaching in greater breadth and detail than possible in the undergraduate curriculum. We sought to gauge motivations for involvement.

Method

Delegates (n = 166) from six UK universities were asked to complete a short questionnaire examining motivations and future career plans prior to the course beginning, only those who consented were involved further in the analysis (n = 98).

Results

Motivations for involvement were predominantly to develop a greater understanding of neuroanatomy (63.3%), to support career plans (13.3%) or to support preparation for an examination or competition (8.2%). The majority (56.1%) had no particular speciality in mind. For those who did, a range of specialities including neurosurgery (24.5%), neurology (8.2%) was given.

Conclusions

There is clear interest within the undergraduate population for more specialised extra-curricular activities in addition to conventional experiences such as conferences. Online courses run over multiple weeks provide further scope for depth and exploration of subjects in further detail. In this course, the majority of delegates did not have a particular speciality in mind, demonstrating neuroanatomy to be a popular subject regardless of potential career plans. For students looking to pursue a career in neuro-related specialities, courses are perceived as important opportunities to support future career development.

1520 Decoding Neurophobia – Insights from an Undergraduate Neuroanatomy Course

Introduction

Neurophobia is a common multifaceted issue amongst students studying medical sciences at an undergraduate level associated with difficulty in understanding neuroscience topics and ongoing negative perceptions of clinical neurosciences. We sought to examine whether neurophobia was present even amongst students who participated in an extracurricular neuroanatomy teaching course.

Method

Prior to the beginning of a twelve-week online neuroanatomy course, delegates were asked to complete a short questionnaire examining perceptions of neurophobia and specialities of interest. This was repeated after the course. This course was open to all undergraduate students in the UK and covered material beyond the remits of the undergraduate curriculum.

Results

From the 166 signups, 98 students completed the pre-course questionnaire. As expected, the majority of students (n = 83) taking part did not identify as neurophobic, describing the subject area as ‘interesting’, ‘enjoyable’ and ‘challenging’. Students who identified as neurophobic described neuroanatomy as ‘complex’ or ‘overwhelming’. Some students (n = 12) continued to describe themselves as neurophobic at the end of the course, despite this 7 of those students continue to consider a future career in a neuro-related speciality.

Conclusions

The fact that students with Neurophobia attended this extra-curricular course speaks volumes of how perception and self-motivation of a student are important for learning a subject. All students who participated in this course recognised the complexity and interesting nature of neuroanatomy. This experience highlights the challenge of medical educators to provide teaching experiences that are stimulating and enjoyable, but not overwhelming.

Predictive accuracy of enhanced versions of the on-admission National Early Warning Score in estimating the risk of COVID-19 for unplanned admission to hospital: a retrospective development and validation study

Background

The novel coronavirus SARS-19 produces ‘COVID-19’ in patients with symptoms. COVID-19 patients admitted to the hospital require early assessment and care including isolation. The National Early Warning Score (NEWS) and its updated version NEWS2 is a simple physiological scoring system used in hospitals, which may be useful in the early identification of COVID-19 patients. We investigate the performance of multiple enhanced NEWS2 models in predicting the risk of COVID-19.

Methods

Our cohort included unplanned adult medical admissions discharged over 3 months (11 March 2020 to 13 June 2020 ) from two hospitals (YH for model development; SH for external model validation). We used logistic regression to build multiple prediction models for the risk of COVID-19 using the first electronically recorded NEWS2 within ± 24 hours of admission. Model M0’ included NEWS2; model M1’ included NEWS2 + age + sex, and model M2’ extends model M1’ with subcomponents of NEWS2 (including diastolic blood pressure + oxygen flow rate + oxygen scale). Model performance was evaluated according to discrimination (c statistic), calibration (graphically), and clinical usefulness at NEWS2 ≥ 5.

Results

The prevalence of COVID-19 was higher in SH (11.0 %=277/2520) than YH (8.7 %=343/3924) with a higher first NEWS2 scores ( SH 3.2 vs YH 2.8) but similar in-hospital mortality (SH 8.4 % vs YH 8.2 %). The c-statistics for predicting the risk of COVID-19 for models M0’,M1’,M2’ in the development dataset were: M0’: 0.71 (95 %CI 0.68–0.74); M1’: 0.67 (95 %CI 0.64–0.70) and M2’: 0.78 (95 %CI 0.75–0.80)). For the validation datasets the c-statistics were: M0’ 0.65 (95 %CI 0.61–0.68); M1’: 0.67 (95 %CI 0.64–0.70) and M2’: 0.72 (95 %CI 0.69–0.75) ). The calibration slope was similar across all models but Model M2’ had the highest sensitivity (M0’ 44 % (95 %CI 38-50 %); M1’ 53 % (95 %CI 47-59 %) and M2’: 57 % (95 %CI 51-63 %)) and specificity (M0’ 75 % (95 %CI 73-77 %); M1’ 72 % (95 %CI 70-74 %) and M2’: 76 % (95 %CI 74-78 %)) for the validation dataset at NEWS2 ≥ 5.

Conclusions

Model M2’ appears to be reasonably accurate for predicting the risk of COVID-19. It may be clinically useful as an early warning system at the time of admission especially to triage large numbers of unplanned hospital admissions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06951-x.

307 Improving Compliance with Standard of Care Guidelines for Suspected Cauda Equina Syndrome Across A District General Hospital Network

Introduction

Cauda equina syndrome (CES) is a spinal emergency that cannot be reliably detected through clinical examination alone and as a result requires prompt MR imaging to provide a diagnosis. This audit examined compliance to standard of care following service improvements in line with the updated SBNS/BASS national guidelines for CES.

Method

A retrospective analysis of 200 patients referred to neurosurgery for suspected CES: 100 pre- and 100 post-service improvement SBNS guideline implementation.

The online neurosurgical database was reviewed, cases assessed for completeness of referral information (including appropriate exam and pre-referral MRI) with patient demographics, referring hospital and outcome also recorded.

Results

Prior to the SBNS guidelines only 19 patients received MRI prior to referral, 70% of all referrals were incomplete or contained erroneous clinical information. Post-service improvements there was a 68% increase of pre-referral MRI (32 cases), and an improvement in quality of clinical information with only 19% of referrals providing insufficient or unreliable information.

Conclusions

Through relatively simple changes to local policy, patient care flow and education of emergency department clinicians we have significantly improved pre-referral MRI rates as well as overall referral quality across the whole DGH network.

Clinical characteristics and outcome of critically ill COVID-19 patients with acute kidney injury: a single centre cohort study

BACKGROUND

Acute kidney injury (AKI) is a common manifestation among patients critically ill with SARS-CoV-2 infection (Coronavirus 2019) and is associated with significant morbidity and mortality. The pathophysiology of renal failure in this context is not fully understood, but likely to be multifactorial. The intensive care unit outcomes of patients following COVID-19 acute critical illness with associated AKI have not been fully explored. We conducted a cohort study to investigate the risk factors for acute kidney injury in patients admitted to and intensive care unit with COVID-19, its incidence and associated outcomes.

METHODS

We reviewed the medical records of all patients admitted to our adult intensive care unit suffering from SARS-CoV-2 infection from 14th March 2020 until 12th May 2020. Acute kidney injury was defined using the Kidney Disease Improving Global Outcome (KDIGO) criteria. The outcome analysis was assessed up to date as 3rd of September 2020.

RESULTS

A total of 81 patients admitted during this period. All patients had acute hypoxic respiratory failure and needed either noninvasive or invasive mechanical ventilatory support. Thirty-six patients (44%) had evidence of AKI (Stage I-33%, Stage II-22%, Renal Replacement Therapy (RRT)-44%). All patients with AKI stage III had RRT. Age, diabetes mellitus, immunosuppression, lymphopenia, high D-Dimer levels, increased APACHE II and SOFA scores, invasive mechanical ventilation and use of inotropic or vasopressor support were significantly associated with AKI. The peak AKI was at day 4 and mean duration of RRT was 12.5 days. The mortality was 25% for the AKI group compared to 6.7% in those without AKI. Among those received RRT and survived their illness, the renal function recovery is complete and back to baseline in all patients.

CONCLUSION

Acute kidney injury and renal replacement therapy is common in critically ill patients presenting with COVID-19. It is associated with increased severity of illness on admission to ICU, increased mortality and prolonged ICU and hospital length of stay. Recovery of renal function was complete in all survived patients.

Use of the first National Early Warning Score recorded within 24 hours of admission to estimate the risk of in-hospital mortality in unplanned COVID-19 patients: a retrospective cohort study

OBJECTIVES

Although the National Early Warning Score (NEWS) and its latest version NEWS2 are recommended for monitoring deterioration in patients admitted to hospital, little is known about their performance in COVID-19 patients. We aimed to compare the performance of the NEWS and NEWS2 in patients with COVID-19 versus those without during the first phase of the pandemic.

DESIGN

A retrospective cross-sectional study.

SETTING

Two acute hospitals (Scarborough and York) are combined into a single dataset and analysed collectively.

PARTICIPANTS

Adult (≥18 years) non-elective admissions discharged between 11 March 2020 and 13 June 2020 with an index or on-admission NEWS2 electronically recorded within ±24 hours of admission to predict mortality at four time points (in-hospital, 24 hours, 48 hours and 72 hours) in COVID-19 versus non-COVID-19 admissions.

RESULTS

Out of 6480 non-elective admissions, 620 (9.6%) had a diagnosis of COVID-19. They were older (73.3 vs 67.7 years), more often male (54.7% vs 50.1%), had higher index NEWS (4 vs 2.5) and NEWS2 (4.6 vs 2.8) scores and higher in-hospital mortality (32.1% vs 5.8%). The c-statistics for predicting in-hospital mortality in COVID-19 admissions was significantly lower using NEWS (0.64 vs 0.74) or NEWS2 (0.64 vs 0.74), however, these differences reduced at 72hours (NEWS: 0.75 vs 0.81; NEWS2: 0.71 vs 0.81), 48 hours (NEWS: 0.78 vs 0.81; NEWS2: 0.76 vs 0.82) and 24hours (NEWS: 0.84 vs 0.84; NEWS2: 0.86 vs 0.84). Increasing NEWS2 values reflected increased mortality, but for any given value the absolute risk was on average 24% higher (eg, NEWS2=5: 36% vs 9%).

CONCLUSIONS

The index or on-admission NEWS and NEWS2 offers lower discrimination for COVID-19 admissions versus non-COVID-19 admissions. The index NEWS2 was not proven to be better than the index NEWS. For each value of the index NEWS/NEWS2, COVID-19 admissions had a substantially higher risk of mortality than non-COVID-19 admissions which reflects the increased baseline mortality risk of COVID-19.

The Impact of Prior Season Vaccination on Subsequent Influenza Vaccine Effectiveness to Prevent Influenza-related Hospitalizations Over 4 Influenza Seasons in Canada

BACKGROUND

Recent studies have demonstrated the possibility of negative associations between prior influenza vaccines and subsequent influenza vaccine effectiveness (VE), depending on season and strain. We investigated this association over 4 consecutive influenza seasons (2011-2012 through 2014-2015) in Canada.

METHODS

Using a matched test-negative design, laboratory-confirmed influenza cases and matched test-negative controls admitted to hospitals were enrolled. Patients were stratified into 4 groups according to influenza vaccine history (not vaccinated current and prior season [referent], vaccinated prior season only, vaccinated current season only, and vaccinated both current and prior season). Conditional logistic regression was used to estimate VE; prior vaccine impact was assessed each season for overall effect and effect stratified by age (<65 years, ≥65 years) and type/subtype (A/H1N1, A/H3N2, influenza B).

RESULTS

Overall, mainly nonsignificant associations were observed. Trends of nonsignificant decreased VE among patients repeatedly vaccinated in both prior and current season relative to the current season only were observed in the A/H3N2-dominant seasons of 2012-2013 and 2014-2015. Conversely, in 2011-2012, during which B viruses circulated, and in 2013-2014, when A/H1N1 circulated, being vaccinated in both seasons tended to result in a high VE in the current season against the dominant circulating subtype.

CONCLUSIONS

Prior vaccine impact on subsequent VE among Canadian inpatients was mainly nonsignificant. Even in circumstances where we observed a trend of negative impact, being repeatedly vaccinated was still more effective than not receiving the current season's vaccine. These findings favor continuation of annual influenza vaccination recommendations, particularly in older adults.

CLINICAL TRIALS REGISTRATION

NCT01517191.

Hyperbaric oxygen and focused rehabilitation program: a feasibility study in improving upper limb motor function after stroke

Neuroplasticity and recovery after stroke can be enhanced by a rehabilitation program pertinent to upper limb motor function exercise and mental imagery (EMI) as well as hyperbaric oxygen therapy (HBOT). We assessed feasibility and safety of the combined approach utilizing both HBOT and EMI, and to derive preliminary estimates of its efficacy. In this randomized controlled trial, 27 patients with upper extremity hemiparesis at 3-48 months after stroke were randomized to receive either a complementary rehabilitation program of HBOT-EMI (intervention group), or EMI alone (control group). Feasibility and safety were assessed as total session attendance, duration of sessions, attrition rates, missing data, and intervention-related adverse events. Secondary clinical outcomes were assessed with both objective tools and self-reported measures at baseline, 8 weeks (end of treatment), and 12-weeks follow-up. Session attendance, duration, and attrition rate did not differ between the groups; there were no serious adverse events. Compared with baseline, there were significant sustained improvements of objective and subjective outcomes' measures in the intervention group, and a single improvement in an objective measure in the control group. Between-group outcome comparisons were not statistically significant. This study demonstrated that the combination HBOT-EMI was a safe and feasible approach in patients recovering from chronic stroke. There were also trends for improved motor function of the affected upper limb after the treatments. ClinicalTrials.gov registration no.: NCT02666469. Novelty HBOT combined with an upper limb exercise and mental imagery rehabilitation program is feasible and safe in chronic stroke patients. This combined approach showed trends for improved functional recovery.

Validation of the Seegene RV15 multiplex PCR for the detection of influenza A subtypes and influenza B lineages during national influenza surveillance in hospitalized adults

Background. The Serious Outcomes Surveillance Network of the Canadian Immunization Research Network (CIRN SOS) has been performing active influenza surveillance since 2009 (ClinicalTrials.gov identifier: NCT01517191). Influenza A and B viruses are identified and characterized using real-time reverse-transcriptase polymerase chain reaction (RT-PCR), and multiplex testing has been performed on a subset of patients to identify other respiratory virus aetiologies. Since both methods can identify influenza A and B, a direct comparison was performed.Methods. Validated real-time RT-PCRs from the World Health Organization (WHO) to identify influenza A and B viruses, characterize influenza A viruses into the H1N1 or H3N2 subtypes and describe influenza B viruses belonging to the Yamagata or Victoria lineages. In a subset of patients, the Seeplex RV15 One-Step ACE Detection assay (RV15) kit was also used for the detection of other respiratory viruses.Results. In total, 1111 nasopharyngeal swabs were tested by RV15 and real-time RT-PCRs for influenza A and B identification and characterization. For influenza A, RV15 showed 98.0 % sensitivity, 100 % specificity and 99.7 % accuracy. The performance characteristics of RV15 were similar for influenza A subtypes H1N1 and H3N2. For influenza B, RV15 had 99.2 % sensitivity, 100 % specificity and 99.8 % accuracy, with similar assay performance being shown for both the Yamagata and Victoria lineages.Conclusions. Overall, the detection of circulating subtypes of influenza A and lineages of influenza B by RV15 was similar to detection by real-time RT-PCR. Multiplex testing with RV15 allows for a more comprehensive respiratory virus surveillance in hospitalized adults, without significantly compromising the reliability of influenza A or B virus detection.

Computer-aided National Early Warning Score to predict the risk of sepsis following emergency medical admission to hospital: a model development and external validation study

BACKGROUND

In hospitals in England, patients' vital signs are monitored and summarized into the National Early Warning Score (NEWS); this score is more accurate than the Quick Sepsis-related Organ Failure Assessment (qSOFA) score at identifying patients with sepsis. We investigated the extent to which the accuracy of the NEWS is enhanced by developing and comparing 3 computer-aided NEWS (cNEWS) models (M0 = NEWS alone, M1 = M0 + age + sex, M2 = M1 + subcomponents of NEWS + diastolic blood pressure) to predict the risk of sepsis.

METHODS

We included all emergency medical admissions of patients 16 years of age and older discharged over 24 months from 2 acute care hospital centres (York Hospital [YH] for model development and a combined data set from 2 hospitals [Diana, Princess of Wales Hospital and Scunthorpe General Hospital] in the Northern Lincolnshire and Goole National Health Service Foundation Trust [NH] for external model validation). We used a validated Canadian method for defining sepsis from administrative hospital data.

RESULTS

The prevalence of sepsis was lower in YH (4.5%, 1596/35 807) than in NH (8.5%, 2983/35 161). The C statistic increased across models (YH: M0 0.705, M1 0.763, M2 0.777; NH: M0 0.708, M1 0.777, M2 0.791). For NEWS of 5 or higher, sensitivity increased (YH: 47.24% v. 50.56% v. 52.69%; NH: 37.91% v. 43.35% v. 48.07%), the positive likelihood ratio increased (YH: 2.77 v. 2.99 v. 3.06; NH: 3.18 v. 3.32 v. 3.45) and the positive predictive value increased (YH: 11.44% v. 12.24% v. 12.49%; NH: 22.75% v. 23.55% v. 24.21%).

INTERPRETATION

From the 3 cNEWS models, model M2 is the most accurate. Given that it places no additional burden of data collection on clinicians and can be automated, it may now be carefully introduced and evaluated in hospitals with sufficient informatics infrastructure.

CHECK: A randomized trial evaluating the efficacy and cost-effectiveness of home visitation in pediatric weight loss treatment

BACKGROUND

Socioeconomically-disadvantaged households have a high prevalence of pediatric overweight/obesity, and also face barriers to accessing weight loss treatment in healthcare settings. Delivering family-based pediatric weight loss treatment in the home setting may enhance its efficacy by facilitating treatment attendance, enabling more tailored treatment recommendations informed by observations of the home environment, and increasing accountability. This paper describes the design of the Creating Health Environments for Chicago Kids (CHECK) Trial, which evaluates the efficacy, cost-effectiveness, and mechanisms of home visitation in family-based pediatric weight loss treatment for children in low-income households.

DESIGN

CHECK is a two-arm, parallel group, randomized controlled trial that is enrolling N = 266 children, ages 6-12 y, who have overweight/obesity (BMI percentile ≥85) and live in a low-income household. Participants are randomized in a 1:1 ratio to either standard of care family-based weight loss treatment delivered in the home, or the identical intervention delivered in an academic medical center. The primary outcome is change in child BMI z-score from baseline to 12 months. Program delivery costs are rigorously documented to enable cost-effectiveness analyses from the societal and payer perspectives. Objectively-documented changes to the home environment and aspects of intervention delivery (e.g., hours of in-person contact received, quantity of behavioral goals set per session) will be tested as hypothesized treatment mechanisms.

IMPLICATIONS

Findings will inform the design of future interventions, and treatment dissemination decisions by public health agencies and third-party payers.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT03195790.

Performance of externally validated enhanced computer-aided versions of the National Early Warning Score in predicting mortality following an emergency admission to hospital in England: a cross-sectional study

OBJECTIVES

In the English National Health Service, the patient's vital signs are monitored and summarised into a National Early Warning Score (NEWS) to support clinical decision making, but it does not provide an estimate of the patient's risk of death. We examine the extent to which the accuracy of NEWS for predicting mortality could be improved by enhanced computer versions of NEWS (cNEWS).

DESIGN

Logistic regression model development and external validation study.

SETTING

Two acute hospitals (YH-York Hospital for model development; NH-Northern Lincolnshire and Goole Hospital for external model validation).

PARTICIPANTS

Adult (≥16 years) medical admissions discharged over a 24-month period with electronic NEWS (eNEWS) recorded on admission are used to predict mortality at four time points (in-hospital, 24 hours, 48 hours and 72 hours) using the first electronically recorded NEWS (model M0) versus a cNEWS model which included age+sex (model M1) +subcomponents of NEWS (including diastolic blood pressure) (model M2).

RESULTS

The risk of dying in-hospital following emergency medical admission was 5.8% (YH: 2080/35 807) and 5.4% (NH: 1900/35 161). The c-statistics for model M2 in YH for predicting mortality (in-hospital=0.82, 24 hours=0.91, 48 hours=0.88 and 72 hours=0.88) was higher than model M0 (in-hospital=0.74, 24 hours=0.89, 48 hours=0.86 and 72 hours=0.85) with higher Positive Predictive Value (PPVs) for in-hospital mortality (M2 19.3% and M0 16.6%). Similar findings were seen in NH. Model M2 performed better than M0 in almost all major disease subgroups.

CONCLUSIONS

An externally validated enhanced computer-aided NEWS model (cNEWS) incrementally improves on the performance of a NEWS only model. Since cNEWS places no additional data collection burden on clinicians and is readily automated, it may now be carefully introduced and evaluated to determine if it can improve care in hospitals that have eNEWS systems.

A prospective study of consecutive emergency medical admissions to compare a novel automated computer-aided mortality risk score and clinical judgement of patient mortality risk

OBJECTIVES

To compare the performance of a validated automatic computer-aided risk of mortality (CARM) score versus medical judgement in predicting the risk of in-hospital mortality for patients following emergency medical admission.

DESIGN

A prospective study.

SETTING

Consecutive emergency medical admissions in York hospital.

PARTICIPANTS

Elderly medical admissions in one ward were assigned a risk of death at the first post-take ward round by consultant staff over a 2-week period. The consultant medical staff used the same variables to assign a risk of death to the patient as the CARM (age, sex, National Early Warning Score and blood test results) but also had access to the clinical history, examination findings and any immediately available investigations such as ECGs. The performance of the CARM versus consultant medical judgement was compared using the c-statistic and the positive predictive value (PPV).

RESULTS

The in-hospital mortality was 31.8% (130/409). For patients with complete blood test results, the c-statistic for CARM was 0.75 (95% CI: 0.69 to 0.81) versus 0.72 (95% CI: 0.66 to 0.78) for medical judgements (p=0.28). For patients with at least one missing blood test result, the c-statistics were similar (medical judgements 0.70 (95% CI: 0.60 to 0.81) vs CARM 0.70 (95% CI: 0.59 to 0.80)). At a 10% mortality risk, the PPV for CARM was higher than medical judgements in patients with complete blood test results, 62.0% (95% CI: 51.2 to 71.9) versus 49.2% (95% CI: 39.8 to 58.5) but not when blood test results were missing, 50.0% (95% CI: 24.7 to 75.3) versus 53.3% (95% CI: 34.3 to 71.7).

CONCLUSIONS

CARM is comparable with medical judgements in discriminating in-hospital mortality following emergency admission to an elderly care ward. CARM may have a promising role in supporting medical judgements in determining the patient's risk of death in hospital. Further evaluation of CARM in routine practice is required.

Usability testing of MySkinSelfie: a mobile phone application for skin self-monitoring

Teledermatology generally involves doctors taking images of patients; however, patients increasingly want to own or have easy access to their health data. MySkinSelfie ( http://myskinselfie.com) is a mobile phone application (app) designed to improve the quality, consistency and accessibility of patient-held photos, and was developed to give patients the ability to generate and hold their own skin images to help guide their skin care. This study assessed the usability of this app in a cohort of patients attending a National Health Service Dermatology clinic. Patients were asked to use the app but were not given specific tasks to achieve. Of the 102 patients recruited, 32 downloaded the app and registered an account, 21 took at least one photo (median 5, range 1-103) and 19 completed the usability questionnaire. The majority of questionnaire respondents found the app easy to use but were more neutral on whether it really helped them to manage their skin problem. MySkinSelfie has been shown to be easy to use. Self-monitoring of skin problems may be useful for a subset of patients, and this is likely to depend on diagnosis, age and other patient factors.

Understanding and applying practitioner and patient views on the implementation of a novel automated Computer-Aided Risk Score (CARS) predicting the risk of death following emergency medical admission to hospital: qualitative study

OBJECTIVES

The Computer-Aided Risk Score (CARS) estimates the risk of death following emergency admission to medical wards using routinely collected vital signs and blood test data. Our aim was to elicit the views of healthcare practitioners (staff) and service users and carers (SU/C) on (1) the potential value, unintended consequences and concerns associated with CARS and practitioner views on (2) the issues to consider before embedding CARS into routine practice.

SETTING

This study was conducted in two National Health Service (NHS) hospital trusts in the North of England. Both had in-house information technology (IT) development teams, mature IT infrastructure with electronic National Early Warning Score (NEWS) and were capable of integrating NEWS with blood test results. The study focused on emergency medical and elderly admissions units. There were 60 and 39 acute medical/elderly admissions beds at the two NHS hospital trusts.

PARTICIPANTS

We conducted eight focus groups with 45 healthcare practitioners and two with 11 SU/Cs in two NHS acute hospitals.

RESULTS

Staff and SU/Cs recognised the potential of CARS but were clear that the score should not replace or undermine clinical judgments. Staff recognised that CARS could enhance clinical decision-making/judgments and aid communication with patients. They wanted to understand the components of CARS and be reassured about its accuracy but were concerned about the impact on intensive care and blood tests.

CONCLUSION

Risk scores are widely used in healthcare, but their development and implementation do not usually involve input from practitioners and SU/Cs. We contributed to the development of CARS by eliciting views of staff and SU/Cs who provided important, often complex, insights to support the development and implementation of CARS to ensure successful implementation in routine clinical practice.

The inclusion of delirium in version 2 of the National Early Warning Score will substantially increase the alerts for escalating levels of care: findings from a retrospective database study of emergency medical admissions in two hospitals

BACKGROUND

The National Early Warning Score (NEWS) is being replaced with NEWS2 which adds 3 points for new confusion or delirium. We estimated the impact of adding delirium on the number of medium/high level alerts that are triggers to escalate care.

METHODS

Analysis of emergency medical admissions in two acute hospitals (York Hospital (YH) and Northern Lincolnshire and Goole NHS Foundation Trust hospitals (NH)) in England. Twenty per cent were randomly assigned to have delirium.

RESULTS

The number of emergency admissions (YH: 35584; NH: 35795), mortality (YH: 5.7%; NH: 5.5%), index NEWS (YH: 2.5; NH: 2.1) and numbers of NEWS recorded (YH: 879193; NH: 884072) were similar in each hospital. The mean number of patients with medium level alerts per day increased from 55.3 (NEWS) to 69.5 (NEWS2), a 25.7% increase in YH and 64.1 (NEWS) to 77.4 (NEWS2), a 20.7% increase in NH. The mean number of patients with high level alerts per day increased from 27.3 (NEWS) to 34.4 (NEWS2), a 26.0% increase in YH and 29.9 (NEWS) to 37.7 (NEWS2), a 26.1% increase in NH.

CONCLUSIONS

The addition of delirium in NEWS2 will have a substantial increase in medium and high level alerts in hospitalised emergency medical patients. Rigorous evaluation of NEWS2 is required before widespread implementation because the extent to which staff can cope with this increase without adverse consequences remains unknown.

Abstract P6-18-27: Withdrawn

This abstract was withdrawn by the authors.

Citation Format: Odom D, Mitra D, Hollis K, Richardson D, Kaye JA, McRoy L. Withdrawn [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P6-18-27.

Development and validation of a novel computer-aided score to predict the risk of in-hospital mortality for acutely ill medical admissions in two acute hospitals using their first electronically recorded blood test results and vital signs: a cross-sectional study

OBJECTIVES

There are no established mortality risk equations specifically for emergency medical patients who are admitted to a general hospital ward. Such risk equations may be useful in supporting the clinical decision-making process. We aim to develop and externally validate a computer-aided risk of mortality (CARM) score by combining the first electronically recorded vital signs and blood test results for emergency medical admissions.

DESIGN

Logistic regression model development and external validation study.

SETTING

Two acute hospitals (Northern Lincolnshire and Goole NHS Foundation Trust Hospital (NH)-model development data; York Hospital (YH)-external validation data).

PARTICIPANTS

Adult (aged ≥16 years) medical admissions discharged over a 24-month period with electronic National Early Warning Score(s) and blood test results recorded on admission.

RESULTS

The risk of in-hospital mortality following emergency medical admission was 5.7% (NH: 1766/30 996) and 6.5% (YH: 1703/26 247). The C-statistic for the CARM score in NH was 0.87 (95% CI 0.86 to 0.88) and was similar in an external hospital setting YH (0.86, 95% CI 0.85 to 0.87) and the calibration slope included 1 (0.97, 95% CI 0.94 to 1.00).

CONCLUSIONS

We have developed a novel, externally validated CARM score with good performance characteristics for estimating the risk of in-hospital mortality following an emergency medical admission using the patient's first, electronically recorded, vital signs and blood test results. Since the CARM score places no additional data collection burden on clinicians and is readily automated, it may now be carefully introduced and evaluated in hospitals with sufficient informatics infrastructure.

A comparison of logistic regression models with alternative machine learning methods to predict the risk of in-hospital mortality in emergency medical admissions via external validation

We compare the performance of logistic regression with several alternative machine learning methods to estimate the risk of death for patients following an emergency admission to hospital based on the patients' first blood test results and physiological measurements using an external validation approach. We trained and tested each model using data from one hospital (n = 24,696) and compared the performance of these models in data from another hospital (n = 13,477). We used two performance measures - the calibration slope and area under the receiver operating characteristic curve. The logistic model performed reasonably well - calibration slope: 0.90, area under the receiver operating characteristic curve: 0.847 compared to the other machine learning methods. Given the complexity of choosing tuning parameters of these methods, the performance of logistic regression with transformations for in-hospital mortality prediction was competitive with the best performing alternative machine learning methods with no evidence of overfitting.

FAANG, establishing metadata standards, validation and best practices for the farmed and companion animal community

The Functional Annotation of ANimal Genomes (FAANG) project aims, through a coordinated international effort, to provide high quality functional annotation of animal genomes with an initial focus on farmed and companion animals. A key goal of the initiative is to ensure high quality and rich supporting metadata to describe the project's animals, specimens, cell cultures and experimental assays. By defining rich sample and experimental metadata standards and promoting best practices in data descriptions, deposition and openness, FAANG champions higher quality and reusability of published datasets. FAANG has established a Data Coordination Centre, which sits at the heart of the Metadata and Data Sharing Committee. It continues to evolve the metadata standards, support submissions and, crucially, create powerful and accessible tools to support deposition and validation of metadata. FAANG conforms to the findable, accessible, interoperable, and reusable (FAIR) data principles, with high quality, open access and functionally interlinked data. In addition to data generated by FAANG members and specific FAANG projects, existing datasets that meet the main—or more permissive legacy—standards are incorporated into a central, focused, functional data resource portal for the entire farmed and companion animal community. Through clear and effective metadata standards, validation and conversion software, combined with promotion of best practices in metadata implementation, FAANG aims to maximise effectiveness and inter‐comparability of assay data. This supports the community to create a rich genome‐to‐phenotype resource and promotes continuing improvements in animal data standards as a whole.

The National Early Warning Score and its subcomponents recorded within ±24 h of emergency medical admission are poor predictors of hospital-acquired acute kidney injury

Hospital-acquired acute kidney injury (H-AKI) is a common cause of avoidable morbidity and mortality. Therefore, in the current study, we investigated whether vital signs data from patients, as defined by a National Early Warning Score (NEWS), can predict H-AKI following emergency admission to hospital. We analysed all emergency admissions (n=33,608) to York Hospital with NEWS data over a 24-month period. Here, we report the area under the curve (AUC) for logistic regression models that used the index NEWS (model A0), plus age and sex (A1), plus subcomponents of NEWS (A2) and two-way interactions (A3), and similarly for maximum NEWS (models B0,B1,B2,B3). Of the total emergency admissions, 4.05% (1,361/33,608) had H-AKI. Models using the index NEWS had lower AUCs (0.59-0.68) than models using the maximum NEWS AUCs (0.75-0.77). The maximum NEWS model (B3) was more sensitive than the index NEWS model (A0) (67.60% vs 19.84%) but identified twice as many cases as being at risk of H-AKI (9581 vs 4099) at a NEWS of 5. Based on these results, we suggest that the index NEWS is a poor predictor of H-AKI. The maximum NEWS is a better predictor but appears to be unfeasible because it is only knowable in retrospect and is associated with a substantial increase in workload, albeit with improved sensitivity.