Creating a Modified Version of the Cambridge Multimorbidity Score to Predict Mortality in People Older Than 16 Years: Model Development and Validation.

BACKGROUND: No single multimorbidity measure is validated for use in NHS (National Health Service) England's General Practice Extraction Service Data for Pandemic Planning and Research (GDPPR), the nationwide primary care data set created for COVID-19 pandemic research. The Cambridge Multimorbidity Score (CMMS) is a validated tool for predicting mortality risk, with 37 conditions defined by Read Codes. The GDPPR uses the more internationally used Systematized Nomenclature of Medicine clinical terms (SNOMED CT). We previously developed a modified version of the CMMS using SNOMED CT, but the number of terms for the GDPPR data set is limited making it impossible to use this version. OBJECTIVE: We aimed to develop and validate a modified version of CMMS using the clinical terms available for the GDPPR. METHODS: We used pseudonymized data from the Oxford-Royal College of General Practitioners Research and Surveillance Centre (RSC), which has an extensive SNOMED CT list. From the 37 conditions in the original CMMS model, we selected conditions either with (1) high prevalence ratio (≥85%), calculated as the prevalence in the RSC data set but using the GDPPR set of SNOMED CT codes, divided by the prevalence included in the RSC SNOMED CT codes or (2) conditions with lower prevalence ratios but with high predictive value. The resulting set of conditions was included in Cox proportional hazard models to determine the 1-year mortality risk in a development data set (n=500,000) and construct a new CMMS model, following the methods for the original CMMS study, with variable reduction and parsimony, achieved by backward elimination and the Akaike information stopping criterion. Model validation involved obtaining 1-year mortality estimates for a synchronous data set (n=250,000) and 1-year and 5-year mortality estimates for an asynchronous data set (n=250,000). We compared the performance with that of the original CMMS and the modified CMMS that we previously developed using RSC data. RESULTS: The initial model contained 22 conditions and our final model included 17 conditions. The conditions overlapped with those of the modified CMMS using the more extensive SNOMED CT list. For 1-year mortality, discrimination was high in both the derivation and validation data sets (Harrell C=0.92) and 5-year mortality was slightly lower (Harrell C=0.90). Calibration was reasonable following an adjustment for overfitting. The performance was similar to that of both the original and previous modified CMMS models. CONCLUSIONS: The new modified version of the CMMS can be used on the GDPPR, a nationwide primary care data set of 54 million people, to enable adjustment for multimorbidity in predicting mortality in people in real-world vaccine effectiveness, pandemic planning, and other research studies. It requires 17 variables to produce a comparable performance with our previous modification of CMMS to enable it to be used in routine data using SNOMED CT.

AZD1222 effectiveness against severe COVID-19 in individuals with comorbidity or frailty: The RAVEN cohort study.

OBJECTIVES: Despite being prioritized during initial COVID-19 vaccine rollout, vulnerable individuals at high risk of severe COVID-19 (hospitalization, intensive care unit admission, or death) remain underrepresented in vaccine effectiveness (VE) studies. The RAVEN cohort study (NCT05047822) assessed AZD1222 (ChAdOx1 nCov-19) two-dose primary series VE in vulnerable populations. METHODS: Using the Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub, linked to secondary care, death registration, and COVID-19 datasets in England, COVID-19 outcomes in 2021 were compared in vaccinated and unvaccinated individuals matched on age, sex, region, and multimorbidity. RESULTS: Over 4.5 million AZD1222 recipients were matched (mean follow-up ∼5 months); 68% were ≥50 years, 57% had high multimorbidity. Overall, high VE against severe COVID-19 was demonstrated, with lower VE observed in vulnerable populations. VE against hospitalization was higher in the lowest multimorbidity quartile (91.1%; 95% CI: 90.1, 92.0) than the highest quartile (80.4%; 79.7, 81.1), and among individuals ≥65 years, higher in the 'fit' (86.2%; 84.5, 87.6) than the frailest (71.8%; 69.3, 74.2). VE against hospitalization was lowest in immunosuppressed individuals (64.6%; 60.7, 68.1). CONCLUSIONS: Based on integrated and comprehensive UK health data, overall population-level VE with AZD1222 was high. VEs were notably lower in vulnerable groups, particularly the immunosuppressed.

Body mass index and survival in people with heart failure.

AIMS: In people with heart failure (HF), a high body mass index (BMI) has been linked with better outcomes ('obesity paradox'), but there is limited evidence in community populations across long-term follow-up. We aimed to examine the association between BMI and long-term survival in patients with HF in a large primary care cohort. METHODS: We included patients with incident HF aged ≥45 years from the Clinical Practice Research Datalink (2000-2017). We used Kaplan-Meier curves, Cox regression and penalised spline methods to assess the association of pre-diagnostic BMI, based on WHO classification, with all-cause mortality. RESULTS: There were 47 531 participants with HF (median age 78.0 years (IQR 70-84), 45.8% female, 79.0% white ethnicity, median BMI 27.1 (IQR 23.9-31.0)) and 25 013 (52.6%) died during follow-up. Compared with healthy weight, people with overweight (HR 0.78, 95% CI 0.75 to 0.81, risk difference (RD) -4.1%), obesity class I (HR 0.76, 95% CI 0.73 to 0.80, RD -4.5%) and class II (HR 0.76, 95% CI 0.71 to 0.81, RD -4.5%) were at decreased risk of death, whereas people with underweight were at increased risk (HR 1.59, 95% CI 1.45 to 1.75, RD 11.2%). In those underweight, this risk was greater among men than women (p value for interaction=0.02). Class III obesity was associated with increased risk of all-cause mortality compared with overweight (HR 1.23, 95% CI 1.17 to 1.29). CONCLUSION: The U-shaped relationship between BMI and long-term all-cause mortality suggests a personalised approach to identifying optimal weight may be needed for patients with HF in primary care. Underweight people have the poorest prognosis and should be recognised as high-risk.

Context Matters: A Qualitative Synthesis of Adherence Literature for People on Hemodialysis.

BACKGROUND: Patients with ESKD treated with hemodialysis in the United States have persistently higher rates of nonadherence compared with patients in other developed countries. Nonadherence is associated with an increased risk of death and higher medical expenditure. There is an urgent need to address it with feasible, effective interventions as the prevalence of patients on hemodialysis in the United States continues to grow. However, published adherence interventions demonstrate limited long-term efficacy. METHODS: We conducted a synthesis of qualitative studies on adherence to hemodialysis treatment, medications, and fluid and dietary restrictions to identify gaps in published adherence interventions, searching PubMed, CINAHL, PsychInfo, Embase, and Web of Science databases. We analyzed qualitative data with a priori codes derived from the World Health Organization's adherence framework and subsequent codes from thematic analysis. RESULTS: We screened 1775 articles and extracted qualitative data from 12. The qualitative data revealed 20 factors unique to hemodialysis across the World Health Organization's five dimensions of adherence. In addition, two overarching themes emerged from the data: (1) adherence in the context of patients' whole lives and (2) dialysis treatment as a double-edged sword. Patient-level factors reflected in the qualitative data extended beyond knowledge about hemodialysis treatment or motivation to adhere to treatment. Patients described a profound grieving process over the loss of their "old self" that impacted adherence. They also navigated complex challenges that could be exacerbated by social determinants of health as they balanced treatment, life tasks, and social roles. CONCLUSIONS: This review adds to the growing evidence that one-size-fits-all approaches to improving adherence among patients on hemodialysis are inadequate. Adherence may improve when routine care incorporates patient context and provides ongoing support to patients and families as they navigate the logistical, physical, and psychological hardships of living with dialysis. New research is urgently needed to guide a change in course.

Natriuretic peptide testing and heart failure diagnosis in primary care: diagnostic accuracy study.

BACKGROUND: Natriuretic peptide (NP) testing is recommended for patients presenting to primary care with symptoms of chronic heart failure (HF) to prioritise referral for diagnosis. AIM: To report NP test performance at European Society of Cardiology (ESC) and National Institute for Health and Care Excellence (NICE) guideline referral thresholds. DESIGN AND SETTING: Diagnostic accuracy study using linked primary and secondary care data (2004 to 2018). METHOD: The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of NP testing for HF diagnosis was assessed. RESULTS: In total, 229 580 patients had an NP test and 21 102 (9.2%) were diagnosed with HF within 6 months. The ESC NT-proBNP threshold ≥125 pg/mL had a sensitivity of 94.6% (95% confidence interval [CI] = 94.2 to 95.0) and specificity of 50.0% (95% CI = 49.7 to 50.3), compared with sensitivity of 81.7% (95% CI = 81.0 to 82.3) and specificity of 80.3% (95% CI = 80.0 to 80.5) for the NICE NT-proBNP ≥400 pg/mL threshold. PPVs for an NT-proBNP test were 16.4% (95% CI = 16.1 to 16.6) and 30.0% (95% CI = 29.6 to 30.5) for ESC and NICE thresholds, respectively. For both guidelines, nearly all patients with an NT-proBNP level below the threshold did not have HF (NPV: ESC 98.9%, 95% CI = 98.8 to 99.0 and NICE 97.7%, 95% CI = 97.6 to 97.8). CONCLUSION: At the higher NICE chronic HF guideline NP thresholds, one in five cases are initially missed in primary care but the lower ESC thresholds require more diagnostic assessments. NP is a reliable 'rule-out' test at both cut-points. The optimal NP threshold will depend on the priorities and capacity of the healthcare system.

Combining probabilistic forecasts of COVID-19 mortality in the United States.

The COVID-19 pandemic has placed forecasting models at the forefront of health policy making. Predictions of mortality, cases and hospitalisations help governments meet planning and resource allocation challenges. In this paper, we consider the weekly forecasting of the cumulative mortality due to COVID-19 at the national and state level in the U.S. Optimal decision-making requires a forecast of a probability distribution, rather than just a single point forecast. Interval forecasts are also important, as they can support decision making and provide situational awareness. We consider the case where probabilistic forecasts have been provided by multiple forecasting teams, and we combine the forecasts to extract the wisdom of the crowd. We use a dataset that has been made publicly available from the COVID-19 Forecast Hub. A notable feature of the dataset is that the availability of forecasts from participating teams varies greatly across the 40 weeks in our study. We evaluate the accuracy of combining methods that have been previously proposed for interval forecasts and predictions of probability distributions. These include the use of the simple average, the median, and trimming methods. In addition, we propose several new weighted combining methods. Our results show that, although the median was very useful for the early weeks of the pandemic, the simple average was preferable thereafter, and that, as a history of forecast accuracy accumulates, the best results can be produced by a weighted combining method that uses weights that are inversely proportional to the historical accuracy of the individual forecasting teams.

Interval forecasts of weekly incident and cumulative COVID-19 mortality in the United States: A comparison of combining methods.

BACKGROUND: A combined forecast from multiple models is typically more accurate than an individual forecast, but there are few examples of studies of combining in infectious disease forecasting. We investigated the accuracy of different ways of combining interval forecasts of weekly incident and cumulative coronavirus disease-2019 (COVID-19) mortality. METHODS: We considered weekly interval forecasts, for 1- to 4-week prediction horizons, with out-of-sample periods of approximately 18 months ending on 8 January 2022, for multiple locations in the United States, using data from the COVID-19 Forecast Hub. Our comparison involved simple and more complex combining methods, including methods that involve trimming outliers or performance-based weights. Prediction accuracy was evaluated using interval scores, weighted interval scores, skill scores, ranks, and reliability diagrams. RESULTS: The weighted inverse score and median combining methods performed best for forecasts of incident deaths. Overall, the leading inverse score method was 12% better than the mean benchmark method in forecasting the 95% interval and, considering all interval forecasts, the median was 7% better than the mean. Overall, the median was the most accurate method for forecasts of cumulative deaths. Compared to the mean, the median's accuracy was 65% better in forecasting the 95% interval, and 43% better considering all interval forecasts. For all combining methods except the median, combining forecasts from only compartmental models produced better forecasts than combining forecasts from all models. CONCLUSIONS: Combining forecasts can improve the contribution of probabilistic forecasting to health policy decision making during epidemics. The relative performance of combining methods depends on the extent of outliers and the type of models in the combination. The median combination has the advantage of being robust to outlying forecasts. Our results support the Hub's use of the median and we recommend further investigation into the use of weighted methods.

Frequency of Renal Monitoring - Creatinine and Cystatin C (FORM-2C): an observational cohort study of patients with reduced eGFR in primary care.

BACKGROUND: Monitoring is the mainstay of chronic kidney disease management in primary care; however, there is little evidence about the best way to do this. AIM: To compare the effectiveness of estimated glomerular filtration rate (eGFR) derived from serum creatinine and serum cystatin C to predict renal function decline among those with a recent eGFR of 30-89 ml/min/1.73 m2. DESIGN AND SETTING: Observational cohort study in UK primary care. METHOD: Serum creatinine and serum cystatin C were both measured at seven study visits over 2 years in 750 patients aged ≥18 years with an eGFR of 30-89 ml/min/1.73 m2 within the previous year. The primary outcome was change in eGFR derived from serum creatinine or serum cystatin C between 6 and 24 months. RESULTS: Average change in eGFR was 0.51 ml/min/1.73 m2/year when estimated by serum creatinine and -2.35 ml/min/1.73 m2/year when estimated by serum cystatin C. The c-statistic for predicting renal decline using serum creatininederived eGFR was 0.495 (95% confidence interval [CI] = 0.471 to 0.519). The equivalent c-statistic using serum cystatin C-derived eGFR was 0.497 (95% CI = 0.468 to 0.525). Similar results were obtained when restricting analyses to those aged ≥75 or <75 years, or with eGFR ≥60 ml/min/1.73 m2. In those with eGFR <60 ml/min/1.73 m2, serum cystatin C-derived eGFR was more predictive than serum creatinine-derived eGFR for future decline in kidney function. CONCLUSION: In the primary analysis neither eGFR estimated from serum creatinine nor from serum cystatin C predicted future change in kidney function, partly due to small changes during 2 years. In some secondary analyses there was a suggestion that serum cystatin C was a more useful biomarker to estimate eGFR, especially in those with a baseline eGFR <60 ml/min/1.73 m2.

UMBRELLA protocol: systematic reviews of multivariable biomarker prognostic models developed to predict clinical outcomes in patients with heart failure.

BACKGROUND: Heart failure (HF) is a chronic and common condition with a rising prevalence, especially in the elderly. Morbidity and mortality rates in people with HF are similar to those with common forms of cancer. Clinical guidelines highlight the need for more detailed prognostic information to optimise treatment and care planning for people with HF. Besides proven prognostic biomarkers and numerous newly developed prognostic models for HF clinical outcomes, no risk stratification models have been adequately established. Through a number of linked systematic reviews, we aim to assess the quality of the existing models with biomarkers in HF and summarise the evidence they present. METHODS: We will search MEDLINE, EMBASE, Web of Science Core Collection, and the prognostic studies database maintained by the Cochrane Prognosis Methods Group combining sensitive published search filters, with no language restriction, from 1990 onwards. Independent pairs of reviewers will screen and extract data. Eligible studies will be those developing, validating, or updating any prognostic model with biomarkers for clinical outcomes in adults with any type of HF. Data will be extracted using a piloted form that combines published good practice guidelines for critical appraisal, data extraction, and risk of bias assessment of prediction modelling studies. Missing information on predictive performance measures will be sought by contacting authors or estimated from available information when possible. If sufficient high quality and homogeneous data are available, we will meta-analyse the predictive performance of identified models. Sources of between-study heterogeneity will be explored through meta-regression using pre-defined study-level covariates. Results will be reported narratively if study quality is deemed to be low or if the between-study heterogeneity is high. Sensitivity analyses for risk of bias impact will be performed. DISCUSSION: This project aims to appraise and summarise the methodological conduct and predictive performance of existing clinically homogeneous HF prognostic models in separate systematic reviews.Registration: PROSPERO registration number CRD42019086990.

Effects of antihypertensives, lipid-modifying drugs, glycaemic control drugs and sodium bicarbonate on the progression of stages 3 and 4 chronic kidney disease in adults: a systematic review and meta-analysis.

OBJECTIVE: To evaluate the effects of drug interventions that may modify the progression of chronic kidney disease (CKD) in adults with CKD stages 3 and 4. DESIGN: Systematic review and meta-analysis. METHODS: Searching MEDLINE, EMBASE, Database of Abstracts of Reviews of Effects, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, International Clinical Trials Registry Platform, Health Technology Assessment, Science Citation Index, Social Sciences Citation Index, Conference Proceedings Citation Index and Clinical Trials Register, from March 1999 to July 2018, we identified randomised controlled trials (RCTs) of drugs for hypertension, lipid modification, glycaemic control and sodium bicarbonate, compared with placebo, no drug or a drug from another class, in ≥40 adults with CKD stages 3 and/or 4, with at least 2 years of follow-up and reporting renal function (primary outcome), proteinuria, adverse events, maintenance dialysis, transplantation, cardiovascular events, cardiovascular mortality or all-cause mortality. Two reviewers independently screened citations and extracted data. For continuous outcomes, we used the ratio of means (ROM) at the end of the trial in random-effects meta-analyses. We assessed methodological quality with the Cochrane Risk of Bias Tool and confidence in the evidence using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework. RESULTS: We included 35 RCTs and over 51 000 patients. Data were limited, and heterogeneity varied. Final renal function (estimated glomerular filtration rate) was 6% higher in those taking glycaemic control drugs (ROM 1.06, 95% CI 1.02 to 1.10, I2=0%, low GRADE confidence) and 4% higher in those taking lipid-modifying drugs (ROM 1.04, 95% CI 1.00 to 1.08, I2=88%, very low GRADE confidence). For RCTs of antihypertensive drugs, there were no significant differences in renal function. Treatment with lipid-modifying drugs led to a 36% reduction in cardiovascular disease and 26% reduction in all-cause mortality. CONCLUSIONS: Glycaemic control and lipid-modifying drugs may slow the progression of CKD, but we found no pooled evidence of benefit nor harm from antihypertensive drugs. However, given the data limitations, further research is needed to confirm these findings. PROSPERO REGISTRATION NUMBER: CRD42015017501.

Weight change and the risk of incident atrial fibrillation: a systematic review and meta-analysis.

BACKGROUND: The prevalence of obesity is increasing globally and this could partly explain the worldwide increase in the prevalence of atrial fibrillation (AF), as both overweight and obesity are established risk factors. However, the relationship between weight change and risk of incident AF, independent of starting weight, remains uncertain. METHODS: MEDLINE, Embase, Pubmed, Web of Science, Cochrane Central Register of Controlled Trials, Database of Abstracts of Reviews of Effects, Trials Register-clinicaltrials.gov, CINAHL and the WHO ICTRP were searched from inception to July 2018.We included randomised controlled trials and cohort studies across all healthcare settings but excluded studies of bariatric surgery. A random effects model was used to calculate pooled hazard ratios. The primary outcome was the risk of incident AF in relation to weight change. RESULTS: Ten studies, including 108 996 people, met our inclusion criteria. For a 5% gain in weight, the incidence of AF increased by 13% (HR 1.13, 95% CI 1.04 to 1.23, I2=70%, n>20 411 in five studies; study size was unknown for one study). A 5% loss in body weight was not associated with a significant change in the incidence of AF (HR 1.04, 95% CI 0.94 to 1.16, I2=73%, n=40 704 in five studies). CONCLUSIONS: Weight gain may increase the risk of AF, but there was no clear evidence that non-surgical weight loss altered AF incidence. Strategies to prevent weight gain in the population may reduce the global burden of AF. Given the lack of studies and methodological limitations, further research is needed.

Novel genetically-modified chimpanzee adenovirus and MVA-vectored respiratory syncytial virus vaccine safely boosts humoral and cellular immunity in healthy older adults.

OBJECTIVES: Respiratory syncytial virus (RSV) causes respiratory infection across the world, with infants and the elderly at particular risk of developing severe disease and death. The replication-defective chimpanzee adenovirus (PanAd3-RSV) and modified vaccinia virus Ankara (MVA-RSV) vaccines were shown to be safe and immunogenic in young healthy adults. Here we report an extension to this first-in-man vaccine trial to include healthy older adults aged 60-75 years. METHODS: We evaluated the safety and immunogenicity of a single dose of MVA-RSV given by intra-muscular (IM) injection (n = 6), two doses of IM PanAd3-RSV given 4-weeks apart (n = 6), IM PanAd3-RSV prime and IM MVA-RSV boost 8-weeks later (n = 6), intra-nasal (IN) spray of PanAd3-RSV prime and IM MVA-RSV boost 8-weeks later (n = 6), or no vaccine (n = 6). Safety measures included all adverse events within one week of vaccination and blood monitoring. Immunogenicity measures included serum antibody responses (RSV- and PanAd3-neutralising antibody titres measured by plaque-reduction neutralisation and SEAP assays, respectively), peripheral B-cell immune responses (frequencies of F-specific IgG and IgA antibody secreting cells and memory B-cells by ex vivo and cultured dual-colour ELISpot assays respectively), and peripheral RSV-specific T-cell immune responses (frequencies of IFNγ-producing T-cells by ex vivo ELISpot and CD4+/CD8+/Tfh-like cell frequencies by ICS/FACS assay). RESULTS: The vaccines were safe and well tolerated. Compared with each individual baseline immunity the mean fold-changes in serum RSV-neutralising antibody, appearance and magnitude of F-specific IgG and IgA ASCs and expansion of CD4+/CD8+ IFNγ-producing T-cells in peripheral circulation were comparable to the results seen from younger healthy adults who received the same vaccine combination and dose. There were little/no IgA memory B-cell responses in younger and older adults. Expansion of IFNγ-producing T-cells was most marked in older adults following IM prime, with balanced CD4+ and CD8+ T cell responses. The RSV-specific immune responses to vaccination did not appear to be attenuated in the presence of PanAd3 (vector) neutralising antibody. CONCLUSIONS: PanAd3-RSV and MVA-RSV was safe and immunogenic in older adults and the parallel induction of RSV-specific humoral and cellular immunity merits further assessment in providing protection from severe disease.

How Do Home and Clinic Blood Pressure Readings Compare in Pregnancy?

Hypertensive disorders during pregnancy result in substantial maternal morbidity and are a leading cause of maternal deaths worldwide. Self-monitoring of blood pressure (BP) might improve the detection and management of hypertensive disorders of pregnancy, but few data are available, including regarding appropriate thresholds. This systematic review and individual patient data analysis aimed to assess the current evidence on differences between clinic and self-monitored BP through pregnancy. MEDLINE and 10 other electronic databases were searched for articles published up to and including July 2016 using a strategy designed to capture all the literature on self-monitoring of BP during pregnancy. Investigators of included studies were contacted requesting individual patient data: self-monitored and clinic BP and demographic data. Twenty-one studies that utilized self-monitoring of BP during pregnancy were identified. Individual patient data from self-monitored and clinic readings were available from 7 plus 1 unpublished articles (8 studies; n=758) and 2 further studies published summary data. Analysis revealed a mean self-monitoring clinic difference of ≤1.2 mm Hg systolic BP throughout pregnancy although there was significant heterogeneity (difference in means, I2 >80% throughout pregnancy). Although the overall population difference was small, levels of white coat hypertension were high, particularly toward the end of pregnancy. The available literature includes no evidence of a systematic difference between self and clinic readings, suggesting that appropriate treatment and diagnostic thresholds for self-monitoring during pregnancy would be equivalent to standard clinic thresholds.