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AbstractObjectiveTo review and appraise the validity and usefulness of published and preprint reports of prediction models for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19 infection or being admitted to hospital or dying with the disease.DesignLiving systematic review and critical appraisal by the covid-PRECISE (Precise Risk Estimation to optimise covid-19 Care for Infected or Suspected patients in diverse sEttings) group.Data sourcesPubMed and Embase through Ovid, up to 17 February 2021, supplemented with arXiv, medRxiv, and bioRxiv up to 5 May 2020.Study selectionStudies that developed or validated a multivariable covid-19 related prediction model.Data extractionAt least two authors independently extracted data using the CHARMS (critical appraisal and data extraction for systematic reviews of prediction modelling studies) checklist; risk of bias was assessed using PROBAST (prediction model risk of bias assessment tool).Results126 978 titles were screened, and 412 studies describing 731 new prediction models or validations were included. Of these 731, 125 were diagnostic models (including 75 based on medical imaging) and the remaining 606 were prognostic models for either identifying those at risk of covid-19 in the general population (13 models) or predicting diverse outcomes in those individuals with confirmed covid-19 (593 models). Owing to the widespread availability of diagnostic testing capacity after the summer of 2020, this living review has now focused on the prognostic models. Of these, 29 had low risk of bias, 32 had unclear risk of bias, and 545 had high risk of bias. The most common causes for high risk of bias were inadequate sample sizes (n=408, 67%) and inappropriate or incomplete evaluation of model performance (n=338, 56%). 381 models were newly developed, and 225 were external validations of existing models. The reported C indexes varied between 0.77 and 0.93 in development studies with low risk of bias, and between 0.56 and 0.78 in external validations with low risk of bias. The Qcovid models, the PRIEST score, Carr’s model, the ISARIC4C Deterioration model, and the Xie model showed adequate predictive performance in studies at low risk of bias. Details on all reviewed models are publicly available at https://www.covprecise.org/.ConclusionPrediction models for covid-19 entered the academic literature to support medical decision making at unprecedented speed and in large numbers. Most published prediction model studies were poorly reported and at high risk of bias such that their reported predictive performances are probably optimistic. Models with low risk of bias should be validated before clinical implementation, preferably through collaborative efforts to also allow an investigation of the heterogeneity in their performance across various populations and settings. Methodological guidance, as provided in this paper, should be followed because unreliable predictions could cause more harm than benefit in guiding clinical decisions. Finally, prediction modellers should adhere to the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) reporting guideline.Systematic review registrationProtocol https://osf.io/ehc47/, registration https://osf.io/wy245.Readers’ noteThis article is the final version of a living systematic review that has been updated over the past two years to reflect emerging evidence. This version is update 4 of the original article published on 7 April 2020 (BMJ 2020;369:m1328). Previous updates can be found as data supplements (https://www.bmj.com/content/369/bmj.m1328/related#datasupp). When citing this paper please consider adding the update number and date of access for clarity.

Aims/hypothesis The aim of this work was to assess the association of advanced glycation end-products (AGEs), measured by skin autofluorescence (SAF), with prevalent heart failure, and with systolic and diastolic cardiac function, in a large population-based cohort study. Methods We assessed the cross-sectional association between SAF and prevalent heart failure among 2426 participants from the population-based Rotterdam Study, using logistic regression. Next, among individuals free of heart failure ( N =2362), we examined the link between SAF (on a continuous scale) and echocardiographic parameters of left ventricular (LV) systolic and diastolic function using linear regressions. Analyses were adjusted for traditional cardiovascular risk factors. Results Higher levels of SAF were associated with higher odds of prevalent heart failure (multivariable adjusted OR 2.90 [95% CI 1.80, 4.62] for one unit higher SAF value). Among individuals without heart failure, one unit increase in SAF was associated with 0.98% lower LV ejection fraction (mean difference [β] −0.98% [95% CI −1.45%, −0.50%]). The association was stronger among participants with diabetes (β −1.84% [95% CI −3.10%, −0.58%] and β −0.78% [95% CI −1.29%, −0.27%] among participants with and without diabetes, respectively). Associations of SAF with diastolic function parameters were not apparent, except in men with diabetes. Conclusions/interpretation AGE accumulation was independently associated with prevalent heart failure. Among individuals free of heart failure, AGEs were associated with cardiac function, in particular systolic function. This association was present in participants with and without diabetes and was more prominent in those with diabetes. Graphical abstract

To establish age- and sex-specific distribution of the infrarenal abdominal aortic diameters (IAD) among non-aneurysmal elderly population and to investigate the associations between traditional cardiovascular risk factors and IAD in men and women. We included 4032 participants (mean age 67.2 years; 60.4% women) from the population-based Rotterdam Study, free of cardiovascular disease, who underwent IAD ultrasound assessment between 2009–2014. Linear regression analysis was used to identify determinants of IAD. The medians (inter-quartile range) of absolute IAD and body surface area (BSA)-adjusted IAD were 17.0 (15.0–18.0) mm and 9.3 (8.5–10.2) mm for women and 19.0 (18.0–21.0) mm and 9.4 (8.6–10.3) mm for men, respectively. There was a non-linear relationship between age and IAD. IAD increased steeply with advancing age and up to 70 years. After around 75 years of age, the diameter values reached a plateau. Waist circumference and diastolic blood pressure were associated with larger diameters in both sexes. Body mass index [Effect estimate (95% CI): 0.04 (0.00 to 0.08)], systolic blood pressure [− 0.01(− 0.02 to 0.00)], current smoking [0.35 (0.06 to 0.65)], total cholesterol levels [− 0.21 (− 0.31 to − 0.11)], and lipid-lowering medication [− 0.43 (− 0.67 to − 0.19)] were significantly associated with IAD in women. Sex differences in IAD values diminished after taking BSA into account. The increase in diameters was attenuated after 70 years. Differences were observed in the associations of several cardiovascular risk factors with IAD among men and women.

Background Advanced glycation end products (AGEs) have been linked to cardiovascular disease (CVD), especially coronary heart disease (CHD), but their role in CVD pathogenesis remains unclear. Therefore, we investigated cross-sectional associations of skin AGEs with subclinical atherosclerosis, arterial stiffness, and hypertension after confirming their relation with CHD. Methods In the population-based Rotterdam Study, skin AGEs were measured as skin autofluorescence (SAF). Prevalent MI was obtained from digital medical records. Carotid plaques, carotid intima-media thickness (IMT), coronary artery calcification (CAC), pulse wave velocity (PWV), and hypertension were assessed. Associations of SAF with endophenotypes were investigated in logistic and linear regression models adjusting for common cardiovascular risk factors. Effect modification by sex, diabetes mellitus, and chronic kidney disease (CKD) was tested. Results 3001 participants were included (mean age 73 (SD 9) years, 57% women). One unit higher SAF was associated with the presence of carotid plaques (OR 1.2 (0.92, 1.57)), a higher max IMT (0.08 SD (0.01, 0.15)), higher CAC (OR 2.2 (1.39, 3.48)), and PWV (0.09 SD (0.01, 0.16)), but not with hypertension (OR 0.99 (0.81, 1.21)). The associations with endophenotypes were more pronounced in men and participants with diabetes or CKD with significant interactions. Conclusions Previously documented associations between SAF and CVD, also found in our study, may be explained by the endophenotypes atherosclerosis and arterial stiffness, especially in men and individuals with diabetes or CKD, but not by hypertension. Longitudinal studies are needed to replicate these findings and to test if SAF is an independent risk factor or biomarker of CVD. Trial registration : The Rotterdam Study has been entered into the Netherlands National Trial Register (NTR; www.trialregister.nl ) and the WHO International Clinical Trials Registry Platform (ICTRP; www.who.int/ictrp/network/primary/en/ ) under shared catalogue number NTR6831.

Non-communicable diseases (NCDs) are leading causes of premature disability and death worldwide. However, the lifetime risk of developing any NCD is unknown, as are the effects of shared common risk factors on this risk. Between July 6, 1989, and January 1, 2012, we followed participants from the prospective Rotterdam Study aged 45 years and older who were free from NCDs at baseline for incident stroke, heart disease, diabetes, chronic respiratory disease, cancer, and neurodegenerative disease. We quantified occurrence/co-occurrence and remaining lifetime risk of any NCD in a competing risk framework. We additionally studied the lifetime risk of any NCD, age at onset, and overall life expectancy for strata of 3 shared risk factors at baseline: smoking, hypertension, and overweight. During 75,354 person-years of follow-up from a total of 9,061 participants (mean age 63.9 years, 60.1% women), 814 participants were diagnosed with stroke, 1,571 with heart disease, 625 with diabetes, 1,004 with chronic respiratory disease, 1,538 with cancer, and 1,065 with neurodegenerative disease. NCDs tended to co-occur substantially, with 1,563 participants (33.7% of those who developed any NCD) diagnosed with multiple diseases during follow-up. The lifetime risk of any NCD from the age of 45 years onwards was 94.0% (95% CI 92.9%-95.1%) for men and 92.8% (95% CI 91.8%-93.8%) for women. These risks remained high (>90.0%) even for those without the 3 risk factors of smoking, hypertension, and overweight. Absence of smoking, hypertension, and overweight was associated with a 9.0-year delay (95% CI 6.3-11.6) in the age at onset of any NCD. Furthermore, the overall life expectancy for participants without these risk factors was 6.0 years (95% CI 5.2-6.8) longer than for those with all 3 risk factors. Participants aged 45 years and older without the 3 risk factors of smoking, hypertension, and overweight at baseline spent 21.6% of their remaining lifetime with 1 or more NCDs, compared to 31.8% of their remaining life for participants with all of these risk factors at baseline. This difference corresponds to a 2-year compression of morbidity of NCDs. Limitations of this study include potential residual confounding, unmeasured changes in risk factor profiles during follow-up, and potentially limited generalisability to different healthcare settings and populations not of European descent. Our study suggests that in this western European community, 9 out of 10 individuals aged 45 years and older develop an NCD during their remaining lifetime. Among those individuals who develop an NCD, at least a third are subsequently diagnosed with multiple NCDs. Absence of 3 common shared risk factors is associated with compression of morbidity of NCDs. These findings underscore the importance of avoidance of these common shared risk factors to reduce the premature morbidity and mortality attributable to NCDs.

Background HRV has mostly shown associations with systolic dysfunction and more recently, with diastolic dysfunction in Heart failure (HF) patients. But the role of sympathetic nervous system in changes of left ventricular (LV) systolic and diastolic function and new-onset HF has not been extensively studied. Methods Among 3157 men and 4405 women free of HF and atrial fibrillation retrospectively included from the population-based Rotterdam Study, we used linear mixed models to examine associations of RR-interval differences and standard deviation of RR-intervals corrected for heart rate (RMSSDc and SDNNc) with longitudinal changes of LV ejection fraction (LVEF), E/A ratio, left atrial (LA) diameter, E/e’ ratio. Afterwards, using cox regressions, we examined their association with new-onset HF. Results Mean (SD) age was 65 (9.95) in men and 65.7 (10.2) in women. Every unit increase in log RMSSDc was accompanied by 0.75% (95%CI:-1.11%;-0.39%) and 0.31% (− 0.60%;-0.01%) lower LVEF among men and women each year, respectively. Higher log RMSSDc was linked to 0.03 (− 0.04;-0.01) and 0.02 (− 0.03;-0.003) lower E/A and also − 1.76 (− 2.77;− 0.75) and − 1.18 (− 1.99;-0.38) lower LVM index in both sexes and 0.72 mm (95% CI: − 1.20;-0.25) smaller LA diameters in women. The associations with LVEF in women diminished after excluding HF cases during the first 3 years of follow-up. During a median follow-up of 8.7 years, hazard ratios (95%CI) for incident HF were 1.34 (1.08;1.65) for log RMSSDc in men and 1.15 (0.93;1.42) in women. SDNNc showed similar associations. Conclusions Indices of HRV were associated with worse systolic function in men but mainly with improvement in LA size in women. Higher HRV was associated with higher risk of new-onset HF in men. Our findings highlight potential sex differences in autonomic function underlying cardiac dysfunction and heart failure in the general population.

IntroductionIt is known that only a limited proportion of developed clinical prediction models (CPMs) are implemented and/or used in clinical practice. This may result in a large amount of research waste, even when considering that some CPMs may demonstrate poor performance. Cross-sectional estimates of the numbers of CPMs that have been developed, validated, evaluated for impact or utilized in practice, have been made in specific medical fields, but studies across multiple fields and studies following up the fate of CPMs are lacking.Methods and analysisWe have conducted a systematic search for prediction model studies published between January 1995 and December 2020 using the Pubmed and Embase databases, applying a validated search strategy. Taking random samples for every calendar year, abstracts and articles were screened until a target of 100 CPM development studies were identified. Next, we will perform a forward citation search of the resulting CPM development article cohort to identify articles on external validation, impact assessment or implementation of those CPMs. We will also invite the authors of the development studies to complete an online survey to track implementation and clinical utilization of the CPMs.We will conduct a descriptive synthesis of the included studies, using data from the forward citation search and online survey to quantify the proportion of developed models that are validated, assessed for their impact, implemented and/or used in patient care. We will conduct time-to-event analysis using Kaplan-Meier plots.Ethics and disseminationNo patient data are involved in the research. Most information will be extracted from published articles. We request written informed consent from the survey respondents. Results will be disseminated through publication in a peer-reviewed journal and presented at international conferences.OSF registration(https://osf.io/nj8s9).

PurposeBreast cancer treatment has been associated with vascular pathology. It is unclear if such treatment is also associated with long-term cerebrovascular changes. We studied the association between radiotherapy and chemotherapy with carotid pathology and brain perfusion in breast cancer survivors.MethodsWe included 173 breast cancer survivors exposed to radiotherapy and chemotherapy, assessed ± 21.2 years after cancer diagnosis, and 346 age-matched cancer-free women (1:2) selected from the population-based Rotterdam Study. Outcome measures were carotid plaque score, intima-media thickness (IMT), total cerebral blood flow (tCBF), and brain perfusion. Additionally, we investigated the association between inclusion of the carotid artery in the radiation field (no/small/large part), tumor location, and these outcome measures within cancer survivors.ResultsCancer survivors had lower tCBF (− 19.6 ml/min, 95%CI − 37.3;− 1.9) and brain perfusion (− 2.5 ml/min per 100 ml, 95%CI − 4.3;− 0.7) than cancer-free women. No statistically significant group differences were observed regarding plaque score or IMT. Among cancer survivors, a large versus a small part of the carotid artery in the radiation field was associated with a higher IMT (0.05, 95%CI0.01;0.09). Also, survivors with a right-sided tumor had lower left carotid plaque score (− 0.31, 95%CI − 0.60;− 0.02) and higher brain perfusion (3.5 ml/min per 100 ml, 95%CI 0.7;6.2) than those with a left-sided tumor.ConclusionsOn average two decades post-diagnosis, breast cancer survivors had lower tCBF and brain perfusion than cancer-free women. Also, survivors with a larger area of the carotid artery within the radiation field had a larger IMT. Future studies should confirm if these cerebrovascular changes underlie the frequently observed cognitive problems in cancer survivors.

Background Despite the growing burden of heart failure (HF), there have been no recommendations for use of any of the primary prevention models in the existing guidelines. HF was also not included as an outcome in the American College of Cardiology/American Heart Association (ACC/AHA) risk score. Methods Among 2743 men and 3646 women aged ≥ 55 years, free of HF, from the population-based Rotterdam Study cohort, 4 Cox models were fitted using the predictors of the ACC/AHA, ARIC and Health-ABC risk scores. Performance of the models for 10-year HF prediction was evaluated. Afterwards, performance and net reclassification improvement (NRI) for adding NT-proBNP to the ACC/AHA model were assessed. Results During a median follow-up of 13 years, 429 men and 489 women developed HF. The ARIC model had the highest performance [c-statistic (95% confidence interval [CI]): 0.80 (0.78; 0.83) and 0.80 (0.78; 0.83) in men and women, respectively]. The c-statistic for the ACC/AHA model was 0.76 (0.74; 0.78) in men and 0.77 (0.75; 0.80) in women. Adding NT-proBNP to the ACC/AHA model increased the c-statistic to 0.80 (0.78 to 0.83) in men and 0.81 (0.79 to 0.84) in women. Sensitivity and specificity of the ACC/AHA model did not drastically change after addition of NT-proBNP. NRI(95%CI) was − 23.8% (− 19.2%; − 28.4%) in men and − 27.6% (− 30.7%; − 24.5%) in women for events and 57.9% (54.8%; 61.0%) in men and 52.8% (50.3%; 55.5%) in women for non-events. Conclusions Acceptable performance of the model based on risk factors included in the ACC/AHA model advocates use of this model for prediction of HF risk in primary prevention setting. Addition of NT-proBNP modestly improved the model performance but did not lead to relevant discrimination improvement in clinical risk reclassification.

Concerns have been expressed about the abundance of new clinical prediction models (CPMs) proposed in the literature. However, the extent of this proliferation in prediction research remains unclear. This study aimed to estimate the total and annual number of CPM development-related publications available across all medical fields. Using a validated search strategy, we conducted a systematic search of literature for prediction model studies published in Pubmed and Embase between 1995 and the end of 2020. By taking random samples for each year, we identified eligible studies that developed a multivariable model (ie, diagnostic or prognostic) for individual-level prediction of a health outcome across all medical fields. Exclusion criteria included development of models with a single predictor, studies not involving humans, methodological studies, conference abstracts, articles with unavailable full text, and those not available in English. We estimated the total and annual number of published regression-based multivariable CPM development articles, based on the total number of publications, proportion of included articles, and the search sensitivity. Furthermore, we used an adjusted Poisson regression to extrapolate our results to the period 1950-2024. Additionally, we estimated the number of articles that developed CPMs using techniques other than regression (eg, machine learning). From a random sample of 10,660 articles published between 1995 and 2020, 109 regression-based CPM development articles were included. We estimated that 82,772 (95% CI 65,313-100,231) CPM development articles using regression were published, with an acceleration in model development from 2010 onward. With the addition of articles that developed non-regression-based CPMs, the number increased to 147,714 (95% CI 125,201-170,226). After extrapolation to the years 1950-2024, the number of articles increased to 156,673 and 248,431 for regression-based models and total CPMs, respectively. Based on a representative sample of publications from the literature, we estimated that nearly 250,000 articles reporting the development of CPMs across all medical fields were published until 2024. CPM development-related publications continue to increase in number. To prevent research waste and close the gap between research and clinical practice, focus should shift away from developing new CPMs to facilitating model validation and impact assessment of the plethora of existing CPMs. Limitations of this study include restriction of search to articles available in English and development of the validated search strategy prior to the popularity of artificial intelligence and machine learning models.