Objective: To describe the discrimination and calibration of clinical prediction models, identify characteristics that contribute to better predictions and investigate predictors that are associated with unplanned hospital readmissions.Design: Systematic review and meta-analysis.Data source: Medline, EMBASE, ICTPR (for study protocols) and Web of Science (for conference proceedings) were searched up to 25 August 2020.Eligibility criteria for selecting studies: Studies were eligible if they reported on (1) hospitalised adult patients with acute heart disease; (2) a clinical presentation of prediction models with c-statistic; (3) unplanned hospital readmission within 6 months. Primary and secondary outcome measures: Model discrimination for unplanned hospital readmission within 6 months measured using concordance (c) statistics and model calibration. Meta-regression and subgroup analyses were performed to investigate predefined sources of heterogeneity. Outcome measures from models reported in multiple independent cohorts and similarly defined risk predictors were pooled.Results: Sixty studies describing 81 models were included: 43 models were newly developed, and 38 were externally validated. Included populations were mainly patients with heart failure (HF) (n=29). The average age ranged between 56.5 and 84 years. The incidence of readmission ranged from 3% to 43%. Risk of bias (RoB) was high in almost all studies. The c-statistic was <0.7 in 72 models, between 0.7 and 0.8 in 16 models and >0.8 in 5 models. The study population, data source and number of predictors were significant moderators for the discrimination. Calibration was reported for 27 models. Only the GRACE (Global Registration of Acute Coronary Events) score had adequate discrimination in independent cohorts (0.78, 95% CI 0.63 to 0.86). Eighteen predictors were pooled. Conclusion: Some promising models require updating and validation before use in clinical practice. The lack of independent validation studies, high RoB and low consistency in measured predictors limit their applicability.PROSPERO registration number: CRD42020159839.
MULTIFILE
AbstractObjective: Many older individuals receive rehabilitation in an out-of-hospital setting (OOHS) after acute hospitalization; however, its effect onmobility and unplanned hospital readmission is unclear. Therefore, a systematic review and meta-analysis were conducted on this topic.Data Sources: Medline OVID, Embase OVID, and CINAHL were searched from their inception until February 22, 2018.Study Selection: OOHS (ie, skilled nursing facilities, outpatient clinics, or community-based at home) randomized trials studying the effect ofmultidisciplinary rehabilitation were selected, including those assessing exercise in older patients (mean age 65y) after discharge from hospitalafter an acute illness.Data Extraction: Two reviewers independently selected the studies, performed independent data extraction, and assessed the risk of bias.Outcomes were pooled using fixed- or random-effect models as appropriate. The main outcomes were mobility at and unplanned hospitalreadmission within 3 months of discharge.Data Synthesis: A total of 15 studies (1255 patients) were included in the systematic review and 12 were included in the meta-analysis (7assessing mobility using the 6-minute walk distance [6MWD] test and 7 assessing unplanned hospital readmission). Based on the 6MWD, patientsreceiving rehabilitation walked an average of 23 m more than controls (95% confidence interval [CI]Z: 1.34 to 48.32; I2: 51%). Rehabilitationdid not lower the 3-month risk of unplanned hospital readmission (risk ratio: 0.93; 95% CI: 0.73-1.19; I2: 34%). The risk of bias was present,mainly due to the nonblinded outcome assessment in 3 studies, and 7 studies scored this unclearly.Conclusion: OOHS-based multidisciplinary rehabilitation leads to improved mobility in older patients 3 months after they are discharged fromhospital following an acute illness and is not associated with a lower risk of unplanned hospital readmission within 3 months of discharge.However, the wide 95% CIs indicate that the evidence is not robust.
Er lijkt een duidelijke mate van evidentie te bestaan betreffende de relatie fysieke activiteit, respectievelijk fitheid en gezondheid in de algemene populatie en bij bepaalde pathologieën. Er is evenwel nog behoefte aan verder wetenschappelijk onderzoek naar mogelijke determinanten en onderliggende mechanismen, als ook naar evidentie bij bepaalde, specifieke aandoeningen. Tevens mag duidelijk zijn dat ondanks de bestaande evidentie fysieke activiteit/oefening te weinig toegepast wordt in de gezondheidszorg. Het onderzoek naar de effectiviteit van gezondheidskundige interventies is dan ook uitermate belangrijk. Dit lectoraat hoopt dan ook een bescheiden bijdrage hieraan te kunnen leveren. Hiervoor heeft zij reeds afspraken tot samenwerking met de academische en medische wereld (in Utrecht, Amsterdam, Maastricht en Leuven), met de gezondheidszorg (RIVM Bilthoven en GG&GD Utrecht) en met de beroepen- of bedrijfswereld (Politie regio Utrecht; Enraf Nonius, Delft). De beoogde doelstellingen zullen echter naar alle waarschijnlijkheid beduidend meer tijd in beslag nemen dan de periode van 4 jaar die de Stichting Kennis Ontwikkeling voorzien heeft met betrekking tot het oprichten en financieren van de lectoraten.
