Aims/hypothesis The aims of this study were to identify all published prognostic models predicting retinopathy risk applicable to people with type 2 diabetes, to assess their quality and accuracy,... Show moreAims/hypothesis The aims of this study were to identify all published prognostic models predicting retinopathy risk applicable to people with type 2 diabetes, to assess their quality and accuracy, and to validate their predictive accuracy in a head-to-head comparison using an independent type 2 diabetes cohort. Methods A systematic search was performed in PubMed and Embase in December 2019. Studies that met the following criteria were included: (1) the model was applicable in type 2 diabetes; (2) the outcome was retinopathy; and (3) follow-up was more than 1 year. Screening, data extraction (using the checklist for critical appraisal and data extraction for systemic reviews of prediction modelling studies [CHARMS]) and risk of bias assessment (by prediction model risk of bias assessment tool [PROBAST]) were performed independently by two reviewers. Selected models were externally validated in the large Hoorn Diabetes Care System (DCS) cohort in the Netherlands. Retinopathy risk was calculated using baseline data and compared with retinopathy incidence over 5 years. Calibration after intercept adjustment and discrimination (Harrell's C statistic) were assessed. Results Twelve studies were included in the systematic review, reporting on 16 models. Outcomes ranged from referable retinopathy to blindness. Discrimination was reported in seven studies with C statistics ranging from 0.55 (95% CI 0.54, 0.56) to 0.84 (95% CI 0.78, 0.88). Five studies reported on calibration. Eight models could be compared head-to-head in the DCS cohort (N = 10,715). Most of the models underestimated retinopathy risk. Validating the models against different severities of retinopathy, C statistics ranged from 0.51 (95% CI 0.49, 0.53) to 0.89 (95% CI 0.88, 0.91). Conclusions/interpretation Several prognostic models can accurately predict retinopathy risk in a population-based type 2 diabetes cohort. Most of the models include easy-to-measure predictors enhancing their applicability. Tailoring retinopathy screening frequency based on accurate risk predictions may increase the efficiency and cost-effectiveness of diabetic retinopathy care. Registration PROSPERO registration ID CRD42018089122 Show less
Objectives: To compare methods to adjust for confounding by disease severity during multicenter intervention studies in ICU, when different disease severity measures are collected across centers.... Show moreObjectives: To compare methods to adjust for confounding by disease severity during multicenter intervention studies in ICU, when different disease severity measures are collected across centers. Design: In silico simulation study using national registry data. Setting: Twenty mixed ICUs in The Netherlands. Subjects: Fifty-five-thousand six-hundred fifty-five ICU admissions between January 1, 2011, and January 1, 2016. Interventions: None. Measurements and Main Results: To mimic an intervention study with confounding, a fictitious treatment variable was simulated whose effect on the outcome was confounded by Acute Physiology and Chronic Health Evaluation IV predicted mortality (a common measure for disease severity). Diverse, realistic scenarios were investigated where the availability of disease severity measures (i.e., Acute Physiology and Chronic Health Evaluation IV, Acute Physiology and Chronic Health Evaluation II, and Simplified Acute Physiology Score II scores) varied across centers. For each scenario, eight different methods to adjust for confounding were used to obtain an estimate of the (fictitious) treatment effect. These were compared in terms of relative (%) and absolute (odds ratio) bias to a reference scenario where the treatment effect was estimated following correction for the Acute Physiology and Chronic Health Evaluation IV scores from all centers. Complete neglect of differences in disease severity measures across centers resulted in bias ranging from 10.2% to 173.6% across scenarios, and no commonly used methodology-such as two-stage modeling or score standardization-was able to effectively eliminate bias. In scenarios where some of the included centers had (only) Acute Physiology and Chronic Health Evaluation II or Simplified Acute Physiology Score II available (and not Acute Physiology and Chronic Health Evaluation IV), either restriction of the analysis to Acute Physiology and Chronic Health Evaluation IV centers alone or multiple imputation of Acute Physiology and Chronic Health Evaluation IV scores resulted in the least amount of relative bias (0.0% and 5.1% for Acute Physiology and Chronic Health Evaluation II, respectively, and 0.0% and 4.6% for Simplified Acute Physiology Score II, respectively). In scenarios where some centers used Acute Physiology and Chronic Health Evaluation II, regression calibration yielded low relative bias too (relative bias, 12.4%); this was not true if these same centers only had Simplified Acute Physiology Score II available (relative bias, 54.8%). Conclusions: When different disease severity measures are available across centers, the performance of various methods to control for confounding by disease severity may show important differences. When planning multicenter studies, researchers should make contingency plans to limit the use of or properly incorporate different disease measures across centers in the statistical analysis. Show less
Pajouheshnia, R.; Smeden, M. van; Peelen, L.M.; Groenwold, R.H.H. 2019
OBJECTIVE\nCardiac surgery and postoperative admission to the ICU may lead to posttraumatic stress disorder and depression. Perioperatively administered corticosteroids potentially alter the risk... Show moreOBJECTIVE\nCardiac surgery and postoperative admission to the ICU may lead to posttraumatic stress disorder and depression. Perioperatively administered corticosteroids potentially alter the risk of development of these psychiatric conditions, by affecting the hypothalamic-pituitary-adrenal axis. However, findings of previous studies are inconsistent. We aimed to assess the effect of a single dose of dexamethasone compared with placebo on symptoms of posttraumatic stress disorder and depression and health-related quality of life after cardiac surgery and ICU admission.\nDESIGN\nFollow-up study of a randomized clinical trial.\nSETTING\nFive Dutch heart centers.\nPATIENTS\nCardiac surgery patients (n = 1,244) who participated in the Dexamethasone for Cardiac Surgery trial.\nINTERVENTIONS\nA single intraoperative IV dose of dexamethasone or placebo was administered in a randomized, double-blind way.\nMEASUREMENTS AND MAIN RESULTS\nSymptoms of posttraumatic stress disorder, depression, and health-related quality of life were assessed with validated questionnaires 1.5 years after randomization. Data were available for 1,125 patients (90.4%); of which 561 patients received dexamethasone and 564 patients received placebo. Overall, the prevalence of psychopathology was not influenced by dexamethasone. Posttraumatic stress disorder and depression were present in, respectively, 52 patients (9.3%) and 69 patients (12.3%) who received dexamethasone and in 66 patients (11.7%) and 78 patients (13.8%) who received placebo (posttraumatic stress disorder: odds ratio, 0.82; 95% CI, 0.55-1.20; p = 0.30; depression: odds ratio, 0.92; 95% CI, 0.64-1.31; p = 0.63). Subgroup analysis revealed a lower prevalence of posttraumatic stress disorder (odds ratio, 0.23; 95% CI, 0.07-0.72; p < 0.01) and depression (odds ratio, 0.29; 95% CI, 0.11-0.77; p < 0.01) in female patients after dexamethasone administration. Health-related quality of life did not differ between groups and was not associated with psychopathology.\nCONCLUSIONS\nOverall, our findings suggest that exogenous administration of the glucocorticoid receptor agonist dexamethasone-compared with placebo-during cardiac surgery does not positively or negatively affect the prevalence of posttraumatic stress disorder and depression. However, in female patients, beneficial effects on the occurrence of posttraumatic stress disorder and depression may be present. Show less
