Table 0; documenting the steps to go from clinical database to research dataset.

OBJECTIVES: Data-driven decision support tools have been increasingly recognized to transform health care. However, such tools are often developed on predefined research datasets without adequate knowledge of the origin of this data and how it was selected. How a dataset is extracted from a clinical database can profoundly impact the validity, interpretability and interoperability of the dataset, and downstream analyses, yet is rarely reported. Therefore, we present a case study illustrating how a definitive patient list was extracted from a clinical source database and how this can be reported. STUDY DESIGN AND SETTING: A single-center observational study was performed at an academic hospital in the Netherlands to illustrate the impact of selecting a definitive patient list for research from a clinical source database, and the importance of documenting this process. All admissions from the critical care database admitted between January 1, 2013, and January 1, 2023, were used. RESULTS: An interdisciplinary team collaborated to identify and address potential sources of data insufficiency and uncertainty. We demonstrate a stepwise data preparation process, reducing the clinical source database of 54,218 admissions to a definitive patient list of 21,553 admissions. Transparent documentation of the data preparation process improves the quality of the definitive patient list before analysis of the corresponding patient data. This study generated seven important recommendations for preparing observational health-care data for research purposes. CONCLUSION: Documenting data preparation is essential for understanding a research dataset originating from a clinical source database before analyzing health-care data. The findings contribute to establishing data standards and offer insights into the complexities of preparing health-care data for scientific investigation. Meticulous data preparation and documentation thereof will improve research validity and advance critical care.

Deep embedded clustering generalisability and adaptation for integrating mixed datatypes: two critical care cohorts.

We validated a Deep Embedded Clustering (DEC) model and its adaptation for integrating mixed datatypes (in this study, numerical and categorical variables). Deep Embedded Clustering (DEC) is a promising technique capable of managing extensive sets of variables and non-linear relationships. Nevertheless, DEC cannot adequately handle mixed datatypes. Therefore, we adapted DEC by replacing the autoencoder with an X-shaped variational autoencoder (XVAE) and optimising hyperparameters for cluster stability. We call this model "X-DEC". We compared DEC and X-DEC by reproducing a previous study that used DEC to identify clusters in a population of intensive care patients. We assessed internal validity based on cluster stability on the development dataset. Since generalisability of clustering models has insufficiently been validated on external populations, we assessed external validity by investigating cluster generalisability onto an external validation dataset. We concluded that both DEC and X-DEC resulted in clinically recognisable and generalisable clusters, but X-DEC produced much more stable clusters.

Pericardial Fat Is Associated With Less Severe Multiorgan Failure Over Time in Patients With Coronavirus Disease-19: The Maastricht Intensive Care COVID Cohort.

PURPOSE: Pericardial fat (PF) and epicardial adipose tissue (EAT) may enhance the proinflammatory response in corona virus-19 (COVID-19) patients. Higher PF and EAT volumes might result in multiorgan failure and explain unfavorable trajectories.The aim of this study was to examine the association between the volume of PF and EAT and multiorgan failure over time. MATERIALS AND METHODS: All mechanically ventilated COVID-19 patients with an available chest computed tomography were prospectively included (March-June 2020). PF and EAT volumes were quantified using chest computed tomography scans. Patients were categorized into sex-specific PF and EAT tertiles. Variables to calculate Sequential Organ Failure Assessment (SOFA) scores were collected daily to indicate multiorgan failure. Linear mixed-effects regression was used to investigate the association between tertiles for PF and EAT volumes separately and serial SOFA scores over time. All models were adjusted. RESULTS: Sixty-three patients were divided into PF and EAT tertiles, with median PF volumes of 131.4 mL (IQR [interquartile range]: 115.7, 143.2 mL), 199.8 mL (IQR: 175.9, 221.6 mL), and 318.8 mL (IQR: 281.9, 376.8 mL) and median EAT volumes of 69.6 mL (IQR: 57.0, 79.4 mL), 107.9 mL (IQR: 104.6, 115.1 mL), and 163.8 mL (IQR: 146.5, 203.1 mL). Patients in the highest PF tertile had a statistically significantly lower SOFA score over time (1.3 [-2.5, -0.1], P =0.033) compared with the lowest PF tertile. EAT tertiles were not significantly associated with SOFA scores over time. CONCLUSION: A higher PF volume is associated with less multiorgan failure in mechanically ventilated COVID-19 patients. EAT volumes were not associated with multiorgan failure.

Hyperglycemia and glucose variability are associated with worse survival in mechanically ventilated COVID-19 patients: the prospective Maastricht Intensive Care Covid Cohort.

BACKGROUND: Data on hyperglycemia and glucose variability in relation to diabetes mellitus, either known or unknown in ICU-setting in COVID-19, are scarce. We prospectively studied daily glucose variables and mortality in strata of diabetes mellitus and glycosylated hemoglobin among mechanically ventilated COVID-19 patients. METHODS: We used linear-mixed effect models in mechanically ventilated COVID-19 patients to investigate mean and maximum difference in glucose concentration per day over time. We compared ICU survivors and non-survivors and tested for effect-modification by pandemic wave 1 and 2, diabetes mellitus, and admission HbA1c. RESULTS: Among 232 mechanically ventilated COVID-19 patients, 21.1% had known diabetes mellitus, whereas 16.9% in wave 2 had unknown diabetes mellitus. Non-survivors had higher mean glucose concentrations (ß 0.62 mmol/l; 95%CI 0.20-1.06; ß 11.2 mg/dl; 95% CI 3.6-19.1; P = 0.004) and higher maximum differences in glucose concentrations per day (ß 0.85 mmol/l; 95%CI 0.37-1.33; ß 15.3; 95%CI 6.7-23.9; P = 0.001). Effect modification by wave, history of diabetes mellitus and admission HbA1c in associations between glucose and survival was not present. Effect of higher mean glucose concentrations was modified by pandemic wave (wave 1 (ß 0.74; 95% CI 0.24-1.23 mmol/l) ; (ß 13.3; 95%CI 4.3-22.1 mg/dl)) vs. (wave 2 (ß 0.37 (95%CI 0.25-0.98) mmol/l) (ß 6.7 (95% ci 4.5-17.6) mg/dl)). CONCLUSIONS: Hyperglycemia and glucose variability are associated with mortality in mechanically ventilated COVID-19 patients irrespective of the presence of diabetes mellitus.

Postsurgical Thrombotic Microangiopathy and Deregulated Complement.

Postsurgical thrombotic microangiopathy (TMA) is a complication associated with significant morbidity and mortality. Still, the pathophysiological underlying mechanism of postsurgical TMA, a diagnosis often overlooked in postoperative patients with acute kidney injury and thrombocytopenia, is largely unknown. Here, we report the case of a 56-year-old male that developed anuric acute kidney injury, Coombs-negative hemolysis, and thrombocytopenia after surgical aortic arch replacement. Massive ex vivo complement activation on the endothelium, a rare complement gene variant in C2, at-risk haplotype MCPggaac, and excellent response to therapeutic complement inhibition, points to the pivotal role of complement in the pathophysiology of disease. Moreover, the importance of a multidisciplinary team approach in (postsurgical) thrombocytopenia is emphasized.

Genetic susceptibility, obesity and lifetime risk of type 2 diabetes: The ARIC study and Rotterdam Study.

AIMS: Both lifestyle factors and genetic background contribute to the development of type 2 diabetes. Estimation of the lifetime risk of diabetes based on genetic information has not been presented, and the extent to which a normal body weight can offset a high lifetime genetic risk is unknown. METHODS: We used data from 15,671 diabetes-free participants of European ancestry aged 45 years and older from the prospective population-based ARIC study and Rotterdam Study (RS). We quantified the remaining lifetime risk of diabetes stratified by genetic risk and quantified the effect of normal weight in terms of relative and lifetime risks in low, intermediate and high genetic risk. RESULTS: At age 45 years, the lifetime risk of type 2 diabetes in ARIC in the low, intermediate and high genetic risk category was 33.2%, 41.3% and 47.2%, and in RS 22.8%, 30.6% and 35.5% respectively. The absolute lifetime risk for individuals with normal weight compared to individuals with obesity was 24% lower in ARIC and 8.6% lower in RS in the low genetic risk group, 36.3% lower in ARIC and 31.3% lower in RS in the intermediate genetic risk group, and 25.0% lower in ARIC and 29.4% lower in RS in the high genetic risk group. CONCLUSIONS: Genetic variants for type 2 diabetes have value in estimating the lifetime risk of type 2 diabetes. Normal weight mitigates partly the deleterious effect of high genetic risk.

Lifetime risk to progress from pre-diabetes to type 2 diabetes among women and men: comparison between American Diabetes Association and World Health Organization diagnostic criteria.

INTRODUCTION: Pre-diabetes, a status conferring high risk of overt diabetes, is defined differently by the American Diabetes Association (ADA) and the WHO. We investigated the impact of applying definitions of pre-diabetes on lifetime risk of diabetes in women and men from the general population. RESEARCH DESIGN AND METHODS: We used data from 8844 women without diabetes and men aged ≥45 years from the prospective population-based Rotterdam Study in the Netherlands. In both gender groups, we calculated pre-diabetes prevalence according to ADA and WHO criteria and estimated the 10-year and lifetime risk to progress to overt diabetes with adjustment for competing risk of death. RESULTS: Out of 8844 individuals, pre-diabetes was identified in 3492 individuals (prevalence 40%, 95% CI 38% to 41%) according to ADA and 1382 individuals (prevalence 16%, 95% CI 15% to 16%) according to WHO criteria. In both women and men and each age category, ADA prevalence estimates doubled WHO-defined pre-diabetes. For women and men aged 45 years having ADA-defined pre-diabetes, the 10-year risk of diabetes was 14.2% (95% CI 6.0% to 22.5%) and 9.2% (95% CI 3.4% to 15.0%) compared with 23.2% (95% CI 6.8% to 39.6%) and 24.6% (95% CI 8.4% to 40.8%) in women and men with WHO-defined pre-diabetes. At age 45 years, the remaining lifetime risk to progress to overt diabetes was 57.5% (95% CI 51.8% to 63.2%) vs 80.2% (95% CI 74.1% to 86.3%) in women and 46.1% (95% CI 40.8% to 51.4%) vs 68.4% (95% CI 58.3% to 78.5%) in men with pre-diabetes according to ADA and WHO definitions, respectively. CONCLUSION: Prevalence of pre-diabetes differed considerably in both women and men when applying ADA and WHO pre-diabetes definitions. Women with pre-diabetes had higher lifetime risk to progress to diabetes. The lifetime risk of diabetes was lower in women and men with ADA-defined pre-diabetes as compared with WHO. Improvement of pre-diabetes definition considering appropriate sex-specific and age-specific glycemic thresholds may lead to better identification of individuals at high risk of diabetes.

Sex difference in the incidence of microvascular complications in patients with type 2 diabetes mellitus: a prospective cohort study.

AIMS: Type 2 diabetes mellitus is a major cause of death and disability due to its long-term macro- and microvascular diseases. Although women with type 2 diabetes have more macrovascular diseases, it is unclear whether there are sex differences in the occurrence of microvascular disease. The aim of our study was to investigate sex differences in the incidence of microvascular complications in type 2 diabetes. METHODS: Analyses were performed in the DiaGene study, a prospective cohort study for complications of type 2 diabetes, collected in the city of Eindhoven, the Netherlands (n = 1886, mean follow-up time = 6.93 years). Cox proportional hazard models adjusted for risk factors for complications (age, smoking, hypertension, dyslipidemia, HbA1c and duration of type 2 diabetes) were used to analyze the incidence of microvascular complications in men and women. RESULTS: The incidence of microalbuminuria was significantly higher in men (HR microalbuminuria 1.64 [CI 1.21-2.24], p = 0.002). Additionally, men are more likely to develop two or three microvascular complications compared to women (OR 2.42 [CI 1.69-3.45], p < 0.001). CONCLUSIONS: This study shows that men with type 2 diabetes are more likely to develop microvascular complications, especially microalbuminuria. Furthermore, men seem to have a higher chance of developing multiple microvascular complications. Our results highlight that men and women may not benefit to a similar extent from current treatment approaches to prevent diabetes-related microvascular diseases.

Introduction of the DiaGene study: clinical characteristics, pathophysiology and determinants of vascular complications of type 2 diabetes.

BACKGROUND: Type 2 diabetes is a major healthcare problem. Glucose-, lipid-, and blood pressure-lowering strategies decrease the risk of micro- and macrovascular complications. However, a substantial residual risk remains. To unravel the etiology of type 2 diabetes and its complications, large-scale, well-phenotyped studies with prospective follow-up are needed. This is the goal of the DiaGene study. In this manuscript, we describe the design and baseline characteristics of the study. METHODS: The DiaGene study is a multi-centre, prospective, extensively phenotyped type 2 diabetes cohort study with concurrent inclusion of diabetes-free individuals at baseline as controls in the city of Eindhoven, The Netherlands. We collected anthropometry, laboratory measurements, DNA material, and detailed information on medication usage, family history, lifestyle and past medical history. Furthermore, we assessed the prevalence and incidence of retinopathy, nephropathy, neuropathy, and diabetic feet in cases. Using logistic regression models, we analyzed the association of 11 well known genetic risk variants with type 2 diabetes in our study. RESULTS: In total, 1886 patients with type 2 diabetes and 854 controls were included. Cases had worse anthropometric and metabolic profiles than controls. Patients in outpatient clinics had higher prevalence of macrovascular (41.9% vs. 34.8%; P = 0.002) and microvascular disease (63.8% vs. 20.7%) compared to patients from primary care. With the exception of the genetic variant in KCNJ11, all type 2 diabetes susceptibility variants had higher allele frequencies in subjects with type 2 diabetes than in controls. CONCLUSIONS: In our study population, considerable rates of macrovascular and microvascular complications are present despite treatment. These prevalence rates are comparable to other type 2 diabetes populations. While planning genomics, we describe that 11 well-known type 2 diabetes genetic risk variants (in TCF7L2, PPARG-P12A, KCNJ11, FTO, IGF2BP2, DUSP9, CENTD2, THADA, HHEX, CDKAL1, KCNQ1) showed similar associations compared to literature. This study is well-suited for multiple omics analyses to further elucidate disease pathophysiology. Our overall goal is to increase the understanding of the underlying mechanisms of type 2 diabetes and its complications for developing new prediction, prevention, and treatment strategies.

ADAMTS13 activity as a novel risk factor for incident type 2 diabetes mellitus: a population-based cohort study.

AIMS/HYPOTHESIS: ADAMTS13 is a protease that breaks down von Willebrand factor (VWF) multimers into smaller, less active particles. VWF has been associated with an increased risk of incident type 2 diabetes mellitus. Here, we determine whether ADAMTS13 activity and VWF antigen are associated with incident diabetes. METHODS: This study included 5176 participants from the Rotterdam Study, a prospective population-based cohort study. Participants were free of diabetes at baseline and followed up for more than 20 years. Cox proportional hazards models were used to examine the association of ADAMTS13 activity and VWF antigen with incident diabetes. RESULTS: ADAMTS13 activity was associated with an increased risk of incident diabetes (HR 1.17 [95% CI 1.08, 1.27]) after adjustment for known risk factors and VWF antigen levels. Although ADAMTS13 activity was positively associated with fasting glucose and insulin, the association with incident diabetes did not change when we adjusted for these covariates. ADAMTS13 activity was also associated with incident prediabetes (defined on the basis of both fasting and non-fasting blood glucose) after adjustment for known risk factors (HR 1.11 [95% CI 1.03, 1.19]), while the VWF antigen level was not. VWF antigen was associated with incident diabetes, but this association was attenuated after adjustment for known risk factors. CONCLUSIONS/INTERPRETATION: ADAMTS13 activity appears to be an independent risk factor for incident prediabetes and type 2 diabetes. As the association between ADAMTS13 and diabetes did not appear to be explained by its cleavage of VWF, ADAMTS13 may have an independent role in the development of diabetes.

The clinical value of metabolic syndrome and risks of cardiometabolic events and mortality in the elderly: the Rotterdam study.

BACKGROUND: To evaluate the clinical value of metabolic syndrome based on different definitions [American Heart Association/National Heart, Lung and Blood Institute (AHA/NHLBI), International Diabetes Federation (IDF) and European Group for the Study of Insulin Resistance (EGIR)] in middle-aged and elderly populations. METHODS: We studied 8643 participants from the Rotterdam study (1990-2012; mean age 62.7; 57.6 % female), a large prospective population-based study with predominantly elderly participants. We performed cox-proportional hazards models for different definitions, triads within definitions and each separate component for the risk of incident type 2 diabetes mellitus, coronary heart disease, stroke, cardiovascular- and all-cause mortality. RESULTS: In our population of 8643 subjects, metabolic syndrome was highly prevalent (prevalence between 19.4 and 42.4 %). Metabolic syndrome in general was associated with incident type 2 diabetes mellitus (median follow-up of 6.8 years, hazard ratios 3.13-3.78). The associations with coronary heart disease (median follow-up of 7.2 years, hazard ratios 1.08-1.32), stroke (median follow-up of 7.7 years, hazard ratios 0.98-1.32), cardiovascular mortality (median follow-up of 8.2 years, ratios 0.95-1.29) and all-cause mortality (median follow-up of 8.7 years, hazard ratios 1.05-1.10) were weaker. AHA/NHLBI- and IDF-definitions showed similar associations with clinical endpoints compared to the EGIR, which was only significantly associated with incident type 2 diabetes mellitus. All significant associations disappeared after correcting metabolic syndrome for its individual components. CONCLUSIONS: Large variability exists between and within definitions of the metabolic syndrome with respect to risk of clinical events and mortality. In a relatively old population the metabolic syndrome did not show an additional predictive value on top of its individual components. So, besides as a manner of easy identification of high risk patients, the metabolic syndrome does not seem to add any predictive value for clinical practice.

Lifetime risk of developing impaired glucose metabolism and eventual progression from prediabetes to type 2 diabetes: a prospective cohort study.

BACKGROUND: Data are scarce for the lifetime risk of developing impaired glucose metabolism, including prediabetes, as are data for the risk of eventual progression from prediabetes to diabetes and for initiation of insulin treatment in previously untreated patients with diabetes. We aimed to calculate the lifetime risk of the full range of glucose impairments, from normoglycaemia to prediabetes, type 2 diabetes, and eventual insulin use. METHODS: In this prospective population-based cohort analysis, we used data from the population-based Rotterdam Study. We identified diagnostic events by use of general practitioners' records, hospital discharge letters, pharmacy dispensing data, and serum fasting glucose measurements taken at the study centre (Rotterdam, Netherlands) visits. Normoglycaemia, prediabetes, and diabetes were defined on the basis of WHO criteria for fasting glucose (normoglycaemia: ≤6·0 mmol/L; prediabetes: >6·0 mmol/L and <7·0 mmol/L; and diabetes ≥7·0 mmol/L or use of glucose-lowering drug). We calculated lifetime risk using a modified version of survival analysis adjusted for the competing risk of death. We also estimated the lifetime risk of progression from prediabetes to overt diabetes and from diabetes free of insulin treatment to insulin use. Additionally, we calculated years lived with healthy glucose metabolism. FINDINGS: We used data from 10 050 participants from the Rotterdam Study. During a follow-up of up to 14·7 years (between April 1, 1997, and Jan 1, 2012), 1148 participants developed prediabetes, 828 developed diabetes, and 237 started insulin treatment. At age 45 years, the remaining lifetime risk was 48·7% (95% CI 46·2-51·3) for prediabetes, 31·3% (29·3-33·3) for diabetes, and 9·1% (7·8-10·3) for insulin use. In individuals aged 45 years, the lifetime risk to progress from prediabetes to diabetes was 74·0% (95% CI 67·6-80·5), and 49·1% (38·2-60·0) of the individuals with overt diabetes at this age started insulin treatment. The lifetime risks attenuated with advancing age, but increased with increasing BMI and waist circumference. On average, individuals with severe obesity lived 10 fewer years without glucose impairment compared with normal-weight individuals. INTERPRETATION: Impaired glucose metabolism is a substantial burden on population health, and our findings emphasise the need for more effective prevention strategies, which should be implemented as soon in a person's life as possible. The substantial lifetime risk of prediabetes and diabetes in lean individuals also supports risk factor control in non-obese individuals. FUNDING: Erasmus MC and Erasmus University Rotterdam; Netherlands Organisation for Scientific Research; Netherlands Organisation for Health Research and Development; Research Institute for Diseases in the Elderly; Netherlands Genomics Initiative; Netherlands Ministry of Education, Culture and Science; Netherlands Ministry of Health, Welfare and Sports; European Commission; and Municipality of Rotterdam.

Effects of lifestyle-related interventions on blood pressure in low and middle-income countries: systematic review and meta-analysis.

Despite the overwhelming evidence supporting the effectiveness of antihypertensive medication, hypertension remains poorly controlled in low and middle-income countries (LMICs). Lifestyle intervention studies reporting effects on blood pressure published from January 1977 to September 2012 were searched on various databases. From the 6211 references identified, 52 were included in the systematic review (12, 024 participants) and 43 were included in the meta-analysis (in total 6779 participants). We calculated and pooled effect sizes in mmHg with random-effects models. We grouped interventions into behavioral counseling (1831 participants), dietary modification (1831 participants), physical activity (1014 participants) and multiple interventions (2103 participants). Subgroup analysis and meta-regression were used to evaluate origins of heterogeneity. Lifestyle interventions significantly lowered blood pressure levels in LMIC populations, including in total 6779 participants. The changes achieved in SBP (95% confidence interval) were: behavioral counseling -5.4 (-10.7, -0.0) mmHg, for dietary modification -3.5 (-5.4, -1.5) mmHg, for physical activity -11.4 (-16.0, -6.7) mmHg and for multiple interventions -6.0 (-8.9, -3.3) mmHg. The heterogeneity was high across studies and the quality was generally low. Subgroup analyses showed smaller samples reporting larger effect sizes; intervention lasting less than 6 months showed larger effect sizes and intention-to-treat analysis showed smaller effect sizes Lifestyle interventions may be of value in preventing and reducing blood pressure in LMICs. Nevertheless, the overall quality and sample size of the studies included were low. Improvements in the size and quality of studies evaluating lifestyle interventions are required.