Assessing the potential for precision medicine in body weight reduction with regard to type 2 diabetes mellitus therapies: A meta-regression analysis of 120 randomized controlled trials.

AIMS: To assess the potential for precision medicine in type 2 diabetes by quantifying the variability of body weight as response to pharmacological treatment and to identify predictors which could explain this variability. METHODS: We used randomized clinical trials (RCTs) comparing glucose-lowering drugs (including but not limited to sodium-glucose cotransporter-2 inhibitors, glucagon-like peptide-1 receptor agonists and thiazolidinediones) to placebo from four recent systematic reviews. RCTs reporting on body weight after treatment to allow for calculation of its logarithmic standard deviation (log[SD], i.e., treatment response heterogeneity) in verum (i.e., treatment) and placebo groups were included. Meta-regression analyses were performed with respect to variability of body weight after treatment and potential predictors. RESULTS: A total of 120 RCTs with a total of 43 663 participants were analysed. A slightly larger treatment response heterogeneity was shown in the verum groups, with a median log(SD) of 2.83 compared to 2.79 from placebo. After full adjustment in the meta-regression model, the difference in body weight log(SD) was -0.026 (95% confidence interval -0.044; 0.008), with greater variability in the placebo groups. Scatterplots did not show any slope divergence (i.e., interaction) between clinical predictors and the respective treatment (verum or placebo). CONCLUSIONS: We found no major treatment response heterogeneity in RCTs of glucose-lowering drugs for body weight reduction in type 2 diabetes. The precision medicine approach may thus be of limited value in this setting.

Clinical relevance of copeptin plasma levels as a biomarker of disease severity and mortality in critically ill patients.

BACKGROUND: Copeptin, also termed C-terminal pre-pro-vasopressin or CTproAVP, mirrors endogenous vasopressin (anti-diuretic hormone, ADH) activity and might thereby serve as a biomarker reflecting the biological stress level. We therefore hypothesized that copeptin plasma concentrations are associated with disease severity in critically ill patients and could predict mortality. METHODS: We analyzed plasma copeptin levels in a prospective, single-center, observational study comprising 218 critically ill patients at admission to the medical intensive care unit (ICU). Mortality was assessed during a 2-year observational follow-up period. RESULTS: Copeptin plasma levels were significantly elevated in critically ill patients (n = 218) at ICU admission, as compared with 66 healthy controls. Neither sepsis as the cause of critical illness nor pre-existing metabolic disorders (type 2 diabetes, obesity) were found to influence copeptin levels. On the contrary, plasma copeptin was closely associated with disease severity (eg APACHE-II score) and correlated with biomarkers of inflammation, renal failure, metabolism, vascular tone, and tissue perfusion. Elevated copeptin levels at ICU admission predicted short-term and long-term mortality. CONCLUSIONS: Copeptin plasma concentrations are significantly elevated in critically ill patients, correlate with disease severity and predict ICU and long-term outcome. Thus, copeptin could be a promising tool for prognostication and management of critically ill patients.

Meta-analysed numbers needed to treat of novel antidiabetic drugs for cardiovascular outcomes.

AIMS: Absolute treatment effects-i.e. numbers needed to treat (NNTs)-of novel antidiabetic drugs for cardiovascular outcomes have not been comprehensively evaluated. We aimed to perform a meta-analysis of digitalized individual patient outcomes to display and compare absolute treatment effects. METHODS AND RESULTS: Individual patient time-to-event information from Kaplan-Meier plots of cardiovascular mortality (CM) and/or hospitalization for heart failure (HHF) endpoints from cardiovascular outcome trials (CVOTs) evaluating dipeptidyl peptidase-4 (DPP-4) inhibitors, glucagon-like peptide-1 (GLP-1) receptor agonists, and sodium glucose transporter 2 (SGLT2) inhibitors vs. placebo were digitalized using WebPlotDigitizer 4.2 and the R code of Guyot et al.; Weibull regression models were generated, validated, and used to estimate NNT for individual trials; random-effects meta-analysis generated Meta-NNT with 95% confidence intervals. Sixteen CVOTs reported time-to-event information (14 in primary diabetes and 2 in primary heart failure populations). Thirteen studies including 96 860 patients were meta-analysed for CM: At the median follow-up of 30 months, Meta-NNTs were 178 (64 to ∞ to -223) for DPP-4 inhibitors, 261 (158 to 745) for GLP-1 receptor agonists, and 118 (68 to 435) for SGLT2 inhibitors. Ten studies including 96 128 patients were meta-analysed for HHF: At the median follow-up of 29 months, estimated Meta-NNTs were -644 (229 to ∞ to -134) for DPP-4 inhibitors, 441 (184 to ∞ to -1100) for GLP-1 receptor agonists, and 126 (91 to 208) for SGLT2 inhibitors. SGLT2 inhibitors were especially effective for HHF in primary heart failure populations [Meta-NNT 25 (19 to 39)] vs. primary diabetes populations [Meta-NNT 233 (167 to 385)] at 16 months of follow-up. CONCLUSIONS: We found only modest treatment benefits of GLP-1 receptor agonists and SGLT2 inhibitors for CM and HHF in primary type 2 diabetes mellitus populations. In primary heart failure populations, SGLT2 inhibitor benefits were substantial and comparable in efficacy to established heart failure medication.

Risk-adjusted management in catheterization procedures for non-ST-segment elevation myocardial infarction: A standard operating procedure pilot study.

BACKGROUND: The effects of standardized risk-adjusted periprocedural management of cardiac catheterization procedures in Non-ST segment elevation myocardial infarction (NSTEMI) remain unknown. We implemented a standard operating procedure (SOP) specifying risk assessment (RA, using National Cardiovascular Data Registry (NCDR) risk models) and risk-adjusted management (RM, e.g. intensified monitoring) in 2018 and aimed to investigate staff SOP adherence and associations with patient outcomes. METHODS AND RESULTS: All 430 invasively managed NSTEMI patients (mean age 72y; 70.9% male) in 2018 were analyzed for staff SOP adherence and in-hospital clinical outcomes. 207 patients (48.1%; RM+) received both RA and RM; 92 patients (21.4%; RM-) received RA but no RM; 131 patients (30.5%; RA-) received neither RA nor RM. Lower staff adherence to RA was associated with emergency settings (51.9% (RA-) vs. 22.1% (RA+); p<0.01), presentation in cardiogenic shock (17.6% (RA-) vs. 6.4% (RA+); p<0.01) and invasive mechanical ventilation (12.2% (RA-) vs. 3.3% (RA+); p<0.01). Early sheath removal (87.9% (RM+) vs. 56.5% (RM-); p<0.01) and intensified monitoring (p<0.01) were more frequent in the RM+ group. All-cause mortality was not different (1.4% (RM+) vs. 4.3% (RM-); p=0.13), but there were fewer major bleeding events with associated with RM (2.4% (RM+) vs. 12% (RM-); p<0.01), which remained independently associated with RM in a multivariate logistic regression model correcting for confounders (p<0.01). CONCLUSION: In an all-comer patient cohort with NSTEMI, staff adherence to risk-adjusted periprocedural management was independently associated with fewer major bleeding events. Staff adherence to SOP-specified risk assessment was frequently neglected in more critical clinical situations.

National Cardiovascular Data Registry-Acute Kidney Injury (NCDR) vs. Mehran risk models for prediction of contrast-induced nephropathy and need for dialysis after coronary angiography in a German patient cohort.

BACKGROUND: Contrast-induced nephropathy (CIN) is a major adverse event in patients undergoing coronary angiography. The Mehran risk model is the gold-standard for CIN risk prediction. However, its performance in comparison to more contemporary National Cardiovascular Data Registry-Acute Kidney Injury (NCDR-AKI) risk models remains unknown. We aimed to compare both in this study. METHODS AND RESULTS: Predictions of Mehran and NCDR-AKI risk models and clinical events of CIN and need for dialysis were assessed in a total of 2067 patients undergoing coronary angiography with or without percutaneous coronary intervention. Risk models were compared regarding discrimination (receiver operating characteristic analysis), net reclassification improvement (NRI) and calibration (graphical and statistical analysis). The NCDR risk model showed superior risk discrimination for predicting CIN (NCDR c-index 0.75, 95% CI 0.72-0.78; vs. Mehran c-index 0.69, 95% CI 0.66-0.72, p < 0.01), and continuous NRI (0.22; 95% CI 0.12-0.32; p < 0.01) compared to the Mehran model. The NCDR risk model tended to underestimate the risk of CIN, while the Mehran model was more evenly calibrated. For the prediction of need for dialysis, NCDR-AKI-D also discriminated risk better (c-index 0.85, 95% CI 0.79-0.91; vs. Mehran c-index 0.75, 95% CI 0.66-0.84; pNCDRvsMehran < 0.01), but continuous NRI showed no benefit and calibration analysis revealed an underestimation of dialysis risk. CONCLUSION: In German patients undergoing coronary angiography, the modern NCDR risk model for predicting contrast-induced nephropathy showed superior discrimination compared to the Mehran model while showing less accurate calibration. Results for the outcome 'need for dialysis' were equivocal.