How baseline, new-onset, and persistent depressive symptoms are associated with cardiovascular and non-cardiovascular mortality in incident patients on chronic dialysis

AbstractObjectiveDepressive symptoms are associated with mortality among patients on chronic dialysis therapy. It is currently unknown how different courses of depressive symptoms are associated with both cardiovascular and non-cardiovascular mortality.MethodsIn a Dutch prospective nation-wide cohort study among incident patients on chronic dialysis, 1077 patients completed the Mental Health Inventory, both at 3 and 12months after starting dialysis. Cox regression models were used to calculate crude and adjusted hazard ratios (HRs) for mortality for patients with depressive symptoms at 3months only (baseline only), at 12months only (new-onset), and both at 3 and 12months (persistent), using patients without depressive symptoms at 3 and 12months as reference group.ResultsDepressive symptoms at baseline only seemed to be a strong marker for non-cardiovascular mortality (HRadj 1.91, 95% CI 1.26–2.90), whereas cardiovascular mortality was only moderately increased (HRadj 1.41, 95% CI 0.85–2.33). In contrast, new-onset depressive symptoms were moderately associated with both cardiovascular (HRadj 1.66, 95% CI 1.06–2.58) and non-cardiovascular mortality (HRadj 1.46, 95% CI 0.97–2.20). Among patients with persistent depressive symptoms, a poor survival was observed due to both cardiovascular (HRadj 2.14, 95% CI 1.42–3.24) and non-cardiovascular related mortality (HRadj 1.76, 95% CI 1.20–2.59).ConclusionThis study showed that different courses of depressive symptoms were associated with a poor survival after the start of dialysis. In particular, temporary depressive symptoms at the start of dialysis may be a strong marker for non-cardiovascular mortality, whereas persistent depressive symptoms were associated with both cardiovascular and non-cardiovascular mortality

Specialty-based, voluntary incident reporting in neonatal intensive care: description of 4846 incident reports

OBJECTIVES: To examine the characteristics of incidents reported after introduction of a voluntary, non-punitive incident reporting system for neonatal intensive care units (NICUs) in the Netherlands; and to investigate which types of reported incident pose the highest risk to patients in the NICU. DESIGN: Prospective multicentre survey. METHODS: Voluntary, non-punitive incident reporting was introduced in eight level III NICUs and one paediatric surgical ICU. An incident was defined as any unintended event which (could have) reduced the safety margin for the patient. Multidisciplinary, unit-based patient safety committees systematically collected and analysed incident reports, and assigned risk scores to each reported incident. Data were centrally collected for specialty-based analysis. This paper describes the characteristics of incidents reported during the first year. Bivariate logistic regression analysis was conducted to identify high-risk incident categories. RESULTS: There were 5225 incident reports on 3859 admissions, of which 4846 were eligible for analysis. Incidents with medication were most frequently reported (27%), followed by laboratory (10%) and enteral nutrition (8%). Severe harm was described in seven incident reports, and moderate harm in 63 incident reports. Incidents involving mechanical ventilation and blood products were most likely to be assigned high-risk scores, followed by those involving parenteral nutrition, intravascular lines and medication dosing errors. CONCLUSIONS: Incidents occur much more frequently in Dutch NICUs than has been previously observed, and their impact on patient morbidity is considerable. Reported incidents concerning mechanical ventilation, blood products, intravascular lines, parenteral nutrition and medication dosing errors pose the highest risk to patients in the NIC

Feasibility and reliability of PRISMA-Medical for specialty-based incident analysis

Aims and objectives: In this study, the feasibility and reliability of the Prevention Recovery Information System for Monitoring and Analysis (PRISMA)-Medical method for systematic, specialty-based analysis and classification of incidents in the neonatal intensive care unit (NICU) were determined. Methods: After the introduction of a Neonatology System for Analysis and Feedback on Medical Events (NEOSAFE) in eight tertiary care NICUs and one paediatric surgical ICU, PRISMA-Medical was started to be used to identify root causes of voluntary reported incidents by multidisciplinary unit patient safety committees. Committee members were PRISMA-trained and familiar with the department and its processes. In this study, the results of PRISMA-analysis of incidents reported during the first year are described. At t¿=¿3 months and t¿=¿12 months after introduction, test cases were performed to measure agreement at three levels of root cause classification using PRISMA-Medical. Inter-rater reliability was determined by calculating generalised ¿ values for each level of classification. Results: During the study period, 981 out of 1786 eligible incidents (55%) were analysed for underlying root causes. In total, 2313 root causes were identified and classified, giving an average of 2.4 root causes for every incident. Although substantial agreement (¿ 0.70–0.81) was reached at the main level of root cause classification of the test cases (discrimination between technical, organisational and human failure) and agreement among the committees at the second level (discrimination between skill-based, rule-based and knowledge-based errors) was acceptable (¿ 0.53–0.59), discrimination between rule-based errors (the third level of classification) was more difficult to assess (¿ 0.40–0.47). Conclusion: With some restraints, PRISMA-Medical proves to be both feasible and acceptably reliable to identify and classify multiple causes of medical events in the NICU

Metabolomic profiles predict individual multidisease outcomes

Publisher Copyright: © 2022, The Author(s).Risk stratification is critical for the early identification of high-risk individuals and disease prevention. Here we explored the potential of nuclear magnetic resonance (NMR) spectroscopy-derived metabolomic profiles to inform on multidisease risk beyond conventional clinical predictors for the onset of 24 common conditions, including metabolic, vascular, respiratory, musculoskeletal and neurological diseases and cancers. Specifically, we trained a neural network to learn disease-specific metabolomic states from 168 circulating metabolic markers measured in 117,981 participants with ~1.4 million person-years of follow-up from the UK Biobank and validated the model in four independent cohorts. We found metabolomic states to be associated with incident event rates in all the investigated conditions, except breast cancer. For 10-year outcome prediction for 15 endpoints, with and without established metabolic contribution, a combination of age and sex and the metabolomic state equaled or outperformed established predictors. Moreover, metabolomic state added predictive information over comprehensive clinical variables for eight common diseases, including type 2 diabetes, dementia and heart failure. Decision curve analyses showed that predictive improvements translated into clinical utility for a wide range of potential decision thresholds. Taken together, our study demonstrates both the potential and limitations of NMR-derived metabolomic profiles as a multidisease assay to inform on the risk of many common diseases simultaneously.Peer reviewe

European regulatory private law : from conflicts to platforms

Discusses the normative design of European legal integration through the prism of private law, going beyond the conflict of laws perspective to the model of platform law

A composite score of protein-energy nutritional status predicts mortality in haemodialysis patients no better than its individual components

Item does not contain fulltextBACKGROUND: Protein-energy wasting is tightly associated with mortality in haemodialysis patients. An expert panel of the International Society of Renal Nutrition and Metabolism (ISRNM) has published a consensus on the parameters that define protein-energy nutritional status and posed the question, 'which scoring system most effectively predicts outcome?' The aim of our study was therefore to develop a composite score of protein-energy nutritional status (cPENS) and to assess its prediction of all-cause mortality. METHODS: We used the data of 560 haemodialysis patients participating in the CONvective TRAnsport STudy (CONTRAST). All participants were followed for occurrence of death. Internationally recommended nutritional targets were used as components of the cPENS, including the subjective global assessment (target score >/= 6), albumin (>/= 4.0 g/dL), normalized protein nitrogen appearance (>/= 0.8 g/kg/day), cholesterol (>/= 100 mg/dL), creatinine (>/= 10 mg/dL) and BMI (> 23 kg/m(2)). A Cox regression model was used to analyse the relation between different cPENS variants and mortality. RESULTS: The median follow-up time was 1.4 years (max 4.2). One hundred and five patients (19%) died. A cPENS variant based on albumin, BMI, creatinine and the nPNA yielded the strongest relation with mortality (hazard ratio 0.63, 95% confidence interval 0.54-0.74, P < 0.001), after adjustments for confounders. Some of the individual parameters of the cPENS, notably albumin and creatinine, were related to mortality with similar strength and magnitude. CONCLUSIONS: In conclusion, albumin reflects mortality risk similarly to multiple nutritional parameters combined. This questions the clinical value of the proposed diagnostic criteria for protein-energy wasting