BackgroundIn intensive care units (ICU) octogenarians become a routine patients group with aggravated therapeutic and diagnostic decision-making. Due to increased mortality and a reduced quality of life in this high-risk population, medical decision-making a fortiori requires an optimum of risk stratification. Recently, the VIP-1 trial prospectively observed that the clinical frailty scale (CFS) performed well in ICU patients in overall-survival and short-term outcome prediction. However, it is known that healthcare systems differ in the 21 countries contributing to the VIP-1 trial. Hence, our main focus was to investigate whether the CFS is usable for risk stratification in octogenarians admitted to diversified and high tech German ICUs.MethodsThis multicentre prospective cohort study analyses very old patients admitted to 20 German ICUs as a sub-analysis of the VIP-1 trial. Three hundred and eight patients of 80 years of age or older admitted consecutively to participating ICUs. CFS, cause of admission, APACHE II, SAPS II and SOFA scores, use of ICU resources and ICU- and 30-day mortality were recorded. Multivariate logistic regression analysis was used to identify factors associated with 30-day mortality.ResultsPatients had a median age of 84 [IQR 82–87] years and a mean CFS of 4.75 (± 1.6 standard-deviation) points. More than half of the patients (53.6%) were classified as frail (CFS ≥ 5). ICU-mortality was 17.3% and 30-day mortality was 31.2%. The cause of admission (planned vs. unplanned), (OR 5.74) and the CFS (OR 1.44 per point increase) were independent predictors of 30-day survival.ConclusionsThe CFS is an easy determinable valuable tool for prediction of 30-day ICU survival in octogenarians, thus, it may facilitate decision-making for intensive care givers in Germany.Trial registrationThe VIP-1 study was retrospectively registered on ClinicalTrials.gov (ID: NCT03134807) on May 1, 2017.Electronic supplementary materialThe online version of this article (10.1186/s12877-018-0847-7) contains supplementary material, which is available to authorized users.

Very‐low‐carbohydrate diet triggers the endogenous production of ketone bodies as alternative energy substrates. There are as yet unproven assumptions that ketone bodies positively affect human immunity. We have investigated this topic in an in vitro model using primary human T cells and in an immuno‐nutritional intervention study enrolling healthy volunteers. We show that ketone bodies profoundly impact human T‐cell responses. CD4+, CD8+, and regulatory T‐cell capacity were markedly enhanced, and T memory cell formation was augmented. RNAseq and functional metabolic analyses revealed a fundamental immunometabolic reprogramming in response to ketones favoring mitochondrial oxidative metabolism. This confers superior respiratory reserve, cellular energy supply, and reactive oxygen species signaling. Our data suggest a very‐low‐carbohydrate diet as a clinical tool to improve human T‐cell immunity. Rethinking the value of nutrition and dietary interventions in modern medicine is required.

Background Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine learning model, based on retrospective & prospective clinical data, to stratify patient risk and predict ICU survival and outcomes. Methods A Germany-wide electronic registry was established to pseudonymously collect admission, therapeutic and discharge information of SARS-CoV-2 ICU patients retrospectively and prospectively. Machine learning approaches were evaluated for the accuracy and interpretability of predictions. The Explainable Boosting Machine approach was selected as the most suitable method. Individual, non-linear shape functions for predictive parameters and parameter interactions are reported. Results 1039 patients were included in the Explainable Boosting Machine model, 596 patients retrospectively collected, and 443 patients prospectively collected. The model for prediction of general ICU outcome was shown to be more reliable to predict “survival”. Age, inflammatory and thrombotic activity, and severity of ARDS at ICU admission were shown to be predictive of ICU survival. Patients’ age, pulmonary dysfunction and transfer from an external institution were predictors for ECMO therapy. The interaction of patient age with D-dimer levels on admission and creatinine levels with SOFA score without GCS were predictors for renal replacement therapy. Conclusions Using Explainable Boosting Machine analysis, we confirmed and weighed previously reported and identified novel predictors for outcome in critically ill COVID-19 patients. Using this strategy, predictive modeling of COVID-19 ICU patient outcomes can be performed overcoming the limitations of linear regression models. Trial registration “ClinicalTrials” (clinicaltrials.gov) under NCT04455451.

Patients with severe infections and especially sepsis have a high in-hospital mortality, but even hospital survivors face long-term sequelae, decreased health-related quality of life, and high risk of death, suggesting a great need for specialized aftercare. However, data regarding a potential benefit of post-discharge rehabilitation in these patients are scarce. In this retrospective matched cohort study the claim data of a large German statutory health care insurer was analyzed. 83,974 hospital survivors having suffered from septic shock, sepsis, and severe infections within the years 2009-2016 were identified using an ICD abstraction strategy closely matched to the current Sepsis-3 definition. Cases were analyzed and compared with their matched pairs to determine their 5-year mortality and the impact of post-discharge rehabilitation. Five years after hospital discharge, mortality of initial hospital survivors were still increased after septic shock (HR adj 2.03, 95%-CI 1.87 to 2.19; P<0.001), sepsis (HR adj 1.73, 95%-CI 1.71 to 1.76; P<0.001), and also in survivors of severe infections without organ dysfunction (HR adj 1.70, 95%-CI 1.65 to 1.74; P<0.001) compared to matched controls without infectious diseases. Strikingly, patients treated in rehabilitation facilities showed a significantly improved 5-year survival after suffering from sepsis or septic shock (HR adj 0.81, 95%-CI 0.77 to 0.85; P<0.001) as well as severe infections without organ dysfunction (HR adj 0.81, 95%-CI 0.73 to 0.90; P<0.001) compared to matched patients discharged to home or self-care. Long-term mortality and morbidity of hospital survivors are markedly increased after septic shock, sepsis and severe infections without organ dysfunction, but best 5-year survival was recorded in patients discharged to a rehabilitation facility in all three groups. Thus, our data suggest that specialized aftercare programs may help to improve long-term outcome in these patients and warrants more vigilance in future investigations.

IMPORTANCEIntraoperative handovers of anesthesia care are common. Handovers might improve care by reducing physician fatigue, but there is also an inherent risk of losing critical information. Large observational analyses report associations between handover of anesthesia care and adverse events, including higher mortality.OBJECTIVE To determine the effect of handovers of anesthesia care on postoperative morbidity and mortality. DESIGN, SETTING, AND PARTICIPANTSThis was a parallel-group, randomized clinical trial conducted in 12 German centers with patients enrolled between June 2019 and June 2021 (final follow-up, July 31, 2021). Eligible participants had an American Society of Anesthesiologists physical status 3 or 4 and were scheduled for major inpatient surgery expected to last at least 2 hours.INTERVENTIONS A total of 1817 participants were randomized to receive either a complete handover to receive anesthesia care by another clinician (n = 908) or no handover of anesthesia care (n = 909). None of the participating institutions used a standardized handover protocol. MAIN OUTCOMES AND MEASURESThe primary outcome was a 30-day composite of all-cause mortality, hospital readmission, or serious postoperative complications. There were 19 secondary outcomes, including the components of the primary composite, along with intensive care unit and hospital lengths of stay. RESULTS Among 1817 randomized patients, 1772 (98%; mean age, 66 [SD,12] years; 997 men [56%]; and 1717 [97%] with an American Society of Anesthesiologists physical status of 3) completed the trial. The median total duration of anesthesia was 267 minutes (IQR, 206-351 minutes), and the median time from start of anesthesia to first handover was 144 minutes in the handover group (IQR, 105-213 minutes). The composite primary outcome occurred in 268 of 891 patients (30%) in the handover group and in 284 of 881 (33%) in the no handover group (absolute risk difference [RD], −2.5%; 95% CI, −6.8% to 1.9%; odds ratio [OR], 0.89; 95% CI, 0.72 to 1.10; P = .27). Nineteen of 889 patients (2.1%) in the handover group and 30 of 873 (3.4%) in the no handover group experienced all-cause 30-day mortality (absolute RD, −1.3%; 95% CI, −2.8% to 0.2%; OR, 0.61; 95% CI, 0.34 to 1.10; P = .11); 115 of 888 (13%) vs 136 of 872 (16%) were readmitted to the hospital (absolute RD, −2.7%; 95% CI, −5.9% to 0.6%; OR, 0.80; 95% CI, 0.61 to 1.05; P = .12); and 195 of 890 (22%) vs 189 of 874 (22%) experienced serious postoperative complications (absolute RD, 0.3%; 95% CI, −3.6% to 4.1%; odds ratio, 1.02; 95% CI, 0.81 to 1.28; P = .91). None of the 19 prespecified secondary end points differed significantly.CONCLUSIONS AND RELEVANCE Among adults undergoing extended surgical procedures, there was no significant difference between the patients randomized to receive handover of anesthesia care from one clinician to another, compared with the no handover group, in the composite primary outcome of mortality, readmission, or serious postoperative complications within 30 days.