Understanding the biases to sepsis surveillance and quality assurance caused by inaccurate coding in administrative health data.

PURPOSE: Timely and accurate data on the epidemiology of sepsis are essential to inform policy decisions and research priorities. We aimed to investigate the validity of inpatient administrative health data (IAHD) for surveillance and quality assurance of sepsis care. METHODS: We conducted a retrospective validation study in a disproportional stratified random sample of 10,334 inpatient cases of age ≥ 15 years treated in 2015-2017 in ten German hospitals. The accuracy of coding of sepsis and risk factors for mortality in IAHD was assessed compared to reference standard diagnoses obtained by a chart review. Hospital-level risk-adjusted mortality of sepsis as calculated from IAHD information was compared to mortality calculated from chart review information. RESULTS: ICD-coding of sepsis in IAHD showed high positive predictive value (76.9-85.7% depending on sepsis definition), but low sensitivity (26.8-38%), which led to an underestimation of sepsis incidence (1.4% vs. 3.3% for severe sepsis-1). Not naming sepsis in the chart was strongly associated with under-coding of sepsis. The frequency of correctly naming sepsis and ICD-coding of sepsis varied strongly between hospitals (range of sensitivity of naming: 29-71.7%, of ICD-diagnosis: 10.7-58.5%). Risk-adjusted mortality of sepsis per hospital calculated from coding in IAHD showed no substantial correlation to reference standard risk-adjusted mortality (r = 0.09). CONCLUSION: Due to the under-coding of sepsis in IAHD, previous epidemiological studies underestimated the burden of sepsis in Germany. There is a large variability between hospitals in accuracy of diagnosing and coding of sepsis. Therefore, IAHD alone is not suited to assess quality of sepsis care.

Interdisciplinary perspectives on computed tomography in sepsis: survey among medical doctors at a large university medical center.

OBJECTIVES: This study aims to describe physicians' perspectives on the use of computed tomography (CT) in patients with sepsis. METHODS: In January 2022, physicians of a large European university medical center were surveyed using a web-based questionnaire asking about their views on the role of CT in sepsis. A total of 371 questionnaires met the inclusion criteria and were analyzed using work experience, workplace, and medical specialty of physicians as variables. Chi-square tests were performed. RESULTS: Physicians considered the ability to detect an unknown focus as the greatest benefit of CT scans in sepsis (70.9%, n = 263/371). Two clinical criteria - "signs of decreased vigilance" (89.2%, n = 331/371) and "increased catecholamine demand" (84.7%, n = 314/371) - were considered highly relevant for a CT request. Elevated procalcitonin (82.7%, n = 307/371) and lactate levels (83.6%, n = 310/371) were consistently found to be critical laboratory values to request a CT. As long as there is evidence of infection in one organ region, most physicians (42.6%, n = 158/371) would order a CT scan based on clinical assessment. Combined examination of the chest, abdomen, and pelvis was favored (34.8%, n = 129/371) in cases without clinical clues of an infection source. A time window of ≥ 1-6 h was preferred for both CT examinations (53.9%, n = 200/371) and CT-guided interventions (59.3%, n = 220/371) in patients with sepsis. CONCLUSION: Despite much consensus, there are significant differences in attitudes towards the use of CT in septic patients among physicians from different workplaces and medical specialties. Knowledge of these perspectives may improve patient management and interprofessional communication. KEY POINTS: Despite interdisciplinary consensus on the use of CT in sepsis, statistically significant differences in the responses are apparent among physicians from different workplaces and medical specialties. The detection of a previously unknown source of infection and the ability to plan interventions and/or surgery based on CT findings are considered key advantages of CT in septic patients. Timing of CT reflects the requirements of specific disciplines.

Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort.

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.

[Laboratory and calorimetric monitoring of medical nutrition therapy in intensive and intermediate care units : Second position paper of the Section Metabolism and Nutrition of the German Interdisciplinary Association for Intensive Care and Emergency Medicine (DIVI)]. / Laborchemisches und kalorimetrisches Monitoring der medizinischen Ernährungstherapie auf der Intensiv- und Intermediate Care Station : Zweites Positionspapier der Sektion Metabolismus und Ernährung der Deutschen Interdisziplinären Vereinigung für Intensiv- und Notfallmedizin (DIVI).

This second position paper of the Section Metabolism and Nutrition of the German Interdisciplinary Association for Intensive Care and Emergency Medicine (DIVI) provides recommendations on the laboratory monitoring of macro- and micronutrient intake as well as the use of indirect calorimetry in the context of medical nutrition therapy of critically ill adult patients. In addition, recommendations are given for disease-related or individual (level determination) substitution and (high-dose) pharmacotherapy of vitamins and trace elements.

[Assessment and technical monitoring of nutritional status of patients in intensive and intermediate care units : Position paper of the Section Metabolism and Nutrition of the German Interdisciplinary Association for Intensive and Emergency Medicine (DIVI)]. / Erfassung und apparatives Monitoring des Ernährungsstatus von Patient*innen auf der Intensiv- und Intermediate Care Station : Positionspapier der Sektion Metabolismus und Ernährung der Deutschen Interdisziplinären Vereinigung für Intensiv- und Notfallmedizin (DIVI).

At the time of admission to an intensive or intermediate care unit, assessment of the patients' nutritional status may have both prognostic and therapeutic relevance with regard to the planning of individualized medical nutrition therapy (MNT). MNT has definitely no priority in the initial treatment of a critically ill patient, but is often also neglected during the course of the disease. Especially with prolonged length of stay, there is an increasing risk of malnutrition with considerable prognostic macro- and/or micronutrient deficit. So far, there are no structured, evidence-based recommendations for assessing nutritional status in intensive or intermediate care patients. This position paper of the Section Metabolism and Nutrition of the German Interdisciplinary Association for Intensive and Emergency Medicine (DIVI) presents consensus-based recommendations for the assessment and technical monitoring of nutritional status of patients in intensive and intermediate care units. These recommendations supplement the current S2k guideline "Clinical Nutrition in Intensive Care Medicine" of the German Society for Nutritional Medicine (DGEM) and the DIVI.

A proteomic survival predictor for COVID-19 patients in intensive care.

Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Additional tools are also needed to monitor treatment, including experimental therapies in clinical trials. Comprehensively capturing human physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index, and APACHE II score showed limited performance in predicting the COVID-19 outcome. Instead, the quantification of 321 plasma protein groups at 349 timepoints in 50 critically ill patients receiving invasive mechanical ventilation revealed 14 proteins that showed trajectories different between survivors and non-survivors. A predictor trained on proteomic measurements obtained at the first time point at maximum treatment level (i.e. WHO grade 7), which was weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81). We tested the established predictor on an independent validation cohort (AUROC 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that plasma proteomics can give rise to prognostic predictors substantially outperforming current prognostic markers in intensive care.

Circadian rhythms in septic shock patients.

BACKGROUND: Despite the intensive efforts to improve the diagnosis and therapy of sepsis over the last decade, the mortality of septic shock remains high and causes substantial socioeconomical burden of disease. The function of immune cells is time-of-day-dependent and is regulated by several circadian clock genes. This study aims to investigate whether the rhythmicity of clock gene expression is altered in patients with septic shock. METHODS: This prospective pilot study was performed at the university hospital Charité-Universitätsmedizin Berlin, Department of Anesthesiology and Operative Intensive Care Medicine (CCM, CVK). We included 20 patients with septic shock between May 2014 and January 2018, from whom blood was drawn every 4 h over a 24-h period to isolate CD14-positive monocytes and to measure the expression of 17 clock and clock-associated genes. Of these patients, 3 whose samples expressed fewer than 8 clock genes were excluded from the final analysis. A rhythmicity score SP was calculated, which comprises values between -1 (arrhythmic) and 1 (rhythmic), and expression data were compared to data of a healthy study population additionally. RESULTS: 77% of the measured clock genes showed inconclusive rhythms, i.e., neither rhythmic nor arrhythmic. The clock genes NR1D1, NR1D2 and CRY2 were the most rhythmic, while CLOCK and ARNTL were the least rhythmic. Overall, the rhythmicity scores for septic shock patients were significantly (p < 0.0001) lower (0.23 ± 0.26) compared to the control group (12 healthy young men, 0.70 ± 0.18). In addition, the expression of clock genes CRY1, NR1D1, NR1D2, DBP, and PER2 was suppressed in septic shock patients and CRY2 was significantly upregulated compared to controls. CONCLUSION: Molecular rhythms in immune cells of septic shock patients were substantially altered and decreased compared to healthy young men. The decrease in rhythmicity was clock gene-dependent. The loss of rhythmicity and down-regulation of clock gene expression might be caused by sepsis and might further deteriorate immune responses and organ injury, but further studies are necessary to understand underlying pathophysiological mechanisms. Trail registration Clinical trial registered with www.ClinicalTrials.gov (NCT02044575) on 24 January 2014.

Validation study of German inpatient administrative health data for epidemiological surveillance and measurement of quality of care for sepsis: the OPTIMISE study protocol.

INTRODUCTION: Sepsis is a major cause of preventable deaths in hospitals. This study aims to investigate if sepsis incidence and quality of care can be assessed using inpatient administrative health data (IAHD). METHODS AND ANALYSIS: Design: Retrospective observational validation study using routine data to assess the diagnostic accuracy of sepsis coding in IAHD regarding sepsis diagnosis based on medical record review. PROCEDURE: A stratified sample of 10 000 patients with an age ≥15 years treated in between 2015 and 2017 in 10 German hospitals is investigated. All available information of medical records is screened by trained physicians to identify true sepsis cases ('gold standard') both according to current ('sepsis-1') definitions and new ('sepsis-3') definitions. Data from medical records are linked to IAHD on patient level using a pseudonym. ANALYSES: Proportions of cases with sepsis according to sepsis-1 and sepsis-3 definitions are calculated and compared with estimates from coding of sepsis in IAHD. Predictive accuracy (sensitivity, specificity) of different coding abstraction strategies regarding the gold standard is estimated. Predictive accuracy of mortality risk factors obtained from IAHD regarding the respective risk factors obtained from medical records is calculated. An IAHD-based risk model for hospital mortality is compared with a record-based risk model regarding model-fit and predicted risk of death. Analyses adjust for sampling weights. The obtained estimates of sensitivity and specificity for sepsis coding in IAHD are used to estimate adjusted incidence proportions of sepsis based on German national IAHD. ETHICS AND DISSEMINATION: The study has been approved by the ethics commission of the Jena University Hospital (No. 2018-1065-Daten). The results of the study will be discussed in an expert panel to write a memorandum on improving the utility of IAHD for epidemiological surveillance and quality management of sepsis care. TRIAL REGISTRATION NUMBER: DRKS00017775; Pre-results.