Freely available datasets have become an invaluable tool to propel data-driven research, especially in the field of critical care medicine. However, the number of datasets available is limited. This leads to the repeated reuse of datasets, inherently increasing the risk of selection bias. Additionally, the need arose to validate insights derived from one dataset with another. In 2023, the Salzburg Intensive Care database (SICdb) was introduced. SICdb offers insights in currently 27,386 intensive care admissions from 21,583 patients. It contains cases of general and surgical intensive care from all disciplines. Amongst others SICdb contains information about: diagnosis, therapies (including data on preceding surgeries), scoring, laboratory values, respiratory and vital signals, and configuration data. Data for SICdb (1.0.6) was collected at one single tertiary care institution of the Department of Anesthesiology and Intensive Care Medicine at the Salzburger Landesklinik (SALK) and Paracelsus Medical University (PMU) between 2013 and 2021. This article aims to elucidate on the characteristics of the dataset, the technical implementation, and provides analysis of its strengths and limitations.

Background: High sensitive cardiac troponin T (hsTnT) is a widely used biomarker of myocardial injury. Along with other high sensitive troponins, HsTnT can predict mortality in both cardiac and non-cardiac surgery. The aim of this study was to determine the association between hsTnT serum elevations in the immediate postoperative period until 120 h after cardiac surgery and the occurrence of in‐hospital mortality compared to the Simplified Acute Physiology Score 3 (SAPS3). Additionally, we identified an ideal hsTnT serum threshold to predict in‐hospital mortality. Methods: We performed a retrospective single-institutional cohort analysis of 2179 patients undergoing cardiac surgery with cardiopulmonary bypass from 2013 to 2021. Logistic regression analysis was used to investigate an association of hsTnT at various time points and in-hospital mortality. The model was adjusted for relevant covariates including SAPS3, lactate and administered norepinephrine dosage. ROC analysis was performed to estimate the accuracy to predict mortality by serum hsTnT concentrations. This prediction was compared to the SAPS3 score. An ideal cutoff of hsTnT concentration was calculated by means of Youden index. Results: In total 7576 troponins were measured at the predefined timepoints. 100 (4.59%) patients died during the hospital stay. The fourth hsTnT on d3 (at 96–120 h postoperatively) showed the highest association with in-hospital death (OR 1.56; 95% CI (1.39–1.76); p < 0.001). This finding persisted after multivariable adjustment (aOR 1.34; 95% CI (1.18–1.53); p < 0.001). In contrast, the third hsTnT on d2 (at 48–72 h postoperatively) showed the best discrimination for in-hospital mortality (AUC 82.75%; 95% CI (0.77–0.89). The prediction by the third hsTnT was comparable to the in-hospital mortality prediction by SAPS3 (AUC 79.36%; 95% CI (0.73–0.85); p = 0.056). The optimal cutoff for the third hsTnT was calculated to be 1264 ng/L (Sensitivity 0.62; Specificity 0.88). Conclusion: Elevated hsTnT after cardiac surgery was associated with an increased risk of in-hospital mortality. HsTnT measured on postoperative day 2 and 3 were most accurate to predict in-hospital mortality. The prediction of in-hospital mortality using hsTNT is comparable to mortality prediction using the SAPS3 score. HsTnT serum levels currently recommended to establish clinically important periprocedural myocardial injury are lower than thresholds identified in this study.

Objectives: EuroSCORE II is widely used to predict perioperative and 30-day mortality in cardiac surgery, yet data on its ability to predict long-term outcomes remain limited. This study investigates whether EuroSCORE II is associated with one-year and long-term mortality in a heterogeneous population undergoing major cardiac surgery with cardiopulmonary bypass. Methods: A retrospective cohort study was conducted including 2179 patients who underwent elective or urgent cardiac surgery with cardiopulmonary bypass between 2017 and 2021 at the University Hospital Salzburg. Data were extracted from the Salzburg Intensive Care database (SICdb) and supplemented with mortality information from Statistik Austria. EuroSCORE II values were compared between survivors and non-survivors. Kaplan–Meier analyses, Cox regression and logistic regression with ROC analysis were performed to evaluate the predictive association of EuroSCORE II with mortality. Results: EuroSCORE II was significantly higher in patients who died within one year and in those who died during a mean follow-up period of 1152.67 ± 521.39 days. Patients who survived at least one year had a median EuroSCORE II of 2.2, whereas those who died within one year had a median of 7.0. Cox regression demonstrated a hazard ratio of 1.062 for one-year mortality and 1.058 for long-term mortality. Kaplan–Meier curves showed significantly reduced survival with increasing EuroSCORE II quartiles. Logistic regression for one-year mortality yielded an AUC of 0.773, indicating good discriminative ability. Conclusions: EuroSCORE II is significantly associated with long-term mortality after major cardiac surgery, demonstrating good discriminatory performance. These findings support its potential utility not only as a short-term but also as a long-term prognostic indicator in cardiac surgery populations.

Open access intensive care unit (ICU) databases, including MIMIC-III, MIMIC-IV, the eICU Collaborative Research Database (eICU-CRD), AmsterdamUMCdb, HiRID-

Elective coronary artery bypass grafting (CABG) surgeries are increasingly scheduled during nighttime or after-hours. This poses unique challenges, such as reduced staffing, disrupted circadian rhythms, and increased fatigue, which may potentially affect outcomes. Despite growing evidence on the impact of daytime on cardiac surgery outcome, results remain inconclusive. The current study aims to investigate a potential association between surgery timing (daytime: 7:00 AM to 7:00 PM vs. nighttime: 7:00 PM to 7:00 AM) and long-term survival in patients undergoing elective CABG. In this retrospective single-institution cohort study at the University Clinic Salzburg, Austria, we analyzed elective CABG surgeries performed between January 1, 2017, and December 31, 2021. The primary hypothesis was that nighttime elective CABG surgeries have worse long-term survival. Among 2,179 cardiac surgical procedures, 723 elective CABG surgeries were identified and analyzed. Long-term survival was assessed using Cox proportional hazard modeling, while secondary outcomes, including 30-day and one-year mortality rates, were evaluated through multiple linear regression analysis. The one-year mortality rate was 2.6% (n = 19) for the observation period. Of the 723 patients, 646 (89.35%) underwent daytime surgery, and 77 (10.65%) had nighttime surgery. The median EuroScore II was 1.50 [1.00, 2.60] for daytime surgeries and 1.70 [1.10, 3.10] for nighttime surgeries (p = 0.111). There was no association between nighttime surgery and long-term mortality (aHR: 1.624, 95% CI: 0.589 to 3.662, p = 0.3179). Multivariable logistic regression analysis confirmed that nighttime surgeries were not significantly associated with increased one-year mortality (aOR: 1.089, 95% CI: 0.208 to 3.711, p = 0.905). No deaths occurred within 30 days in either group. This analysis found no significant association between nocturnal elective CABG operations and increased long-term or one-year mortality. This study did not aim to evaluate the economics of nocturnal surgeries at the investigated institution. To confirm our results that there is no increased morbidity and mortality associated with nocturnal CABG operations, and to understand the economic impact of nocturnal surgeries, prospective randomized studies would be necessary.