Comparative Evaluation of the Prognosis of Septic Shock Patients from before to after the Onset of the COVID-19 Pandemic: A Retrospective Single-Center Clinical Analysis

In this study, we investigated the mortality of septic shock patients visiting emergency departments (ED) before and after the coronavirus disease (COVID-19) pandemic onset. We retrospectively reviewed medical records and National Emergency Department Information System data of septic shock patients who visited the ED of a tertiary medical center in South Korea from February 2019 to February 2021. Following the COVID-19 pandemic onset, revised institutional ED processes included a stringent isolation protocol for patients visiting the ED. The primary goal of this study was to determine the mortality rate of septic shock patients from before and after the onset of the COVID-19 pandemic. Durations of vasopressor use, mechanical ventilation, intensive care unit stay, and hospitalization were investigated. The mortality rates increased from 24.8% to 35.8%, before and after COVID-19-onset, but the difference was not statistically significant (p = 0.079). No significant differences in other outcomes were found. Multivariable analysis revealed that the Simplified Acute Physiology Score III (SAPS III) was the only risk factor for mortality (OR 1.07; 95% CI 1.04-1.10), whereas COVID-19 pandemic was not included in the final model. The non-significant influence of the COVID-19 pandemic on septic shock mortality rates in the present study belies the actual mortality-influencing potential of the COVID-19 pandemic.

Trends in Mortality after Intensive Care of Patients with Aneurysmal Subarachnoid Hemorrhage in Finland in 2003–2019: A Finnish Intensive Care Consortium study

Background Previous studies suggest that case mortality of aneurysmal subarachnoid hemorrhage (aSAH) has decreased during the last decades, but most studies have been unable to assess case severities among individual patients. We aimed to assess changes in severity-adjusted aSAH mortality in patients admitted to intensive care units (ICUs). Methods We conducted a retrospective, register-based study by using the prospectively collected Finnish Intensive Care Consortium database. Four out of five ICUs providing neurosurgical and neurointensive care in Finland participated in the Finnish Intensive Care Consortium. We extracted data on adult patients admitted to Finnish ICUs with aSAH between 2003 and 2019. The primary outcome was 12-month mortality during three periods: 2003–2008, 2009–2014, and 2015–2019. Using a multivariable logistic regression model—with variables including age, sex, World Federation of Neurological Surgeons grade, preadmission dependency, significant comorbidities, and modified Simplified Acute Physiology Score II—we analyzed whether admission period was independently associated with mortality. Results A total of 1,847 patients were included in the study. For the periods 2003–2008 and 2015–2019, the mean number of patients with aSAH admitted per year increased from 81 to 123. At the same time, the patients’ median age increased from 55 to 58 years (p = 0.001), and the proportion of patients with World Federation of Neurological Surgeons grades I–III increased from 42 to 58% (p < 0.001). The unadjusted 12-month mortality declined from 30% in 2003–2008 to 23% in 2015–2019 (p = 0.001), but there was no statistically significant change in severity-adjusted mortality. Conclusions Between 2003 and 2019, patients with aSAH admitted to ICUs became older and the proportion of less severe cases increased. Unadjusted mortality decreased but age and case severity adjusted–mortality remained unchanged.

Performance of Sequential Organ Failure Assessment and Simplified Acute Physiology Score II for Post-Cardiac Surgery Patients in Intensive Care Unit

Background: The aim of this study is to assess the performance of Sequential Organ Failure Assessment (SOFA) score and Simplified Acute Physiology Score (SAPS II) on outcomes of patients with cardiac surgery and identify the cutoff values to provide a reference for early intervention.Methods: All data were extracted from MIMIC-III (Medical Information Mart for Intensive Care-III) database. Cutoff values were calculated by the receiver-operating characteristic curve and Youden indexes. Patients were grouped, respectively, according to the cutoff values of SOFA and SAPS II. A non-adjusted model and adjusted model were established to evaluate the prediction of risk. Comparison of clinical efficacy between two scoring systems was made by decision curve analysis (DCA). The primary outcomes of this study were in-hospital mortality, 28-day mortality, 90-day mortality, and 1-year mortality after cardiac surgery. The secondary outcomes included length of hospital stay and intensive care unit (ICU) stay and the incidence of acute kidney injury (AKI) within 7 days after ICU admission.Results: A total of 6,122 patients were collected and divided into the H-SOFA group (SOFA ≥ 7) and L-SOFA group (SOFA &lt; 7) or H-SAPS II group (SAPS II ≥ 43) and L-SAPS II group (SAPS II &lt; 43). In-hospital mortality, 28-day mortality, 90-day mortality, and 1-year mortality were higher, the length of hospital and ICU stay were longer in the H-SOFA group than in the L-SOFA group (p &lt; 0.05), while the incidence of AKI was not significantly different. In-hospital mortality, 28-day mortality, 90-day mortality, 1-year mortality, and the incidence of AKI were all significantly higher in the H-SAPS II group than in the L-SAPS II group (p &lt; 0.05). Hospital stay and ICU stay were longer in the H-SAPS II group than in the L-SAPS II group (p &lt; 0.05). According to DCA, the SAPS II scoring system had more net benefits on assessing the long-term mortality compared with the SOFA scoring system.Conclusion: Exceeding the cutoff values of SOFA and SAPS II scores could lead to increased mortality and extended length of ICU and hospital stay. The SAPS II scoring system had a better discriminative performance of 90-day mortality and 1-year mortality in post-cardiac surgery patients than the SOFA scoring system. Emphasizing the critical value of the scoring system is of significance for timely treatment.

Retrospective observational study evaluating zinc plasma level in patients undergoing thoracoabdominal aortic aneurysm repair and its correlation with outcome

Thoracoabdominal aortic aneurysm (TAAA) repair is related to a relevant morbidity and in-hospital mortality rate. In this retrospective observational single-center study including serum zinc levels of 33 patients we investigated the relationship between zinc and patients’ outcome following TAAA repair. Six patients died during the hospital stay (18%). These patients showed significantly decreased zinc levels before the intervention (zinc levels before intervention: 60.09 µg/dl [survivors] vs. 45.92 µg/dl [non-survivors]). The post-interventional intensive care SOFA-score (Sepsis-related organ failure assessment) (at day 2) as well as the SAPS (Simplified Acute Physiology Score) (at day 2) showed higher score points in case of low pre-interventional zinc levels. No significant correlation between patient comorbidities and zinc level before intervention, except for peripheral arterial disease (PAD), which was significantly correlated to reduced baseline zinc levels, was observed. Septic shock, pneumonia and urinary tract infections were not associated to reduced zinc levels preoperatively as well as during therapy. Patients with adverse outcome after TAAA repair showed reduced pre-interventional zinc levels. We speculate that decreased zinc levels before intervention may be related to a poorer outcome because of poorer physical status as well as negatively altered perioperative inflammatory response.

Effect of antibiotic therapy on the prognosis of ventilator-associated pneumonia caused by Stenotrophomonas maltophilia

Background Ventilator-associated pneumonia (VAP) caused by Stenotrophomonas maltophilia is poorly described in the literature. However, it has been shown to be associated with increased morbidity and mortality. Probabilistic antibiotic therapy against S. maltophilia is often ineffective as this pathogen is resistant to many antibiotics. There is no consensus at present on the best therapeutic strategy to adopt (class of antibiotics, antibiotic combination, dosage, treatment duration). The aim of this study was to evaluate the effect of antibiotic therapy strategy on the prognosis of patients with VAP caused by S. maltophilia. Results This retrospective study evaluated all consecutive patients who developed VAP caused by S. maltophilia between 2010 and 2018 while hospitalized in the intensive care unit (ICU) of a French university hospital in Reunion Island, in the Indian Ocean region. A total of 130 patients with a median Simplified Acute Physiology Score II of 58 [43–73] had VAP caused by S. maltophilia after a median duration of mechanical ventilation of 12 [5–18] days. Ventilator-associated pneumonia was polymicrobial in 44.6% of cases, and ICU mortality was 50.0%. After multivariate Cox regression analysis, the factors associated with increased ICU mortality were older age (hazard ratio (HR): 1.03; 95% CI 1.01–1.04, p = 0.001) and high Sequential Organ Failure Assessment score on the day of VAP onset (HR: 1.08; 95% CI 1.03–1.14, p = 0.002). Appropriate antibiotic therapy, and in particular trimethoprim–sulfamethoxazole, was associated with decreased ICU mortality (HR: 0.42; 95% CI 0.24–0.74, p = 0.003) and decreased hospital mortality (HR: 0.47; 95% CI 0.28–0.79, p = 0.04). Time to start of appropriate antibiotic therapy, combination therapy, and duration of appropriate antibiotic therapy had no effect on ICU mortality (p > 0.5). Conclusion In our study, appropriate antibiotic therapy, and in particular trimethoprim–sulfamethoxazole, was associated with decreased ICU and hospital mortality in patients with VAP caused by S. maltophilia.

Neutrophil-to-lymphocyte ratio as a predictor of mortality in intensive care unit patients: a retrospective analysis of the Medical Information Mart for Intensive Care III Database

ObjectivesIdentifying high-risk patients in the intensive care unit (ICU) is important given the high mortality rate. However, existing scoring systems lack easily accessible, low-cost and effective inflammatory markers. We aimed to identify inflammatory markers in routine blood tests to predict mortality in ICU patients and evaluate their predictive power.DesignRetrospective case–control study.SettingSingle secondary care centre.ParticipantsWe analysed data from the Medical Information Mart for Intensive Care III database. A total of 21 822 ICU patients were enrolled and divided into survival and death groups based on in-hospital mortality.Primary and secondary outcome measuresThe predictive values of potential inflammatory markers were evaluated and compared using receiver operating characteristic curve analysis. After identifying the neutrophil-to-lymphocyte ratio (NLR) as having the best predictive ability, patients were redivided into low (≤1), medium (1–6) and high (>6) NLR groups. Univariate and multivariate logistic regression analyses were performed to evaluate the association between the NLR and mortality. The area under the curve (AUC), net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were used to assess whether incorporating the NLR could improve the predictive power of existing scoring systems.ResultsThe NLR had the best predictive ability (AUC: 0.609; p<0.001). In-hospital mortality rates were significantly higher in the low (OR (OR): 2.09; 95% CI 1.64 to 2.66) and high (OR 1.64; 95% CI 1.50 to 1.80) NLR groups than in the medium NLR group. Adding the NLR to the Simplified Acute Physiology Score II improved the AUC from 0.789 to 0.798, with an NRI and IDI of 16.64% and 0.27%, respectively.ConclusionsThe NLR predicted mortality in ICU patients well. Both low and high NLRs were associated with elevated mortality rates, including the NLR may improve the predictive power of the Simplified Acute Physiology Score II.

Development and Validation of an Interpretable 3-day Intensive Care Unit Readmission Prediction Model Using Explainable Boosting Machines

Intensive care unit readmissions are associated with mortality and bad outcomes. Machine learning could help to identify patients at risk to improve discharge decisions. However, many models are black boxes, so that dangerous properties might remain unnoticed. In this study, an inherently interpretable model for 3-day ICU readmission prediction was developed. We used a retrospective cohort of 15,589 ICU stays and 169 variables collected between 2006 and 2019. A team of doctors inspected the model, checked the plausibility of each component, and removed problematic parts. Qualitative feedback revealed several challenges for interpretable machine learning in healthcare. The resulting model used 67 features and showed an area under the precision-recall curve of 0.119+/-0.020 and an area under the receiver operating characteristic curve of 0.680+/-0.025. This is on par with state-of-the-art gradient boosting machines and outperforms the Simplified Acute Physiology Score II. External validation with the Medical Information Mart for Intensive Care database version IV confirmed our findings. Hence, a machine learning model for readmission prediction with a high level of human control is feasible without sacrificing performance.

Pediatric Simplified Acute Physiology Score II: Establishment of a New, Repeatable Pediatric Mortality Risk Assessment Score

Objectives: In critical care it is crucial to appropriately assess the risk of mortality for each patient. This is especially relevant in pediatrics, with its need for accurate and repeatable scoring. Aim of this study was to evaluate an age-adapted version of the expanded Simplified Acute Physiology Score II; (p-SAPS II), a repeatable, newly-designed scoring system compared to established scores (Pediatric Sequential Organ Failure Assessment Score/pSOFA, Pediatric Logistic Organ Dysfunction Score-2/PELOD-2 and Pediatric Index of Mortality 3/PIM3).Design: This retrospective cohort pilot study included data collected from patients admitted to the Pediatric Intensive Care Unit (PICU) at the Medical University of Vienna between July 2017 through December 2018.Patients: 231 admissions were included, comprising neonates (gestational age of ≥ 37 weeks) and patients up to 18 years of age with a PICU stay longer than 48 h.Main Outcomes: Mortality risk prediction and discrimination between survivors and non-survivors were the main outcomes of this study. The primary statistical methods for evaluating the performance of each score were the area under the receiver operating characteristic curve (AUROC) and goodness-of-fit test.Results: Highest AUROC curve was calculated for p-SAPS II (AUC = 0.86; 95% CI: 0.77–0.96; p &lt; 0.001). This was significantly higher than the AUROCs of PELOD-2/pSOFA but not of PIM3. However, in a logistic regression model including p-SAPS II and PIM3 as covariates, p-SAPS II had a significant effect on the accuracy of prediction (p = 0.003). Nevertheless, according to the goodness-of-fit test for p-SAPS II and PIM3, p-SAPS II overestimated the number of deaths, whereas PIM3 showed acceptable estimations. Repeatability testing showed increasing AUROC values for p-SAPS II throughout the clinical stay (0.96 at day 28) but still no significant difference to PIM 3. The prediction accuracy, although improved over the days and even exceeded PIM 3.Conclusions: The newly-created p-SAPS II performed better than the established PIM3 in terms of discriminating between survivors and non-survivors. Furthermore, p-SAPS II can be assessed repeatably throughout a patient's PICU stay what improves mortality prediction. However, there is still a need to optimize calibration of the score to accurately predict mortality sooner throughout the clinical stay.

Sentiment Analysis for Necessary Preview of 30-Day Mortality in Sepsis Patients and the Control Strategies

This study was to preview the risk of 30-day mortality in sepsis patients using sentiment analysis. The clinical data of patients and nursing notes were collected from the Medical Information Mart for Intensive Care (MIMIC-III) database. The factors influencing 30-day mortality were analyzed using the Cox regression model. And, the prognostic index (PI) was estimated. The receiver operating characteristic (ROC) curve was used to determine the PI cut-off point and assess the prediction ability of the model. In total, 1844 of 3560 patients were eligible for the study, with a 30-day mortality of 37.58%. Multivariate Cox analysis showed that sentiment polarity scores, sentiment subjectivity scores, simplified acute physiology score (SAPS)-II, age, and intensive care unit (ICU) types were all associated with the risk of 30-day mortality ( P < 0.05 ). In the preview of 30-day mortality, the area under the curve (AUC) of ROC was 0.78 (95%CI: 0.74–0.81, P < 0.001 ) when the cut-off point of PI was 0.467. The documented notes from nurses were described for the first time. Sentiment scores measured in nursing notes are associated with the risk of 30-day mortality in sepsis patients and may improve the preview of 30-day mortality.