BACKGROUND: Sepsis is a severe medical condition that can be life-threatening. If sepsis progresses to septic shock, the mortality rate increases to around 40%, much higher than the 10% mortality observed in sepsis. Diabetes increases infection and sepsis risk, making management complex. Various scores of screening tools, such as Modified Early Warning Score (MEWS), Simplified Acute Physiology Score (SAPS II), Sequential Organ Failure Assessment Score (SOFA), and Acute Physiology and Chronic Health Evaluation (APACHE II), are used to predict the severity or mortality rate of disease. Our study aimed to compare the effectiveness and optimal cutoff points of these scores. We focused on the early prediction of septic shock in patients with diabetes in the Emergency Department (ED).
METHODS: We conducted a retrospective cohort study to collect data on patients with diabetes. We collected prediction factors and MEWS, SOFA, SAPS II and APACHE II scores to predict septic shock in these patients. We determined the optimal cutoff points for each score. Subsequently, we compared the identified scores with the gold standard for diagnosing septic shock by applying the Sepsis-3 criteria.
RESULTS: Systolic blood pressure (SBP), peripheral oxygen saturation (SpO2), Glasgow Coma Scale (GCS), pH, and lactate concentrations were significant predictors of septic shock (p < 0.001). The SOFA score performed well in predicting septic shock in patients with diabetes. The area under the receiver operating characteristics (ROC) curve for the SOFA score was 0.866 for detection within 48 h and 0.840 for detection after 2 h of admission to the ED, with the optimal cutoff score of ≥ 6.
CONCLUSIONS: SBP, SpO2, GCS, pH, and lactate concentrations are crucial for the early prediction of septic shock in patients with diabetes. The SOFA score is a superior predictor for the onset of septic shock in patients with diabetes compared with MEWS, SAPS II, and APACHE II scores. Specifically, a cutoff of ≥ 6 in the SOFA score demonstrates high accuracy in predicting shock within 48 h post-ED visit and as early as 2 h after ED admission.

UNASSIGNED: Intermediate care units (IMCUs) serve as step-up units for emergency department patients and as step-down units for critically ill patients transferred from intensive care units. This study compares four critical illness scores for assessment of acutely ill patients and their accuracy in predicting mortality in patients admitted to IMCU.
UNASSIGNED: A comparative cross-sectional study on patients aged ≥18 admitted to IMCU of Aga Khan University Hospital from 2017 to 2019. All patients admitted to IMCU from the emergency room were included in the study. Patient\'s record were reviewed for demographic data, physiological and laboratory parameters. Critical illness scores were calculated from these variables for each patient.
UNASSIGNED: A total of 1192 patients were admitted to the IMCU, of which 923 (77.4%) medical records were finally analyzed. The mean (SD) age of participants was 62 years (± 16.5) and 469 (50.8%) were women. The overall hospital mortality rate of patients managed in IMCU was 6.4% (59/923 patients). The median scores of APACHE II, SOFA, SAPS II and MEWS were 16 (IQR 11-21), 4 (IQR 2-6), 36 (IQR 30-53) and 3 (IQR 2-4) points respectively. AUC for SAPS II was 0.763 (95% CI: 0.71-0.81), SOFA score was 0.735 (95% CI: 0.68-0.79) and MEWS score was 0.714 (95% CI: 0.66-0.77). The lowest ROC curve was 0.584 (95% CI: 0.52-0.64) for APACHE II.
UNASSIGNED: In conclusion, our study found that SAPS II, followed by SOFA and MEWS scores, provided better discrimination in stratifying critical illness in patients admitted to IMCU of a tertiary care hospital in Pakistan.

BACKGROUND: Intensive Care Units (ICUs) pose challenges in managing critically-ill patients with polypharmacy, potentially leading to Adverse Drug Reactions (ADRs), particularly in the elderly.
OBJECTIVE: To evaluate whether the severity and clinical prognosis scores used in ICUs correlate with the prediction of ADRs in aged patients admitted to an ICU.
METHODS: A cohort study was conducted in a Brazilian University Hospital ICU. APACHE II and SAPS 3 assessed clinical prognosis, while GerontoNet ADR Risk Score and BADRI evaluated ADR risk at ICU admission. Severity of the patients\' clinical conditions was evaluated daily based on the SOFA score. Adverse Drug Reaction (ADR) screening was performed daily through the identification of ADR triggers.
RESULTS: 1295 triggers were identified (median 30 per patient, IQR = 28), with 15 suspected ADRs. No correlation was observed between patient severity and ADRs at admission (p=0.26), during hospitalization (p=0.91), or at follow-up (p=0.77). There was also no association between death and ADRs (p=0.28) or worse prognosis and ADRs (p>0.05). Higher BADRI scores correlated with more ADRs (p=0.001).
CONCLUSIONS: The data suggest that employing the severity and clinical prognosis scores used in Intensive Care Units is not sufficient to direct active pharmacovigilance efforts, which are therefore indicated for critically ill patients.

The study of the outcomes of critically ill patients has been a hard stuff in the field of intensive care. To explore the relationship between changes of severity scores, bioelectrical impedance analysis (BIA) and outcomes of critically ill patients, we enrolled patients (n = 206) admitted to intensive care unit (ICU) in Jinling Hospital from 2018 to 2021 with records of BIA on the days 1- and 3- ICU. Collected BIA and clinical data including simplified acute physiology score II (SAPS II) and sequential organ failure assessment. According to the baseline and change of severity scores or phase angle (PA) values, the patients were divided into: G-G, baseline good status, 3rd day unchanged; G-B, baseline good status, 3rd day deteriorated; B-G, baseline bad status, 3rd day improved; and B-B, baseline bad status, 3rd day unchanged. According to PA, the mortality of group G-G was 8.6%, and it was greater than 50% in group B-B for severity scores. The new score combining PA and severity scores established. Multivariate logistic regression analysis revealed that PA-SAPS II score was the only independent factor for 90-day mortality (P < 0.05). A linear correlation was found between mortality and PA-SAPS II score (prediction equation: Y ( % ) = 16.97 × X - 9.67 , R2 = 0.96, P < 0.05).

OBJECTIVE: The identification of patients at greater mortality risk of death at admission into an intensive cardiovascular care unit (ICCU) has relevant consequences for clinical decision-making. We described patient characteristics at admission into an ICCU by predicted mortality risk assessed with noncardiac intensive care unit (ICU) and evaluated their performance in predicting patient outcomes.
METHODS: A total of 202 consecutive patients (130 men, 75 ± 12 years) were admitted into our tertiary-care ICCU in a 20-week period. We evaluated, on the first 24 h data, in-hospital mortality risk according to Acute Physiology and Chronic Health Evaluation II (APACHE II) and Simplified Acute Physiology Score 3 (SAPS 3); Sepsis related Organ Failure Assessment (SOFA) Score and the Mayo Cardiac intensive care unit Admission Risk Score (M-CARS) were also calculated.
RESULTS: Predicted mortality was significantly lower than observed (5% during ICCU and 7% at discharge) for APACHE II and SAPS 3 (17% for both scores). Mortality risk was associated with older age, more frequent comorbidities, severe clinical presentation and complications. The APACHE II, SAPS 3, SOFA and M-CARS had good discriminative ability in distinguishing deaths and survivors with poor calibration of risk scores predicting mortality.
CONCLUSIONS: In a recent contemporary cohort of patients admitted into the ICCU for a variety of acute and critical cardiovascular conditions, scoring systems used in general ICU had good discrimination for patients\' clinical severity and mortality. Available scores preserve powerful discrimination but the overestimation of mortality suggests the importance of specific tailored scores to improve risk assessment of patients admitted into ICCUs.

BACKGROUND: Intensive care units (ICUs) pose challenges in managing critically ill patients with polypharmacy, potentially leading to adverse drug reactions (ADRs), particularly in the elderly.
OBJECTIVE: To evaluate whether the severity and clinical prognosis scores used in ICUs correlate with the prediction of ADRs in aged patients admitted to an ICU.
METHODS: A cohort study was conducted in a Brazilian University Hospital ICU. APACHE II and SAPS 3 assessed clinical prognosis, while GerontoNet ADR Risk Score and BADRI evaluated ADR risk at ICU admission. Severity of the patients\' clinical conditions was evaluated daily based on the SOFA score. ADR screening was performed daily through the identification of ADR triggers.
RESULTS: 1295 triggers were identified (median 30 per patient, IQR=28), with 15 suspected ADRs. No correlation was observed between patient severity and ADRs at admission (p=0.26), during hospitalization (p=0.91), or at follow-up (p=0.77). There was also no association between death and ADRs (p=0.28) or worse prognosis and ADRs (p>0.05). Higher BADRI scores correlated with more ADRs (p=0.001).
CONCLUSIONS: These data suggest that employing the severity and clinical prognosis scores used in ICUs is not sufficient to direct active pharmacovigilance efforts, which are therefore indicated for critically ill patients.

This study investigates the predictive value and suitable cutoff values of the Sepsis-related Organ Failure Assessment Score (SOFA) and Simplified Acute Physiology Score II (SAPS-II) to predict mortality during or after Intensive Care Unit Cardiac Arrest (ICU-CA).
In this secondary analysis the ICU database of a German university hospital with five ICU was screened for all ICU-CA between 2016-2019. SOFA and SAPS-II were used for prediction of mortality during ICU-CA, hospital-stay and one-year-mortality. Receiver operating characteristic curves (ROC), area under the ROC (AUROC) and its confidence intervals were calculated. If the AUROC was significant and considered \"acceptable,\" cutoff values were determined for SOFA and SAPS-II by Youden Index. Odds ratios and sensitivity, specificity, positive and negative predictive values were calculated for the cutoff values.
A total of 114 (78 male; mean age: 72.8±12.5 years) ICU-CA were observed out of 14,264 ICU-admissions (incidence: 0.8%; 95% CI: 0.7-1.0%). 29.8% (N.=34; 95% CI: 21.6-39.1%) died during ICU-CA. SOFA and SAPS-II were not predictive for mortality during ICU-CA (P>0.05). Hospital-mortality was 78.1% (N.=89; 95% CI: 69.3-85.3%). SAPS-II (recorded within 24 hours before and after ICU-CA) indicated a better discrimination between survival and death during hospital stay than SOFA (AUROC: 0.81 [95% CI: 0.70-0.92] vs. 0.70 [95% CI: 0.58-0.83]). A SAPS-II-cutoff-value of 43.5 seems to be suitable for prognosis of hospital mortality after ICU-CA (specificity: 87.5%, sensitivity: 65.6%; SAPS-II>43.5: 87.5% died in hospital; SAPS-II<43.5: 65.6% survived; odds ratio:13.4 [95% CI: 3.25-54.9]). Also for 1-year-mortality (89.5%; 95% CI: 82.3-94.4) SAPS-II showed a better discrimination between survival and death than SOFA: AUROC: 0.78 (95% CI: 0.65-0.91) vs. 0.69 (95% CI: 0.52-0.87) with a cutoff value of the SAPS-II of 40.5 (specificity: 91.7%, sensitivity: 64.3%; SAPS-II>40.5: 96.4% died; SAPS-II<40.5: 42.3% survived; odd ratio: 19.8 [95% CI: 2.3-168.7]).
Compared to SOFA, SAPS-II seems to be more suitable for prediction of hospital and 1-year-mortality after ICU-CA.

OBJECTIVE: Intensive care requires extensive resources. The ICUs\' resource use can be compared using standardized resource use ratios (SRURs). We assessed the effect of mortality prediction models on the SRURs.
METHODS: We compared SRURs using different mortality prediction models: the recent Finnish Intensive Care Consortium (FICC) model and the SAPS-II model (n = 68,914 admissions). We allocated the resources to severity of illness strata using deciles of predicted mortality. In each risk and year stratum, we calculated the expected resource use per survivor from our modelling approaches using length of ICU stay and Therapeutic Intervention Scoring System (TISS) points.
RESULTS: Resource use per survivor increased from one length of stay (LOS) day and around 50 TISS points in the first decile to 10 LOS-days and 450 TISS in the tenth decile for both risk scoring systems. The FICC model predicted mortality risk accurately whereas the SAPS-II grossly overestimated the risk of death. Despite this, SRURs were practically identical and consistent.
CONCLUSIONS: SRURs provide a robust tool for benchmarking resource use within and between ICUs. SRURs can be used for benchmarking even if recently calibrated risk scores for the specific population are not available.

BACKGROUND: The elderly population is unique and the prognostic scoring systems developed for the adult population need to be validated. We evaluated the predictive value of frequently used scoring systems on mortality in critically ill elderly sepsis patients.
METHODS: In this single-center, observational, prospective study, critically ill elderly sepsis patients were evaluated. Sequential organ failure evaluation score (SOFA), acute physiology and chronic health evaluation score-II (APACHE-II), logistic organ dysfunction score (LODS), multiple organ dysfunction score (MODS), and simplified acute physiology score-II (SAPS-II) were calculated. The participants were followed up for 28 days for in-hospital mortality. Prognostic scoring systems, demographic characteristics, comorbid conditions, and baseline laboratory findings were compared between \"survivor\" and \"non-survivor\" groups.
RESULTS: 202 patients with a mean age of 79 (interquartile range, IQR: 11) years were included, and 51% (n = 103) were female. The overall mortality was 41% (n = 83). SOFA, APACHE-II, LODS, MODS, and SAPS-II scores were significantly higher in the non-survivor group (p < 0.001), and higher scores were correlated with higher mortality. The receiver operator characteristics (ROC) - area under curve (AUC) values were 0.802, 0.784, 0.735, 0.702 and 0.780 for SOFA, APACHE-II, LODS, MODS, and SAPS-II, respectively. All prognostic scoring models had a significant discriminative ability on the prediction of mortality among critically ill elderly sepsis patients (p < 0.001).
CONCLUSIONS: This study showed that SOFA, APACHE-II, LODS, MODS, and SAPS-II scores are significantly associated with 28-day mortality in critically ill elderly sepsis patients, and can be successfully used for predicting mortality.

Background: It is not known whether anatomical scores perform better than general critical care scores for trauma patients admitted to the intensive care unit (ICU). We compare the predictive performance for hospital mortality of general critical care scores (SAPS 3 and SOFA) with anatomical injury-based scores (Injury Severity Score [ISS] and New ISS [NISS]). Methods: Retrospective cohort study of patients admitted to a specialized trauma ICU from a tertiary hospital in São Paulo, Brazil between May, 2012 and January, 2016. We retrieved data from the ICU database for critical care scores and calculated ISS and NISS from chart data and whole body computed tomography results. We compared the predictive performance for hospital mortality of each model through discrimination, calibration, and decision-curve analysis. Results: The sample comprised 1053 victims of trauma admitted to the ICU, with 84.2% male patients and mean age of 40 (±18) years. Main injury mechanism was blunt trauma (90.7%). Traumatic brain injury was present in 67.8% of patients; 43.3% with severe TBI. At the time of ICU admission, 846 patients (80.3%) were on mechanical ventilation and 644 (64.3%) on vasoactive drugs. Hospital mortality was 23.8% (251). Median SAPS 3 was 41; median maximum SOFA within 24 h of admission, 7; ISS, 29; and NISS, 41. AUROCs (95% CI) were: SAPS 3 = 0.786 (0.756-0.817), SOFA = 0.807 (0.778-0.837), ISS = 0.616 (0.577-0.656), and NISS = 0.689 (0.649-0.729). In pairwise comparisons, SAPS 3 and SOFA did not differ, while both outperformed the anatomical scores (p < .001). Maximum SOFA within 24 h of admission presented the best calibration and net benefit in decision-curve analysis. Conclusions: Trauma-specific anatomical scores have fair performance in critically ill trauma patients and are outperformed by SAPS 3 and SOFA. Illness severity is best characterized by organ dysfunction and physiological variables than anatomical injuries.