Prognostic value of PGI score compared to poison severity score (PSS) and simplified acute physiology score (SAPS) II as predictors of mortality and other adverse outcomes in acute poisoning with aluminum phosphide.

Aluminum phosphide (AlP) poisoning is a life-threatening emergency prevalent in the Middle East region including Egypt. Early prediction of prognosis is critical for initiating the utmost intensive interventions. Though many scoring systems were studied for predicting the prognosis of AlP poisoning, these scores received wide criticism. Complexity and reliability were the main concerns. Therefore, this retrospective cross-sectional study aimed to evaluate the performance of the recently introduced PGI score as a predictor of case fatality, the need for mechanical ventilation and vasopressor therapy in acute AlP poisoning. Moreover, it compares the performance of PGI with the known poison severity score (PSS), and the simplified acute physiology score (SAPS) II. Among 144 exposed patients, we reported a mortality rate of 61.1%. Non-survivors exhibited significantly higher PGI, PSS, and SAPS II than survivors. Though the PGI, PSS, and SAPS II proved their significance as predictors of mortality and, the need for MV and vasopressors, the PGI score showed a significantly higher area under the curve (AUC) as a predictor of MV (AUC = 0.848) compared to PSS (AUC = 0.731) and SAPS II (AUC = 0.749). Additively, PGI of 2 or more was a significant predictor of mortality (AUC = 0.831, sensitivity = 65.9%, and specificity = 89.3 %) and MV (p < 0.001), while PGI of 1 or more was another predictor of vasopressor need (AUC = 0.881, sensitivity = 89.0% and specificity = 79.4%). Given the PGI score's high AUCs across all outcomes, coupled with its balanced sensitivity and specificity, the PGI score could be a simple, and robust tool replacing the PSS and SAPS II for predicting mortality, clinical decision-making including the need for MV and vasopressor therapy in acute AlP exposure. Adopting the PGI score seems substantially useful in managing acute AlP poisoning, notably in resource-restricted countries.

Towards better mortality prediction in cancer patients in the ICU: a comparative analysis of prognostic scales: systematic literature review.

OBJECTIVE: To evaluate the predictive ability of mortality prediction scales in cancer patients admitted to intensive care units (ICUs). DESIGN: A systematic review of the literature was conducted using a search algorithm in October 2022. The following databases were searched: PubMed, Scopus, Virtual Health Library (BVS), and Medrxiv. The risk of bias was assessed using the QUADAS-2 scale. SETTING: ICUs admitting cancer patients. PARTICIPANTS: Studies that included adult patients with an active cancer diagnosis who were admitted to the ICU. INTERVENTIONS: Integrative study without interventions. MAIN VARIABLES OF INTEREST: Mortality prediction, standardized mortality, discrimination, and calibration. RESULTS: Seven mortality risk prediction models were analyzed in cancer patients in the ICU. Most models (APACHE II, APACHE IV, SOFA, SAPS-II, SAPS-III, and MPM II) underestimated mortality, while the ICMM overestimated it. The APACHE II had the SMR (Standardized Mortality Ratio) value closest to 1, suggesting a better prognostic ability compared to the other models. CONCLUSIONS: Predicting mortality in ICU cancer patients remains an intricate challenge due to the lack of a definitive superior model and the inherent limitations of available prediction tools. For evidence-based informed clinical decision-making, it is crucial to consider the healthcare team's familiarity with each tool and its inherent limitations. Developing novel instruments or conducting large-scale validation studies is essential to enhance prediction accuracy and optimize patient care in this population.

Comparison of Critical Illness Score in Patients Admitted to Intermediate Care Units of a Tertiary Care Hospital: A Comparative Cross-Sectional Study from Karachi, Pakistan.

Introduction: 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. Methods: 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. Results: 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. Conclusion: 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.

Prediction of adverse drug reactions in geriatric patients admitted to intensive care units. / [Artículo traducido] Predicción de reacciones adversas a medicamentos en pacientes geriátricos ingresados en unidades de cuidados intensivos.

INTRODUCTION: 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.

Prediction of adverse drug reactions in geriatric patients admitted to intensive care units.

INTRODUCTION: 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.

Predictors of Mortality in Hospitalized Patients With Pesticide Poisoning.

Background Organophosphorus poisoning (OPP) is a prevalent mortality rate that varies from 2% to 25% method of suicides worldwide. ICUs commonly employ various scoring systems such as the Glasgow Coma Scale (GCS), Acute Physiology and Chronic Health Evaluation II (APACHE II), Simplified Acute Physiology Score II (SAPS II), and International Programme on Chemical Safety (IPCS) Poison Severity Score (PSS) tools for risk stratification for mortality prediction scores and prognosis. This study aims to compare the predictive validity of these systems in hospitalized patients suffering from pesticide poisoning in a teaching hospital located in central India. Methods A prospective study design was utilized to gather relevant variables for calculating the GCS, APACHE II, SAPS II, and IPCS scales in patients affected by pesticide poisoning. Data on the administered doses of atropine and pralidoxime (PAM) were also recorded. Results We have identified several independent predictors of mortality among patients suffering from pesticide poisoning. The GCS (P=0.001), tracheostomy (P=0.001), APACHE II score (P=0.01), and SAPS II score (P=0.001) were all found to be significant indicators of mortality. Interestingly, the GCS demonstrated comparable predictive ability for mortality when compared to the APACHE II (0.82 (95% confidence interval (CI) 0.70 to 0.94)) and SAPS II (0.83 (95% CI 0.72 to 0.94)) scores, with no statistically significant difference (P=0.75) observed. Among the variables used in the IPCS PSS (GCS, heart rate, systolic blood pressure (BP), intubation, and pupil size), only GCS (P=0.05), and intubation (P=0.01) exhibited a significant association with mortality. Conclusions Our study determined that the GCS score, SAPS II, IPCS PSS, and APACHE II exhibited equal efficacy in predicting mortality. Notably, the GCS offered an added advantage due to its simplicity and minimal time requirements compared to the other scales.

Factors Affecting Delirium in ICU Patients.

This study examined delirium severity using a delirium screening tool and analyzed the predictors, including pain, acuity, level of consciousness, fall risk, and pain score, to increase understanding of delirium and present foundational data for developing nursing interventions for delirium prevention. This was a retrospective study of 165 patients admitted to three intensive care units (ICUs). the Nursing Delirium Screening Scale (Nu-DESC) was used as a research tool to screen for delirium and measure the degree of delirium. The incidence of delirium in patients was 53.3%, and the average delirium score in the delirium group was 2.40 ± 0.56. Nu-DESC scores were significantly correlated with ICU days, ventilator days, restraint applications, the number of catheters inserted, sedative medication use, the Simplified Acute Physiology Score (SAPS III), the Morse Fall Scale (MFS), the Glasgow Coma Scale (GCS) scores, pain scores, and blood urea nitrogen (BUN). Stepwise multiple linear regression showed that the number of restraint applications, GCS score, ICU days, and BUN levels were factors influencing delirium. Based on the findings, ICU nurses should use delirium screening tools to ensure accurate delirium screening and work to reduce the incidence and degree of delirium by observing factors affecting delirium in patients.

A Comparison of ICU Mortality Scoring Systems Applied to COVID-19.

Background Over the past three years, COVID-19 has been a major source of mortality in intensive care units around the world. Many scoring systems have been developed to estimate mortality in critically ill patients. Our intent with this study was to compare the efficacy of these systems when applied to COVID-19. Methods The was a multicenter, retrospective cohort study of critically ill patients with COVID-19 admitted to 16 hospitals in Texas from February 2020 to March 2022. The Simplified Acute Physiology Score (SAPS) II, Acute Physiology and Chronic Health Evaluation (APACHE) II, Sequential Organ Failure Assessment (SOFA) score, and 4C Mortality scores were calculated on the initial day of ICU admission. Primary endpoints were all-cause mortality, ICU length of stay, and hospital length of stay. Results Initially, 62,881 patient encounters were assessed, and the cohort of 292 was selected based on the inclusion of the requisite values for each of the scoring systems. The median age was 56 +/- 14.93 years and 61% of patients were male. Mortality was defined as patients who expired or were discharged to hospice and was 78%. The different scoring systems were compared using logistic regression, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC) analysis to compare the accuracy of prediction of the mortality and length of stay. The multivariate analysis showed that SOFA, APACHE II, SAPS II, and 4C scores were all significant predictors of mortality. The SOFA score had the highest AUC, though the confidence intervals for all of the models overlap therefore one model could not be considered superior to any of the others. Linear regression was performed to evaluate the models' ability to predict ICU and hospital length of stay, and none of the tested systems were found to be significant predictors of length of stay. Conclusion The SOFA, APACHE II, ISARIC 4-C, and SAPS II scores all accurately predicted mortality in critically ill patients with COVID-19. The SOFA score trended to perform the best.

A first-level customization study of SAPS II with Norwegian Intensive Care and Pandemic Registry (NIPaR) data.

BACKGROUND: Severity scores and mortality prediction models (MPMs) are important tools for benchmarking and stratification in the intensive care unit (ICU) and need to be regularly updated using data from a local and contextual cohort. Simplified acute physiology score II (SAPS II) is widely used in European ICUs. METHODS: A first-level customization was performed on the SAPS II model using data from the Norwegian Intensive Care and Pandemic Registry (NIPaR). Two previous SAPS II models (Model A: the original SAPS II model and Model B: a SAPS II model based on NIPaR data from 2008 to 2010) were compared to the new Model C. Model C was based on patients from 2018 to 2020 (corona virus disease 2019 patients omitted; n = 43,891), and its performances (calibration, discrimination, and uniformity of fit) compared to the previous models (Model A and Model B). RESULTS: Model C was better calibrated than Model A with a Brier score 0.132 (95% confidence interval 0.130-0.135) versus 0.143 (95% confidence interval 0.141-0.146). The Brier score for Model B was 0.133 (95% confidence interval 0.130-0.135). In the Cox's calibration regression α ≈ 0 and ß ≈ 1 for both Model C and Model B but not for Model A. Uniformity of fit was similar for Model B and for Model C, both better than for Model A, across age groups, sex, length of stay, type of admission, hospital category, and days on respirator. The area under the receiver operating characteristic curve was 0.79 (95% confidence interval 0.79-0.80), showing acceptable discrimination. CONCLUSIONS: The observed mortality and corresponding SAPS II scores have significantly changed during the last decades and an updated MPM is superior to the original SAPS II. However, proper external validation is required to confirm our findings. Prediction models need to be regularly customized using local datasets in order to optimize their performances.

Elderly in the ICU.

How to cite this article: Jagathkar G. Elderly in the ICU. Indian J Crit Care Med 2023;27(3):157-158.

Comparison of Mortality Prediction Scores in Intermediate-Care Patients with Liver Cirrhosis at a German University Transplant Centre: A Prospective Study.

BACKGROUND AND AIMS: Mortality prediction models help to extract and relate patient data upon admission to intensive or intermediate care units (ImCUs). Considering technical and economic healthcare developments, re-evaluations of score performances are required to warrant their validity. This study validates and compares established scoring systems in cirrhotic ImCU patients. METHODS: Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 2 and 3, Sepsis Organ Failure Assessment (SOFA), Mortality Probability Model at ICU admission (MPMo) II and III, Model for End stage Liver Disease (MELD), CLIF-Consortium Acute-on-Chronic Liver Failure (CLIF-C ACLF), CLIF-Consortium Acute Decompensation (CLIF-C AD), and Intermediate Care Unit Severity Score (ImCUSS) were calculated in patients with cirrhosis (n = 98) at ImCU admission. Discrimination performances were evaluated by area under the receiver operating characteristic curves (AUROCs), calibration performances with calibration belt plots, and their corresponding p values. RESULTS: Overall, SAPS 3 and CLIF-C ACLF have shown the best 90-day mortality prediction outcomes with AUROCs of 0.825 and 0.783 along with calibration belt p values of 0.128 and 0.061, respectively. In a subgroup analysis of patients with acute-on-chronic liver failure (ACLF), expanded SAPS 2, SOFA, and SAPS 3 reached the best AUROCs, i.e., 0.760, 0.750, and 0.714, but none of the tested scores reached an acceptable calibration. CONCLUSION: Ninety-day mortality risk prediction of the SAPS 3 and CLIF-C ACLF was accurate in our cohort of patients with liver cirrhosis admitted to ImCUs. A particular challenge remains that is the mortality prediction in patients with ACLF requiring ImCU-level care; here, further developments are needed to generate scores with acceptable predictive performances.

Comparison of mNUTRIC-S2 and mNUTRIC scores to assess nutritional risk and predict intensive care unit mortality.

BACKGROUND: Nutritional status is associated with mortality. The modified Nutrition Risk in the Critically Ill (mNUTRIC) score is one of the most commonly used nutritional risk assessment tools in intensive care units (ICUs). The purpose of this study was to compare the mortality predictive ability of the mNUTRIC score to that of the mNUTRIC-S2 score, which uses the Simplified Acute Physiology Score (SAPS) II instead of the Acute Physiology and Chronic Health Evaluation (APACHE) II. METHODS: This retrospective cohort analysis included patients admitted to the ICU between January and September 2020. Each patient's electronic medical records were reviewed. The model discrimination for predicting ICU mortality was assessed by the area under the receiver operating characteristic (ROC) curve, and a Cox regression model was performed to confirm the relationship between the groups and mortality. RESULTS: In total, 220 patients were enrolled. The ROC curve for predicting ICU mortality was 0.64 for the mNUTRIC score versus 0.67 for the mNUTRIC-S2 score. The difference between the areas was 0.03 (95% confidence interval [CI], -0.01 to 0.06; P=0.09). Patients with mNUTRIC-S2 score ≥5 had a greater risk of ICU mortality (hazard ratio [HR], 3.64; 95% CI, 1.85-7.14; P<0.001); however, no such relationship was observed with mNUTRIC score (HR, 1.69; 95% CI, 0.62-4.62; P=0.31). CONCLUSIONS: The mNUTRIC-S2 score was significantly associated with ICU mortality. A cutoff score of 5 was selected as most appropriate.

Optimized diagnosis-based comorbidity measures for all-cause mortality prediction in a national population-based ICU population.

BACKGROUND: We aimed to optimize prediction of long-term all-cause mortality of intensive care unit (ICU) patients, using quantitative register-based comorbidity information assessed from hospital discharge diagnoses prior to intensive care treatment. MATERIAL AND METHODS: Adult ICU admissions during 2006 to 2012 in the Swedish intensive care register were followed for at least 4 years. The performance of quantitative comorbidity measures based on the 5-year history of number of hospital admissions, length of stay, and time since latest admission in 36 comorbidity categories was compared in time-to-event analyses with the Charlson comorbidity index (CCI) and the Simplified Acute Physiology Score (SAPS3). RESULTS: During a 7-year period, there were 230,056 ICU admissions and 62,225 deaths among 188,965 unique individuals. The time interval from the most recent hospital stays and total length of stay within each comorbidity category optimized mortality prediction and provided clear separation of risk categories also within strata of age and CCI, with hazard ratios (HRs) comparing lowest to highest quartile ranging from 1.17 (95% CI: 0.52-2.64) to 6.41 (95% CI: 5.19-7.92). Risk separation was also observed within SAPS deciles with HR ranging from 1.07 (95% CI: 0.83-1.38) to 3.58 (95% CI: 2.12-6.03). CONCLUSION: Baseline comorbidity measures that included the time interval from the most recent hospital stay in 36 different comorbidity categories substantially improved long-term mortality prediction after ICU admission compared to the Charlson index and the SAPS score. Trial registration ClinicalTrials.gov ID NCT04109001, date of registration 2019-09-26 retrospectively.

Complications of invasive mechanical ventilation in critically Ill Covid-19 patients - A narrative review.

Critically ill COVID-19 patients have to undergo positive pressure ventilation, a non-physiological and invasive intervention that can be lifesaving in severe ARDS. Similar to any other intervention, it has its pros and cons. Despite following Lung Protective Ventilation (LPV), some of the complications are frequently reported in these critically ill patients and significantly impact overall mortality. The complications related to invasive mechanical ventilation (IMV) in critically ill COVID-19 patients can be broadly divided into pulmonary and non-pulmonary. Among pulmonary complications, the most frequent is ventilator-associated pneumonia. Others are barotrauma, including subcutaneous emphysema, pneumomediastinum, pneumothorax, bullous lesions, cardiopulmonary effects of right ventricular dysfunction, and pulmonary complications mimicking cardiac failure, including pulmonary edema. Tracheal complications, including full-thickness tracheal lesions (FTTLs) and tracheoesophageal fistulas (TEFs) are serious but rare complications. Non-Pulmonary complications include neurological, nephrological, ocular, and oral complications.

Association between thrombocytopenia and the severity of Covid-19 infection among hospitalized Egyptian patients.

Background: COVID-19, which is caused by the corona virus 2 that causes severe acute respiratory syndrome, causes a respiratory and systemic illness that in 10-15% of patients escalates to a severe form of pneumonia. Thrombocytopenia is frequent in patients with COVID-19. We aimed to evaluate the association between thrombocytopenia and the severity of COVID-19 infection in hospitalized patients. Methods: A cross-sectional study was done on 800 Egyptian patients with confirmed covid-19 infection. They were divided into Group I (Mild): 200 symptomatic patients meeting the case definition for COVID-19 without radiological evidence of pneumonia or hypoxia. Group II (Moderate): 200 patients with clinical signs of non-severe pneumonia and radiological evidence of pneumonia. Group III (Severe): 200 patients with clinical signs of pneumonia plus: respiratory or lung dysfunction. Group IV: 200 critically ill patient in ICU: Acute respiratory distress syndrome (ARDS).Results: there was a highly statistically significant difference between the studied groups regarding thrombocytopenia (p < 0.001). Thrombocytopenia was statistically higher in severe and critically ill patients. In addition, a statistically significant difference found in outcome among the studied groups (p < 0.05) {critically ill (40%), severe (17.5%)}. The most common cause of death was respiratory failure, which occurred in 28 severe patients (80%) and 65 critically ill patients (81.25%), followed by hemorrhage due to thrombocytopenia, which occurred in 7 severe patients (20%) and 15 critically ill patients, respectively (18.75%). Conclusion: The Platelet count is a straightforward, inexpensive, as well as easily available laboratory parameter that is frequently linked to severe covid-19 infection and a significant death risk.

Comparison of elevated cardiac troponin I with SAPS-II and APACHE-II score in predicting outcome of severe intoxications.

Background and Aims: To date, different methods have been invented to risk-stratify critically ill patients, however, there is a paucity of information regarding assessing the severity of poisonings. This study was designed to determine the comparative efficacy of Simplified Acute Physiology Score-II (SAPS-II) and Acute Physiology and Chronic Health Evaluation-II (APACHE-II)score with cardiac troponin I (cTnI) in predicting severe intoxication outcomes. Methods: This was a prospective study conducted on patients who fulfilled defined severe intoxication criteria necessitating intensive care unit (ICU) admission over a period of 6 months. SAPS-II and APACHE-II scores were calculated and cTnI concentrations were measured. These indicators were compared to determine which has the better ability to prognosticate mortality and complications. Results: A total of 55 cases (median age, 35 [24-49] years) were enroled. Eight patients (14.5%) died. Mean SAPS-II, median APACHE-II score and median cTnI concentrations were 32.05 ± 11.24, 13 [10-17] and 0.008 [0.002-0.300] ng/ml, respectively, which were significantly different between the survivors and non-survivors. Receiver operating characteristics curve results of SAPS-II, APACHE-II score and cTnI concentrations in predicting mortality were 0.945, 0.932 and 0.763 and in predicting complications were 0.779, 0.739 and 0.727, respectively. High cTnI concentration (>0.37 ng/ml) correlated with soft clinical outcomes, including length of ventilatory support, length of ICU stay and length of hospital stay (LOS) (r: 0.928, 0.881 and 0.735 respectively; all P < 0.001). Conclusion: SAPS-II scores were superior in predicting death and complications, while cTnI correlated more closely with soft clinical outcomes, such as the length of ventilator support, length of ICU stay or LOS.

The impact of body mass index on the prognostic performance of the Simplified Acute Physiology Score 3: A prospective cohort study.

Objective: To assess the Simplified Acute Physiology Score 3 (SAPS3) prognostic score performance across different body mass index categories. Methods: A retrospective cohort study in a general ICU in Brazil. A secondary analysis of medical records was performed with clinical and epidemiological data. Patients were stratified according to their body mass index (BMI) category, and a binary logistic regression was then performed to identify factors independently associated with mortality. SAPS3 accuracy was determined using the area under the receiver operating characteristics curve and the Hosmer-Lemeshow test. A modified Kaplan-Meyer plot was employed to evaluate death probability according to BMI. ICU mortality was evaluated as the primary outcome. Results: A total of 2,179 patients (mean age of 67.9 years and female predominance (53.1%)) were enrolled. SAPS3 was found accurate in all groups except in the underweight (AUC: 0.694 95% CI 0.616-0.773; HL = 0.042). The patients in the underweight group tended to be older, have longer hospital stay, have worse functional status, and have a higher value on prognostic scores. After the adjustments, no statistically significant difference between the BMI groups was noted in relation to mortality, except for the low weight that presented a likelihood of death of 3.50 (95% CI, 1.43-8.58, p = 0.006). Conclusion: This research showed that SAPS3 had poor accuracy in predicting ICU mortality in underweight patients. This group was shown to be an independent risk factor for worse clinical outcomes.

Critically ill COVID-19 patients in northeast Brazil: mortality predictors during the first and second waves including SAPS 3.

BACKGROUND: The Simplified Acute Physiology Score (SAPS) 3 is a reliable score to predict mortality. This study aims to investigate the predictive values of SAPS 3 and other clinical parameters for death in critically ill coronavirus disease 2019 (COVID-19) patients. METHODS: This is a prospective study in a tertiary hospital for patients who required intensive care due to COVID-19 infection in northeast Brazil. Two distinct groups were constructed according to the epidemiological data: first wave and second wave. The severity of patients admitted was estimated using the SAPS 3 score. RESULTS: A total of 767 patients were included: 290 were enrolled in the first wave and 477 in the second wave. Patients in the first wave had more comorbidities, were put on mechanical ventilation and required dialysis and vasopressors more frequently (p<0.05). During the second wave, non-invasive ventilation was more often required (p<0.05). In both periods, older patients and higher SAPS 3 scores on admission were associated with death (p<0.05). Non-invasive ventilation use showed a negative association with death only in the second wave period. In the first wave, the SAPS 3 score was more useful (area under the curve [AUC] 0.897) in predicting death in critically ill COVID-19 patients than in the second wave (AUC 0.810). CONCLUSION: The SAPS 3 showed very reliable predictive values for death during the waves of the COVID-19 pandemic, mostly together with kidney and pulmonary dysfunction.

Systemic Inflammation Evaluated by Interleukin-6 or C-Reactive Protein in Critically Ill Patients: Results From the FROG-ICU Study.

Background: The prognostic impact of high concentration of interleukin-6 (IL-6) or C-reactive protein (CRP), two routinely available markers of systemic inflammation in the general population of critically ill patients, remains unclear. In a large cohort of critically ill patients including septic and non-septic patients, we assessed the relationship between baseline IL-6 or CRP and mortality, organ dysfunction, and the need for organ support. Methods: This was an ancillary analysis of the prospective French and euRopean Outcome reGistry in Intensive Care Units (FROG-ICU) study including patients with a requirement for invasive mechanical ventilation and/or vasoactive drug support for more than 24 h following intensive care unit (ICU) admission. The primary objective was to determine the association between baseline IL-6 or CRP concentration and survival until day 90. Secondary outcomes included organ dysfunction as evaluated by the Sequential Organ Failure Assessment (SOFA) score, and the need for organ support, including vasopressors/inotropes and/or renal replacement therapy (RRT). Results: Median IL-6 and CRP concentrations (n = 2,076) at baseline were 100.9 pg/ml (IQR 43.5-261.7) and 143.7 mg/L (IQR 78.6-219.8), respectively. Day-90 mortality was 30%. High IL-6 or CRP was associated with worse 90-day survival (hazard ratios 1.92 [1.63-2.26] and 1.21 [1.03-1.41], respectively), after adjustment on the Simplified Acute Physiology Score II (SAPS-II). High IL-6 was also associated with the need for organ-support therapies, such as vasopressors/inotropes (OR 2.67 [2.15-3.31]) and RRT (OR 1.55 [1.26-1.91]), including when considering only patients independent from those supports at the time of IL-6 measurement. Associations between high CRP and organ support were inconsistent. Conclusion: IL-6 appears to be preferred over CRP to evaluate critically ill patients' prognoses.

Simplified Acute Physiology Score 3 Performance in Austrian COVID-19 Patients Admitted to Intensive Care Units with and without Diabetes.

This study evaluated and compared the performance of simplified acute physiology score 3 (SAPS 3) for predicting in-hospital mortality in COVID-19 patients admitted to intensive care units (ICUs) with and without diabetes in Austria. The Austrian national public health institute (GÖG) data of COVID-19 patients admitted to ICUs (n = 5850) were analyzed. Three versions of SAPS 3 were used: standard equation, Central European equation, and Austrian equation customized for COVID-19 patients. The observed in-hospital mortality was 38.9%, 42.9%, and 37.3% in all, diabetes, and non-diabetes patients, respectively. The overall C-statistics was 0.69 with an insignificant (p = 0.193) difference between diabetes (0.70) and non-diabetes (0.68) patients. The Brier score was > 0.20 for all SAPS 3 equations in all cohorts. Calibration was unsatisfactory for both standard and Central European equations in all cohorts, whereas it was satisfactory for the Austrian equation in diabetes patients only. The SAPS 3 score demonstrated low discrimination and accuracy in Austrian COVID-19 patients, with an insignificant difference between diabetes and non-diabetes. All equations were miscalibrated particularly in non-diabetes patients, while the Austrian equation showed satisfactory calibration in diabetes patients only. Both uncalibrated and calibrated versions of SAPS 3 should be used with caution in COVID-19 patients.