Comparison of Four Severity Assessment Scoring Systems in Critically Ill Patients for Predicting Patient Outcomes: A Prospective Observational Study From a Single Tertiary Center in Central India.

Background and aim A variety of scoring systems are employed in intensive care units (ICUs) with the objective of predicting patient morbidity and mortality. The present study aimed to compare four different severity assessment scoring systems, namely, Acute Physiology and Chronic Health Evaluation II (APACHE II), Rapid Emergency Medicine Score (REMS), Sequential Organ Failure Assessment (SOFA), and Simplified Acute Physiologic Score II (SAPS II) to predict prognosis of all patients admitted to a mixed medical ICU of a tertiary care teaching hospital in central India. Methods The prospective observational study included 1136 patients aged 18 years or more, admitted to the mixed medical ICU. All patients underwent severity assessment using the four scoring systems, namely APACHE II, SOFA, REMS, and SAPS II, after admission. Predicted mortality was calculated from each of the scores and actual patient outcomes were noted. Receiver operating curve analysis was undertaken to identify the cut-off value of individual scoring systems for predicting mortality with optimum sensitivity and specificity. Calibration and discrimination were employed to ascertain the validity of each scoring model. Bivariate and multivariable logistic regression analyses among the study participants were conducted to identify the best scoring system, after adjusting for potential confounders. Results Final analysis was done on 957 study participants (mean (±SD) age-58.4 (±12.9) years; males-62.2%). The mortality rate was 14.7%. APACHE II, SOFA, SAPS II, and REMS scores were significantly higher among the non-survivors as compared to the survivors (p<0.05). SAPS II was found to have the highest AUC of 0.981 (p<0.001). SAPS II score >58 had 93.6% sensitivity, 94.1% specificity, 73.3% PPV, 98.8% NPV, and 94.0% diagnostic accuracy in predicting mortality. This scoring system also had the best calibration. Binary logistic regression showed that all four scoring systems were significantly associated with ICU mortality. After adjusting for each other, only SAPS II remained significantly associated with ICU mortality. Conclusion Both SAPS II and APACHE II were observed to have good calibration and discriminatory power; however, SAPS II had the best prediction power suggesting that it may be a useful tool for clinicians and researchers in assessing the severity of illness and mortality risk in critically ill patients.

Synergizing Survival: Uniting Acute Gastrointestinal Injury Grade and Disease Severity Scores in Critical Care Prognostication.

How to cite this article: Patnaik RK, Karan N. Synergizing Survival: Uniting Acute Gastrointestinal Injury Grade and Disease Severity Scores in Critical Care Prognostication. Indian J Crit Care Med 2024;28(6):529-530.

Infectious Foci, Comorbidities and Its Influence on the Outcomes of Septic Critically Ill Patients.

Sepsis is among the most frequent diagnoses on admission to the intensive care unit (ICU). A systemic inflammatory response, activated by uncontrolled infection, fosters hypoperfusion and multiorgan failure and often leads to septic shock and mortality. These infections arise from a specific anatomic source, and how the infection foci influence the outcomes is unknown. All patients admitted to the ICU of Hospital de Vila Franca de Xira, between 1 January 2017 and 31 June 2023, were screened for sepsis and categorized according to their infection foci. During the study period, 1296 patients (32.2%) had sepsis on admission. Their mean age was 67.5 ± 15.3 and 58.1% were male; 73.0% had community-acquired infections. The lung was the main focus of infection. Septic shock was present in 37.9% of the patients and was associated with hospital mortality. Severe imbalances were noted in its incidence, and there was lower mortality in lung infections. The hospital-acquired infections had a slightly higher mortality but, after adjustment, this difference was non-significant. Patients with secondary bacteremia had a worse prognosis (one-year adjusted hazard ratio of 1.36, 95% confidence interval 1.06-1.74, p = 0.015), especially those with an isolated non-fermenting Gram-negative infection. Lung, skin, and skin structure infections and peritonitis had a worse prognosis, whilst urinary, biliary tract, and other intra-abdominal infections had a better one-year outcome.

Effectiveness of Copeptin, MR-proADM and MR-proANP in Predicting Adverse Outcomes, Alone and in Combination with Traditional Severity Scores, a Secondary Analysis in COVID-19 Patients Requiring Intensive Care Admission.

Objective: To investigate whether copeptin, MR-proADM and MR-proANP, alone or integrated with the SOFA, MuLBSTA and SAPS II scores, are capable of early recognition of COVID-19 ICU patients at increased risk of adverse outcomes. Methods: For this predefined secondary analysis of a larger cohort previously described, all consecutive COVID-19 adult patients admitted between March and December 2020 to the ICU of a referral, university hospital in Northern Italy were screened, and clinical severity scores were calculated upon admission. A blood sample for copeptin, MR-proADM and MR-proANP was collected within 48 h (T1), on day 3 (T3) and 7 (T7). Outcomes considered were ICU and in-hospital mortality, bacterial superinfection, recourse to renal replacement therapy (RRT) or veno-venous extracorporeal membrane oxygenation, need for invasive mechanical ventilation (IMV) and pronation. Results: Sixty-eight patients were enrolled, and in-hospital mortality was 69.1%. ICU mortality was predicted by MR-proANP measured at T1 (HR 1.005, 95% CI 1.001-1.010, p = 0.049), although significance was lost if the analysis was adjusted for procalcitonin and steroid treatment (p = 0.056). Non-survivors showed higher MR-proADM levels than survivors at all time points, and an increase in the ratio between values at baseline and at T7 > 4.9% resulted in a more than four-fold greater risk of in-hospital mortality (HR 4.417, p < 0.001). Finally, when considering patients with any reduction in glomerular filtration, an early copeptin level > 23.4 pmol/L correlated with a more than five-fold higher risk of requiring RRT during hospitalization (HR 5.305, p = 0.044). Conclusion: Timely evaluation of MR-proADM, MR-proANP and copeptin, as well as changes in the former over time, might predict mortality and other adverse outcomes in ICU patients suffering from severe COVID-19.

Complicaciones y mortalidad en pacientes neurocríticos / Complications and mortality in neurocritic patients

Objetivo: Relacionar las complicaciones y el riesgo de muerte en pacientes neurocríticos admitidos en la unidad de cuidados intensivos (UCI) del Hospital Universitario de Caracas durante un período de 5 meses. Métodos: investigación observacional, prospectiva, descriptiva. La muestra estuvo conformada por 65 pacientes neurocríticos, ≥ 18 años, con patologías médicas o quirúrgicas, ingresados en la UCI. El análisis estadístico incluyó la determinación de frecuencias, promedios, porcentajes y medias para descripción de variables y el T de Student. Resultados: La edad promedio fue 50,98 ± 16,66 años; la población masculinarepresentó el 50,76%. Entre las complicaciones, la mayor incidencia correspondió a las no infecciosas (70,77 %) y los trastornos ácido-básicos de tipo metabólico, la anemia y las alteraciones electrolíticas fueron las más frecuentes; el 29,23% de los pacientes presentaron complicaciones infecciosas, y la neumonía asociada a ventilación mecánica fue la más frecuente (73,91 %). La comorbilidad con mayor incidencia fue hipertensión arterial sistémica (53,84%). El 90.70% requirió ventilación mecánica y el tiempo en VM fue 4.29 ± 6.43 días. La estancia en UCI fue 5.96 ± 7.72 días. El 29,23% presentó un puntaje en la escala APACHE II entre 5-9; el SAPS II presentó mayor incidencia entre los 6-21 y 22-37 puntos con (66,70%); el SOFA al ingreso se reportó < 15 puntos en 98,46% y > 15 en 1,53%. La mortalidad del grupo fue 23,08 % (n=15). Conclusiones: Las complicaciones no infecciosas predominaron sobre las infecciosas las primeras íntimamente relacionadas con la mortalida(AU)

Objective: To relate complications and the risk of death in neurocritical patients admitted to the intensive care unit (ICU) of the University Hospital of Caracas during a period of 5 months. Methods: observational, prospective, descriptive research. The sample was made up of 65 neurocritical patients, ≥ 18 years old, with medical or surgical pathologies, admitted to the ICU.The statistical analysis included the determination of frequencies, averages, percentages and meansfor description of variables and Student's T.Results: The average age was 50.98 ± 16.66 years; the male population represented 50.76%. Among the complications, the highest incidence corresponded to non-infectious complications (70.77%) and metabolic acid-base disorders, anemia and electrolyte alterations were the most frequent; 29.23% of patients presented infectious complications, and pneumonia associated with mechanical ventilation was the most frequent (73.91%). The comorbidity with the highest incidence was systemic arterial hypertension (53.84%), 90.70% required mechanical ventilation and the time on MV was 4.29 ± 6.43 days. The ICU stay was 5.96 ± 7.72 days. 29.23% had a score on the APACHE II scale between 5-9; SAPS II presented the highest incidence between 6-21 and 22-37 points with (66.70%); The SOFA upon admission was reported to be < 15 points in 98.46% and > 15 in 1.53%. The mortality of the group was 23.08% (n=15). Conclusions: Non-infectious complications predominated over infectious complications, the former being closely related to mortalit(AU)

The value of five scoring systems in predicting the prognosis of patients with sepsis-associated acute respiratory failure.

Our study aimed to identify the optimal scoring system for predicting the prognosis of patients with sepsis-associated acute respiratory failure (SA-ARF). All data were taken from the fourth version of the Markets in Intensive Care Medicine (MIMIC-IV) database. Independent risk factors for death in hospitals were confirmed by regression analysis. The predictive value of the five scoring systems was evaluated by receiving operating characteristic (ROC) curves. Kaplan‒Meier curves showed the impact of acute physiology score III (APSIII) on survival and prognosis in patients with SA-ARF. Decision curve analysis (DCA) identified a scoring system with the highest net clinical benefit. ROC curve analysis showed that APS III (AUC: 0.755, 95% Cl 0.714-0.768) and Logical Organ Dysfunction System (LODS) (AUC: 0.731, 95% Cl 0.717-0.7745) were better than Simplified Acute Physiology Score II (SAPS II) (AUC: 0.727, 95% CI 0.713-0.741), Oxford Acute Severity of Illness Score (OASIS) (AUC: 0.706, 95% CI 0.691-0.720) and Sequential Organ Failure Assessment (SOFA) (AUC: 0.606, 95% CI 0.590-0.621) in assessing in-hospital mortality. Kaplan‒Meier survival analysis patients in the high-APS III score group had a considerably poorer median survival time. The DCA curve showed that APS III may provide better clinical benefits for patients. We demonstrated that the APS III score is an excellent predictor of in-hospital mortality.

Critically ill patients with high predicted mortality: Incidence and outcome.

OBJECTIVE: As calculated by the severity scores, an unknown number of patients are admitted to the Intensive Care Unit (ICU) with a very high risk of death. Clinical studies have poorly addressed this population, and their prognosis is largely unknown. DESIGN: Post hoc analysis of a multicenter, cohort, longitudinal, observational, retrospective study (CIMbA). SETTING: Sixteen Portuguese multipurpose ICUs. PATIENTS: Patients with a Simplified Acute Physiology Score II (SAPS II) predicted hospital mortality above 80% on admission to the ICU (high-risk group); A comparison with the remaining patients was obtained. INTERVENTIONS: None. MAIN VARIABLES OF INTEREST: Hospital, 30 days, 1 year mortality. RESULTS: We identified 4546 patients (59.9% male), 12.2% of the whole population. Their SAPS II predicted hospital mortality was 89.0±5.8%, whilst the observed mortality was lower, 61.0%. This group had higher mortality, both during the first 30 days (aHR 3.52 [95% CI 3.34-3.71]) and from day 31 to day 365 after ICU admission (aHR 1.14 [95%CI 1.04-1.26]), respectively. However, their hospital standardized mortality ratio was similar to the other patients (0.69 vs. 0.69, P=.92). At one year of follow-up, 30% of patients in the high-risk group were alive. CONCLUSIONS: Roughly 12% of patients admitted to the ICU for more than 24h had a SAPS II score predicted mortality above 80%. Their hospital standardized mortality was similar to the less severe population and 30% were alive after one year of follow-up.

Is Carboxyhaemoglobin an Effective Bedside Prognostic Tool for Sepsis and Septic Shock Patients?

Introduction: Proper management of sepsis poses a challenge even today, with early diagnosis and targeted treatment being the most important steps. Easy, cost-effective bedside tools are needed in order to pinpoint towards the outcome of sepsis or septic shock. Aim of study: This study aims to find a correlation between Sequential Organ Failure Assessment (SOFA), Acute Physiology and Chronic Health Evaluation II (APACHE II) and Simplified Acute Physiology Score II (SAPS II) severity scores, the Neutrophil-Lymphocytes Ratio (NLR) and carboxyhaemoglobin (COHb) levels in septic or septic shock patients with the scope of establishing a bed side cost-effective prognostic tool. Materials and methods: A pilot, prospective, observational, and ongoing study was conducted on 61 patients admitted with sepsis or septic shock according to the SEPSIS 3 Consensus definition. We followed clinical and paraclinical parameters on day 1 (D1) and day 5 (D5) after meeting the inclusion criteria. Results: On D1 we found a statistically significant positive correlation between each severity score (p <0.0001), r = 0.7287 for SOFA vs. APACHE II with CI: 0.5841-0.8285, r = 0.6862 for SOFA vs. SAPS II with CI: 0.5251-0.7998 and r = 0.8534 for APACHE II vs. SAPS II with CI: 0.7663 to 0.9097. On D5 we observed similar results: a significant positive correlation between each severity score (p <0.0001), with r = 0.7877 for SOFA vs. APACHE II with CI: 0.6283 to 0.8836, r = 0.8210 for SOFA vs. SAPS II with CI: 0.6822 to 0.9027 and r = 0.8880 for APACHE II vs. SAPS II., CI: 0.7952 to 0.9401. Nil correlation was found between the severity scores, NLR and COHb on D1 and D5. Conclusion: Cost-effective bedside tools to pinpoint towards the outcome of sepsis are yet to be found, however the positive correlation between the severity scores point out to a combination of such tools for prognosis prediction of septic or septic shock patients.

Association between nutritional status scores and the 30-day mortality in patients with acute kidney injury: an analysis of MIMIC-III database.

BACKGROUND: Studies have proven that the risk of acute kidney injury (AKI) increased in patients with malnutrition. Prognostic nutritional index (PNI) and geriatric nutritional risk index (GNRI) were general tools to predict the risk of mortality, but the prognostic value of them for in-hospital mortality among patients with AKI have not been validated yet. Herein, this study aims to explore the association between PNI and GNRI and 30-day mortality in patients with AKI. METHODS: Demographic and clinical data of 863 adult patients with AKI were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database in 2001-2012 in this retrospective cohort study. Univariate and multivariate Cox proportional regression analyses were used to explore the association between PNI and GNRI and 30-day mortality. The evaluation indexes were hazard ratios (HRs) and 95% confidence intervals (CIs). Subgroup analyses of age, Sequential Organ Failure Assessment (SOFA) score and Simplified Acute Physiology (SAPS-II) score were also performed. RESULTS: Totally, 222 (26.71%) patients died within 30 days. After adjusting for covariates, PNI ≥ 28.5 [HR = 0.71, 95%CI: (0.51-0.98)] and GNRI ≥ 83.25 [HR = 0.63, 95%CI: (0.47-0.86)] were both associated with low risk of 30-day mortality. These relationships were also found in patients who aged ≥ 65 years old. Differently, high PNI level was associated with low risk of 30-day mortality among patients with SOFA score < 6 or SAPS-II score < 43, while high GNRI was associated with low risk of 30-day mortality among those who with SOFA score ≥ 6 or SAPS-II score ≥ 43 (all P < 0.05). CONCLUSION: PNI and GNRI may be potential predictors of 30-day mortality in patients with AKI. Whether the PNI is more recommended for patients with mild AKI, while GNRI for those with severe AKI is needed further exploration.

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.

Etiology and severity features of acute pancreatitis in HIV-positive patients with different immune status.

Objectives: Acute pancreatitis is common in HIV-infected patients; however, the causes and severity of pancreatitis in HIV-positive patients have a number of significant features that affect both the severity of destruction of the pancreas and the methods of diagnosis and treatment. Material and Methods: Anamnestic data, results of diagnosis and treatment of two groups of patients with acute pancreatitis were analyzed. The first group included 79 patients with acute pancreatitis combined with HIV infection who were admitted to the clinic for the period from 2017 to 2021. In people living with HIV, drugs and infectious agents caused acute pancreatitis in 11.4% and 24.1% of the cases, respectively. As our study showed, in patients with normal immune status, the drug etiology of pancreatitis prevailed in the structure of the causes of AP, in patients with immunodeficiency, infectious causes of pancreatitis were dominant. Results: According to the results of data analysis, it is clear that HIV infection is a factor that makes the course of pancreatitis about two times worse regardless of the presence of immunosuppression. The etiological structure of HIV-associated acute pancreatitis directly depends on the patient's immune status and differs in many ways from that of HIV-negative patients or patients receiving ART. Conclusion: The severity of the disease and the risk of death remain high in acute pancreatitis caused by infectious agents against the background of immunosuppression.

Sarcoma Patients Admitted to the Intensive Care Unit (ICU): Predictive Relevance of Common Sepsis and Performance Parameters.

Purpose: Prognosis of sarcoma patients is improving, with a better understanding of sarcomagenesis revealing novel therapeutic targets. However, aggressive chemotherapy remains an essential part of treatment, bearing the risk of severe side effects that require intensive medical treatment. Available data on the characteristics and clinical outcome of sarcoma patients admitted to intensive care units (ICU) are sparse. Patients and Methods: We performed a retrospective analysis of sarcoma patients admitted to the ICU from 2005 to 2022. Patients ≥18 years with histologically proven sarcoma were included in our study. Results: Sixty-six patients were eligible for analysis. The following characteristics had significant impact on overall survival: sex (p=0.046), tumour localization (p=0.02), therapeutic intention (p=0.02), line of chemotherapy (p<0.001), SAPS II score (p=0.03) and SOFA score (p=0.02). Conclusion: Our study confirms the predictive relevance of established sepsis and performance scores in sarcoma patients. For overall survival, common clinical characteristics are also of significant value. Further investigation is needed to optimize ICU treatment of sarcoma 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.

Critically ill patient mortality by age: long-term follow-up (CIMbA-LT).

BACKGROUND: The past years have witnessed dramatic changes in the population admitted to the intensive care unit (ICU). Older and sicker patients are now commonly treated in this setting due to the newly available sophisticated life support. However, the short- and long-term benefit of this strategy is scarcely studied. METHODS: The Critically Ill patients' mortality by age: Long-Term follow-up (CIMbA-LT) was a multicentric, nationwide, retrospective, observational study addressing short- and long-term prognosis of patients admitted to Portuguese multipurpose ICUs, during 4 years, according to their age and disease severity. Patients were followed for two years after ICU admission. The standardized hospital mortality ratio (SMR) was calculated according to the Simplified Acute Physiology Score (SAPS) II and the follow-up risk, for patients discharged alive from the hospital, according to official demographic national data for age and gender. Survival curves were plotted according to age group. RESULTS: We included 37.118 patients, including 15.8% over 80 years old. The mean SAPS II score was 42.8 ± 19.4. The ICU all-cause mortality was 16.1% and 76% of all patients survive until hospital discharge. The SAPS II score overestimated hospital mortality [SMR at hospital discharge 0.7; 95% confidence interval (CI) 0.63-0.76] but accurately predicted one-year all-cause mortality [1-year SMR 1.01; (95% CI 0.98-1.08)]. Survival curves showed a peak in mortality, during the first 30 days, followed by a much slower survival decline thereafter. Older patients had higher short- and long-term mortality and their hospital SMR was also slightly higher (0.76 vs. 0.69). Patients discharged alive from the hospital had a 1-year relative mortality risk of 6.3; [95% CI 5.8-6.7]. This increased risk was higher for younger patients [21.1; (95% CI 15.1-39.6) vs. 2.4; (95% CI 2.2-2.7) for older patients]. CONCLUSIONS: Critically ill patients' mortality peaked in the first 30 days after ICU admission. Older critically ill patients had higher all-cause mortality, including a higher hospital SMR. A long-term increased relative mortality risk was noted in patients discharged alive from the hospital, but this was more noticeable in younger patients.

Predictive outcomes of APACHE II and expanded SAPS II mortality scoring systems in coronary care unit.

OBJECTIVE: We investigated the predictive values of the expanded Simplified Acute Physiology Score (SAPS) II and Acute Physiologic Score and Chronic Health Evaluation (APACHE) II score in predicting in-hospital mortality in coronary care unit (CCU) patients. METHODS: In this study, expanded SAPS II and APACHE II scores were calculated in the CCU of a single-center tertiary hospital. Patients admitted to CCU with any cardivascular indication were included in the study. Both scores were calculated according to previously determined criteria. Calibration and discrimination abilities of the scores in predicting in-hospital mortality were tested with Hosmer-Lemeshow goodness-of-fit C chi-square and receiver operating characteristics (ROC) curve analyses. RESULTS: A total of 871 patients were included in the analysis. The goodness-of-fit C chi-square test showed that both scores have a good performance in predicting survivors and nonsurvivors in CCU. Expanded SAPS II score has a sensitivity of 80% and a specificity of 91.8% with the cut-off value of 5.55, while APACHE II has a sensitivity of 75.9% and a specificity of 87.4% with the cut-off value of 16.5 in predicting mortality. CONCLUSION: Expanded SAPS II and APACHE II scores have good ability to predict in-hospital mortality in CCU patients. Therefore, they can be used as a tool to predict short-term mortality in cardiovascular emergencies.

Simplified acute physiology score III is excellent for predicting in-hospital mortality in coronary care unit patients with acute myocardial infarction: A retrospective study.

Background: Coronary care unit (CCU) patients with acute myocardial infarction (AMI) lack effective predictors of in-hospital mortality. This study aimed to investigate the performance of four scoring systems in predicting in-hospital mortality in CCU patients with AMI. Methods: The baseline data, the logistic organ dysfunction system (LODS), the Oxford acute severity of illness score (OASIS), the simplified acute physiology score II (SAPS II), and the simplified acute physiology score III (SAPS III) scores of the patients were extracted from the fourth edition of the Medical Information Mart for Critical Care (MIMIC-IV) database. Independent risk factors for in-hospital mortality were identified by regression analysis. We performed receiver operating characteristic (ROC) curves and compared the area under the curve (AUC) to clarify the predictive value of the four scoring systems. Meanwhile, Kaplan-Meier curves and decision curve analysis (DCA) were performed to determine the optimal scoring system for predicting in-hospital mortality. Results: A total of 1,098 patients were included. The SAPS III was an independent risk factor for predicting in-hospital mortality in CCU patients with AMI before and after the propensity score matching (PSM) analysis. The discrimination of in-hospital mortality by SAPS III was superior to that of LODS, OASIS, and SAPS II. The AUC of the SAPS III scoring system was the highest among the four scoring systems, at 0.901 (before PSM) and 0.736 (after PSM). Survival analysis showed that significantly more in-hospital mortality occurred in the high-score SAPS III group compared to the low-score SAPS III group before PSM (HR 7.636, P < 0.001) and after PSM (HR 2.077, P = 0.005). The DCA curve of SAPS III had the greatest benefit score across the largest threshold range compared to the other three scoring systems. Conclusion: The SAPS III was an independent risk factor for predicting in-hospital mortality in CCU patients with AMI. The predictive value for in-hospital mortality with SAPS III is superior to that of LODS, OASIS, and SAPS II. The results of the DCA analysis suggest that SAPS III may provide a better clinical benefit for patients. We demonstrated that SAPS III is an excellent scoring system for predicting in-hospital mortality for CCU patients with AMI.

Comparison of different clinical risk scores to predict long-term survival and neurological outcome in adults after cardiac arrest: results from a prospective cohort study.

BACKGROUND: Several scoring systems have been used to predict short-term outcome in patients with out-of-hospital cardiac arrest (OHCA), including the disease-specific OHCA and CAHP (Cardiac Arrest Hospital Prognosis) scores, as well as the general severity-of-illness scores Acute Physiology and Chronic Health Evaluation II (APACHE II) and Simplified Acute Physiology Score II (SAPS II). This study aimed to assess the prognostic performance of these four scores to predict long-term outcomes (≥ 2 years) in adult cardiac arrest patients. METHODS: This is a prospective single-centre cohort study including consecutive cardiac arrest patients admitted to intensive care in a Swiss tertiary academic medical centre. The primary endpoint was 2-year mortality. Secondary endpoints were neurological outcome at 2 years post-arrest assessed by Cerebral Performance Category with CPC 1-2 defined as good and CPC 3-5 as poor neurological outcome, and 6-year mortality. RESULTS: In 415 patients admitted to intensive care, the 2-year mortality was 58.1%, with 96.7% of survivors showing good neurological outcome. The 6-year mortality was 82.5%. All four scores showed good discriminatory performance for 2-year mortality, with areas under the receiver operating characteristics curve (AUROC) of 0.82, 0.87, 0.83 and 0.81 for the OHCA, CAHP, APACHE II and SAPS II scores. The results were similar for poor neurological outcome at 2 years and 6-year mortality. CONCLUSION: This study suggests that two established cardiac arrest-specific scores and two severity-of-illness scores provide good prognostic value to predict long-term outcome after cardiac arrest and thus may help in early goals-of-care discussions.

Comparison of POSSUM and SAPS II in Prediction of Postoperative Mortality in Hollow Viscus Perforation.

BACKGROUND: There have been very few studies in the literature assessing various scoring systems to predict mortality in patients with hollow viscous perforation. Scoring systems like POSSUM and SAPS II are among the most widely validated risk predictors. Objective of the study was to compare POSSUM and SAPS II in prediction of mortality in patients undergoing surgery for hollow viscus perforation. METHODS: Prospective observational study was conducted at Department of Surgery, Tribhuvan University Teaching Hospital, Kathmandu, Nepal, over a period of 18 months. Ethical approval was obtained from the Institutional Review Board of Institute of Medicine. Informed consent was taken from all the patients. Patients aged less than 16 years, discharged on request and patients in whom no perforation found during surgery were excluded from the study. RESULTS: Among 121 patients enrolled in the study, in-hospital mortality was seen in 19 patients (17.0%). Mean POSSUM score in survivors was 39.7 ± 7.3 and in non-survivors was 52.8 ± 5.8 (p < 0.001). Similarly mean SAPS II score was 16.4 ± 9.7 in survivors and 41.8 ± 6.4 in non-survivors ( p < 0.001). Area under ROC curve was higher for SAPS II (0.964) as compared to POSSUM (0.906) suggesting that SAPS was better. CONCLUSIONS: Both POSSUM and SAPS II provided good discrimination between survivors and non survivors in patients undergoing surgery for hollow viscus perforation. SAPS II showed better sensitivity and specificity than POSSUM in predicting mortality.

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.