Quick SOFA Score Research Articles

Development and validation of a community acquired sepsis-worsening score in the adult emergency department: a prospective cohort: the CASC score

BackgroundSepsis is a leading cause of death and serious illness that requires early recognition and therapeutic management to improve survival. The quick-SOFA score helps in its recognition, but its diagnostic performance is insufficient. To develop a score that can rapidly identify a community acquired septic situation at risk of clinical complications in patients consulting the emergency department (ED).MethodsWe conducted a monocentric, prospective cohort study in the emergency department of a university hospital between March 2016 and August 2018 (NCT03280992). All patients admitted to the emergency department for a suspicion of a community-acquired infection were included. Predictor variables of progression to septic shock or death within the first 90 days were selected using backward stepwise multivariable logistic regression to develop a clinical score. Receiver operating characteristic (ROC) curves were constructed to determine the discriminating power of the area under the curve (AUC). We also determined the threshold of our score that optimized the performance required for a sepsis-worsening score. We have compared our score with the NEWS-2 and qSOFA scores.ResultsAmong the 21,826 patients admitted to the ED, 796 patients were suspected of having community-acquired infection and 461 met the sepsis criteria; therefore, these patients were included in the analysis. The median [interquartile range] age was 72 [54–84] years, 248 (54%) were males, and 244 (53%) had respiratory symptoms. The clinical score ranged from 0 to 90 and included 8 variables with an area under the ROC curve of 0.85 (confidence interval [CI] 95% 0.81–0.89). A cut-off of 26 yields a sensitivity of 88% (CI 95% 0.79–0.93), a specificity of 62% (CI 95% 57–67), and a negative predictive value of 95% (CI 95% 91–97). The area under the ROC curve for our score was 0.85 (95% CI, 0.81–0.89) versus 0.73 (95% CI, 0.68–0.78) for qSOFA and 0.66 (95% CI, 0.60–0.72) for NEWS-2.ConclusionsOur study provides an accurate clinical score for identifying septic patients consulting the ED early at risk of worsening disease. This score could be implemented at admission.

Clinically Evident Cardiopulmonary Congestion Does Not Significantly Impact the Prognosis of Patients With Septic Acute Kidney Injury.

Acute kidney injury (AKI) is a common issue among in-hospital patients, with high mortality rates. Sepsis is a primary cause of AKI, particularly in the intensive care unit. Patients with septic AKI often experience cardiovascular congestion, leading to the formal classification of cardiorenal syndrome type 5. The study aimed to evaluate the prognosis of septic AKI patients with and without clinical evidence of cardiovascular congestion. This was a retrospective observational study. AKI patients were identified using the in-hospital AKI alert system. Sepsis was diagnosed based on laboratory, clinical, and hemodynamic characteristics, with additional consideration of the quickSOFA score. Cardiovascular congestion was diagnosed by assessing clinical (edema), radiographic (pulmonary congestion), echocardiographic (e.g., wall motion abnormalities), and laboratory variables (e.g., N-terminal pro-B-type natriuretic peptide). Endpoints included in-hospital survival, the need for kidney replacement therapy (KRT), and recovery of kidney function (ROKF). In total, 102 patients were included, and cardiopulmonary congestion was diagnosed in 78.4%. Individuals with congestion did not differ from patients without congestion in any of the pre-defined endpoints. It is justified not to consider clinically apparent cardiovascular congestion in septic AKI patients as a risk factor for death per se. Rather, especially in the case of sepsis, clinically apparent positive fluid balance does not seem to be a disadvantage in terms of survival, KRT, and ROKF.

Role of SFGSI, microbial culture and qSOFA as predictive factors in determining the survival rate in Fournier Gangrene patient.

To examine the simplified Fournier Gangrene Severe Index Score (SFGSI) and the number of species in culture findings for predicting death in Fournier Gangrene (FG) patients in terms of their predictive power. From January 2017 to July 2022, the medical records of individuals undergoing emergency surgery for FG were obtained. A total of 80 patients were examined for clinical data such as age, gender, laboratory parameters, etiology, isolated bacteria, and mortality rate. We identified a statistically significant mean difference between SFGSI (p<0.0001) and quickSOFA (qSOFA) scores (p=0.002) in determining the survival rate of FG patients. The sensitivity and specificity of the SFGSI score in predicting mortality were 90.1% and 88.3% respectively, whereas the sensitivity and specificity of the qSOFA score were 88.2% and 86.2%. E. Coli comprised 56.2% of the bacteria, followed by S. Haemolyticus, S. Aureus, P. Aeruginosa, and K. Pneumoniae. On the basis of bacterial culture results, P. Aeruginosa had the highest fatality rate (100%) followed by S. Aureus (75%), S. Haemolyticus (30%), and E. Coli (20%), in that order. The survival rate of FG patients can be predicted using the sensitivity and specificity of the SFGSI and qSOFA scores together. P. Aeruginosa-infected patients have the greatest mortality rate (100%) compared to the other groups.

Usefulness of the quick-SOFA Score in Cardiovascular intensive care unit to Predict prognosis in Acute Coronary Syndrome

Usefulness of the quick-SOFA Score in Cardiovascular intensive care unit to Predict prognosis in Acute Coronary Syndrome

Usefulness of the quick-SOFA Score in Cardiovascular intensive care unit to Predict prognosis in Acute Coronary Syndrome

Usefulness of the quick-SOFA Score in Cardiovascular intensive care unit to Predict prognosis in Acute Coronary Syndrome

Comparison of different prognostic scores in estimating short- and long-term mortality in COVID-19 patients above 60years old in a university hospital in Belgium.

Multiple scoring systems were used for risk stratification in COVID-19 patients. The objective was to determine among 6 scores which performed the best in predicting short-and long-term mortality in hospitalized COVID-19 patients ≥ 60years. An observational, retrospective cohort study conducted between 21/10/2020 and 20/01/2021. 6 scores were calculated (Clinical Frailty Scale (CFS), Charlson Comorbidity Index (CCI), 4C Mortality Score (4CMS), NEWS score (NEWS), quick-SOFA score (qSOFA), and Quick COVID-19 Severity Index (qCSI)). We included unvaccinated hospitalized patients with COVID-19 ≥ 60years old in Brugmann hospital, detected by PCR and/or suggestive CT thorax images. Old and nosocomial infections, and patients admitted immediately at the intensive care unit were excluded. 199 patients were included, mean age was 76.2years (60-99). 47.2% were female. 56 patients (28%) died within 1year after the first day of hospitalization. The 4CMS predicted the best intrahospital, 30days and 6months mortality, with area under the ROC curve (AUROC) 0.695 (0.58-0.81), 0.76 (0.65-0.86) and 0.72 (0.63-0.82) respectively. The CCI came right after with respectively AUROC of 0.69 (0.59-0.79), 0.74 (0.65-0.83) and 0.71 (0.64-0.8). To predict mortality at 12months after hospitalization, the CCI had the highest AUROC with 0.77 (0.69-0.85), before the 4CMS with 0.69 (0.60-0.79). Among 6 scores, the 4CMS was the best to predict intrahospital, 30-day and 6-month mortality. To predict mortality at 12months, CCI had the best performance before 4CMS. This reflects the importance of considering comorbidities for short- and long-term mortality after COVID 19. This study was approved by the ethical committee of Brugmann University Hospital (reference CE 2020/228).

Prospective analysis of febrile neutropenia patients with bacteraemia: the results of an international ID–IRI study

Bacteraemia during the course of neutropenia is often fatal. We aimed to identify factors predicting mortality to have an insight into better clinical management. The study has a prospective, observational design using pooled data from febrile neutropenia patients with bacteraemia in 41 centres in 16 countries. Polymicrobial bacteraemias were excluded. It was performed through the Infectious Diseases-International Research Initiative platform between 17 March 2021 and June 2021. Univariate analysis followed by a multivariate binary logistic regression model was used to determine independent predictors of 30-d in-hospital mortality (sensitivity, 81.2%; specificity, 65%). A total of 431 patients were enrolled, and 85 (19.7%) died. Haematological malignancies were detected in 361 (83.7%) patients. Escherichia coli (n=117, 27.1%), Klebsiellae (n=95, 22% %), Pseudomonadaceae (n=63, 14.6%), Coagulase-negative Staphylococci (n=57, 13.2%), Staphylococcus aureus (n=30, 7%), and Enterococci (n=21, 4.9%) were the common pathogens. Meropenem and piperacillin-tazobactam susceptibility, among the isolated pathogens, were only 66.1% and 53.6%, respectively. Pulse rate (odds ratio [OR], 1.018; 95% confidence interval [CI], 1.002-1.034), quick SOFA score (OR, 2.857; 95% CI, 2.120-3.851), inappropriate antimicrobial treatment (OR, 1.774; 95% CI, 1.011-3.851), Gram-negative bacteraemia (OR, 2.894; 95% CI, 1.437-5.825), bacteraemia of non-urinary origin (OR, 11.262; 95% CI, 1.368-92.720), and advancing age (OR, 1.017; 95% CI, 1.001-1.034) were independent predictors of mortality. Bacteraemia in our neutropenic patient population had distinctive characteristics. The severity of infection and the way to control it with appropriate antimicrobials, and local epidemiological data, came forward. Local antibiotic susceptibility profiles should be integrated into therapeutic recommendations, and infection control and prevention measures should be prioritised in this era of rapidly increasing antibiotic resistance.

Delayed diagnosis of pneumonia in the emergency department: factors associated and prognosis.

Whether a delayed diagnosis of community-acquired pneumonia (CAP) in the emergency department (ED) is associated with worse outcome is uncertain. We sought factors associated with a delayed diagnosis of CAP in the ED and those associated with in-hospital mortality. Retrospective study including all inpatients admitted to an ED (Dijon University Hospital, France) from 1 January to 31 December 2019, and hospitalized with a diagnosis of CAP. Patients diagnosed with CAP in the ED (n = 361, early diagnosis) were compared with those diagnosed later, in the hospital ward, after the ED visit (n = 74, delayed diagnosis). Demographic, clinical, biological and radiological data were collected upon admission to the ED, as well as administered therapies and outcomes including in-hospital mortality. 435 inpatients were included: 361 (83%) with an early and 74 (17%) with a delayed diagnosis. The latter less frequently required oxygen (54 vs. 77%; p < 0.001) and were less likely to have a quick-SOFA score ≥ 2 (20 vs. 32%; p = 0.056). Absence of chronic neurocognitive disorders, of dyspnea, and of radiological signs of pneumonia were independently associated with a delayed diagnosis. Patients with a delayed diagnosis less frequently received antibiotics in the ED (34 vs. 75%; p < 0.001). However, a delayed diagnosis was not associated with in-hospital mortality after adjusting on initial severity. Delayed diagnosis of pneumonia was associated with a less severe clinical presentation, lack of obvious signs of pneumonia on chest X-ray, and delayed antibiotics initiation, but was not associated with worse outcome.

Development and validation of a simple machine learning tool to predict mortality in leptospirosis

Predicting risk factors for death in leptospirosis is challenging, and identifying high-risk patients is crucial as it might expedite the start of life-saving supportive care. Admission data of 295 leptospirosis patients were enrolled, and a machine-learning approach was used to fit models in a derivation cohort. The comparison of accuracy metrics was performed with two previous models—SPIRO score and quick SOFA score. A Lasso regression analysis was the selected model, demonstrating the best accuracy to predict mortality in leptospirosis [area under the curve (AUC-ROC) = 0.776]. A score-based prediction was carried out with the coefficients of this model and named LeptoScore. Then, to simplify the predictive tool, a new score was built by attributing points to the predictors with importance values higher than 1. The simplified score, named QuickLepto, has five variables (age > 40 years; lethargy; pulmonary symptom; mean arterial pressure < 80 mmHg and hematocrit < 30%) and good predictive accuracy (AUC-ROC = 0.788). LeptoScore and QuickLepto had better accuracy to predict mortality in patients with leptospirosis when compared to SPIRO score (AUC-ROC = 0.500) and quick SOFA score (AUC-ROC = 0.782). The main result is a new scoring system, the QuickLepto, that is a simple and useful tool to predict death in leptospirosis patients at hospital admission.

Does the intubation timeline affect the in-hospital mortality of COVID-19 patients? A retrospective cohort study.

BackgroundEffective strategies for managing coronavirus disease 19 (COVID-19) patients suffering from acute respiratory distress are constantly evolving. The timeline and threshold for transitioning from non-invasive ventilation to intermittent mandatory ventilation in critical cases who develop COVID-19-related respiratory distress are undetermined. The present research intends to investigate if emergency room intubations in COVID-19 patients affect mortality.MethodsBetween January 1, 2021 and June 30, 2021, we retrospectively reviewed chart analysis on all patients with confirmed positive COVID-19 screening and who underwent endotracheal intubation. Depending on when the intubation was performed; early in the emergency room or delayed outside the emergency room, patients were separated into two cohorts. In addition to comorbid clinical manifestations, the quick sequential organ failure assessment (qSOFA) score, and in-hospital mortality were all recorded as demographic and clinical information.ResultsFifty-eight of the 224 corona-positive patients who underwent intubation had their intubations performed in the emergency room. Age, sex, alcohol use, and smoking status did not significantly differ between the two categories at the baseline. The mean qSOFA score was higher in the early intubation cohort (3.5; p < 0.000) along with more underlying comorbidities (3.0; p < 0.000). When compared to the late intubation cohort (45.78%), patients treated with early intubation had a significantly greater death rate (67.24%).ConclusionIn summary, we discovered that patients who underwent intubation in the emergency units exhibited a high quick SOFA score as well as maximum co-morbid conditions than patients intubated somewhere else in the hospital. The findings of our investigation imply that intubating patients too early might be risky.

Heparin-binding protein-enhanced quick SOFA score improves mortality prediction in sepsis patients.

PurposeThe Quick Sequential Organ Failure Assessment (qSOFA) score proposed by Sepsis-3 as a sepsis screening tool has shown suboptimal accuracy. Heparin-binding protein (HBP) has been shown to identify early sepsis with high accuracy. Herein, we aim to investigate whether or not HBP improves the model performance of qSOFA.MethodsWe conducted a multicenter prospective observational study of 794 adult patients who presented to the emergency department (ED) with presumed sepsis between 2018 and 2019. For each participant, serum HBP levels were measured and the hospital course was followed. The qSOFA score was used as the comparator. The data was split into a training dataset (n = 556) and a validation dataset (n = 238). The primary endpoint was 30-day all-cause mortality.ResultsCompared with survivors, non-survivors had significantly higher serum HBP levels (median: 71.5 ng/mL vs 209.5 ng/mL, p < 0.001). Serum level of HBP weakly correlated with qSOFA class (r2 = 0.240, p < 0.001). Compared with the qSOFA model alone, the addition of admission HBP level to the qSOFA model significantly improved 30-day mortality discrimination (AUC, 0.70 vs. 0.80; P < 0.001), net reclassification improvement [26% (CI, 17–35%); P < 0.001], and integrated discrimination improvement [12% (CI, 9–14%); P < 0.001]. Addition of C-reactive protein (CRP) level or neutrophil-to-lymphocyte ratio (NLR) to qSOFA did not improve its performance. A web-based mortality risk prediction calculator was created to facilitate clinical implementation.ConclusionThis study confirms the value of combining qSOFA and HBP in predicting sepsis mortality. The web calculator provides a user-friendly tool for clinical implementation. Further validation in different patient populations is needed before widespread application of this prediction model.

Could quick SOFA and SOFA score be a predictive tool for 30-day and in-hospital mortality in acute empyema?

While acute empyema is a critical infectious disease showing a high mortality rate, there are no prognostic tools to evaluate the disease severity and prognosis for patients. We conducted a retrospective cohort to determine whether quick Sequential Organ Failure Assessment (qSOFA) and SOFA score can predict the disease severity and prognosis of acute empyema. A total of 53 patients were enrolled in the study. The mean age was 69 years and 41 patients (77%) were male. Twenty-two patients (42%) had multiple underlying diseases with the Charlson comorbidity index ≥3. The-30 days, and in-hospital deaths were 7 (13%) and 10 (19%), respectively. The area under the ROC curve of SOFA score and CCI for 30-day and in-hospital deaths were 0.814 (p = 0.073) and 0.752 (p = 0.082), 0.848 (p = 0.07) and 0.762 (p = 0.011), respectively. Univariate analysis showed that qSOFA ≥2 and SOFA score ≥2, isolation of potentially drug-resistant (PDR) pathogen, high CCI (≥3), performance status of 2–4, surgical intervention, and anaerobic bacteria involvement were prognostic factors. Of these, multivariate logistic regression analysis showed that qSOFA ≥2 and SOFA score ≥2 (p = 0.011), isolation of PDR pathogen (p = 0.005), and high CCI (≥3) (p = 0.015) were independently poor prognostic factors. We concluded that qSOFA and SOFA scores could predict the disease severity and prognosis in acute empyema. Additionally, isolation of PDR pathogens and high CCI could be poor prognostic factors for patients.

Diagnostic accuracy of quick SOFA score and inflammatory biomarkers for predicting community-onset bacteremia

The potential use of quick SOFA (qSOFA) score and inflammatory biomarkers as bacteremia predictors is unelucidated. Herein the aim of this study was to evaluate the diagnostic accuracy of the qSOFA score and biomarkers for predicting community-onset bacteremia. We enrolled adult outpatients with blood culture samples drawn between 2018 and 2020. Contamination, intensive care unit admission, and hemodialysis were excluded. We performed a case-control study, and analyzed 115 patients (58 with bacteremia and 57 without bacteremia). The positive likelihood ratio (LR) for bacteremia was 2.46 (95% confidence interval [CI] 0.76–9.05) for a qSOFA score ≥ 2, and 4.07 (95% CI 1.92–9.58) for tachypnea (≥ 22/min). The highest performing biomarkers were procalcitonin (area under the curve [AUC] 0.80; 95% CI 0.72–0.88), followed by presepsin (AUC 0.69; 95% CI 0.60–0.79), and C-reactive protein (AUC 0.60; 95% CI 0.49–0.70). The estimated optimal cut-off value of procalcitonin was 0.377 ng/mL, with a sensitivity of 74.1%, a specificity of 73.7%, and a positive LR of 2.82. Presepsin was 407 pg/mL, with a sensitivity of 60.3%, a specificity of 75.4%, and a positive LR of 2.46. Procalcitonin was found to be a modestly useful biomarker for predicting non-severe community-onset bacteremia. Tachypnea (≥ 22/min) itself, rather than the qSOFA score, can be a diagnostic predictor. These predictors may aid decision-making regarding the collection of blood culture samples in the emergency department and outpatient clinics.

Quick COVID-19 Severity Index, CURB-65 and Quick SOFA Scores Comparison in Predicting Mortality and Risk Factors of COVID-19 Patients.

This study aimed to investigate CURB-65, quick COVID-19 Severity Index (qCSI) and quick Sepsis Related Organ Failure Assessment (qSOFA) scores in predicting mortality and risk factors for death in patients with COVID-19. We retrospectively analyzed a total of 1919 cases for whom the rRT-PCR assay for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was positive. For mortality risk factors, univariate and multivariate logistic regression analyses were used. Receiver operator characteristics (ROC) analysis and Kaplan-Meier survival analysis were performed for CURB-65, qCSI and qSOFA scores. The patients' average age was 45.7 (21.6) years. Male patients accounted for 51.7% (n=992). In univariate analysis, some clinical variables including age over 65 years and comorbid diseases such as hypertension, chronic kidney disease, malignancy, lymphopenia, troponin, lactate dehydrogenase (LDH) and fibrinogen elevation were associated with the mortality rate. In multivariate logistic regression analysis: Neutrophil lymphocyte ratio (NLR) 3.3 and above (OR, 9.1; 95% CI, 1.9-42), C-reactive protein (CRP)30 mg/L and above (OR, 4.1; 95% CI, 1.2-13.6), D-dimer 1000 ng/mL and above (OR, 4; 95% CI, 1.5-10.7) and age (OR, 1.11; 95% CI, 1.04-1.18-year increase) were identified as risk factors for mortality among COVID-19 patients. The CURB-65 and qCSI scores exhibited a high degree of discrimination in mortality prediction (AUC values were 0.928 and 0.865, respectively). Also, the qSOFA score had a moderate discriminant power (AUC value was 0.754). CURB-65 and qSCI scores had a high discriminatory power to predict mortality. Also, this study identified CURB-65, qCSI and qSOFA scores, NLR, CRP, D-dimer level, and annual age increase as important mortality risk factors.

A New Early Predictor of Fatal Outcome for COVID-19 in an Italian Emergency Department: The Modified Quick-SOFA.

Background: Since 2019, the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is causing a rapidly spreading pandemic. The present study aims to compare a modified quick SOFA (MqSOFA) score with the NEWS-2 score to predict in-hospital mortality (IHM), 30-days mortality and recovery setting. Methods: All patients admitted from March to October 2020 to the Emergency Department of St. Anna Hospital, Ferrara, Italy with clinically suspected SARS-CoV-2 infection were retrospectively included in this single-centre study and evaluated with the MqSOFA and NEWS-2 scores. Statistical and logistic regression analyses were applied to our database. Results: A total of 3359 individual records were retrieved. Among them, 2716 patients were excluded because of a negative nasopharyngeal swab and 206 for lacking data; thus, 437 patients were eligible. The data showed that the MqSOFA and NEWS-2 scores equally predicted IHM (p < 0.001) and 30-days mortality (p < 0.001). Higher incidences of coronary artery disease, congestive heart failure, cerebrovascular accidents, dementia, chronic kidney disease and cancer were found in the deceased vs. survived group. Conclusions: In this study we confirmed that the MqSOFA score was non-inferior to the NEWS-2 score in predicting IHM and 30-days mortality. Furthermore, the MqSOFA score was easier to use than NEWS-2 and is more suitable for emergency settings. Neither the NEWS-2 nor the MqSOFA scores were able to predict the recovery setting.

The Survival of Septic Patients with Compensated Liver Cirrhosis Is Not Inferior to That of Septic Patients without Liver Cirrhosis: A Propensity Score Matching Analysis.

Background: We aimed to determine whether septic patients with liver cirrhosis (LC) had worse survival than septic patients without liver cirrhosis (WLC). We also investigated the survival of septic patients with compensated liver cirrhosis (CLC) and decompensated liver cirrhosis (DLC). Methods: This study enrolled 776 consecutive adult patients with sepsis admitted to the medical intensive care units of a tertiary referral hospital. Clinical factors and laboratory data were collected for analysis. Propensity scoring was also used for the control of selection bias. The variables included in the propensity model were age, sex, presence of diabetes mellitus, hypertension, cardiovascular accident, chronic kidney disease, malignancy, APCHE II (Acute Physiology and Chronic Health Evaluation) score, hemoglobin, and platelet data on the day when sepsis was confirmed. Seven-day, ICU, and hospital mortality were analyzed after correcting for these confounding factors. Results: Of the 776 septic patients, 64 (8.2%) septic patients presented with LC. Patients were divided into two groups—LC (n = 64) and WLC (n = 712)—which presented different rates of hospital mortality (LC: 62.5% vs. WLC: 41.0%, p = 0.001). We further separated septic patients with LC into two groups: patients with CLC (n = 24) and those with DLC (n = 40). After propensity score matching, the survival of septic patients with CLC (63.6%) was not inferior to patients WLC (54.5%) (p = 0.411). Patients with DLC had more hospital mortality, even after matching (p < 0.05). The Quick SOFA (qSOFA) score, SOFA score, and sub-SOFA score were also comparable between groups. SOFA scores were not significantly different between the CLC and WLC groups after matching. Poor SOFA scores were observed in the DLC group on days 3 and 7 after matching (p < 0.05). Conclusions: Septic patients with LC had higher mortality compared to patients WLC before matching. However, after propensity score matching, the survival of septic patients with CLC was non-inferior to patients WLC.

Comparison of quick Pitt to quick sofa and sofa scores for scoring of severity for patients with urinary tract infection

Quick Pitt (qPitt), which includes temperature, systolic blood pressure, respiratory rate, cardiac arrest, and mental status, is a new prognostic score derived from the Pitt Bacteremia score. The aim of our study is to compare qPitt with quick SOFA (qSOFA) and SOFA for scoring of severity in patients with urinary tract infection (UTI). Prospective observational study of patients diagnosed with UTI. Area under the ROC curve, sensibility, and specificity to predict 30-day mortality were calculated for qPitt, qSOFA and SOFA and compared. 382 UTI cases were analyzed. Thirty-day mortality (18.8% vs. 5.9%, p < 0.001) and longer hospital stay (6 [1–11] vs. 4 [1–7] days, p < 0.001) were associated with qPitt ≥ 2. However, qPitt had a worse performance to predict 30-day mortality compared to qSOFA and SOFA (AUROC 0.692 vs. 0.832 and 0.806, respectively, p = 0.010 and p = 0.041). The sensitivity of qPitt was lower than the sensitivity of qSOFA and SOFA (70.45 vs. 84.09 for both qSOFA and SOFA, p < 0.001), with a specificity lower than qSOFA and similar to SOFA (60.36 vs. 82.25 and 63.61, p < 0.001 and p = 0.742, respectively). Quick Pitt had moderate prognostic accuracy and performed worse than qSOFA and SOFA scores for predicting mortality in patients with UTI.

Sequential organ failure assessment and modified early warning score system versus quick SOFA score to predict the length of hospital stay in sepsis patients – accuracy scoring study.

Sequential organ failure assessment and modified early warning score system versus quick SOFA score to predict the length of hospital stay in sepsis patients – accuracy scoring study.

Outfacing second wave of pandemic in COVID-19 positive mothers at Gandhi hospital

The novel coronavirus is a single stranded RNA virus with spike proteins triggering an immune response leading to cytokine storm and coagulopathy. Pregnancy is an immunocompromised and hypercoagulable state, with predisposition to severe illness. An insight into impact of COVID-19 in pregnancy is essential to combat its future.This study was conducted at a tertiary care centre. Analytical study was conducted from the data collected regarding COVID-19 positive labour room admissions, deliveries and deaths during the second wave of pandemic.There was a discharge rate of 88.14% after safe delivery. Among COVID-19 maternal mortalities, most deaths were due to ARDS. Quick SOFA score was a good predictor for morbidity and mortality. Deranged coagulation profile and D-Dimer levels more than 500 ng/ml were good predictors of mortality. Silent hypoxia needs to be identified and corrected at admission. Delay in seeking medical advice was a major contributory risk factor.Increasingawareness among public about seeking medical advice during early stages of disease. Early identification and treatment according to latest guidelines for a positive outcome.Making aware the policy makers regarding risk-benefits of vaccination in mothers can come a long way in changing the fate of COVID-19 in pregnancy.

Case fatality rate and survival functions of severe COVID–19 patients in intensive care unit of Bangabandhu Sheikh Mujib Medical University in Bangladesh: an observational study

Background: Emergence of current pandemic caused by novel SARS–COV–2 has already caused over 963000 deaths. Case fatality rate (CFR) estimation helps understanding the disease severity and the lethality trend, high risk population and subsequently, optimization of quality healthcare facilities. Our observational study aimed to find out existing trends in treating the most vulnerable group with scarce medical resource allocation and to implement necessary support services to comply with the ensuing need for best possible outcomes in our ICU. Methodology: In this observational study, all COVID–19 diagnosed patients admitted in our ICU from July 4, 2020 to September 22, 2020, were enrolled. Data were obtained from the core ICU register of Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh. Information accumulated on predesigned data sheets comprised of particulars of patients, co–morbidities, duration of ICU stay, mode of oxygenation, organ support and quick SOFA scores. Total deaths in ICU (in hospital or referred from outside of BSMMU) were recorded. Results: The results revealed that all patients were either very severe or critically sick with COVID–19 pneumonia at the time of ICU admission. Out of 174 patients, 46 (26.44%) were put on invasive ventilation and the rest received noninvasive ventilation in the form of NRM, high flow nasal cannula (HFNC), continuous positive airway pressure (CPAP or BiPAP), CTEX CPAP and non–invasive ventilation (NIV) as appropriate. Male and female ratio was 74:26. Age of patients ranged between 19–95y. The median age of patients was 65 y (IQR: 57–70).Quick SOFA scores were more than 2 in 65.37% of patients. Regarding co–existing organ dysfunction 13.8% had 3 or more co–morbidities; while 74.1% had 2 and 9.8% had a single systemic illness along with COVID–19. Most common diseases encountered among 135 deceased were hypertension (64%), IHD (49%), diabetes mellitus (45%), bronchial asthma or COPD (32%), renal failure (either ARF or CRF) (20%). Overall CFR due to COVID–19 pneumonia associated with co–morbidities was 77.6%. Relatively higher CFR (82.6%) was evident harboring multi–organ dysfunction especially among COVID–19 patients aged 50y or more. Gender linked CFR were 81.4% and 66.7% in males and females respectively. Conclusion: High CFR demonstrates significant correlation with increasing age and co–morbidities and survival functions. Late presentation to the hospital and invasive mechanical ventilation also contributed to high CFR. Keywords: Case fatality rate; CFR; COVID–19; Intensive Care Unit; Survival function Abbreviations: CFR – Case fatality rate; NRM – Non-rebreathing mask; HFNC – high flow nasal cannula; CPAP – continuous positive airway pressure; BiPAP – Bi-level positive airway pressure; NIV – Non–invasive ventilation; IHD – Ischemic heart disease; ARF – Acute renal failure; CRF – Chronic renal failure Citation: Islam MS, Bhowmick DK, Parveen M, Kamal MM, Akhtaruzzaman AKM. Case fatality rate and survival functions of severe COVID–19 patients in intensive care unit of Bangabandhu Sheikh Mujib Medical University in Bangladesh: an observational study. Anaesth. pain intensive care 2021;25(4):443–449. DOI: Received: June 4, 2021, Reviewed: June 7, 2021, Accepted: June 12, 2021