Invasive group A streptococcal infections requiring admission to ICU: a nationwide, multicenter, retrospective study (ISTRE study).

BACKGROUND: Group A Streptococcus is responsible for severe and potentially lethal invasive conditions requiring intensive care unit (ICU) admission, such as streptococcal toxic shock-like syndrome (STSS). A rebound of invasive group A streptococcal (iGAS) infection after COVID-19-associated barrier measures has been observed in children. Several intensivists of French adult ICUs have reported similar bedside impressions without objective data. We aimed to compare the incidence of iGAS infection before and after the COVID-19 pandemic, describe iGAS patients' characteristics, and determine ICU mortality associated factors. METHODS: We performed a retrospective multicenter cohort study in 37 French ICUs, including all patients admitted for iGAS infections for two periods: two years before period (October 2018 to March 2019 and October 2019 to March 2020) and a one-year after period (October 2022 to March 2023) COVID-19 pandemic. iGAS infection was defined by Group A Streptococcus isolation from a normally sterile site. iGAS infections were identified using the International Classification of Diseases and confirmed with each center's microbiology laboratory databases. The incidence of iGAS infections was expressed in case rate. RESULTS: Two hundred and twenty-two patients were admitted to ICU for iGAS infections: 73 before and 149 after COVID-19 pandemic. Their case rate during the period before and after COVID-19 pandemic was 205 and 949/100,000 ICU admissions, respectively (p < 0.001), with more frequent STSS after the COVID-19 pandemic (61% vs. 45%, p = 0.015). iGAS patients (n = 222) had a median SOFA score of 8 (5-13), invasive mechanical ventilation and norepinephrine in 61% and 74% of patients. ICU mortality in iGAS patients was 19% (14% before and 22% after COVID-19 pandemic; p = 0.135). In multivariate analysis, invasive mechanical ventilation (OR = 6.08 (1.71-21.60), p = 0.005), STSS (OR = 5.75 (1.71-19.22), p = 0.005), acute kidney injury (OR = 4.85 (1.05-22.42), p = 0.043), immunosuppression (OR = 4.02 (1.03-15.59), p = 0.044), and diabetes (OR = 3.92 (1.42-10.79), p = 0.008) were significantly associated with ICU mortality. CONCLUSION: The incidence of iGAS infections requiring ICU admission increased by 4 to 5 after the COVID-19 pandemic. After the COVID-19 pandemic, the rate of STSS was higher, with no significant increase in ICU mortality rate.

Prediction of sepsis mortality in ICU patients using machine learning methods.

PROBLEM: Sepsis, a life-threatening condition, accounts for the deaths of millions of people worldwide. Accurate prediction of sepsis outcomes is crucial for effective treatment and management. Previous studies have utilized machine learning for prognosis, but have limitations in feature sets and model interpretability. AIM: This study aims to develop a machine learning model that enhances prediction accuracy for sepsis outcomes using a reduced set of features, thereby addressing the limitations of previous studies and enhancing model interpretability. METHODS: This study analyzes intensive care patient outcomes using the MIMIC-IV database, focusing on adult sepsis cases. Employing the latest data extraction tools, such as Google BigQuery, and following stringent selection criteria, we selected 38 features in this study. This selection is also informed by a comprehensive literature review and clinical expertise. Data preprocessing included handling missing values, regrouping categorical variables, and using the Synthetic Minority Over-sampling Technique (SMOTE) to balance the data. We evaluated several machine learning models: Decision Trees, Gradient Boosting, XGBoost, LightGBM, Multilayer Perceptrons (MLP), Support Vector Machines (SVM), and Random Forest. The Sequential Halving and Classification (SHAC) algorithm was used for hyperparameter tuning, and both train-test split and cross-validation methodologies were employed for performance and computational efficiency. RESULTS: The Random Forest model was the most effective, achieving an area under the receiver operating characteristic curve (AUROC) of 0.94 with a confidence interval of ±0.01. This significantly outperformed other models and set a new benchmark in the literature. The model also provided detailed insights into the importance of various clinical features, with the Sequential Organ Failure Assessment (SOFA) score and average urine output being highly predictive. SHAP (Shapley Additive Explanations) analysis further enhanced the model's interpretability, offering a clearer understanding of feature impacts. CONCLUSION: This study demonstrates significant improvements in predicting sepsis outcomes using a Random Forest model, supported by advanced machine learning techniques and thorough data preprocessing. Our approach provided detailed insights into the key clinical features impacting sepsis mortality, making the model both highly accurate and interpretable. By enhancing the model's practical utility in clinical settings, we offer a valuable tool for healthcare professionals to make data-driven decisions, ultimately aiming to minimize sepsis-induced fatalities.

mNUTRIC Score in ICU Mortality Prediction: An Emerging Frontier or Yet Another Transient Trend?

How to cite this article: Arunachala S, Kumar J. mNUTRIC Score in ICU Mortality Prediction: An Emerging Frontier or Yet Another Transient Trend? Indian J Crit Care Med 2024;28(5):422-423.

Effectiveness of prolonged versus standard-course of oseltamivir in critically ill patients with severe influenza infection: A multicentre cohort study.

The aim of this study is to investigate the effectiveness of prolonged versus standard course oseltamivir treatment among critically ill patients with severe influenza. A retrospective study of a prospectively collected database including adults with influenza infection admitted to 184 intensive care units (ICUs) in Spain from 2009 to 2018. Prolonged oseltamivir was defined if patients received the treatment beyond 5 days, whereas the standard-course group received oseltamivir for 5 days. The primary outcome was all-cause ICU mortality. Propensity score matching (PSM) was constructed, and the outcome was investigated through Cox regression and RCSs. Two thousand three hundred and ninety-seven subjects were included, of whom 1943 (81.1%) received prolonged oseltamivir and 454 (18.9%) received standard treatment. An optimal full matching algorithm was performed by matching 2171 patients, 1750 treated in the prolonged oseltamivir group and 421 controls in the standard oseltamivir group. After PSM, 387 (22.1%) patients in the prolonged oseltamivir and 119 (28.3%) patients in the standard group died (p = 0.009). After adjusting confounding factors, prolonged oseltamivir significantly reduced ICU mortality (odds ratio [OR]: 0.53, 95% confidence interval [CI]: 0.40-0.69). Prolonged oseltamivir may have protective effects on survival at Day 10 compared with a standard treatment course. Sensitivity analysis confirmed these findings. Compared with standard treatment, prolonged oseltamivir was associated with reduced ICU mortality in critically ill patients with severe influenza. Clinicians should consider extending the oseltamivir treatment duration to 10 days, particularly in higher-risk groups of prolonged viral shedding. Further randomized controlled trials are warranted to confirm these findings.

Identification of an optimal threshold to define oliguria in critically ill patients: an observational study.

BACKGROUND: The relevance of current consensus threshold to define oliguria has been challenged by small observational studies. We aimed to determine the optimal threshold to define oliguria in critically-ill patients. METHODS: Cohort study including adult patients admitted within a multi-disciplinary intensive care unit between January 1st 2010 and June 15th 2020. Patients on chronic dialysis or who declined consent were excluded. We extracted hourly urinary output (UO) measurements along with patient's characteristics from electronic medical records and 90-day mortality from the Swiss national death registry. We randomly split our data into a training (80%) and a validation (20%) set. In the training set, we developed multivariable models to assess the relationship between 90-day mortality and the minimum average UO calculated over time windows of 3, 6, 12 and 24 h. Optimal thresholds were determined by visually identifying cut-off values for the minimum average UO below which predicted mortality increased substantially. We tested models' discrimination and calibration on the entire validation set as well as on a subset of patients with oliguria according to proposed thresholds. RESULTS: Among the 15,500 patients included in this analysis (training set: 12,440, validation set: 3110), 73.0% (95% CI [72.3-73.8]) presented an episode of oliguria as defined by consensus criteria (UO < 0.5 ml/kg/h for 6 h). Our models had excellent (AUC > 85% for all time windows) discrimination and calibration. The relationship between minimum average UO and predicted 90-day mortality was nonlinear with an inflexion point at 0.2 ml/kg/h for 3 and 6 h windows and 0.3 ml/kg/h for 12 and 24 h windows. Considering a threshold of < 0.2 ml/kg/h over 6 h, the proportion of patients with an episode of oliguria decreased substantially to 24.7% (95% CI [24.0-25.4]). Contrary to consensus definition, this threshold identified a population with a higher predicted 90-day mortality. CONCLUSIONS: The widely used cut-off for oliguria of 0.5 ml/kg/h over 6 h may be too conservative. A cut-off of 0.2 ml/kg/h over 3 or 6 h is supported by the data and should be considered in further definitions of oliguria.

A generalizable and interpretable model for mortality risk stratification of sepsis patients in intensive care unit.

PURPOSE: This study aimed to construct a mortality model for the risk stratification of intensive care unit (ICU) patients with sepsis by applying a machine learning algorithm. METHODS: Adult patients who were diagnosed with sepsis during admission to ICU were extracted from MIMIC-III, MIMIC-IV, eICU, and Zigong databases. MIMIC-III was used for model development and internal validation. The other three databases were used for external validation. Our proposed model was developed based on the Extreme Gradient Boosting (XGBoost) algorithm. The generalizability, discrimination, and validation of our model were evaluated. The Shapley Additive Explanation values were used to interpret our model and analyze the contribution of individual features. RESULTS: A total of 16,741, 15,532, 22,617, and 1,198 sepsis patients were extracted from the MIMIC-III, MIMIC-IV, eICU, and Zigong databases, respectively. The proposed model had an area under the receiver operating characteristic curve (AUROC) of 0.84 in the internal validation, which outperformed all the traditional scoring systems. In the external validations, the AUROC was 0.87 in the MIMIC-IV database, better than all the traditional scoring systems; the AUROC was 0.83 in the eICU database, higher than the Simplified Acute Physiology Score III and Sequential Organ Failure Assessment (SOFA),equal to 0.83 of the Acute Physiology and Chronic Health Evaluation IV (APACHE-IV), and the AUROC was 0.68 in the Zigong database, higher than those from the systemic inflammatory response syndrome and SOFA. Furthermore, the proposed model showed the best discriminatory and calibrated capabilities and had the best net benefit in each validation. CONCLUSIONS: The proposed algorithm based on XGBoost and SHAP-value feature selection had high performance in predicting the mortality of sepsis patients within 24 h of ICU admission.

A differential therapeutic consideration for use of corticosteroids according to established COVID-19 clinical phenotypes in critically ill patients.

Objective: To determine if the use of corticosteroids was associated with Intensive Care Unit (ICU) mortality among whole population and pre-specified clinical phenotypes. Design: A secondary analysis derived from multicenter, observational study. Setting: Critical Care Units. Patients: Adult critically ill patients with confirmed COVID-19 disease admitted to 63 ICUs in Spain. Interventions: Corticosteroids vs. no corticosteroids. Main variables of interest: Three phenotypes were derived by non-supervised clustering analysis from whole population and classified as (A: severe, B: critical and C: life-threatening). We performed a multivariate analysis after propensity optimal full matching (PS) for whole population and weighted Cox regression (HR) and Fine-Gray analysis (sHR) to assess the impact of corticosteroids on ICU mortality according to the whole population and distinctive patient clinical phenotypes. Results: A total of 2017 patients were analyzed, 1171 (58%) with corticosteroids. After PS, corticosteroids were shown not to be associated with ICU mortality (OR: 1.0; 95% CI: 0.98-1.15). Corticosteroids were administered in 298/537 (55.5%) patients of "A" phenotype and their use was not associated with ICU mortality (HR = 0.85 [0.55-1.33]). A total of 338/623 (54.2%) patients in "B" phenotype received corticosteroids. No effect of corticosteroids on ICU mortality was observed when HR was performed (0.72 [0.49-1.05]). Finally, 535/857 (62.4%) patients in "C" phenotype received corticosteroids. In this phenotype HR (0.75 [0.58-0.98]) and sHR (0.79 [0.63-0.98]) suggest a protective effect of corticosteroids on ICU mortality. Conclusion: Our finding warns against the widespread use of corticosteroids in all critically ill patients with COVID-19 at moderate dose. Only patients with the highest inflammatory levels could benefit from steroid treatment.

Objetivo: Evaluar si el uso de corticoesteroides (CC) se asocia con la mortalidad en la unidad de cuidados intensivos (UCI) en la población global y dentro de los fenotipos clínicos predeterminados. Diseño: Análisis secundario de estudio multicéntrico observacional. Ámbito: UCI. Pacientes: Pacientes adultos con COVID-19 confirmado ingresados en 63 UCI de España. Intervención: Corticoides vs. no corticoides. Variables de interés principales: A partir del análisis no supervisado de grupos, 3 fenotipos clínicos fueron derivados y clasificados como: A grave, B crítico y C potencialmente mortal. Se efectuó un análisis multivariado después de un propensity optimal full matching (PS) y una regresión ponderada de Cox (HR) y análisis de Fine-Gray (sHR) para evaluar el impacto del tratamiento con CC sobre la mortalidad en la población general y en cada fenotipo clínico. Resultados: Un total de 2.017 pacientes fueron analizados, 1.171 (58%) con CC. Después del PS, el uso de CC no se relacionó significativamente con la mortalidad en UCI (OR: 1,0; IC 95%: 0,98-1,15). Los CC fueron administrados en 298/537 (55,5%) pacientes del fenotipo A y no se observó asociación significativa con la mortalidad (HR = 0,85; 0,55-1,33). Un total de 338/623 (54,2%) pacientes del fenotipo B recibieron CC sin efecto significativo sobre la mortalidad (HR = 0,72; 0,49-1,05). Por último, 535/857 (62,4%) pacientes del fenotipo C recibieron CC. En este fenotipo, se evidenció un efecto protector de los CC sobre la mortalidad HR (0,75; 0,58-0,98). Conclusión: Nuestros hallazgos alertan sobre el uso indiscriminado de CC a dosis moderadas en todos los pacientes críticos con COVID-19. Solamente pacientes con elevado estado de inflamación podrían beneficiarse con el tratamiento con CC.

Fusion of sequential visits and medical ontology for mortality prediction.

The goal of mortality prediction task is to predict the future death risk of patients according to their previous Electronic Healthcare Records (EHR). The main challenge of mortality prediction is how to design an accurate and robust predictive model with sequential, multivariate, sparse and irregular EHR data. In addition, the performance of model may be affected by lack of sufficient information of some patients with rare diseases in EHRs. To address these challenges, we propose a model to fuse Sequential visits and Medical Ontology to predict patients' death risk. SeMO not only learns reasonable embeddings for medical concepts from sequential and irregular visits, but also exploits medical ontology to improve the prediction performance. With integration of multivariate features, SeMO learns robust representations of medical codes, mitigating data insufficiency and insightful sequential dependencies among patient's visits. Experimental results on real world datasets prove that the proposed SeMO improves the prediction performance compared with the baseline approaches. Our model achieves an precision of up to 0.975. Compared with RNN, the precision has been improved up to 2.204%.

The relationship between ventilatory ratio (VR) and 28-day hospital mortality by restricted cubic splines (RCS) in 14,328 mechanically ventilated ICU patients.

BACKGROUND: Previous studies found that high levels of ventilatory ratio (VR) were associated with a poor prognosis due to worse ventilatory efficiency in acute respiratory distress syndrome patients. However, relatively few large studies have assessed the association between VR and intensive care unit (ICU) mortality in the general adult ventilated population. METHODS: The present study is a retrospective cohort study. Patients mechanically ventilated for more than 12 h were included. VR was calculated based on a previously reported formula. Restricted cubic spline models were used to fit the relationship between VR and mortality risks. RESULTS: A total of 14,328 mechanically ventilated ICU patients were included in the study, of which 1311 died within 28 days. The results of the study are as follows: (1) In the general adult ventilated population, VR was positively associated with 28-day mortality when VR ≥ 1.3 (increase of 0.1 per VR; HR 1.05, p < 0.001). The same tendency was also observed in the populations of severe hypoxemia with a PaO2/FiO2 (P/F) ratio < 200 mmHg. (2) However, in the population with a P/F ratio ≥ 200, a J-shaped dose-response association between VR and the risk of mortality was observed, with the risk of death positively associated with VR when VR ≥ 0.9 (10% increase in HR for every 0.1 increase in VR, p = 0.000) but negatively associated with VR when VR < 0.9 (10% decrease in HR for every 0.1 increase in VR, p = 0.034). In the population of P/F ratio ≥ 200 with VR less than 0.9, compared to the survival group, the nonsurvival group had a lower level PCO2 (33 mmHg [29.1, 37.9] vs. 34.4 mmHg [30.6, 38.5]), rather than a significant level of measured minute ventilation or P/F ratio. CONCLUSIONS: VR was positively associated with the risk of death in the general ICU population; however, VR was inversely associated with 28-day mortality in the population with a P/F ratio ≥ 200 and low VR . Further research should investigate this relationship, and VR should be interpreted with caution in clinical practice.

Female Patients with Pneumonia on Intensive Care Unit Are under Risk of Fatal Outcome.

Background and Objectives: The impact of sex on mortality in patients with pneumonia requiring intensive care unit (ICU) treatment is still a controversial discussion, with studies providing heterogeneous results. The reasons for sex differences are widespread, including hormonal, immunologic and therapeutic approaches. This study's aim was to evaluate sex-related differences in the mortality of ICU patients with pneumonia. Material and Methods: A prospective observational clinical trial was performed at Charité University Hospital in Berlin. Inclusion criteria were a diagnosis of pneumonia and a treatment period of over 24 h on ICU. A total of 436 mainly postoperative patients were included. Results: Out of 436 patients, 166 (38.1%) were female and 270 (61.9%) were male. Significant differences in their SOFA scores on admission, presence of immunosuppression and diagnosed cardiovascular disease were observed. Male patients were administered more types of antibiotics per day (p = 0.028) at significantly higher daily costs (in Euros) per applied anti-infective drug (p = 0.003). Mortalities on ICU were 34 (20.5%) in females and 39 (14.4%) in males (p = 0.113), before correcting for differences in patient characteristics using logistic regression analysis, and afterwards, the female sex showed an increased risk of ICU mortality with an OR of 1.775 (1.029-3.062, p = 0.039). Conclusions: ICU mortality was significantly higher in female patients with pneumonia. The identification of sex-specific differences is important to increase awareness among clinicians and allow resource allocation. The impact of sex on illness severity, sex differences in infectious diseases and the consequences on treatment need to be elucidated in the future.

Mortality Prediction in the ICU: The Daunting Task of Predicting the Unpredictable.

How to cite this article: Kumar AAK. Mortality Prediction in the ICU: The Daunting Task of Predicting the Unpredictable. Indian J Crit Care Med 2022;26(1):13-14.

Clinical outcomes of intravenous immunoglobulin therapy in COVID-19 related acute respiratory distress syndrome: a retrospective cohort study.

BACKGROUND: Intravenous immunoglobulin (IVIG) has been used as an immunomodulatory therapy to counteract severe systemic inflammation in coronavirus disease 2019 (COVID-19). But its use in COVID-19 related acute respiratory distress syndrome (ARDS) is not well established. METHODS: We conducted a retrospective analysis of electronic health records of COVID-19 patients admitted to intensive care units (ICUs) at Hazm Mebaireek General Hospital, Qatar, between March 7, 2020 and September 9, 2020. Patients receiving invasive mechanical ventilation for moderate-to-severe ARDS were divided into two groups based on whether they received IVIG therapy or not. The primary outcome was all-cause ICU mortality. Secondary outcomes studied were ventilator-free days and ICU-free days at day-28, and incidence of acute kidney injury (AKI). Propensity score matching was used to adjust for confounders, and the primary outcome was compared using competing-risks survival analysis. RESULTS: Among 590 patients included in the study, 400 received routine care, and 190 received IVIG therapy in addition to routine care. One hundred eighteen pairs were created after propensity score matching with no statistically significant differences between the groups. Overall ICU mortality in the study population was 27.1%, and in the matched cohort, it was 25.8%. Mortality was higher among IVIG-treated patients (36.4% vs. 15.3%; sHR 3.5; 95% CI 1.98-6.19; P < 0.001). Ventilator-free days and ICU-free days at day-28 were lower (P < 0.001 for both), and incidence of AKI was significantly higher (85.6% vs. 67.8%; P = 0.001) in the IVIG group. CONCLUSION: IVIG therapy in mechanically ventilated patients with COVID-19 related moderate-to-severe ARDS was associated with higher ICU mortality. A randomized clinical trial is needed to confirm this observation further.

The 4-Hour Cairns Sepsis Model: A novel approach to predicting sepsis mortality at intensive care unit admission.

BACKGROUND: Sepsis commonly causes intensive care unit (ICU) mortality, yet early identification of adults with sepsis at risk of dying in the ICU remains a challenge. OBJECTIVE: The aim of the study was to derive a mortality prediction model (MPM) to assist ICU clinicians and researchers as a clinical decision support tool for adults with sepsis within 4 h of ICU admission. METHODS: A cohort study was performed using 500 consecutive admissions between 2014 and 2018 to an Australian tertiary ICU, who were aged ≥18 years and had sepsis. A total of 106 independent variables were assessed against ICU episode-of-care mortality. Multivariable backward stepwise logistic regression derived an MPM, which was assessed on discrimination, calibration, fit, sensitivity, specificity, and predictive values and bootstrapped. RESULTS: The average cohort age was 58 years, the Acute Physiology and Chronic Health Evaluation III-j severity score was 72, and the case fatality rate was 12%. The 4-Hour Cairns Sepsis Model (CSM-4) consists of age, history of renal disease, number of vasopressors, Glasgow Coma Scale, lactate, bicarbonate, aspartate aminotransferase, lactate dehydrogenase, albumin, and magnesium with an area under the receiver operating characteristic curve of 0.90 (95% confidence interval = 0.84-0.95, p < 0.00001), a Nagelkerke R2 of 0.51, specificity of 0.94, a negative predictive value of 0.98, and almost identical odds ratios during bootstrapping. The CSM-4 outperformed existing MPMs tested on our data set. The CSM-4 also performed similar to existing MPMs in their derivation papers whilst using fewer, routinely collected, and inexpensive variables. CONCLUSIONS: The CSM-4 is a newly derived MPM for adults with sepsis at ICU admission. It displays excellent discrimination, calibration, fit, specificity, negative predictive value, and bootstrapping values whilst being easy to use and inexpensive. External validation is required.

Risk factors associated with mortality in intensive care COVID-19 patients: the importance of chest CT score and intubation timing as risk factors

Background/aim: Coronavirus disease 2019 (COVID-19) is a disease with a high rate of progression to critical illness. However, the predictors of mortality in critically ill patients admitted to the intensive care unit (ICU) are not yet well understood. In this study, we aimed to investigate the risk factors associated with ICU mortality in our hospital. Materials and methods: In this single-centered retrospective study, we enrolled 86 critically ill adult patients with COVID-19 admitted to ICU of Dokuz Eylül University Hospital (Izmir, Turkey) between 18 March 2020 and 31 October 2020. Data on demographic information, preexisting comorbidities, treatments, the laboratory findings at ICU admission, and clinical outcomes were collected. The chest computerized tomography (CT) of the patients were evaluated specifically for COVID-19 and CT score was calculated. Data of the survivors and nonsurvivors were compared with survival analysis to identify risk factors of mortality in the ICU. Results: The mean age of the patients was 71.1 ± 14.1 years. The patients were predominantly male. The most common comorbidity in patients was hypertension. ICU mortality was 62.8%. Being over 60 years old, CT score > 15, acute physiology and chronic health evaluation (APACHE) II score ≥ 15, having dementia, treatment without favipiravir, base excess in blood gas analysis ≤ ­2.0, WBC > 10,000/mm3, D-dimer > 1.6 µg/mL, troponin > 24 ng/L, Na ≥ 145 mmol/L were considered to link with ICU mortality according to Kaplan­Meier curves (log-rank test, p < 0.05). The APACHE II score (HR: 1.055, 95% CI: 1.021­1.090) and chest CT score (HR: 2.411, 95% CI:1.193­4.875) were associated with ICU mortality in the cox proportional-hazard regression model adjusted for age, dementia, favipiravir treatment and troponin. Howewer, no difference was found between survivors and nonsurvivors in terms of intubation timing. Conclusions: COVID-19 patients have a high ICU admission and mortality rate. Studies in the ICU are also crucial in this respect. In our study, we investigated the ICU mortality risk factors of COVID-19 patients. We determined a predictive mortality model consisting of APACHE II score and chest CT score. It was thought that this feasible and practical model would assist in making clinical decisions.

Clinical Outcome of Patients on Ceftazidime-Avibactam and Combination Therapy in Carbapenem-resistant Enterobacteriaceae.

INTRODUCTION: Carbapenem-resistant Enterobacteriaceae (CRE) infections have a major effect on mortality as well as healthcare cost. Intensive care units (ICUs) in India, the epicenters for multidrug-resistant organisms, are facing a "postantibiotic era" because of very limited treatment options. A latest beta-lactam/beta-lactamase inhibitor ceftazidime-avibactam (CZA) new has a broad-spectrum antibacterial activity. CZA inhibits class-A and class-C beta-lactamases (as well Klebsiella pneumoniae carbapenemase (KPC)), along with some class-D carbapenems such as OXA-48-like enzymes that are seen in Enterobacteriaceae has recently become available. The current study aimed to assess and present the clinical response and patient outcome with infections due to CRE when treated with CZA alone or in combination with other drugs. MATERIALS AND METHODS: This retrospective study reviews the experience recorded and analyzed at two tertiary care centers including only adult patients with CRE infection who had received CZA alone or in combination with other antibiotics over a period between February 2019 and January 2020. RESULTS: In the period from February 2019 to January 2020, 119 culture-confirmed CRE isolates were tested for Xpert Carba-R. The predominant genetic mechanism was a combination of NDM+OXA-48 in 45/119 (37.81%). Total 40/57 patients received CZA+aztreonam alone or in combination with other drugs with an overall cure rate of 77.5% while the rest 17 received CZA alone in combination with the cure rate of 82.35%. 41/57 (71.92%) patients were in ICU. CONCLUSION: With overall mortality of 21%, these data suggest that CZA is a viable option for patients with CRE infections. To our knowledge, this is the first Indian study reporting CZA data in CRE infections. HOW TO CITE THIS ARTICLE: Nagvekar V, Shah A, Unadkat VP, Chavan A, Kohli R, Hodgar S, et al. Clinical Outcome of Patients on Ceftazidime-Avibactam and Combination Therapy in Carbapenem-resistant Enterobacteriaceae. Indian J Crit Care Med 2021;25(7):780-784.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Pandemic: Is Sequela the Bigger Threat?

How to cite this article: Rai N, Baidya DK. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Pandemic: Is Sequela the Bigger Threat? Indian J Crit Care Med 2021;25(2):245-246.

The Second- vs First-wave COVID-19: More of the Same or a Lot Worse? A Comparison of Mortality between the Two Waves in Patients Admitted to Intensive Care Units in Nine Hospitals in Western Maharashtra.

BACKGROUND: India, along with the rest of the world, faced the challenging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. The second wave in India lagged behind that in the Western world, due to different timing of seasons. There is scarce data about the differences between the two waves, for intensive care unit (ICU) patients. We present the data of 3,498 patients from 9 ICUs of western Maharashtra. MATERIALS AND METHODS: We collected prospective data of hospitalized, RT-PCR confirmed, coronavirus-2019 (COVID-19) patients, from nine tertiary centers, after institutional ethics committee (IEC) approval. Then, we segregated and analyzed the data of patients admitted to the ICU, for comorbidities, high-resolution computed tomography (HRCT) score, ventilatory support, etc. The primary outcomes were ICU and hospital mortality. We also performed multivariable analysis for predictors of ICU mortality. RESULTS: Overall, there were 3,498 ICU patients. In the first wave, 1,921 patients needed ICU admission, while in the second wave, 1,577 patients. Patients in the second wave had significantly higher ICU (26.1 vs 13.4%, p <0.001) and hospital mortality (29.9 vs 18.2%, p <0.001) and need for ventilatory support of any type. More patients received steroids during the second wave. On multivariable regression, male gender, ICU admission during the second wave, increasing HRCT score, and need for intubation and mechanical ventilation were significant predictors of ICU mortality. CONCLUSION: ICU patients admitted during the two waves were of the similar age, but there were more females, and more patients had comorbidities during the second wave. The ICU and hospital mortality were significantly higher during the second wave. HOW TO CITE THIS ARTICLE: Zirpe KG, Dixit S, Kulkarni AP, Pandit RA, Ranganathan P, Prasad S, et al. The Second- vs First-wave COVID-19: More of the Same or a Lot Worse? A Comparison of Mortality between the Two Waves in Patients Admitted to Intensive Care Units in Nine Hospitals in Western Maharashtra. Indian J Crit Care Med 2021; 25(12):1343-1348.

Quantifying the Homeostatic Model Assessment of Insulin Resistance to Predict Mortality in Multi-organ Dysfunction Syndrome.

BACKGROUND: Insulin resistance is an integral component of a multi-organ dysfunction syndrome (MODS) associated with increased mortality. We determined a cutoff value for the homeostatic model assessment of insulin resistance (HOMA-IR) during an ICU admission that could predict 28-day mortality of nondiabetic MODS patients. MATERIALS AND METHODS: In this prospective, outcome assessor blinded cohort design, we evaluated 82 such patients for fasting blood glucose (FBG)/insulin levels (FIL) during an ICU admission and followed their outcome for 28 days. The primary outcome variable was the HOMA-IR score calculated from the above variables. The statistical tool included receiver operating characteristic curve, Youden index, and correlation and regression analysis. RESULTS: Overall, 38 patients succumbed to their illness. The optimal cutoff value for HOMA-IR was ≥1.61 (area under curve: 0.684, sensitivity: 36.8%, specificity: 95.5%). The 28-day survival was significantly lower (p = 0.001) at HOMA-IR threshold ≥1.61 (odds ratio: 12.25, hazard ratio: 2.98). The mean HOMA-IR among survivors vs nonsurvivors was 0.76 ± 0.61 and 1.38 ± 1.14, respectively (p = 0.004). Except for FIL and FBG, HOMA-IR values did not correlate with any other baseline or outcome parameters (demographics, APACHE II/sequential organ failure assessment score, vasopressor needs, or ICU/hospital stay). On comparing these parameters across the HOMA-IR threshold, only FIL and the hospital stay varied significantly. Most of the outcome parameters, however, varied significantly among nonsurvivors vs survivors. CONCLUSION: The HOMA-IR is a significant predictor of mortality in MODS. Its cutoff value may assist in determining a reference range for critically ill patients. Its routine use in the light of other disease severity scores may serve in their better prognostication. HOW TO CITE THIS ARTICLE: Sama S, Jain G, Kant R, Bhadoria AS, Naithani M, Kumar A. Quantifying the Homeostatic Model Assessment of Insulin Resistance to Predict Mortality in Multi-organ Dysfunction Syndrome. Indian J Crit Care Med 2021;25(12):1364-1369.

Epidemiology of Intensive Care Unit-acquired Infections in a Tertiary Care Hospital of North India.

BACKGROUND: The majority of nosocomial infections in the hospital setting are found in intensive care units (ICUs). The present study was undertaken to determine the incidence, risk factors, causative microorganisms, and outcome of various ICU-acquired infections. MATERIALS AND METHODS: The patients admitted to the ICU of a teaching hospital in North India were prospectively studied. Detailed history, clinical examination, acute physiology and chronic health evaluation score II, simplified acute physiology score II, sequential organ failure assessment score, and baseline investigations were recorded. Patients were assessed daily till 14th day for nosocomial infection as per Centers for Disease Control and Prevention (CDC) guidelines and were followed till death or discharge. Incidence, risk factors, and outcome parameters were calculated using Student t-test, Chi-square test, and stepwise multivariate logistic regression model. RESULTS: The overall incidence rate of ICU infections was 27.9%. The most common ICU-acquired infection was ventilator-associated pneumonia followed by catheter-related bloodstream infection and catheter-associated urinary tract infection. Pseudomonas aeruginosa, Acinetobacter baumannii, and Klebsiella pneumoniae were implicated in most of the infections. ICU length of stay (LOS) >7 days, neurological dysfunction, endotracheal intubation, ischemic heart disease, and use of antacids/H2 blockers were significantly associated with ICU-acquired infections. The mortality rate was 32.8 and 28.8% in patients with and without ICU infections, respectively (p = 0.531). The ICU LOS (19.23 ± 12.79 days) was significantly higher in the ICU infections group (p <0.001). CONCLUSION: Ventilator-associated pneumonia was the most common nosocomial infection in our study. Gram-negative microorganisms were the predominant causative agents for various ICU-acquired infections. Mortality was not found to be affected but ICU LOS was significantly prolonged as a consequence of the development of ICU-acquired infection. HOW TO CITE THIS ARTICLE: Kumar A, Chaudhry D, Goel N, Tanwar S. Epidemiology of Intensive Care Unit-acquired Infections in a Tertiary Care Hospital of North India. Indian J Crit Care Med 2021;25(12):1427-1433.

INDICAPS II: A Bird's Eye View of the Indian Intensive Care Landscape.

How to cite this article: Mani RK. INDICAPS II: A Bird's Eye View of the Indian Intensive Care Landscape. Indian J Crit Care Med 2021; 25(10):1087-1088.