Understanding of the basis for severity and fatal outcome of SARS-CoV-2 infection is of paramount importance for developing therapeutic options and identification of prognostic markers. So far, accumulation of neutrophils and increased levels of pro-inflammatory cytokines are associated with disease severity in COVID-19 patients. In this study, we aimed to compare circulatory levels of neutrophil secretory proteins, alpha-defensins (DEFA1), calprotectin (S100A8/A9), and myeloperoxidase (MPO) in COVID-19 patients with different clinical presentations. We studied 19 healthy subjects, 63 COVID-19 patients with mild (n=32) and severe (n=31) disease, 23 asymptomatic individuals identified through contact tracing programme and 23 recovering patients (1-4 months post-disease). At the time of disease presentation, serum levels of DEFA1 were significantly higher in patients with mild (mean230 ± 17, p<0.0001) and severe (mean452 ± 46, p<0.0001) disease respectively in comparison to healthy subjects (mean113 ± 11). S100A8/A9 proteins were significantly higher in COVID-19 patients (p<0.0001) irrespective of disease severity. The levels of DEFA1, S100A8/A9 and MPO reduced to normal in recovering patients and comparable to healthy subjects. Surprisingly, DEFA1 levels were higher in severe than mild patients in first week of onset of disease (p=0.004). Odds-ratio analysis showed that DEFA1 could act as potential biomarker in predicting disease severity (OR=11.34). In addition, levels of DEFA1 and S100A8/A9 were significantly higher in patients with fatal outcome (p=0.004 and p=0.03) respectively. The rise in DEFA1 levels was independent of secondary infections. In conclusion, our data suggest that induction of elevated levels of alpha-defensins and S100A8/A9 is associated with poor disease outcome in COVID-19 patients.
Tracheostomy in patients with COVID-19 requires significant decision making and procedural planning. Use of tracheostomy can facilitate weaning from ventilation and potentially increase the availability of much needed intensive care unit (ICU) beds, however this being a high aerosol generating procedure it does put the health care worker to risk of transmission. Here we present our experience and protocols for performing tracheostomy in COVID-19 positive patients. Eleven tracheostomies were performed in COIVD-19 patients over a period of 2 months (May-June 2020) at this tertiary care hospital dedicated to manage COVID patients. All patients underwent open surgical tracheostomy, the specific indication, preoperative protocols, surgical steps and precautions taken have been discussed. Tracheostomy was done not before 10 days after initiation of mechanical ventilation. Patient's cardiovascular vitals should show recovery with some spontaneous effort. There should be reduction in need for FiO 2 and ventilator requirements. Of total 11 tracheostomies performed only one patient had post procedure bleeding which was controlled conservatively. We have summarized our experience in performing tracheostomies in 11 such patients. Our guidelines and recommendations on tracheostomy during the COVID-19 pandemic are presented in this study. We suggest tracheostomies to be done after 10 days of intubation with precautions and given indications with the idea of early weaning off of patient from ventilator and more availability of ICU beds which is already overwhelmed by patient load.
A bstract Introduction Intensive care unit (ICU) admission is required for approximately 25% of patients affected with coronavirus disease-19 (COVID-19) and imposes a high economic burden on patients in resource-limited settings. Method We conducted a retrospective direct medical care cost analysis of COVID-19 patients requiring ICU admission after obtaining the Institutional Ethics Committee approval. Data were obtained from the records of patients admitted to the COVID-19 ICU of a tertiary care trust teaching hospital from June 2020 to December 2020. Direct costs were analyzed and correlated with various demographic variables and clinical outcomes. Results A total of 176 patients were included (males—76%). The median direct medical cost for a median stay of 13 days was INR 202248.5 ($ 2742.91). Hospital drugs and disposables accounted for 20% of the total cost followed by bed charges (19%), equipment charges (17%), biosafety protective gear (15.5%), pathological and radiological tests (15%), clinical management (7.6%), and biomedical waste management (1.6%). Government schemes accounted for 79% of medical claims followed by directly paying patients (12.5%) and private insurance (8.5%). The cost was significantly higher in patients with diabetes mellitus and sepsis and in those requiring mechanical ventilation (MV) ( p <0.05). Shorter lead time to hospital admission and lesser length of hospital stay were associated with significant lower direct cost. Conclusion Direct medical care cost is substantial for COVID-19 patients requiring ICU admission. This cost is significantly associated with increased ICU and hospital stay, longer lead time to admission, diabetes mellitus, sepsis, and those who need high-flow nasal cannula (HFNC), noninvasive ventilation (NIV), and MV. How to cite this article Reddy KN, Shah J, Iyer S, Chowdhury M, Yerrapalem N, Pasalkar N, et al . Direct Medical Cost Analysis of Indian COVID-19 Patients Requiring Critical Care Admission. Indian J Crit Care Med 2021;25(10):1120–1125.
Background: Code Blue systems are communication systems that ensure the most rapid and effective resuscitation of a patient in respiratory or cardiac arrest. Code blue was established in Bharati Hospital and Research Centre in Sept 2011 in order to reduce morbidity and mortality in wards. The aim of the study was to evaluate the current code blue system and suggest possible interventions to strengthen the system.Methods: It was retrospective observational descriptive study. The study population included all consecutive patients above the age of 18 years for whom code blue had been activated. Data was collected using code blue audit forms. The data was analysed using SPSS (Statistical Package for social sciences) software.Results: A total of 260 calls were made using the blue code system between September 2011 to December 2012. The most common place for blue code activation was casualty. The wards were next, followed by dialysis unit and OPD. The indications for code blue team activation were cardio-respiratory arrest (CRA) (88 patients, 33.84%), change in mental status (52 patients, 20%), road traffic accidents RTA (21, 8.07%), convulsions (29 patients 11.15%), chest pain (19 patients, 8.46%), breathlessness (18 patients,6.92%) and worry of staff about the patient (17 patients, 6.53%), presyncope (10 patients, 3.84%), and others (6 patients, 2.30%). The average response time was 1.58±0.96 minutes in our study. Survival rate was more in medical emergency group 46.15% than in CRA group 31.61%. Initial success rate was 35.2% and a final success rate was 34.6%.Conclusions: Establishment of code blue team in the hospital enabled us to provide timely resuscitation for patients who had “out of ICU” CRA. Further study is needed to establish the overall effectiveness and the optimal implementation of code blue teams. The increasing use of an existing service to review patients meeting blue code criteria requires repeated education and a periodic assessment of site-specific obstacles to utilization.
Introduction: In early stage of disease of Coronavirus Disease 2019 (COVID-19) infection chest Computed Tomography (CT) imaging is considered as the most effective method for detecting lung abnormalities. A Brixia Chest X-ray (CXR) scoring system which uses an 18-point severity scale to grade lung abnormalities due to COVID-19 was developed to improve the risk stratification for infected patients. Aim: To ascertain the validity of Brixia scoring system and to measure the outcome in COVID-19 patients. Materials and Methods: A retrospective study was conducted from 1st April 2020 to 31st July 2020, at a tertiary care hospital in India. Baseline CXR of COVID-19 patients were scored based on Brixia scoring system. The lungs were divided into six equal zones. Subsequently, scores (from 0-3) were assigned to each zone, based on lung abnormalities. A group comparison was implemented using Chi-Square test for categorical variables. Whereas an independent t-test was applied for continuous variables that followed normal distribution. Results: The study included 130 patients. The mean age was 57.09±13.73 years, 70.8% patients included were males. Out of 130 patients, 79 patients died. Among patients who died the mean CXR score was calculated to be 12.13±2.50. The mean CXR score was calculated to be 11.18±2.30 in patients who recovered and got discharged. During the process of comparison of CXR scores with the outcomes, the t-value came out to be 2.20 and the resulting p-value was 0.03 (statistically significant). Conclusion: Brixia score more than 12 was associated with increased mortality due to COVID-19, with p-value of 0.03.
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