Effect of the Angiotensin-Converting Enzyme (ACE) (I/D) Polymorphism in COVID-19 Patients and Their Healthy Contacts.

Introduction The quest to understand the pathophysiology behind the deleterious effects of the coronavirus disease 2019 (COVID-19) outbreak took a turn when involvement of the angiotensin converting enzyme (ACE) receptors in different organs, especially the lungs, could explain all the clinical manifestations and adverse events in patients. The I/D polymorphism in the ACE gene, having been attributed in various studies, was also seen to have an effect in this pandemic. Present study aimed to analyze the effect of this I/D mutation in COVID-19 patients and in their healthy contacts. Methods Patients with past history of COVID-19 infection and their healthy contacts were enrolled in the study after obtaining ethical clearance and informed consent. The polymorphism was studied by real-time polymerase chain reaction (PCR). Data was analyzed in SPSS version 20 (IBM Corp., Armonk, NY, USA). p value less than 0.05 was taken as significant. Results The allelic distribution followed the Hardy-Weinberg equilibrium, with the wild 'D' allele being dominant in the population. Between the case and controls, the mutant 'I' allele was observed more in the controls, and the association was statistically significant. Conclusion From the results of the present study, it could be concluded that while the wild 'D' allele led to higher chances of being affected with COVID-19, the polymorphism to 'I' allele was relatively protective in nature.

An Assessment of the Profile and Predictors of Outcomes in COVID-19 Patients Hospitalized in a Tertiary Care Institute in Central India.

Background Coronavirus disease 2019 (COVID-19) is the largest pandemic that has affected people around the globe. Various researches have been conducted worldwide, but there is a scarcity of data from Central India on the relationship between several risk factors for infection and mortality. Our study assessed the predictors and patient profiles of those with COVID-19, which will aid in prioritizing patient treatment and preventive measures. Methods A retrospective study was done between March and December 2020. The study included 5,552 COVID-19 patients admitted to the All India Institute of Medical Sciences (AIIMS), Raipur. A validated questionnaire form provided by the WHO was used. Data for multiple clinical and nonclinical parameters were collected, and analysis was done using SPSS version 26 (IBM Corp., Armonk, NY, USA) and STATA version 12 (StataCorp LLC, College Station, TX, USA). Mortality and risk assessment of patients was done using multivariate logistic regression. Result In our study cohort of 5,552 COVID-19 patients, the median age was found to be 47 years (interquartile range (IQR): 31-60 years; range: 14-100 years), and 3,557 (64%) were male. Predominantly, patients presented with fever (41.30%), cough (40.20%), and dyspnea (29.29%). The major comorbidities were hypertension (29.70%), diabetes (25.40%), and chronic cardiac disease (5.79%). The common complications were liver dysfunction (26.83%), viral pneumonitis (23.66%), acute renal injury (15.25%), and acute respiratory distress syndrome (ARDS) (13.41%). In multivariate analysis, age (more than 40 years) (odds ratio (OR): 2.63; 95% confidence interval (CI): 1.531-4.512; p<0.001), diabetes (OR: 1.61; 95% CI: 1.088-2.399; p=0.017), obesity (OR: 6.88; 95% CI: 2.188-12.153; p=0.004), leukocytosis (OR: 1.74; 95% CI: 1.422-2.422; p<0.001), lymphocytopenia (OR: 2.54, 95% CI: 1.718-3.826; p<0.001), thrombocytopenia (OR: 1.15; 95% CI: 1.777-8.700; p=0.001), and ferritin concentration > 1,000 ng/mL (OR: 4.67; 95% CI: 1.991-10.975; p<0.001) were the independent predictors of mortality among COVID-19 patients. Conclusion The leading comorbidities in our study were hypertension, followed by diabetes. Patients who were 40 years or older, obese patients, and diabetic patients have a higher mortality risk. The poor prognostic predictors in COVID-19 patients were high ferritin levels (>1,000 ng/mL), leukocytosis, lymphocytopenia, and thrombocytopenia.

Predictors of Mortality among Patients Hospitalized with COVID-19 during the First Wave in India: A Multisite Case-Control Study.

Severe acute respiratory syndrome coronavirus 2 disease (COVID-19) has caused more than 6 million deaths globally. Understanding predictors of mortality will help in prioritizing patient care and preventive approaches. This was a multicentric, unmatched, hospital-based case-control study conducted in nine teaching hospitals in India. Cases were microbiologically confirmed COVID-19 patients who died in the hospital during the period of study and controls were microbiologically confirmed COVID-19 patients who were discharged from the same hospital after recovery. Cases were recruited sequentially from March 2020 until December-March 2021. All information regarding cases and controls was extracted retrospectively from the medical records of patients by trained physicians. Univariable and multivariable logistic regression was done to assess the association between various predictor variables and deaths due to COVID-19. A total of 2,431 patients (1,137 cases and 1,294 controls) were included in the study. The mean age of patients was 52.8 years (SD: 16.5 years), and 32.1% were females. Breathlessness was the most common symptom at the time of admission (53.2%). Increasing age (adjusted odds ratio [aOR]: 46-59 years, 3.4 [95% CI: 1.5-7.7]; 60-74 years, 4.1 [95% CI: 1.7-9.5]; and ≥ 75 years, 11.0 [95% CI: 4.0-30.6]); preexisting diabetes mellitus (aOR: 1.9 [95% CI: 1.2-2.9]); malignancy (aOR: 3.1 [95% CI: 1.3-7.8]); pulmonary tuberculosis (aOR: 3.3 [95% CI: 1.2-8.8]); breathlessness at the time of admission (aOR: 2.2 [95% CI: 1.4-3.5]); high quick Sequential Organ Failure Assessment score at the time of admission (aOR: 5.6 [95% CI: 2.7-11.4]); and oxygen saturation < 94% at the time of admission (aOR: 2.5 [95% CI: 1.6-3.9]) were associated with mortality due to COVID-19. These results can be used to prioritize patients who are at increased risk of death and to rationalize therapy to reduce mortality due to COVID-19.

Multidisciplinary Management of COVID-Associated Mucormycosis Syndemic in India.

The study aimed to determine clinical presentation, contributing factors, medical and surgical management, and outcome of patients with coronavirus disease 2019 (COVID-19)-associated mucormycosis (CAM). A cross-sectional, single-center study was conducted on patients receiving multidisciplinary treatment for mucormycosis following the second wave of COVID-19 pandemic from April to June 2021 in India. Clinicoepidemiological factors were analyzed, 30-day overall survival and disease-specific survival were determined, and t-test was used to determine the statistical significance. A total of 215 patients were included in the study, the cases were stratified into sino-nasal 95 (44.2%), sino-naso-orbital 32 (14.9%), sino-naso-palatal 55 (25.6%), sino-naso-cerebral 12 (5.6%), sino-naso-orbito-cerebral 16 (7.4%), and sino-naso-orbito-palato-cerebral 5 (2.3%) based on their presentation. A multidisciplinary team treated patients by surgical wound debridement and medical therapy with broad-spectrum antibiotics and amphotericin B. Across all disease stages, cumulative 30-day disease-specific survival is 94% (p < 0.001, intergroup comparison, Breslow (generalized Wilcoxon) CI 95%) and overall 30-day survival is 87.9% (p < 0.001, intergroup comparison, Breslow (generalized Wilcoxon) CI 95%) (censored). Early identification, triaging, and proper multidisciplinary team management with systemic antifungals, surgical debridement, and control of comorbidities lead to desirable outcomes in COVID-associated mucormycosis. The patients with intracranial involvement have a higher chance of mortality compared to the other group. Supplementary Information: The online version contains supplementary material available at 10.1007/s12262-021-03134-0.

A Delphi consensus statement for the management of post-COVID interstitial lung disease.

INTRODUCTION: As millions of people worldwide recover from COVID-19, a substantial proportion continue to have persistent symptoms, pulmonary function abnormalities, and radiological findings suggestive of post-COVID interstitial lung disease (ILD). To date, there is limited scientific evidence on the management of post-COVID ILD, necessitating a consensus-based approach. AREAS COVERED: A panel of experts in pulmonology and thoracic radiology was constituted. Key questions regarding the management of post-COVID ILD were identified. A search was performed on PubMed and EMBASE and updated till 1 March 2022. The relevant literature regarding the epidemiology, pathophysiology, diagnosis and treatment of post-COVID ILD was summarized. Subsequently, suggestions regarding the management of these patients were framed, and a consensus was obtained using the Delphi approach. Those suggestions which were approved by over 80% of the panelists were accepted. The final document was approved by all panel members. EXPERT OPINION: Dedicated facilities should be established for the care of patients with post-COVID ILD. Symptom screening, pulmonary function testing, and thoracic imaging have a role in the diagnosis. The pharmacologic and non-pharmacologic options for the management of post-COVID ILD are discussed. Further research into the pathophysiology and management of post-COVID ILD will improve our understanding of this condition.

An Assessment of the Profile and Predictors of Outcomes in COVID-19 Patients Hospitalized in a Tertiary Care Institute in Central India

Background Coronavirus disease 2019 (COVID-19) is the largest pandemic that has affected people around the globe. Various researches have been conducted worldwide, but there is a scarcity of data from Central India on the relationship between several risk factors for infection and mortality. Our study assessed the predictors and patient profiles of those with COVID-19, which will aid in prioritizing patient treatment and preventive measures. Methods A retrospective study was done between March and December 2020. The study included 5,552 COVID-19 patients admitted to the All India Institute of Medical Sciences (AIIMS), Raipur. A validated questionnaire form provided by the WHO was used. Data for multiple clinical and nonclinical parameters were collected, and analysis was done using SPSS version 26 (IBM Corp., Armonk, NY, USA) and STATA version 12 (StataCorp LLC, College Station, TX, USA). Mortality and risk assessment of patients was done using multivariate logistic regression. Result In our study cohort of 5,552 COVID-19 patients, the median age was found to be 47 years (interquartile range (IQR): 31-60 years;range: 14-100 years), and 3,557 (64%) were male. Predominantly, patients presented with fever (41.30%), cough (40.20%), and dyspnea (29.29%). The major comorbidities were hypertension (29.70%), diabetes (25.40%), and chronic cardiac disease (5.79%). The common complications were liver dysfunction (26.83%), viral pneumonitis (23.66%), acute renal injury (15.25%), and acute respiratory distress syndrome (ARDS) (13.41%). In multivariate analysis, age (more than 40 years) (odds ratio (OR): 2.63;95% confidence interval (CI): 1.531-4.512;p<0.001), diabetes (OR: 1.61;95% CI: 1.088-2.399;p=0.017), obesity (OR: 6.88;95% CI: 2.188-12.153;p=0.004), leukocytosis (OR: 1.74;95% CI: 1.422-2.422;p<0.001), lymphocytopenia (OR: 2.54, 95% CI: 1.718-3.826;p<0.001), thrombocytopenia (OR: 1.15;95% CI: 1.777-8.700;p=0.001), and ferritin concentration > 1,000 ng/mL (OR: 4.67;95% CI: 1.991-10.975;p<0.001) were the independent predictors of mortality among COVID-19 patients. Conclusion The leading comorbidities in our study were hypertension, followed by diabetes. Patients who were 40 years or older, obese patients, and diabetic patients have a higher mortality risk. The poor prognostic predictors in COVID-19 patients were high ferritin levels (>1,000 ng/mL), leukocytosis, lymphocytopenia, and thrombocytopenia.

Influence of laboratory biomarkers on inflammatory indices for assessing severity progression in COVID-19 cases.

Background and Objective: This study explored the role of various laboratory biomarkers on inflammatory indices for predicting disease progression toward severity in COVID-19 patients. Methods: This retrospective study was conducted on 1233 adults confirmed for COVID-19. The participants were grouped undermild, moderate, and severe grade disease. Serum bio-inflammatory index (SBII) and systemic inflammatory index (SII) were calculated and correlated with disease severity. The study variables, including clinical details and laboratory variables, were analyzed for impact on the inflammatory indices and severity status using a sequential multiple regression model to determine the predictors for mortality. Receiver operating characteristics defined the cut-off values for severity. Results: Among the study population, 56.2%, 20.7%, and 23.1% were categorized as mild, moderate, and severe COVID-19 cases. Diabetes with hypertension was the most prevalent comorbid condition. The odds for males to have the severe form of the disease was 1.6 times (95% CI = 1.18-2.18, P = 0.002). The median (inter-quartile-range) of SBII was 549 (387.84-741.34) and SII was 2097.6 (1113.9-4153.73) in severe cases. Serum urea, electrolytes, gamma-glutamyl transferase, red-cell distribution width-to-hematocrit ratio, monocytopenia, and eosinopenia exhibited a significant influence on the SpO2, SBII, and SII. Both SBII (r = -0.582, P < 0.001) and SII (r = -0.52, P < 0.001) strongly correlated inversely with SpO2 values [Figures 3a and 3b]. More than 80% of individuals admitted with severe grade COVID-19 had values of more than 50th percentile of SBII and SII. The sensitivity and specificity of SBII at 343.67 for severity were 81.4% and 70.1%, respectively. SII exhibited 77.2% sensitivity and 70.8% specificity at 998.72. Conclusion: Serial monitoring of the routinely available biomarkers would provide considerable input regarding inflammatory status and severity progression in COVID-19.

Early Biochemical Markers in Predicting the Clinical Outcome of COVID-19 Patients Admitted in Tertiary Care Hospital.

Introduction An array of routinely accessible serum biomarkers was assessed to explore their overall impact on severity and mortality in coronavirus disease 2019. Materials and Methods A retrospective analysis of 1,233 adults was conducted. The study groups comprised 127 nonsurvivors and 1,106 survivors. Data for demographic details, clinical presentations, and laboratory reports were recorded from the medical record section. The predictors were analyzed for their influence on mortality. Results The mean (+ standard deviation) age of the patients in the nonsurvivor group was 58.8 (13.8) years. The mean age (56.4 years) was highest in severe grade patients. The odds ratio for death was 2.72 times for patients above the age of 40 years. About 46% of nonsurvivors died within 5 days of admission. Males were found to be more prone to death than females by a factor of 1.36. Serum urea depicted highest sensitivity (85%) for nonsurvival at 52.5 mg/dL. Serum albumin (3.23 g/dL), albumin-to-globulin ratio (0.97), and C-reactive protein-to albumin ratio (CAR) (2.08) showed a sensitivity of more than 70% for mortality outcomes. The high hazard ratio (HR) for deceased patients with hyperkalemia was 2.419 (95% confidence interval [CI] = 1.96-2.99; p < 0.001). The risk for nonsurvival was increased with elevated serum creatinine by 15.6% and uric acid by 21.7% ( p < 0.001). The HR for hypoalbuminemia was 0.254 (95% CI: 0.196-0.33; p < 0.001) and CAR was 1.319 (95% CI: 1.246-1.397; p < 0.001). Saturation of oxygen ( p < 0.001), lactate dehydrogenase ( p = 0.006), ferritin ( p = 0.004), hyperuricemia ( p = 0.027), hyperkalemia ( p < 0.001), hypoalbuminemia ( p = 0.002), and high CAR values (0.031) served as potential predictors for mortality. Conclusion Adjusting for all the predictor variables, serum uric acid, potassium, albumin, and CAR values at the time of admission were affirmed as the potential biomarkers for mortality.