Risk Factors of Severity and Mortality Among COVID-19 Patients: A Prospective Observational Study From a Tertiary Care Center.

Introduction The COVID-19 pandemic has been a major public health threat for the past three years. The RNA virus has been constantly evolving, changing the manifestations and progression of the disease. Some factors which impact the progression to severe COVID-19 or mortality include comorbidities such as diabetes mellitus, hypertension, and obesity. In this study, we followed a cohort of patients to evaluate the risk factors leading to severe manifestations and mortality from COVID-19. Methodology We conducted a prospective observational study of 589 COVID-19 patients to assess the risk factors associated with the severity and mortality of the disease. Results In our cohort, 83.5% were male, with a median age (p25, p75) of 39.71 (30-48) years. The most common comorbidities included diabetes mellitus (7.8%) and hypertension (7.9%). About 41.7% had an asymptomatic disease, and of the symptomatic, 45% were mild, 6% moderate, and 7% severe. The mortality rate was 4.1%. Risk factors for severity included breathlessness (p=0.02), leukocytosis (p=0.02), and deranged renal function (p=0.04). Risk factors for mortality included older age (p=0.04), anemia (p=0.02), and leukocytosis (p=0.02). Conclusions COVID-19 commonly leads to asymptomatic or mild illness. The major factors we found that were associated with severity include breathlessness at presentation, leukocytosis, and deranged renal functions. The factors associated with mortality include older age, anemia, and leukocytosis.

Post COVID-19 sequelae: A prospective observational study from Northern India.

Post COVID-19 sequelae are a constellation of symptoms often reported after recovering from COVID-19. There is a need to better understand the clinical spectrum and long-term course of this clinical entity. The aim of this study is to describe the clinical features and risk factors of post COVID-19 sequelae in the North Indian population. This prospective observational study was conducted at a tertiary healthcare centre in Northern India between October 2020 and February 2021. Patients aged >18 years with laboratory-confirmed COVID-19 were recruited after at least two weeks of diagnosis, and details were captured. A total of 1234 patients were recruited and followed up for a median duration of 91 days (IQR: 45-181 days). Among them, 495 (40.1%) had persistent symptoms post-discharge or recovery. In 223 (18.1%) patients, the symptoms resolved within four weeks; 150 (12.1%) patients had symptoms till 12 weeks, and 122 (9.9%) patients had symptoms beyond 12 weeks of diagnosis/symptom-onset of COVID-19. Most common symptoms included myalgia (10.9%), fatigue (5.5%), shortness of breath (6.1%), cough (2.1%), insomnia (1.4%), mood disturbances (0.48%) and anxiety (0.6%). Patients who were hospitalized were more likely to report fatigue as a feature of long COVID. Hypothyroidism (OR: 4.13, 95% CI: 2.2-7.6, p-value < 0.001) and hypoxia (SpO2 ≤ 93%) (OR: 1.7, 95% CI: 1.1-2.4, p-value 0.012) were identified as risk factors for long COVID sequelae. In conclusion, long COVID symptoms were common (22%), and 9.9% had the post COVID-19 syndrome. Myalgias, fatigue and dyspnoea were common symptoms. Patients with hypothyroidism and hypoxia during acute illness were at higher risk of long COVID.

Mild COVID-19 infection-predicting symptomatic phase and outcome: A study from AIIMS, New Delhi.

CONTEXT: Comprehensive management of mild COVID infection calls for better understanding of symptomatology in these group of patients as well as early identification and close monitoring of patients at risk, data on which is limited. AIM: To study association between inflammatory markers and clinical presentation with progression of disease and the duration of resolution of symptoms. SETTINGS AND DESIGN: This is a retrospective study that has been conducted at a designated COVID -19 medical ward at AIIMS, New Delhi. METHODS AND MATERIAL: Fifty healthcare workers and their dependents who were admitted with asymptomatic and mild COVID-19 infection were included. Their records were retrospectively reviewed, entered into a predesigned proforma and analyzed. RESULTS: A total of 50 participants were included in the study of which 70% were healthcare workers. The patients were admitted with mild COVID illness out of which 22 (44%) were males. Most common symptom at presentation was fever (72%). Among patients who had mild disease versus those who progressed to moderate illness (n = 3), the patients with moderate illness were older [mean (SD): 57.33 (10.21) vs. 36.13 (14.05); P = 0.014] and had a longer duration of hospital stay [17 (1.41) days vs. 11.20 (3.86) days; P = 0.04]. Inflammatory markers, C-Reactive Protein (CRP) [2.46 vs. 0.20 (P = 0.024)], and Ferritin [306.15 vs. 72.53 (P = 0.023)] were higher in patients with moderate illness. There is also a significant correlation between the number of days taken for symptoms to resolve with Serum Ferritin (P = 0.007), CRP (P = 0.0256), and neutrophil lymphocyte ratio (NLR) (P = 0.044). CONCLUSIONS: Acute phase reactants/Inflammatory markers serve as good indicators of time taken to resolution of symptoms in acute COVID infection. NLR is a simple and inexpensive method to provide insight into symptomatic phase. These may be utility tools for primary care physician in the management in periphery and timely decision.

Risk factors and outcome among COVID-19 exposed and quarantined healthcare workers: A study on the status of existing practices of standard precautions.

CONTEXT: Health care workers (HCWs) are at high risk of COVID-19 infection but data on the risk factors for exposure and infection rate among Indian HCWs are limited. AIMS: Our study aims to identify the risk factors and behavior of HCWs which make them high risk for COVID-19 infection and the infection rate among them. SETTINGS AND DESIGN: This is a retrospective study conducted at All India Institute of Medical Sciences, New Delhi. METHODS AND MATERIAL: Fifty HCWs quarantined at our institute in April and May 2020 following exposure to confirmed or suspected COVID-19 cases, or due to development of Influenza-Like Illness (ILI) were included. Data was collected from medical records in a predesigned proforma and analyzed. RESULTS: Thirty-eight (76%) of the 50 quarantined HCWs had high-risk exposure and there was a significant breach in personal protective measures. N-95 masks were worn by 59.6%, gloves by 61.7%, and goggles or face shields by 2%. Exposures were more common in non-COVID areas of the hospital. Hydroxychloroquine pre-exposure prophylaxis was taken by 7 (14%). 3 (6%) were confirmed to be COVID-19 positive during the quarantine period. CONCLUSIONS: Our study has shown leniency among HCWs in adhering to infection control and personal protective measures resulting in an increased quarantine and infection rate and loss of manpower. The safety of our HCWs must be given paramount importance during this pandemic and should be ensured by educating them about infection control, and persistently reinforcing and strictly adhering to standard precautions.

Diagnostic accuracy of non-contact infrared thermometers and thermal scanners: a systematic review and meta-analysis.

Infrared thermal screening, via the use of handheld non-contact infrared thermometers (NCITs) and thermal scanners, has been widely implemented all over the world. We performed a systematic review and meta-analysis to investigate its diagnostic accuracy for the detection of fever. We searched PubMed, Embase, the Cochrane Library, medRxiv, bioRxiv, ClinicalTrials.gov, COVID-19 Open Research Dataset, COVID-19 research database, Epistemonikos, EPPI-Centre, World Health Organization International Clinical Trials Registry Platform, Scopus and Web of Science databases for studies where a non-contact infrared device was used to detect fever against a reference standard of conventional thermometers. Forest plots and Hierarchical Summary Receiver Operating Characteristics curves were used to describe the pooled summary estimates of sensitivity, specificity and diagnostic odds ratio. From a total of 1063 results, 30 studies were included in the qualitative synthesis, of which 19 were included in the meta-analysis. The pooled sensitivity and specificity were 0.808 (95%CI 0.656-0.903) and 0.920 (95%CI 0.769-0.975), respectively, for the NCITs (using forehead as the site of measurement), and 0.818 (95%CI 0.758-0.866) and 0.923 (95%CI 0.823-0.969), respectively, for thermal scanners. The sensitivity of NCITs increased on use of rectal temperature as the reference. The sensitivity of thermal scanners decreased in a disease outbreak/pandemic setting. Changes approaching statistical significance were also observed on the exclusion of neonates from the analysis. Thermal screening had a low positive predictive value, especially at the initial stage of an outbreak, whereas the negative predictive value (NPV) continued to be high even at later stages. Thermal screening has reasonable diagnostic accuracy in the detection of fever, although it may vary with changes in subject characteristics, setting, index test and the reference standard used. Thermal screening has a good NPV even during a pandemic. The policymakers must take into consideration the factors surrounding the screening strategy while forming ad-hoc guidelines.