ABSTRACT
Importance: Post-COVID-19 condition (PCC) is a complex heterogeneous disorder that has affected the lives of millions of people globally. Identification of potential risk factors to better understand who is at risk of developing PCC is important because it would allow for early and appropriate clinical support. Objective: To evaluate the demographic characteristics and comorbidities that have been found to be associated with an increased risk of developing PCC. Data sources: Medline and Embase databases were systematically searched from inception to December 5, 2022. Study Selection: The meta-analysis included all published studies that investigated the risk factors and/or predictors of PCC in adult (≥18 years) patients. Data Extraction and Synthesis: Odds ratios (ORs) for each risk factor were pooled from the selected studies. For each potential risk factor, the random-effects model was used to compare the risk of developing PCC between individuals with and without the risk factor. Data analyses were performed from December 5, 2022, to February 10, 2023. Main Outcomes and Measures: The risk factors for PCC included patient age; sex; body mass index, calculated as weight in kilograms divided by height in meters squared; smoking status; comorbidities, including anxiety and/or depression, asthma, chronic kidney disease, chronic obstructive pulmonary disease, diabetes, immunosuppression, and ischemic heart disease; previous hospitalization or ICU (intensive care unit) admission with COVID-19; and previous vaccination against COVID-19. Results: The initial search yielded 5334 records of which 255 articles underwent full-text evaluation, which identified 41 articles and a total of 860â¯783 patients that were included. The findings of the meta-analysis showed that female sex (OR, 1.56; 95% CI, 1.41-1.73), age (OR, 1.21; 95% CI, 1.11-1.33), high BMI (OR, 1.15; 95% CI, 1.08-1.23), and smoking (OR, 1.10; 95% CI, 1.07-1.13) were associated with an increased risk of developing PCC. In addition, the presence of comorbidities and previous hospitalization or ICU admission were found to be associated with high risk of PCC (OR, 2.48; 95% CI, 1.97-3.13 and OR, 2.37; 95% CI, 2.18-2.56, respectively). Patients who had been vaccinated against COVID-19 with 2 doses had a significantly lower risk of developing PCC compared with patients who were not vaccinated (OR, 0.57; 95% CI, 0.43-0.76). Conclusions and Relevance: This systematic review and meta-analysis demonstrated that certain demographic characteristics (eg, age and sex), comorbidities, and severe COVID-19 were associated with an increased risk of PCC, whereas vaccination had a protective role against developing PCC sequelae. These findings may enable a better understanding of who may develop PCC and provide additional evidence for the benefits of vaccination. Trial Registration: PROSPERO Identifier: CRD42022381002.
Subject(s)
COVID-19 , Adult , Humans , Female , COVID-19/epidemiology , Risk Factors , Comorbidity , HospitalizationABSTRACT
India experienced two of the major cyclones in the month of May and June, in the midst of the outbreak of COVID-19. Super cyclone on May 20, hit east coast of India, West Bengal and Odisha. Thereafter Cyclone Nisarga hit west coast of Maharashtra on June 2. Later on it was needed to put people in cyclone shelters in the context of COVID-19. It has become an extremely challenging task. While maintaining social distancing the cyclone shelter capacity is reduced to around 40 percent. Tropical Cyclones are one of the dearest and exceedingly baneful natural calamities happen around the world. Generally tropical cyclones are formed over warm ocean surfaces;consist of high sea surface temperature (SST), lower magnitudes of vertical wind shear and larger magnitudes of low-level relative curl of the velocity field, carioles' force along with middle tropospheric relative humidity. If we see cyclones formed in the Bay of Bengal are greater in numbers than those formed in the Arabian Sea. In order to predict the occurrence of tropical cyclone precisely, it is important to understand the various factors that act upon tropical cyclone activities. For seasonal forecasting of tropical cyclone activities we will use El Niño-Southern Oscillation (ENSO) as one of the vital predictors. The phenomenon to understand the relationship between tropical cyclone activity in various ocean basins and the El NiñoSouthern Oscillation (ENSO) has gone up during the last two decades. In this paper impact of El Niño-Southern Oscillation (ENSO) combining El Niño(warm phase of ENSO) and La Niña(cool phase of ENSO) events on frequency of Tropical Cyclone over the Bay of Bengal, the Arabian Sea and land mass of India during April to December over the period 1950-2015 has been studied based on statistical models. Aggregated frequency of tropical cyclone and ONI index in Niño 3.4 region has been used as the measures of frequency of tropical cyclone and ENSO events. It has been found that La Niña events significantly enhance tropical cyclone activity during pre-monsoon and monsoon seasons (April to September), particularly during the monsoon season (July-August-September). The amount of enhancement has been quantified.