E-ISSN 2231-3206 | ISSN 2320-4672
 

Original Research 


Predict the hospitalization in COVID-19: Magic is in the air

Jyoti Prakash Sahoo, Siddhartha Goutam, Muktikanta Parida, Satyabrata Sahoo.

Abstract
Background: Although pathogenesis and pattern of disease are still not completely understood, tactical management of overcrowding of hospitals and rational usage of resources is the need of the hour.

Aims and Objectives: The study objectives were as follows: Finding of correlation between various attributes of COVID; evaluation of the association of common characteristics with hospital stay; prediction of cooccurrence of different symptoms; calculation of odds ratio of prolonged hospitalization due to various symptoms; and estimation of the rate of prolonged hospitalization due to different symptoms and comorbidities.

Materials and Methods: Retrospective data of 6918 COVID-19-positive cases from SCB Medical College and Hospital, India, were obtained from the hospital records from March 2020 to January 2021. The patients’ age, gender, symptoms, and comorbidities were analyzed against their hospital stay using R software (version 4.0.2).

Results: Elderly patients (>65 years) had a higher rate (91.22%) of prolonged hospital stay as compared to others (47.61%). Frequently observed symptoms (in decreasing order) were fever (73.93%), cough (67.52%), myalgia (62.11%), dyspnea (49.59%), dizziness (47.38%), and anosmia (44.10%). The risk of prolonged hospitalization was highest with dyspnea [odds ratio: 2.29 (95% confidence interval: 2.07–2.52)], followed by diarrhea [odds ratio [OR] 1.98 (confidence interval [CI] 1.77–2.21)], fever [OR 1.89 (CI 1.69–2.10)], anosmia [OR 1.86 (CI 1.69–2.05)], and dizziness [OR 1.46 (CI 1.32–1.60)]. The rate of hospitalization for more than 7 days was highest with diabetes (86.80%) followed by respiratory illnesses (71.85%) and hypertension (71.28%).

Conclusion: These findings can help manage patients based on their symptoms and comorbidities before admission.

Key words: Pandemics; Dyspnea; Fever; COVID Hospitalization; Health-care System


 
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How to Cite this Article
Pubmed Style

Sahoo JP, Goutam S, Parida M, Sahoo S. Predict the hospitalization in COVID-19: Magic is in the air. doi:10.5455/njppp.2022.12.09344202128092021


Web Style

Sahoo JP, Goutam S, Parida M, Sahoo S. Predict the hospitalization in COVID-19: Magic is in the air. http://www.njppp.com/?mno=126375 [Access: November 30, 2021]. doi:10.5455/njppp.2022.12.09344202128092021


AMA (American Medical Association) Style

Sahoo JP, Goutam S, Parida M, Sahoo S. Predict the hospitalization in COVID-19: Magic is in the air. doi:10.5455/njppp.2022.12.09344202128092021



Vancouver/ICMJE Style

Sahoo JP, Goutam S, Parida M, Sahoo S. Predict the hospitalization in COVID-19: Magic is in the air. doi:10.5455/njppp.2022.12.09344202128092021



Harvard Style

Sahoo, J. P., Goutam, . S., Parida, . M. & Sahoo, . S. (2022) Predict the hospitalization in COVID-19: Magic is in the air. doi:10.5455/njppp.2022.12.09344202128092021



Turabian Style

Sahoo, Jyoti Prakash, Siddhartha Goutam, Muktikanta Parida, and Satyabrata Sahoo. 2022. Predict the hospitalization in COVID-19: Magic is in the air. doi:10.5455/njppp.2022.12.09344202128092021



Chicago Style

Sahoo, Jyoti Prakash, Siddhartha Goutam, Muktikanta Parida, and Satyabrata Sahoo. "Predict the hospitalization in COVID-19: Magic is in the air." doi:10.5455/njppp.2022.12.09344202128092021



MLA (The Modern Language Association) Style

Sahoo, Jyoti Prakash, Siddhartha Goutam, Muktikanta Parida, and Satyabrata Sahoo. "Predict the hospitalization in COVID-19: Magic is in the air." doi:10.5455/njppp.2022.12.09344202128092021



APA (American Psychological Association) Style

Sahoo, J. P., Goutam, . S., Parida, . M. & Sahoo, . S. (2022) Predict the hospitalization in COVID-19: Magic is in the air. doi:10.5455/njppp.2022.12.09344202128092021