Risk factors for disease severity among children with Covid-19: a clinical prediction model
Background: Children account for a significant proportion of COVID-19 hospitalizations, but data on the predictors of disease severity in children are limited. We aimed to identify risk factors associated with moderate/severe COVID-19 and develop a nomogram for predicting children with moderate/seve...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English English |
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Springer Nature
2023
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| Online Access: | https://eprints.ums.edu.my/id/eprint/36605/1/ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/36605/2/FULL%20TEXT.pdf |
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| author | David Chun‑Ern Ng Liew, Chuin‑Hen Tan, Kah Kee Ling Chin Grace Sieng Sing Ting Nur Fadzreena Fadzilah Lim, Hui Yi Nur Emylia Zailanalhuddin Shir Fong Tan Muhamad Akmal Afan Fatin Farihah Wan Ahmad Nasir Thayasheri Subramaniam Marlindawati Mohd Ali Mohammad Faid Abd Rashid Ong, Song Quan Ch’ng, Chin Chin |
| author_facet | David Chun‑Ern Ng Liew, Chuin‑Hen Tan, Kah Kee Ling Chin Grace Sieng Sing Ting Nur Fadzreena Fadzilah Lim, Hui Yi Nur Emylia Zailanalhuddin Shir Fong Tan Muhamad Akmal Afan Fatin Farihah Wan Ahmad Nasir Thayasheri Subramaniam Marlindawati Mohd Ali Mohammad Faid Abd Rashid Ong, Song Quan Ch’ng, Chin Chin |
| author_sort | David Chun‑Ern Ng |
| collection | UMS |
| description | Background: Children account for a significant proportion of COVID-19 hospitalizations, but data on the predictors of disease severity in children are limited. We aimed to identify risk factors associated with moderate/severe COVID-19 and develop a nomogram for predicting children with moderate/severe COVID-19.
Methods: We identified children ≤ 12 years old hospitalized for COVID-19 across five hospitals in Negeri Sembilan, Malaysia, from 1 January 2021 to 31 December 2021 from the state’s pediatric COVID-19 case registration system. The primary outcome was the development of moderate/severe COVID-19 during hospitalization. Multivariate logistic regression was performed to identify independent risk factors for moderate/severe COVID-19. A nomogram was constructed to predict moderate/severe disease. The model performance was evaluated using the area under the curve (AUC), sensitivity, specificity, and accuracy.
Results: A total of 1,717 patients were included. After excluding the asymptomatic cases, 1,234 patients (1,023 mild cases and 211 moderate/severe cases) were used to develop the prediction model. Nine independent risk factors were identified, including the presence of at least one comorbidity, shortness of breath, vomiting, diarrhea, rash, seizures, temperature on arrival, chest recessions, and abnormal breath sounds. The nomogram’s sensitivity, specificity, accuracy, and AUC for predicting moderate/severe COVID-19 were 58·1%, 80·5%, 76·8%, and 0·86 (95% CI, 0·79 – 0·92) respectively.
Conclusion: Our nomogram, which incorporated readily available clinical parameters, would be useful to facilitate individualized clinical decisions. |
| first_indexed | 2024-03-06T03:25:04Z |
| format | Article |
| id | ums.eprints-36605 |
| institution | Universiti Malaysia Sabah |
| language | English English |
| last_indexed | 2024-03-06T03:25:04Z |
| publishDate | 2023 |
| publisher | Springer Nature |
| record_format | dspace |
| spelling | ums.eprints-366052023-09-01T00:41:28Z https://eprints.ums.edu.my/id/eprint/36605/ Risk factors for disease severity among children with Covid-19: a clinical prediction model David Chun‑Ern Ng Liew, Chuin‑Hen Tan, Kah Kee Ling Chin Grace Sieng Sing Ting Nur Fadzreena Fadzilah Lim, Hui Yi Nur Emylia Zailanalhuddin Shir Fong Tan Muhamad Akmal Afan Fatin Farihah Wan Ahmad Nasir Thayasheri Subramaniam Marlindawati Mohd Ali Mohammad Faid Abd Rashid Ong, Song Quan Ch’ng, Chin Chin RA643-645 Disease (Communicable and noninfectious) and public health RJ1-570 Pediatrics Background: Children account for a significant proportion of COVID-19 hospitalizations, but data on the predictors of disease severity in children are limited. We aimed to identify risk factors associated with moderate/severe COVID-19 and develop a nomogram for predicting children with moderate/severe COVID-19. Methods: We identified children ≤ 12 years old hospitalized for COVID-19 across five hospitals in Negeri Sembilan, Malaysia, from 1 January 2021 to 31 December 2021 from the state’s pediatric COVID-19 case registration system. The primary outcome was the development of moderate/severe COVID-19 during hospitalization. Multivariate logistic regression was performed to identify independent risk factors for moderate/severe COVID-19. A nomogram was constructed to predict moderate/severe disease. The model performance was evaluated using the area under the curve (AUC), sensitivity, specificity, and accuracy. Results: A total of 1,717 patients were included. After excluding the asymptomatic cases, 1,234 patients (1,023 mild cases and 211 moderate/severe cases) were used to develop the prediction model. Nine independent risk factors were identified, including the presence of at least one comorbidity, shortness of breath, vomiting, diarrhea, rash, seizures, temperature on arrival, chest recessions, and abnormal breath sounds. The nomogram’s sensitivity, specificity, accuracy, and AUC for predicting moderate/severe COVID-19 were 58·1%, 80·5%, 76·8%, and 0·86 (95% CI, 0·79 – 0·92) respectively. Conclusion: Our nomogram, which incorporated readily available clinical parameters, would be useful to facilitate individualized clinical decisions. Springer Nature 2023 Article NonPeerReviewed text en https://eprints.ums.edu.my/id/eprint/36605/1/ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/36605/2/FULL%20TEXT.pdf David Chun‑Ern Ng and Liew, Chuin‑Hen and Tan, Kah Kee and Ling Chin and Grace Sieng Sing Ting and Nur Fadzreena Fadzilah and Lim, Hui Yi and Nur Emylia Zailanalhuddin and Shir Fong Tan and Muhamad Akmal Afan and Fatin Farihah Wan Ahmad Nasir and Thayasheri Subramaniam and Marlindawati Mohd Ali and Mohammad Faid Abd Rashid and Ong, Song Quan and Ch’ng, Chin Chin (2023) Risk factors for disease severity among children with Covid-19: a clinical prediction model. BMC Infectious Diseases, 23 (398). pp. 1-12. ISSN 1471-2334 https://doi.org/10.1186/s12879-023-08357-y |
| spellingShingle | RA643-645 Disease (Communicable and noninfectious) and public health RJ1-570 Pediatrics David Chun‑Ern Ng Liew, Chuin‑Hen Tan, Kah Kee Ling Chin Grace Sieng Sing Ting Nur Fadzreena Fadzilah Lim, Hui Yi Nur Emylia Zailanalhuddin Shir Fong Tan Muhamad Akmal Afan Fatin Farihah Wan Ahmad Nasir Thayasheri Subramaniam Marlindawati Mohd Ali Mohammad Faid Abd Rashid Ong, Song Quan Ch’ng, Chin Chin Risk factors for disease severity among children with Covid-19: a clinical prediction model |
| title | Risk factors for disease severity among children with Covid-19: a clinical prediction model |
| title_full | Risk factors for disease severity among children with Covid-19: a clinical prediction model |
| title_fullStr | Risk factors for disease severity among children with Covid-19: a clinical prediction model |
| title_full_unstemmed | Risk factors for disease severity among children with Covid-19: a clinical prediction model |
| title_short | Risk factors for disease severity among children with Covid-19: a clinical prediction model |
| title_sort | risk factors for disease severity among children with covid 19 a clinical prediction model |
| topic | RA643-645 Disease (Communicable and noninfectious) and public health RJ1-570 Pediatrics |
| url | https://eprints.ums.edu.my/id/eprint/36605/1/ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/36605/2/FULL%20TEXT.pdf |
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