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Risk factors for disease severity among children with Covid-19: a clinical prediction model.
Ng, David Chun-Ern; Liew, Chuin-Hen; Tan, Kah Kee; Chin, Ling; Ting, Grace Sieng Sing; Fadzilah, Nur Fadzreena; Lim, Hui Yi; Zailanalhuddin, Nur Emylia; Tan, Shir Fong; Affan, Muhamad Akmal; Nasir, Fatin Farihah Wan Ahmad; Subramaniam, Thayasheri; Ali, Marlindawati Mohd; Rashid, Mohammad Faid Abd; Ong, Song-Quan; Ch'ng, Chin Chin.
Afiliación
  • Ng DC; Hospital Tuanku Ja'afar, Negeri Sembilan, Ministry of Health, Jalan Rasah, 70300, Seremban, Malaysia. davidngce@gmail.com.
  • Liew CH; Hospital Tuanku Ampuan Najihah, Negeri Sembilan, Ministry of Health, Jalan Melang, 72000, Kuala Pilah, Malaysia.
  • Tan KK; Perdana University Seremban Clinical Academic Center, Negeri Sembilan, Jalan Rasah, 70300, Seremban, Malaysia.
  • Chin L; Hospital Tuanku Ja'afar, Negeri Sembilan, Ministry of Health, Jalan Rasah, 70300, Seremban, Malaysia.
  • Ting GSS; Hospital Tuanku Ja'afar, Negeri Sembilan, Ministry of Health, Jalan Rasah, 70300, Seremban, Malaysia.
  • Fadzilah NF; Hospital Tuanku Ja'afar, Negeri Sembilan, Ministry of Health, Jalan Rasah, 70300, Seremban, Malaysia.
  • Lim HY; Hospital Tuanku Ja'afar, Negeri Sembilan, Ministry of Health, Jalan Rasah, 70300, Seremban, Malaysia.
  • Zailanalhuddin NE; Hospital Tuanku Ja'afar, Negeri Sembilan, Ministry of Health, Jalan Rasah, 70300, Seremban, Malaysia.
  • Tan SF; Hospital Tuanku Ja'afar, Negeri Sembilan, Ministry of Health, Jalan Rasah, 70300, Seremban, Malaysia.
  • Affan MA; Hospital Tuanku Ja'afar, Negeri Sembilan, Ministry of Health, Jalan Rasah, 70300, Seremban, Malaysia.
  • Nasir FFWA; Hospital Tuanku Ja'afar, Negeri Sembilan, Ministry of Health, Jalan Rasah, 70300, Seremban, Malaysia.
  • Subramaniam T; Hospital Tuanku Ja'afar, Negeri Sembilan, Ministry of Health, Jalan Rasah, 70300, Seremban, Malaysia.
  • Ali MM; Hospital Tuanku Ja'afar, Negeri Sembilan, Ministry of Health, Jalan Rasah, 70300, Seremban, Malaysia.
  • Rashid MFA; Negeri Sembilan State Health Department, Negeri Sembilan, Ministry of Health, Jalan Rasah, 70300, Seremban, Malaysia.
  • Ong SQ; Institute for Tropical Biology and Conservation, University Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia.
  • Ch'ng CC; Clinical Research Centre Hospital Pulau Pinang, Ministry of Health, Jalan Residensi, 10450, Pulau Pinang, Malaysia.
BMC Infect Dis ; 23(1): 398, 2023 Jun 12.
Article en En | MEDLINE | ID: mdl-37308825
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Modelos Estadísticos / COVID-19 Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Aspecto: Patient_preference Límite: Child / Humans Idioma: En Revista: BMC Infect Dis Asunto de la revista: DOENCAS TRANSMISSIVEIS Año: 2023 Tipo del documento: Article País de afiliación: Malasia Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Modelos Estadísticos / COVID-19 Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Aspecto: Patient_preference Límite: Child / Humans Idioma: En Revista: BMC Infect Dis Asunto de la revista: DOENCAS TRANSMISSIVEIS Año: 2023 Tipo del documento: Article País de afiliación: Malasia Pais de publicación: Reino Unido