Rainer Tan, Arjun Chandna, Tim Colbourn, Shubhada Hooli, Carina King, Norman Lufesi, Eric McCollum, Charles Mwansambo, Joseph L. Matthew, Clare Cutland, Shabir Ahmed Madhi, Sudha Basnet, Tor A. Strand, Kerry-Ann O'Grady, Brad Gessner, Emmanuel Addo-Yobo, Noel Chisaka, Patricia L. Hibberd, Prakash Jeena, Juan M. Lozano, William B. MacLeod, Archana Patel, Donald M. Thea, Ngoc Tuong Vy Nguyen, Marilla Lucero, Syed Mohammad Akram uz Zaman, Shinhini Bhatnagar, Nitya Wadhwa, Rakesh Lodha, Satinder Aneja, Mathuram Santosham, Shally Awasthi, Ashish Bavdekar, Monidarin Chou, Pagbajabyn Nymadawa, Jean-William Pape, Glaucia Paranhos-Baccala, Valentina S. Picot, Mala Rakoto-Andrianarivelo, Vanessa Rouzier, Graciela Russomando, Mariam Sylla, Philippe Vanhems, Jianwei Wang, Romina Libster, Alexey W. Clara, Fenella Beynon, Gillian Levine, Chris A Rees, Mark I Neuman, Shamin A Qazi, Yasir Bin Nisar, World Health Organization PREPARE Study Group
{"title":"Development and validation of a novel clinical risk score to predict hypoxemia in children with pneumonia using the WHO PREPARE dataset","authors":"Rainer Tan, Arjun Chandna, Tim Colbourn, Shubhada Hooli, Carina King, Norman Lufesi, Eric McCollum, Charles Mwansambo, Joseph L. Matthew, Clare Cutland, Shabir Ahmed Madhi, Sudha Basnet, Tor A. Strand, Kerry-Ann O'Grady, Brad Gessner, Emmanuel Addo-Yobo, Noel Chisaka, Patricia L. Hibberd, Prakash Jeena, Juan M. Lozano, William B. MacLeod, Archana Patel, Donald M. Thea, Ngoc Tuong Vy Nguyen, Marilla Lucero, Syed Mohammad Akram uz Zaman, Shinhini Bhatnagar, Nitya Wadhwa, Rakesh Lodha, Satinder Aneja, Mathuram Santosham, Shally Awasthi, Ashish Bavdekar, Monidarin Chou, Pagbajabyn Nymadawa, Jean-William Pape, Glaucia Paranhos-Baccala, Valentina S. Picot, Mala Rakoto-Andrianarivelo, Vanessa Rouzier, Graciela Russomando, Mariam Sylla, Philippe Vanhems, Jianwei Wang, Romina Libster, Alexey W. Clara, Fenella Beynon, Gillian Levine, Chris A Rees, Mark I Neuman, Shamin A Qazi, Yasir Bin Nisar, World Health Organization PREPARE Study Group","doi":"10.1101/2024.08.19.24312238","DOIUrl":null,"url":null,"abstract":"Background\nHypoxemia predicts mortality at all levels of care, and appropriate management can reduce preventable deaths. However, pulse oximetry and oxygen therapy remain inaccessible in many primary care health facilities. We aimed to develop and validate a simple risk score comprising commonly evaluated clinical features to predict hypoxemia in 2-59-month-old children with pneumonia.\nMethods\nData from 7 studies conducted in 5 countries from the Pneumonia Research Partnership to Assess WHO Recommendations (PREPARE) dataset were included. Readily available clinical features and demographic variables were used to develop a multivariable logistic regression model to predict hypoxemia (SpO2<90%) at presentation to care. The adjusted log coefficients were transformed to derive the PREPARE hypoxemia risk score and its diagnostic value was assessed in a held-out, temporal validation dataset.\nResults\nWe included 14,509 children in the analysis; 9.8% (n=2,515) were hypoxemic at presentation. The multivariable regression model to predict hypoxemia included age, sex, respiratory distress (nasal flaring, grunting and/or head nodding), lower chest indrawing, respiratory rate, body temperature and weight-for-age z-score. The model showed fair discrimination (area under the curve 0.70, 95% CI 0.67 to 0.73) and calibration in the validation dataset. The simplified PREPARE hypoxemia risk score includes 5 variables: age, respiratory distress, lower chest indrawing, respiratory rate and weight-for-age z-score. Conclusion\nThe PREPARE hypoxemia risk score, comprising five easily available characteristics, can be used to identify hypoxemia in children with pneumonia with a fair degree of certainty for use in health facilities without pulse oximetry. Its implementation would require careful consideration to limit inappropriate referrals on patients and the health system. Further external validation in community settings in low- and middle-income countries is required.","PeriodicalId":501549,"journal":{"name":"medRxiv - Pediatrics","volume":"43 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Pediatrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.08.19.24312238","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background
Hypoxemia predicts mortality at all levels of care, and appropriate management can reduce preventable deaths. However, pulse oximetry and oxygen therapy remain inaccessible in many primary care health facilities. We aimed to develop and validate a simple risk score comprising commonly evaluated clinical features to predict hypoxemia in 2-59-month-old children with pneumonia.
Methods
Data from 7 studies conducted in 5 countries from the Pneumonia Research Partnership to Assess WHO Recommendations (PREPARE) dataset were included. Readily available clinical features and demographic variables were used to develop a multivariable logistic regression model to predict hypoxemia (SpO2<90%) at presentation to care. The adjusted log coefficients were transformed to derive the PREPARE hypoxemia risk score and its diagnostic value was assessed in a held-out, temporal validation dataset.
Results
We included 14,509 children in the analysis; 9.8% (n=2,515) were hypoxemic at presentation. The multivariable regression model to predict hypoxemia included age, sex, respiratory distress (nasal flaring, grunting and/or head nodding), lower chest indrawing, respiratory rate, body temperature and weight-for-age z-score. The model showed fair discrimination (area under the curve 0.70, 95% CI 0.67 to 0.73) and calibration in the validation dataset. The simplified PREPARE hypoxemia risk score includes 5 variables: age, respiratory distress, lower chest indrawing, respiratory rate and weight-for-age z-score. Conclusion
The PREPARE hypoxemia risk score, comprising five easily available characteristics, can be used to identify hypoxemia in children with pneumonia with a fair degree of certainty for use in health facilities without pulse oximetry. Its implementation would require careful consideration to limit inappropriate referrals on patients and the health system. Further external validation in community settings in low- and middle-income countries is required.