Dataset Information

Prediction of disease severity in young children presenting with acute febrile illness in resource-limited settings: a protocol for a prospective observational study.

ABSTRACT:

Introduction

In rural and difficult-to-access settings, early and accurate recognition of febrile children at risk of progressing to serious illness could contribute to improved patient outcomes and better resource allocation. This study aims to develop a prognostic clinical prediction tool to assist community healthcare providers identify febrile children who might benefit from referral or admission for facility-based medical care.

Methods and analysis

This prospective observational study will recruit at least 4900 paediatric inpatients and outpatients under the age of 5?years presenting with an acute febrile illness to seven hospitals in six countries across Asia. A venous blood sample and nasopharyngeal swab is collected from each participant and detailed clinical data recorded at presentation, and each day for the first 48 hours of admission for inpatients. Multianalyte assays are performed at reference laboratories to measure a panel of host biomarkers, as well as targeted aetiological investigations for common bacterial and viral pathogens. Clinical outcome is ascertained on day 2 and day 28.Presenting syndromes, clinical outcomes and aetiology of acute febrile illness will be described and compared across sites. Following the latest guidance in prediction model building, a prognostic clinical prediction model, combining simple clinical features and measurements of host biomarkers, will be derived and geographically externally validated. The performance of the model will be evaluated in specific presenting clinical syndromes and fever aetiologies.

Ethics and dissemination

The study has received approval from all relevant international, national and institutional ethics committees. Written informed consent is provided by the caretaker of all participants. Results will be shared with local and national stakeholders, and disseminated via peer-reviewed open-access journals and scientific meetings.

Trial registration number

NCT04285021.

SUBMITTER: Chandna A

PROVIDER: S-EPMC7839891 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

Prediction of disease severity in young children presenting with acute febrile illness in resource-limited settings: a protocol for a prospective observational study.

Chandna Arjun A Aderie Endashaw M EM Ahmad Riris R Arguni Eggi E Ashley Elizabeth A EA Cope Tanya T Dat Vu Quoc VQ Day Nicholas P J NPJ Dondorp Arjen M AM Illanes Victor V De Jesus Joanne J Jimenez Carolina C Kain Kevin K Suy Keang K Koshiaris Constantinos C Lasry Estrella E Mayxay Mayfong M Mondal Dinesh D Perera Rafael R Pongvongsa Tiengkham T Rattanavong Sayaphet S Rekart Michael M Richard-Greenblatt Melissa M Shomik Mohammad M Souvannasing Phouthalavanh P Tallo Veronica V Turner Claudia C Turner Paul P Waithira Naomi N Watson James A JA Yosia Mikhael M Burza Sakib S Burza Sakib S Lubell Yoel Y

BMJ open 20210125 1

<h4>Introduction</h4>In rural and difficult-to-access settings, early and accurate recognition of febrile children at risk of progressing to serious illness could contribute to improved patient outcomes and better resource allocation. This study aims to develop a prognostic clinical prediction tool to assist community healthcare providers identify febrile children who might benefit from referral or admission for facility-based medical care.<h4>Methods and analysis</h4>This prospective observatio ...[more]

PMID: 33495264

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Project description:Neonatal disease severity scoring systems are needed to make standardized comparison between performances of different units and to give prognostic information to parents of individual babies admitted. Existing scoring systems are unsuitable for resource-limited settings which lack investigations like pH, pO2/FiO2 ratio, and base excess. This study was planned to evaluate Modified Sick Neonatal Score (MSNS), a novel neonatal disease severity score designed for resource-constrained settings. It was a facility-based cross-sectional analytical study, conducted in the "Special Newborn Care Unit" (SNCU) of government district hospital, attached to Kasturba Medical College, Mangalore, India from November 2016 to October 2017. A convenience sample of 585 neonates was included. Disease severity was assessed immediately at admission using MSNS. MSNS had 8 parameters with 0, 1, and 2 scores for each. 41% of study population was preterm (n=240), and 84.1% had birth weight less than 2500 grams (n=492). The mean (SD) of the total MSNS scores for neonates who expired and discharged was, respectively, 8.22 (2.96) and 13.4 (2.14), a difference being statistically significant at P < 0.001. Expired newborns had statistically significant frequency of lower scores across each of the parameters. An optimum cutoff score of ≤10 with 80% sensitivity and 88.8% specificity in predicting mortality was obtained when the ROC curve was generated with the MSNS score as the test variable. Area under the curve was 0.913 (95% CI: 0.879-0.946). In conclusion, MSNS is a practicable disease severity score in resource-restricted settings like district SNCUs. It is for application in both term and preterm neonates. Total score ≤10 has a good sensitivity and specificity in predicting mortality of admitted neonates when used early during the course of hospitalization. MSNS could be used as a tool to compare performance of SNCUs and also enable early referral of individual cases to units with better facilities.

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Dataset Information

Prediction of disease severity in young children presenting with acute febrile illness in resource-limited settings: a protocol for a prospective observational study.

Introduction

Methods and analysis

Ethics and dissemination

Trial registration number

Publications

Prediction of disease severity in young children presenting with acute febrile illness in resource-limited settings: a protocol for a prospective observational study.

Similar Datasets

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