Samuel R Neal, Sarah Sturrock, David Musorowegomo, Hannah Gannon, Michele Zaman, Mario Cortina-Borja, Kirsty Le Doare, Michelle Heys, Gwen Chimhini, Felicity Fitzgerald
{"title":"中低收入国家诊断新生儿败血症的临床预测模型:范围综述","authors":"Samuel R Neal, Sarah Sturrock, David Musorowegomo, Hannah Gannon, Michele Zaman, Mario Cortina-Borja, Kirsty Le Doare, Michelle Heys, Gwen Chimhini, Felicity Fitzgerald","doi":"10.1101/2024.09.05.24313133","DOIUrl":null,"url":null,"abstract":"Neonatal sepsis causes significant morbidity and mortality worldwide but is difficult to diagnose clinically. Clinical prediction models (CPMs) could improve diagnostic accuracy. Neonates in low-income and middle-income countries are disproportionately affected by sepsis, yet no review has comprehensively synthesised CPMs validated in this setting. We performed a scoping review of CPMs for neonatal sepsis diagnosis validated in low-income and middle-income countries. From 4598 unique records, we included 82 studies validating 44 distinct models. Most studies were set in neonatal intensive or special care units in middle-income countries and included neonates already suspected of sepsis. Three quarters of models were only validated in one study. Our review highlights several literature gaps, particularly a paucity of studies validating models in low-income countries and the WHO African region, and models for the general neonatal population. Furthermore, heterogeneity in study populations, definitions of sepsis and reporting of models may hinder progress in this field.","PeriodicalId":501549,"journal":{"name":"medRxiv - Pediatrics","volume":"9 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Clinical prediction models to diagnose neonatal sepsis in low-income and middle-income countries: a scoping review\",\"authors\":\"Samuel R Neal, Sarah Sturrock, David Musorowegomo, Hannah Gannon, Michele Zaman, Mario Cortina-Borja, Kirsty Le Doare, Michelle Heys, Gwen Chimhini, Felicity Fitzgerald\",\"doi\":\"10.1101/2024.09.05.24313133\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Neonatal sepsis causes significant morbidity and mortality worldwide but is difficult to diagnose clinically. Clinical prediction models (CPMs) could improve diagnostic accuracy. Neonates in low-income and middle-income countries are disproportionately affected by sepsis, yet no review has comprehensively synthesised CPMs validated in this setting. We performed a scoping review of CPMs for neonatal sepsis diagnosis validated in low-income and middle-income countries. From 4598 unique records, we included 82 studies validating 44 distinct models. Most studies were set in neonatal intensive or special care units in middle-income countries and included neonates already suspected of sepsis. Three quarters of models were only validated in one study. Our review highlights several literature gaps, particularly a paucity of studies validating models in low-income countries and the WHO African region, and models for the general neonatal population. Furthermore, heterogeneity in study populations, definitions of sepsis and reporting of models may hinder progress in this field.\",\"PeriodicalId\":501549,\"journal\":{\"name\":\"medRxiv - Pediatrics\",\"volume\":\"9 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-06\",\"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/10.1101/2024.09.05.24313133\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Pediatrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.09.05.24313133","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Clinical prediction models to diagnose neonatal sepsis in low-income and middle-income countries: a scoping review
Neonatal sepsis causes significant morbidity and mortality worldwide but is difficult to diagnose clinically. Clinical prediction models (CPMs) could improve diagnostic accuracy. Neonates in low-income and middle-income countries are disproportionately affected by sepsis, yet no review has comprehensively synthesised CPMs validated in this setting. We performed a scoping review of CPMs for neonatal sepsis diagnosis validated in low-income and middle-income countries. From 4598 unique records, we included 82 studies validating 44 distinct models. Most studies were set in neonatal intensive or special care units in middle-income countries and included neonates already suspected of sepsis. Three quarters of models were only validated in one study. Our review highlights several literature gaps, particularly a paucity of studies validating models in low-income countries and the WHO African region, and models for the general neonatal population. Furthermore, heterogeneity in study populations, definitions of sepsis and reporting of models may hinder progress in this field.