The future of big data: Remote monitoring of positive airway pressure treatment for obstructive sleep apnea - insights from adults and implications for pediatric care.
Rakesh Bhattacharjee, Joao Carlos Winck, David Gozal
{"title":"The future of big data: Remote monitoring of positive airway pressure treatment for obstructive sleep apnea - insights from adults and implications for pediatric care.","authors":"Rakesh Bhattacharjee, Joao Carlos Winck, David Gozal","doi":"10.1002/ppul.27334","DOIUrl":null,"url":null,"abstract":"<p><p>The advent of large expansive datasets has generated substantial interest as a means of developing and implementing unique algorithms that facilitate more precise and personalized interventions. This methodology has permeated the realm of sleep medicine and in the care of patients with sleep disorders. One of the large repositories of information consists of adherence and physiological datasets across long periods of time as derived from patients undergoing positive airway pressure (PAP) treatment for sleep-disordered breathing. Here, we evaluate the extant and yet scarce findings derived from big data in both adults and children receiving PAP for obstructive sleep apnea and suggest future directions towards more expansive utilization of such valuable approaches to improve therapeutic decisions and outcomes.</p>","PeriodicalId":19932,"journal":{"name":"Pediatric Pulmonology","volume":" ","pages":"e27334"},"PeriodicalIF":2.7000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pediatric Pulmonology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/ppul.27334","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/2 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PEDIATRICS","Score":null,"Total":0}
引用次数: 0
Abstract
The advent of large expansive datasets has generated substantial interest as a means of developing and implementing unique algorithms that facilitate more precise and personalized interventions. This methodology has permeated the realm of sleep medicine and in the care of patients with sleep disorders. One of the large repositories of information consists of adherence and physiological datasets across long periods of time as derived from patients undergoing positive airway pressure (PAP) treatment for sleep-disordered breathing. Here, we evaluate the extant and yet scarce findings derived from big data in both adults and children receiving PAP for obstructive sleep apnea and suggest future directions towards more expansive utilization of such valuable approaches to improve therapeutic decisions and outcomes.
期刊介绍：
Pediatric Pulmonology (PPUL) is the foremost global journal studying the respiratory system in disease and in health as it develops from intrauterine life though adolescence to adulthood. Combining explicit and informative analysis of clinical as well as basic scientific research, PPUL provides a look at the many facets of respiratory system disorders in infants and children, ranging from pathological anatomy, developmental issues, and pathophysiology to infectious disease, asthma, cystic fibrosis, and airborne toxins. Focused attention is given to the reporting of diagnostic and therapeutic methods for neonates, preschool children, and adolescents, the enduring effects of childhood respiratory diseases, and newly described infectious diseases.
PPUL concentrates on subject matters of crucial interest to specialists preparing for the Pediatric Subspecialty Examinations in the United States and other countries. With its attentive coverage and extensive clinical data, this journal is a principle source for pediatricians in practice and in training and a must have for all pediatric pulmonologists.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
