Development of an algorithm impacting COPD care through personalized nutrition and IoT-based monitoring

开发一种通过个性化营养和基于物联网的监测来改善慢性阻塞性肺病治疗的算法

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Abstract

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a chronic respiratory condition characterized by high morbidity and mortality rates. This study aims to assess the clinical outcomes of COPD patients after implementing an algorithm within the MyTatva app. METHODS: The study involved a sample of 10 COPD patients, evaluating key parameters such as Forced Expiratory Volume in 1 s (FEV1), Forced Vital Capacity, Weight, Body Mass Index (BMI), Fat-Free Mass Index, and Distance Covered during the 6-Minute Walk Test (6MWT) before and after the algorithm's implementation in the MyTatva app. Patient satisfaction was assessed through a CSAT survey. RESULTS: Following the implementation of the MyTatva care plan, significant improvements were observed in several key clinical outcomes for COPD patients. FEV1 increased from a median of 3.24-2.0 L (p = 0.0379), while weight and BMI decreased significantly, with a reduction in weight from a median of 86-70 kg (p = 0.0007) and a corresponding decrease in BMI from 28.43 to 24 kg/m(2) (p = 0.0031). The distance covered during the 6MWT also improved from 420 to 568 m (p = 0.0019). The participation of 10 COPD patients in surveys yielded an overall CSAT score of 85%, indicating a high level of satisfaction with the MyTatva app. CONCLUSION: The comprehensive features and functionalities of the MyTatva app, combined with the personalized care plan and real-time feedback mechanisms, have led to substantial clinical improvements in COPD management. These findings highlight the promise of this innovative digital therapeutic approach in addressing chronic respiratory conditions.

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