ArticleJournal of health, population, and nutrition2025
Development of an algorithm impacting COPD care through personalized nutrition and IoT-based monitoring.
Article in Journal of health, population, and nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review and evaluation framework for IoB-based adaptive health coaching systems.Frontiers in digital health · 2026Pooled it
- [Application of Digital Nutrition Technologies in Adult Weight Management].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2025Article
- Optimizing Treatment for Hospitalized Patients with COPD: A Study on the Impact of a LINE App-Based Multidisciplinary Team Approach Targeting Pharmacological Treatment, Lifestyle Changes, and Smoking Cessation.International journal of chronic obstructive pulmonary disease · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundChronic 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.
methodsThe 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.
resultsFollowing 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
conclusionThe 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.