ArticleRespiration; international review of thoracic diseases2026
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Article in Respiration; international review of thoracic diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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9 authors.
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Abstract
introductionOptimal management of long-term home noninvasive ventilation (NIV) therapy is not clearly defined. This study determined whether patient experience of disease and NIV therapy (S3-NIV score) in the first month was associated with successful NIV delivery and termination rate at 6 months.
methodsParticipants were adults starting home nocturnal NIV for chronic respiratory failure in 2019-2022, who used telemonitoring, completed ≥1 S3-NIV questionnaire in the first month of NIV, and were followed by the same home service provider. As no S3-NIV score thresholds are defined, participants were grouped by S3-NIV score quartiles (Q) (Q1 = most negative impact of symptoms/NIV; Q4 = lowest impact of disease/treatment). Factors associated with successful NIV delivery at 6 months were determined using multivariate logistic regression analysis.
resultsOne hundred fifty-three patients were included (mean age 65.9 ± 12.9 years, 60% male). The proportion of patients with successful NIV delivery at 6 months increased as initial S3-NIV score increased: Q1 42%, Q2 60%, Q3 63%, and Q4 63% (p = 0.007). Individuals with lower S3-NIV scores had more home interventions and mask changes during follow-up, regardless of whether NIV was successful or not. Termination rate was higher in S3-NIV score Q1 versus Q4 (29% vs. 11%). The probability of successful NIV delivery at 6 months increased by 1.14-fold for each 1-point increase in the initial S3-NIV score, independent of the association between the score and NIV data at 1 month.
conclusionThe S3-NIV questionnaire helped identify patients at higher risk of therapy termination more effectively than relying only on objective ventilator data.
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