Deconstructing Therapeutic Failure with Inhaled Therapy in Hospitalized Patients: Phenotypes, Risk Profiles, and Clinical Inertia

Background: Hospitalized patients on chronic inhaled therapy suffer high rates of therapeutic failure. Current approaches often overlook patient heterogeneity, treating failure as a uniform problem. We hypothesized that clinical inertia, a key driver of failure, is not a monolithic entity but is governed by specific, non-overlapping factors. Methods: In this unicentric, observational cohort study of 499 hospitalized adults on chronic inhaled therapy, we used unsupervised clustering to identify patient phenotypes. Multivariable logistic regression was used to model predictors of critical inhaler errors and three distinct forms of clinical inertia: Therapeutic Class (TCI), Device-Level (DLI), and Adherence-Related (ARI). Results: Inhaler misuse was driven by objective capability—deficient knowledge (aOR 6.03, 95% CI 2.88–12.64) and low inspiratory flow (aOR 3.11, 95% CI 1.06–9.12)—while patient-reported adherence was not a significant independent predictor. Crucially, the three forms of clinical inertia were governed by distinct, non-overlapping predictors: TCI was predicted by high therapeutic potency (aOR 7.80, 95% CI 3.65–16.64), DLI by a failure in the clinical process (lack of patient training, aOR 3.49, 95% CI 1.21–10.03), and ARI by regimen complexity (aOR 0.06, 95% CI 0.02–0.25). Post-discharge mortality (21.6% overall; 25.8% in Cluster 1 vs. 18.3% in Cluster 2) was independently predicted by objective risk factors, including older age (aOR 1.51, 95% CI 1.20–1.89) and an unassessed inspiratory flow (aOR 2.44, 95% CI 1.19–5.03). Two underlying patient phenotypes were identified—an “Unassessed/Older” (n = 225) and an “Assessed/Younger” (n = 274)—which represented distinct in-hospital care pathways but did not independently predict mortality after multivariate adjustment. Conclusions: Therapeutic failure in hospitalized patients is a predictable outcome driven by distinct, non-overlapping factors. This study deconstructs this failure by identifying the specific, actionable drivers of inhaler misuse (patient capability) and the three forms of clinical inertia (therapeutic potency, failures in the care process, and regimen complexity). These processes occur within two distinct patient phenotypes that represent different in-hospital care pathways. Our findings provide a new framework to move beyond generic interventions toward a more precise, evidence-based approach to inhaled therapy.

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