A 28-day randomized open-label multicenter study was conducted to assess the efficacy of bromhexine plus standard of care (SOC) (n = 98) vs. SOC alone (n = 93) in 191 outpatients with mild-to-moderate COVID-19 in the primary health care setting. Bromhexine three daily doses of 10 mL (48 mg/day) were administered for seven days. The primary efficacy endpoint was the reduction of viral load estimated as the cycle thresholds (Ct) to detect ORF1ab, N Protein, and S Protein genes by RT-qPCR in saliva samples on day 4 as compared with baseline. Ct values of the three genes increased from baseline throughout days 4 to 14 (p < 0.001) but significant differences between the study groups were not found. Differences in the percentages of patients with low, medium, and high viral loads at 4, 7, and 14 days were not found either. In summary, treatment with bromhexine plus SCO was associated with a viral load reduction of ORF1ab, N Protein, and S Protein genes at day 4, which was not significantly different than similar viral load reductions observed with SOC alone. The present findings do not seem to favor the use of bromhexine as an antiviral in patients with COVID-19.

Background: Poor clinical control in Chronic Obstructive Pulmonary Disease (COPD) is prevalent, yet the interplay of disease severity, modifiable factors, and clinician perception remains poorly understood. This study aimed to determine the frequency of poor control, identify its independent determinants, and characterize the heterogeneity of the poorly controlled population receiving maintenance inhaled therapy with various devices in primary care. Methods: In a multicenter, cross-sectional analysis of 988 patients from the Study SIMPLIFY, clinical control of COPD was classified using the objective RADAR score. We used multivariable logistic regression and Machine Learning (Random Forest with SHAP analysis) to identify determinants of poor control (RADAR ≥ 4) and k-medoids cluster analysis to characterize the poorly controlled subgroup (n = 452). Results: Nearly half the cohort (45.7%, n = 452) had poor clinical control. Agreement between physician-assessed control (five categories) and RADAR classification was 49.3%, with overestimation in 34.0% and underestimation in 16.7% of cases (Cohen’s κ = −0.081; weighted κ = −0.037). The strongest independent determinants were the exacerbator phenotypes (eosinophilic aOR 6.85; non-eosinophilic aOR 4.91). Key modifiable factors included active smoking (aOR 1.92), lower TAI-12 adherence score (per point; aOR 0.96), high dosing frequency (≥4 inhalations/day; aOR 1.54) and high inhaler burden (≥3 devices; aOR 1.84). Machine learning analysis identified clinical phenotype and adherence behavior as the top two scale-independent predictors of poor control. Cluster analysis of the poorly controlled group revealed five reproducible and clinically meaningful phenotypes (C0–C4), primarily separated by treatment complexity, comorbidities, and adherence. Conclusions: Poor clinical control is common and critically under-recognized in primary care patients with COPD on maintenance inhaled therapy. This is driven by a profound clinician perception gap and a failure to address key modifiable determinants, such as high dosing frequency, regimen complexity, and poor adherence, which likely drives therapeutic inertia. Our findings underscore the need to integrate objective tools to unmask poor control and highlight the importance of treatment simplification. The identification of distinct clinical phenotypes provides a roadmap toward a more personalized, evidence-based standard of care.