Predicting Response to In-Hospital Pulmonary Rehabilitation in Individuals Recovering From Exacerbations of Chronic Obstructive Pulmonary Disease / Predicción de la respuesta a la rehabilitación pulmonar hospitalaria en personas que se recuperan de exacerbaciones de la enfermedad pulmonar obstructiva crónica

Background: Predicting the response to pulmonary rehabilitation (PR) could be valuable in defining admission priorities. We aimed to investigate whether the response of individuals recovering from a COPD exacerbation (ECOPD) could be forecasted using machine learning approaches. Method: This multicenter, retrospective study recorded data on anthropometrics, demographics, physiological characteristics, post-PR changes in six-minute walking distance test (6MWT), Medical Research Council scale for dyspnea (MRC), Barthel Index dyspnea (BId), COPD assessment test (CAT) and proportion of participants reaching the minimal clinically important difference (MCID). The ability of multivariate approaches (linear regression, quantile regression, regression trees, and conditional inference trees) in predicting changes in each outcome measure has been assessed. Results: Individuals with lower baseline 6MWT, as well as those with less severe airway obstruction or admitted from acute care hospitals, exhibited greater improvements in 6MWT, whereas older as well as more dyspnoeic individuals had a lower forecasted improvement. Individuals with more severe CAT and dyspnea, and lower 6MWT had a greater potential improvement in CAT. More dyspnoeic individuals were also more likely to show improvement in BId and MRC. The Mean Absolute Error estimates of change prediction were 44.70m, 3.22 points, 5.35 points, and 0.32 points for 6MWT, CAT, BId, and MRC respectively. Sensitivity and specificity in discriminating individuals reaching the MCID of outcomes ranged from 61.78% to 98.99% and from 14.00% to 71.20%, respectively. Conclusion: While the assessed models were not entirely satisfactory, predictive equations derived from clinical practice data might help in forecasting the response to PR in individuals recovering from an ECOPD. Future larger studies will be essential to confirm the methodology, variables, and utility.(AU)

Predicting Response to In-Hospital Pulmonary Rehabilitation in Individuals Recovering From Exacerbations of Chronic Obstructive Pulmonary Disease.

BACKGROUND: Predicting the response to pulmonary rehabilitation (PR) could be valuable in defining admission priorities. We aimed to investigate whether the response of individuals recovering from a COPD exacerbation (ECOPD) could be forecasted using machine learning approaches. METHOD: This multicenter, retrospective study recorded data on anthropometrics, demographics, physiological characteristics, post-PR changes in six-minute walking distance test (6MWT), Medical Research Council scale for dyspnea (MRC), Barthel Index dyspnea (BId), COPD assessment test (CAT) and proportion of participants reaching the minimal clinically important difference (MCID). The ability of multivariate approaches (linear regression, quantile regression, regression trees, and conditional inference trees) in predicting changes in each outcome measure has been assessed. RESULTS: Individuals with lower baseline 6MWT, as well as those with less severe airway obstruction or admitted from acute care hospitals, exhibited greater improvements in 6MWT, whereas older as well as more dyspnoeic individuals had a lower forecasted improvement. Individuals with more severe CAT and dyspnea, and lower 6MWT had a greater potential improvement in CAT. More dyspnoeic individuals were also more likely to show improvement in BId and MRC. The Mean Absolute Error estimates of change prediction were 44.70m, 3.22 points, 5.35 points, and 0.32 points for 6MWT, CAT, BId, and MRC respectively. Sensitivity and specificity in discriminating individuals reaching the MCID of outcomes ranged from 61.78% to 98.99% and from 14.00% to 71.20%, respectively. CONCLUSION: While the assessed models were not entirely satisfactory, predictive equations derived from clinical practice data might help in forecasting the response to PR in individuals recovering from an ECOPD. Future larger studies will be essential to confirm the methodology, variables, and utility.

Fixed and autoadjusting continuous positive airway pressure treatments are not similar in reducing cardiovascular risk factors in patients with obstructive sleep apnea.

BACKGROUND: A strong association between obstructive sleep apnea (OSA) and the risk for cardiovascular and cerebrovascular diseases has been reported. Continuous positive airway pressure (CPAP) is the first-line therapy for OSA, able not only to reduce daytime sleepiness but also to improve cardiovascular and metabolic outcomes. Autoadjusting CPAP (APAP), an alternative treatment to CPAP, can reduce OSA symptoms while increasing long-term CPAP compliance without the high costs of CPAP titration. However, no data are available on the effects of APAP on cardiovascular risk factors METHODS: We performed standard full polysomnography; obtained plasma levels of glucose, insulin, and C-reactive protein (CRP); and measured systolic BP (SBP) and diastolic BP (DBP) in 31 patients with newly diagnosed, severe OSA. After standard CPAP titration, all subjects were randomized to CPAP or APAP treatment. Measurements were obtained at baseline and after 3 months of treatment. RESULTS: The two groups were similar in terms of age, sex, body mass index (BMI), and severity of OSA. SBP, DBP, heart rate (HR), homeostasis model assessment index (HOMA-IR), and CRP were similar in the two groups. After 3 months of treatment, BMI, HR, and compliance to therapy were also comparable. OSA indexes were significantly reduced in both groups. Significant reductions in SBP, DBP, and HOMA-IR were observed in the CPAP group but not in the APAP group, while CRP plasma levels were similarly reduced. CONCLUSIONS: Our results suggest that CPAP and APAP, despite significant effects on OSA indexes and symptoms, do not improve cardiovascular risk factors in the same fashion.