T2 Biomarkers as Predictors of Exacerbations of Chronic Obstructive Pulmonary Disease

Introduction: Type 2 (T2) biomarkers such as blood eosinophil count (BEC) and FeNO have been related to a higher risk of exacerbations in COPD. It is unknown whether combining these biomarkers could be useful in forecasting COPD exacerbations. Methods: COPD patients were enrolled in this prospective, multicenter, observational study and followed up for 1 year, during which BEC were analysed at baseline (V0) while FeNO analyses were performed at baseline (V0), 6 months (V1) and 12 months (V2). The risk of moderate or severe exacerbation during follow up was assessed by Cox regression analysis, and the predictive capacity of both measurements was assessed by ROC curves and the DeLong test. Statistical significance was assumed at P<.05. Results: Of the 322 COPD patients initially recruited, 287 were followed up. At baseline, 28.0% were active smokers, and experienced moderate airflow limitation (mean FEV1 56.4%±17.0% predicted). Patients with at least one elevated T2 biomarker (n=125, 42.5%) were at increased risk of COPD exacerbation (HR 1.75, 95% CI 1.25–2.45, P=.001) and of shorter time to first COPD exacerbation. There was no difference between BEC and FeNO regarding the predictive capacity for moderate to severe exacerbation (AUC 0.584 vs 0.576, P=.183) but FeNO predicted severe episodes more accurately than BEC (AUC 0.607 vs 0.539, P<.05). Combining the two biomarkers enhanced the detection of moderate and severe COPD exacerbations. Conclusions: Both eosinophil count and FeNO have limited utility for predicting COPD exacerbations. Combining these T2 biomarkers could enhance the detection of future COPD exacerbations. (AU)

T2 Biomarkers as Predictors of Exacerbations of Chronic Obstructive Pulmonary Disease.

INTRODUCTION: Type 2 (T2) biomarkers such as blood eosinophil count (BEC) and FeNO have been related to a higher risk of exacerbations in COPD. It is unknown whether combining these biomarkers could be useful in forecasting COPD exacerbations. METHODS: COPD patients were enrolled in this prospective, multicenter, observational study and followed up for 1 year, during which BEC were analysed at baseline (V0) while FeNO analyses were performed at baseline (V0), 6 months (V1) and 12 months (V2). The risk of moderate or severe exacerbation during follow up was assessed by Cox regression analysis, and the predictive capacity of both measurements was assessed by ROC curves and the DeLong test. Statistical significance was assumed at P<.05. RESULTS: Of the 322 COPD patients initially recruited, 287 were followed up. At baseline, 28.0% were active smokers, and experienced moderate airflow limitation (mean FEV1 56.4%±17.0% predicted). Patients with at least one elevated T2 biomarker (n=125, 42.5%) were at increased risk of COPD exacerbation (HR 1.75, 95% CI 1.25-2.45, P=.001) and of shorter time to first COPD exacerbation. There was no difference between BEC and FeNO regarding the predictive capacity for moderate to severe exacerbation (AUC 0.584 vs 0.576, P=.183) but FeNO predicted severe episodes more accurately than BEC (AUC 0.607 vs 0.539, P<.05). Combining the two biomarkers enhanced the detection of moderate and severe COPD exacerbations. CONCLUSIONS: Both eosinophil count and FeNO have limited utility for predicting COPD exacerbations. Combining these T2 biomarkers could enhance the detection of future COPD exacerbations.

Un modelo de deprescripción prudente / A prudent deprescription model

La estructura terapéutica de los sistemas sanitarios descansa en gran medida sobre la prescripción, lo que genera una tendencia mantenida a sumar fármacos en la historia clínica del paciente. Por el lado contrario, destaca una ausencia significativa de estímulos sobre los profesionales para la reevaluación de prescripciones y la retirada de aquellas con un balance riesgo/beneficio negativo o neutro, lo que supone una desviación de recursos sanitarios hacia el mantenimiento de tratamientos inútiles, cuando no dañinos. La deprescripción, como la retirada meditada de medicación que complementa una prescripción prudente, está dirigida a frenar esta desviación injusta de recursos hacia prescripciones no beneficentes, cuando no maleficentes (AU)

The therapeutic structure of health systems relies heavily on medical prescription, which generates a marked tendency to add drugs to a patient's medical history. There is an absence of incentives for professionals to reassess prescriptions and withdraw those with a negative or neutral risk/benefit. This can create a deviation of medical resources to the maintenance of useless or even harmful treatments. Deprescribing, a process of thoughtful medication withdrawal that complements moderate prescribing, is aimed to stop this unfair deviation of resources towards non-beneficial, if not maleficent, prescription (AU)

[A prudent deprescription model]. / Un modelo de deprescripción prudente.

The therapeutic structure of health systems relies heavily on medical prescription, which generates a marked tendency to add drugs to a patient's medical history. There is an absence of incentives for professionals to reassess prescriptions and withdraw those with a negative or neutral risk/benefit. This can create a deviation of medical resources to the maintenance of useless or even harmful treatments. Deprescribing, a process of thoughtful medication withdrawal that complements moderate prescribing, is aimed to stop this unfair deviation of resources towards non-beneficial, if not maleficent, prescription.

Manejo urgente de la retención aguda de orina en hombres / Emergency management of acute urinary retention in men

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