Second running title: Prediction of COPD-related exacerbations.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is the fourth most important cause of death in high-income countries. Inappropriate use of COPD inhaled therapy, including the low adherence (only 10% to 40% of patients reporting an adequate compliance) may shrink or even nullify the proven benefits of these medications. As such, an accurate prediction algorithm to assess at national level the risk of COPD exacerbation might be relevant for general practictioners (GPs) to improve patient's therapy.

METHODS: We formed a cohort of patients aged 45 years or older being diagnosed with COPD in the period between January 2013 to December 2021. Each patient was followed until occurrence of COPD exacerbation up to the end of 2021. Sixteen determinants were adopted to assemble the CopdEX(CEX)-Health Search(HS)core, which was therefore developed and validated though the related two sub-cohorts.

RESULTS: We idenfied 63763 patients aged 45 years or older being diagnosed with COPD (mean age: 67.8 (SD:11.7); 57.7% males).When the risk of COPD exacerbation was estimated via CEX-HScore, its predicted value was equal to 14.22% over a 6-month event horizon. Discrimination accuracy and explained variation were equal to 66% (95% CI: 65-67%) and 10% (95% CI: 9-11%), respectively. The calibration slope did not significantly differ from the unit (p=0.514).

CONCLUSIONS: The CEX-HScore was featured by fair accuracy for prediction of COPD-related exacerbations over a 6-month follow-up. Such a tool might therefore support GPs to enhance COPD patients' care, and improve their outcomes by facilitating personalized approaches through a score-based decision support system.