GOLD Classifications, COPD Hospitalization, and All-Cause Mortality in Chronic Obstructive Pulmonary Disease: The HUNT Study.

Purpose: The Global Initiative for Chronic Obstructive Lung Disease (GOLD) has published three classifications of COPD from 2007 to 2017. No studies have investigated the ability of these classifications to predict COPD-related hospitalizations. We aimed to compare the discrimination ability of the GOLD 2007, 2011, and 2017 classifications to predict COPD hospitalization and all-cause mortality. Patients and Methods: We followed 1300 participants with COPD aged ≥40 years who participated in the HUNT Study (1995-1997) through to December 31, 2015. Survival analysis and time-dependent area under receiver operating characteristics curves (AUC) were used to compare the discrimination abilities of the GOLD classifications. Results: Of the 1300 participants, 522 were hospitalized due to COPD and 896 died over 20.4 years of follow-up. In adjusted models, worsening GOLD 2007, GOLD 2011, or GOLD 2017 categories were associated with higher hazards for COPD hospitalization and all-cause mortality, except for the GOLD 2017 classification and all-cause mortality (ptrend=0.114). In crude models, the AUCs (95% CI) for the GOLD 2007, GOLD 2011, and GOLD 2017 for COPD hospitalization were 63.1 (58.7-66.9), 60.9 (56.1-64.4), and 56.1 (54.0-58.1), respectively, at 20-years' follow-up. Corresponding estimates for all-cause mortality were 57.0 (54.8-59.1), 54.1 (52.1-56.0), and 52.6 (51.0-54.3). The differences in AUCs between the GOLD classifications to predict COPD hospitalization and all-cause mortality were constant over the follow-up time. Conclusion: The GOLD 2007 classification was better than the GOLD 2011 and 2017 classifications at predicting COPD hospitalization and all-cause mortality.

Author Correction: Systematic assessment of prescribed medications and short-term risk of myocardial infarction - a pharmacopeia-wide association study from Norway and Sweden.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Systematic assessment of prescribed medications and short-term risk of myocardial infarction - a pharmacopeia-wide association study from Norway and Sweden.

Wholesale, unbiased assessment of Scandinavian electronic health-care databases offer a unique opportunity to reveal potentially important undiscovered drug side effects. We examined the short-term risk of acute myocardial infarction (AMI) associated with drugs prescribed in Norway or Sweden. We identified 24,584 and 97,068 AMI patients via the patient- and the cause-of-death registers and linked to prescription databases in Norway (2004-2014) and Sweden (2005-2014), respectively. A case-crossover design was used to compare the drugs dispensed 1-7 days before the date of AMI diagnosis with 15-21 days' time -window for all the drug individually while controlling the receipt of other drugs. A BOLASSO approach was used to select drugs that acutely either increase or decrease the apparent risk of AMI. We found 48 drugs to be associated with AMI in both countries. Some antithrombotics, antibiotics, opioid analgesics, adrenergics, proton-pump inhibitors, nitroglycerin, diazepam, metoclopramide, acetylcysteine were associated with higher risk for AMI; whereas angiotensin-II-antagonists, calcium-channel blockers, angiotensin-converting-enzyme inhibitors, serotonin-specific reuptake inhibitors, allopurinol, mometasone, metformin, simvastatin, levothyroxine were inversely associated. The results were generally robust in different sensitivity analyses. This study confirms previous findings for certain drugs. Based on the known effects or indications, some other associations could be anticipated. However, inverse associations of hydroxocobalamin, levothyroxine and mometasone were unexpected and needs further investigation. This pharmacopeia-wide association study demonstrates the feasibility of a systematic, unbiased approach to pharmacological triggers of AMI and other diseases with acute, identifiable onsets.