Methods: The study population consists of two independent cohorts of stable patients undergoing coronary angiography with suspected or known CAD: as derivation cohort, the ongoing biomarker registry BioPROSPECTIVE with n=1,766 enrolled patients between 2010 and 2013(median age 70.1 yrs; 30.8% females); and as validation cohort, the Ludwigshafen Risk and Cardiovascular Health (LURIC) Study with n=3,299 patients(median age 63.5 yrs; 30.3% females). In the derivation cohort 235 (13.3%) patients were known to be deceased by 08/2018. In the validation cohort 760 (23.0%) patients died within a median follow-up time of 7.75 years. 25-OH vitamin D levels were measured by commercial assays. Vitamin D deficiency was defined as 25-OH vitamin D levels =20 ng/mL. Daily averaged data on six weather conditions of the 180 days prior to enrolment were collected for each patient from the weather station located closest to the respective study centre. Using air pressure, precipitation height, sunshine duration, temperature, relative humidity, and vapour pressure a weather model was constructed that significantly correlated with vitamin D levels (r=0.37; p<0.001).
Results: In the derivation cohort, median vitamin D levels were lower in non-survivors (13.3 [9.65-19.65] ng/mL) than in survivors (15.70 [10.7-22.65] ng/mL; p<0.001). Vitamin D predicted all-cause mortality with an area under the receiver operator characteristic curve (AUROC) of 0.576 (CI: 0.54-0.62). Adding the weather model to vitamin D significantly improved the AUROC to 0.601 (CI: 0.56-0.64; p=0.031). The vitamin D/weather model combination enhanced the prognostic value of the ESC SCORE to predict mortality (AUROC=0.571 [CI: 0.53-0.61] vs. 0.628 [CI: 0.59-0.67]; p=0.004). Comparable results were observed in the validation cohort. Here, vitamin D deficiency predicted mortality with a hazard ratio (HR) of 1.89 (CI: 1.59-2.26) after adjustment for ESC SCORE. Adding the weather model improved this HR to 1.92 (1.62-2.32). Reclassification analyses support the additive prognostic information of weather conditions with a continuous net reclassification improvement of 0.114 ([0.033-0.194]; p=0.006) if adding the weather model to vitamin D as base model for predicting mortality.
Conclusions: Different weather conditions show a significant impact on vitamin D levels in stable patients. Adding data on weather conditions improve the risk stratification by vitamin D for predicting mortality in stable CAD patients.