Hospital admissions due to diseases of arteries and veins peaked at physiological equivalent temperature -10 to 10 °C in Germany in 2009-2011

We aimed to understand relationships of the weather as biometeorological and hospital admissions due to diseases of arteries and veins by subtypes, which have been scarcely studied, in a national setting in recent years. This is an ecological study. Ten percent of daily hospital admissions from the included hospitals (n = 1,618) across Germany that were available between 1 January 2009 and 31 December 2011 (n = 5,235,600) were extracted from Statistisches Bundesamt, Germany. We identified I70-I79 Diseases of arteries, arterioles and capillaries and I80-I89 Diseases of veins, lymphatic vessels and lymph nodes by International Classification of Diseases version 10 as the study outcomes. Daily weather data from 64 weather stations that covered 13 German states including air temperature, humidity, wind speed, cloud cover, radiation flux and vapour pressure were obtained and generated into physiologically equivalent temperature (PET). Two-way fractional-polynomial prediction was plotted with 95 % confidence intervals. For most of the subtypes from diseases of arteries and veins, hospital admissions slightly peaked in spring and dropped when PET was at 10 °C. There were no other large differences across 12 months. Admissions of peripheral vascular diseases, arterial embolism and thrombosis, phlebitis and thrombophlebitis, oesophageal varices and nonspecific lymphadenitis peaked when PET was between 0 and -10 °C, while others peaked when PET was between 0 and 10 °C. More medical resources could have been needed on days when PETs were at -10 to 10 °C than on other days. Adaptation to such weather change for health professionals and the general public would seem to be imperative.

Data-driven discovery of seasonally linked diseases from an Electronic Health Records system

BACKGROUND

Patterns of disease incidence can identify new risk factors for the disease or provide insight into the etiology. For example, allergies and infectious diseases have been shown to follow periodic temporal patterns due to seasonal changes in environmental or infectious agents. Previous work searching for seasonal or other temporal patterns in disease diagnosis rates has been limited both in the scope of the diseases examined and in the ability to distinguish unexpected seasonal patterns. Electronic Health Records (EHR) compile extensive longitudinal clinical information, constituting a unique source for discovery of trends in occurrence of disease. However, the data suffer from inherent biases that preclude an identification of temporal trends.

METHODS

Motivated by observation of the biases in this data source, we developed a method (Lomb-Scargle periodograms in detrended data, LSP-detrend) to find periodic patterns by adjusting the temporal information for broad trends in incidence, as well as seasonal changes in total hospitalizations. LSP-detrend can sensitively uncover periodic temporal patterns in the corrected data and identify the significance of the trend. We apply LSP-detrend to a compilation of records from 1.5 million patients encoded by ICD-9-CM (International Classification of Diseases, Ninth Revision, Clinical Modification), including 2,805 disorders with more than 500 occurrences across a 12 year period, recorded from 1.5 million patients.

RESULTS AND CONCLUSIONS

Although EHR data, and ICD-9 coded records in particular, were not created with the intention of aggregated use for research, these data can in fact be mined for periodic patterns in incidence of disease, if confounders are properly removed. Of all diagnoses, around 10% are identified as seasonal by LSP-detrend, including many known phenomena. We robustly reproduce previous findings, even for relatively rare diseases. For instance, Kawasaki disease, a rare childhood disease that has been associated with weather patterns, is detected as strongly linked with winter months. Among the novel results, we find a bi-annual increase in exacerbations of myasthenia gravis, a potentially life threatening complication of an autoimmune disease. We dissect the causes of this seasonal incidence and propose that factors predisposing patients to this event vary through the year.