Clear skies and sunny days predict an increase in full-body CT scans

In a bizarre twist on the science of interconnectedness between people and their environment, medical researchers in Switzerland have uncovered a correlation between the incidence of multiple injury CT scans performed in their hospital, and the weather.

Polytrauma patients are those who have suffered multiple traumatic injuries at once and require whole-body CT scans – that typically include large areas such as the chest, abdomen and pelvis – for immediate analysis and follow-up scans.

Researchers at the University of Basel in Switzerland have discovered that high temperatures and fewer clouds were associated with an increase in polytrauma scans performed at the hospital.

The scientists made the discovery by analysing data collected on 4,613 polytrauma CT scans at the hospital from 2011 to 2020 and comparing it to measurements of weather data including average temperature, total cloud cover, wind speed, sunshine duration and precipitation, over the same time period. The median age of patients was 57 years, and 66% were male.

“Trauma accounts for a large portion of hospital admissions, and since polytrauma is particularly time-consuming and unpredictable, we wanted to investigate the association between weather fluctuations and the number of polytrauma CTs performed at our hospital,” says study co-author Martin Segeroth,  a radiology resident in the Department of Radiology and Nuclear Medicine at the University of Basel.

“Many hospital admission rates, most notably those for respiratory and cardiovascular disease, are linked to weather variations.”

Statistical analysis of the weather data demonstrated that more polytrauma CTs were performed during summer than winter, and more occurred during weather conditions that involved more sunshine and UV, less wind and fewer clouds.

Polytrauma ct scans incident compared to various weather conditions - graphs
The data showed a positive correlation between number of polytrauma CTs and increased temperature (A), sunshine (D) and UV-light amount (E), a negligible correlation between number of polytrauma CTs and precipitation (B) and negative correlation between number of polytrauma CTs and wind speed (C) and cloudiness (F). Credit: RSNA/Martin Segeroth

“The amount of cloud cover and temperature were the most important parameters for predicting daily polytrauma CT occurrence,” says Segeroth.

Segeroth is quick, however, to reinforce the old adage: correlation does not equal causation, and the exact relationship and driving cause behind the apparent relationship isn’t certain.

“One speculation is that in the summer, people are engaging in more outdoor activities—for instance sports—whereas in winter people are less often outside,” says Segeroth. “Although we don’t have an explanation for it, we’ve observed a strong association.”

Using machine learning algorithms, the team focussed on predicting future polytrauma CT scan incidence. The models were able to predict 73% of the days when polytrauma CT use was higher than average and 83% of days where polytrauma use was lower than average.

Read more: We’re in the largest boom in the application and development of AI for science in history

“These results imply that our model could predict a higher-than-normal demand for polytrauma CT scanning on 253 days of a calendar year,” says Segeroth.

The tool could soon be incorporated into the hospital’s intranet to automatically alert staff of times when higher than average incidence of polytrauma CTs might occur.

“Our results demonstrate that it’s possible to partially forecast normal or above normal daily numbers of polytrauma CT volume based on weather data,” says Segeroth. “Any approach that helps us be more prepared for polytrauma patients would improve resource planning in the ER and Radiology Department.”

Please login to favourite this article.