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Purpose <p>This study aimed to identify both clinical and meteorological risk factors for surgical site infection (SSI) following spine fusion surgery (SFS), with a focus on integrating medical big data and weather data.</p> Methods <p>We retrospectively analyzed data from 10,880 patients who underwent SFS between January 2013 and November 2022 at eight university-affiliated hospitals. Clinical data were sourced from the Catholic Medical Center Clinical Data Warehouse, and regional meteorological data were obtained from the Korea Meteorological Administration. SSI was defined based on diagnostic codes and antibiotic prescriptions within three months postoperatively. Risk factors were assessed using logistic regression and correlation analyses.</p> Results <p>The overall SSI incidence was 4.66% (507/10,880 cases). Significant clinical risk factors included older age (OR = 1.91 for ≥ 80 vs. 60–69 years, <i>p</i> &lt; 0.01), severe obesity (BMI ≥ 35; OR = 2.06, <i>p</i> = 0.02), and longer operative time (OR = 4.00 for ≥ 300 vs. &lt;120&#xa0;min, <i>p</i> &lt; 0.01). Surgeries on Wednesdays showed lower SSI risk (OR = 0.67, <i>p</i> &lt; 0.01, survives Bonferroni correction). Climatic factors demonstrated significant associations: 7-day average temperature (<i>r</i> = 0.51, <i>p</i> &lt; 0.01), 7-day maximum temperature (<i>r</i> = 0.56, <i>p</i> &lt; 0.01), and 7-day average humidity (<i>r</i> = 0.65, <i>p</i> &lt; 0.01) correlated with SSI incidence. Maximum daily temperatures &gt; 30&#xa0;°C significantly increased SSI risk (OR = 2.03, 95% CI: 1.06–3.86, <i>p</i> = 0.03, survives Bonferroni correction). Bayesian generalized additive mixed models confirmed non-linear dose-response relationships with inflection points near 25&#xa0;°C for temperature and 80% for humidity, independent of hospital and temporal effects.</p> Conclusion <p>This large-scale study is the first to integrate clinical and climatic big data in assessing SSI risk after SFS. In addition to established clinical factors, environmental conditions such as temperature and humidity were associated with infection risk. These findings suggest that weather-related factors should be considered in perioperative infection control strategies. Further prospective studies are needed to validate these results and guide clinical practice.</p>

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Climatic and clinical risk factors for surgical site infection following spine fusion surgery: a large-scale big data analysis

  • 期刊论文

  • 发表日期：

    2026年1月10日

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  • Myung-Sup Ko,
  • Soyeong Park,
  • Young-Hoon Kim,
  • Yohan Ko,
  • Kee-Yong Ha,
  • Hyung-Youl Park,
  • Young-Il Ko,
  • Yunseong Kim,
  • Sangjun Park,
  • Youngho Lee,
  • Sang-Il Kim

摘要

Purpose

This study aimed to identify both clinical and meteorological risk factors for surgical site infection (SSI) following spine fusion surgery (SFS), with a focus on integrating medical big data and weather data.

Methods

We retrospectively analyzed data from 10,880 patients who underwent SFS between January 2013 and November 2022 at eight university-affiliated hospitals. Clinical data were sourced from the Catholic Medical Center Clinical Data Warehouse, and regional meteorological data were obtained from the Korea Meteorological Administration. SSI was defined based on diagnostic codes and antibiotic prescriptions within three months postoperatively. Risk factors were assessed using logistic regression and correlation analyses.

Results

The overall SSI incidence was 4.66% (507/10,880 cases). Significant clinical risk factors included older age (OR = 1.91 for ≥ 80 vs. 60–69 years, p < 0.01), severe obesity (BMI ≥ 35; OR = 2.06, p = 0.02), and longer operative time (OR = 4.00 for ≥ 300 vs. <120 min, p < 0.01). Surgeries on Wednesdays showed lower SSI risk (OR = 0.67, p < 0.01, survives Bonferroni correction). Climatic factors demonstrated significant associations: 7-day average temperature (r = 0.51, p < 0.01), 7-day maximum temperature (r = 0.56, p < 0.01), and 7-day average humidity (r = 0.65, p < 0.01) correlated with SSI incidence. Maximum daily temperatures > 30 °C significantly increased SSI risk (OR = 2.03, 95% CI: 1.06–3.86, p = 0.03, survives Bonferroni correction). Bayesian generalized additive mixed models confirmed non-linear dose-response relationships with inflection points near 25 °C for temperature and 80% for humidity, independent of hospital and temporal effects.

Conclusion

This large-scale study is the first to integrate clinical and climatic big data in assessing SSI risk after SFS. In addition to established clinical factors, environmental conditions such as temperature and humidity were associated with infection risk. These findings suggest that weather-related factors should be considered in perioperative infection control strategies. Further prospective studies are needed to validate these results and guide clinical practice.