Biomedical Evaluation of Early Chronic Kidney Disease in the Air Force: Building a Predictive Model from the Taiwan Military Health Service

Po-Jen Hsiao; Ruei-Lin Wang; Fu-Kang Hu; Fu-Ru Tsai; Chih-Chien Chiu; Wen-Fang Chiang; Kun-Lin Wu; Yuan-Kuei Li; Jenq-Shyong Chan; Chi-Ming Chu; Chi-Wen Chang

doi:10.3390/bioengineering11030231

Biomedical Evaluation of Early Chronic Kidney Disease in the Air Force: Building a Predictive Model from the Taiwan Military Health Service

Bioengineering (Basel). 2024 Feb 28;11(3):231. doi: 10.3390/bioengineering11030231.

Authors

Po-Jen Hsiao^{1

2

3

4}, Ruei-Lin Wang⁵, Fu-Kang Hu⁶, Fu-Ru Tsai^{7

8}, Chih-Chien Chiu^{9

10}, Wen-Fang Chiang^{1

2}, Kun-Lin Wu^{1

2}, Yuan-Kuei Li^{11

12}, Jenq-Shyong Chan^{1

2}, Chi-Ming Chu^{6

13

14

15

16

17

18

19}, Chi-Wen Chang^{8

20}

Affiliations

¹ Division of Nephrology, Department of Medicine, Armed Forces Taoyuan General Hospital, Taoyuan 325, Taiwan.
² Division of Nephrology, Department of Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei 114, Taiwan.
³ Institute of Cellular and System Medicine, National Health Research Institutes, Miaoli County 350, Taiwan.
⁴ Department of Life Sciences, National Central University, Taoyuan 320, Taiwan.
⁵ Department of Medicine, Armed Forces Taoyuan General Hospital, Taoyuan 325, Taiwan.
⁶ School of Public Health, National Defense Medical Center, Taipei 114, Taiwan.
⁷ Department of Nursing, Armed Forces Taoyuan General Hospital, Taoyuan 325, Taiwan.
⁸ School of Nursing, College of Medicine, Chang Gung University, Taoyuan 333, Taiwan.
⁹ Division of Infectious Disease, Department of Internal Medicine, Taoyuan Armed Forces General Hospital, Taoyuan 325, Taiwan.
¹⁰ Division of Infectious Disease, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei 114, Taiwan.
¹¹ Division of Colorectal Surgery, Department of Surgery, Taoyuan Armed Forces General Hospital, Taoyuan 325, Taiwan.
¹² Department of Biomedical Sciences and Engineering, National Central University, Taoyuan 320, Taiwan.
¹³ Graduate Institute of Life Sciences, National Defense Medical Center, Taipei 114, Taiwan.
¹⁴ Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei 114, Taiwan.
¹⁵ Department of Public Health, School of Public Health, China Medical University, Taichung 404, Taiwan.
¹⁶ Department of Public Health, Kaohsiung Medical University, Kaohsiung 807, Taiwan.
¹⁷ Big Data Research Center, Fu-Jen Catholic University, New Taipei City 242, Taiwan.
¹⁸ Division of Biostatistics and Medical Informatics, Department of Epidemiology, National Defense Medical Center, Taipei 114, Taiwan.
¹⁹ Department of Healthcare Administration and Medical Informatics, Kaohsiung Medical University, 100, Shi-Chuan 1st Road, Kaohsiung 807, Taiwan.
²⁰ Division of Pediatric Endocrinology & Genetics, Department of Pediatrics, Chang-Gung Memorial Hospital, Taoyuan 333, Taiwan.

Abstract

Objective: Chronic kidney disease (CKD) is one of the most common diseases worldwide. The increasing prevalence and incidence of CKD have contributed to the critical problem of high medical costs. Due to stressful environments, aircrew members may have a high risk of renal dysfunction. A better strategy to prevent CKD progression in Air Force personnel would be to diagnosis CKD at an early stage. Since few studies have been conducted in Taiwan to examine the long-term trends in early CKD in Air Force aircrew members, this study is highly important. We investigated the prevalence of CKD and established a predictive model of disease variation among aircrew members.

Materials and methods: In this retrospective study, we included all subjects who had received physical examinations at a military hospital from 2004 to 2010 and who could be tracked for four years. The Abbreviated Modification of Diet in Renal Disease Formula (aMDRD) was used to estimate the glomerular filtration rate (GFR) and was combined with the National Kidney Foundation/ Kidney Disease Outcomes Quality Initiative (NKF-K/DOQI) to identify CKD patients.

Results: A total of 212 aircrew members were assessed. The results showed that the prevalence of CKD was 3.8%, 9.4%, 9.0%, and 9.4% in each of the four years. According to the logistic regression analysis, abnormal urobilinogen levels, ketones, and white blood cell (WBC) counts in urine and a positive urine occult blood test increased the risk of CKD. A positive urine occult blood test can be used to predict the future risk of CKD. Moreover, the generalized estimating equation (GEE) model showed that a greater risk of CKD with increased examination time, age and seniority had a negative effect. In conclusion, abnormal urobilinogen levels, ketones, and urine WBC counts in urine as well as a positive urine occult blood test might serve as independent predictors for CKD.

Conclusion: In the future, we can focus not only on annual physical examinations but also on simple and accurate examinations, such as urine occult blood testing, to determine the risk of CKD and prevent its progression in our aircrew members.

Keywords: Air Force; chronic kidney disease; military health; predictive model.

Abstract

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