Identification of risk factors and clinical outcomes for symmetric peripheral gangrene: A new scoring system using a common data model database

Author:

Deslivia Maria Florencia12,Kim Do-Hoon34,Lee Suk-Joong5,Kim Hee-June1,Kholinne Erica6,Lee Hyun-Joo1ORCID

Affiliation:

1. Department of Orthopaedic Surgery, Kyungpook National University School of Medicine and Hospital, Daegu, Republic of Korea

2. Department of Orthopedic Surgery, St Carolus Hospital, Jakarta, Indonesia

3. Medical Big Data Research Center, Kyungpook National University Hospital, Daegu, Republic of Korea

4. Department of Nuclear Medicine, Daejeon Eulji Medical Center, Daejeon, Republic of Korea

5. Department of Orthopaedic Surgery, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Changwon, Republic of Korea

6. Department of Orthopedic Surgery, Faculty of Medicine, St Carolus Hospital, Universitas Trisakti, Jakarta, Indonesia

Abstract

Background: Symmetrical peripheral gangrene (SPG) is a destructive clinical condition where amputation is often the final treatment option. We aimed to identify the predictors of SPG using the common data model (CDM) and propose a new scoring system for predicting hospitalized patients at risk of developing SPG. Methods: A cohort of patients treated with intravenous noradrenaline, epinephrine, and vasopressin between 2011 and 2020 was retrospectively analyzed using the CDM database. The main outcome was amputation performed as a resuscitation measure. We investigated risk factors including demographic characteristics, comorbidities, and preoperative laboratory values. Based on demographic variables such as age and sex, a 1:10 propensity score matching (PSM) was performed. The odds ratio (OR) was calculated using logistic regression analysis. Results: Amputation was performed in 308 (0.4%) patients out of a cohort of 73,902 patients. Age, sex, hypertension, diabetes mellitus (DM), renal disease (RD), heart failure, anemia, hypercholesterolemia, peripheral vascular disease (PVD), and laboratory markers such as albumin, eosinophils, hematocrit, lymphocytes, monocytes, neutrophils, ESR, aPTT, creatinine, and BUN were statistically significant. Logistic regression analysis revealed statistically significant differences in DM (OR 5.51), RD (OR 2.90), PVD (OR 9.67), and cerebrovascular disease (CVD) (OR 0.49). Compared to the group without amputation, logistic regression analysis after matching the age and sex group with 1:10 PSM showed statistically significant results in DM (OR 3.59), RD (OR 2.59), PVD (OR 7.76), and CVD (OR 0.40). Conclusion: Early recognition of high-risk patients may help medical providers prevent severe outcomes, including amputation surgery.

Funder

Ministry of Health & Welfare

Publisher

SAGE Publications

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