ArticleScientific reports2024
Identifying key risk factors for acute compartment syndrome in tibial diaphysis fracture patients.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- Acute compartment syndrome in tibial fractures: a meta-analysis.BMC musculoskeletal disorders · 2025Pooled it
- Ultrasound-derived tibia-fascia angle for noninvasive assessment of intracompartmental pressure in tibial plateau fractures.PloS one · 2026Observational
- Development and validation of a nomogram for predicting fasciotomy requirement in lower extremity arterial injuries: a retrospective case-control study.Journal of orthopaedics and traumatology : official journal of the Italian Society of Orthopaedics and Traumatology · 2025Article
- Shear wave elastography for noninvasive assessment of intracompartmental pressure in tibial plateau fractures: a cross-sectional study.Journal of orthopaedic surgery and research · 2025Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Acute compartment syndrome (ACS) is a severe orthopedic issue that, if left untreated, can result in lasting nerve and muscle damage or even necessitate amputation. The association between admission laboratory blood test indicators and the occurrence of ACS in patients with tibial diaphysis fractures is currently a subject of debate. The objective of this research was to identify the contributing factors for ACS in individuals suffering from tibial diaphysis fractures. In this retrospective study, we collected data on a total of 705 individuals from our hospital, comprising 86 ACS patients and 619 non-ACS patients with tibial diaphysis fractures. These participants were categorized into two distinct groups: the ACS group and the non-ACS group. Despite the inherent limitations associated with retrospective analyses, such as potential biases in data collection and interpretation, we conducted a comprehensive analysis of demographics, comorbidities, and admission lab results. Our analytical approach included univariate analysis, logistic regression, and receiver operating characteristic (ROC) curve analysis techniques, aiming to mitigate these limitations and provide robust findings. The statistical analysis revealed several predictors of ACS, including gender (p = 0.011, OR = 3.200), crush injuries (p = 0.004, OR = 4.622), lactic dehydrogenase (LDH) levels (p < 0.001, OR = 1.003), and white blood cell (WBC) count (p < 0.001, OR = 1.246). Interestingly, the study also found that certain factors, such as falls on the same level (p = 0.007, OR = 0.334) and cholinesterase (CHE) levels (p < 0.001, OR = 0.721), seem to provide a degree of protection against ACS. In order to better predict ACS, the ROC curve analysis was employed, which determined threshold values for LDH and WBC. The established cut-off points were set at 266.26 U/L for LDH and 11.7 × 10
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