Mean Platelet Volume to Platelet Count Ratio as a Predictor of Mortality in Unstable Pertrochanteric Fracture Treated with Short Proximal Femoral Anterograde Nail

Blister formation in acute compartment syndrome: Unraveling the underlying predictors

Blisters are a common complication of orthopedic trauma and can cause surgery delay and increase the risk of infection. This study aims to identify risk factors for blisters in patients with acute compartment syndrome (ACS). Our study collected data from 206 ACS patients admitted to 2 hospitals between November 2013 and January 2021. Patients were divided into 2 groups: the blister group (BG) and the control group (CG), based on the presence or absence of blisters. We conducted univariate analysis, logistic regression analysis, and receiver operating characteristic (ROC) curve analysis to identify any significant differences in demographics, comorbidities, and admission laboratory test results between the 2 groups. Our study found that the incidence of blisters in ACS patients was 21.8% (45 out of 206). Univariate analysis identified several factors that were significantly associated with blister formation. Logistic regression analysis showed that patients who developed ACS in the winter or spring (P = .007, OR = 2.690, 95% CI [1.308-5.534]), patients who received a referral (the process whereby patients are transferred between medical facilities for further evaluation and treatment attempts prior to admission to our hospital) (P = .009, OR = 4.235, 95% CI [1.432-12.527]), and patients with higher PLR (P = .036, OR = 1.005, 95% CI [1.000-1.009]) were independent risk factors for blisters. Additionally, a history of drinking (P = .039, OR = 0.027, 95% CI [0.046-0.927]) was found to be a protective factor for blister formation in these patients. Moreover, ROC curve analysis showed that a PLR value of 138 was the cutoff point for predicting the development of blisters in ACS patients. Our study identified seasonal factors (refer to these months like winter or spring), referral, and patients with higher PLR as independent risk factors, and a history of drinking as a protective factor for blister formation in ACS patients. These findings allow clinicians to individualize the evaluation of blister risk and perform early targeted therapies.

Can Platelets/Mean Platelet Volume Accurately Diagnose Periprosthetic Joint Infection? Revealing Their Actual Diagnostic Efficacy

Background

Currently, there is no single test indicator for diagnosing periprosthetic joint infection (PJI) with an acceptable level of sensitivity. Therefore, ratio indicators have been introduced to improve the accuracy of diagnostic algorithms. Platelet count /mean platelet volume (PMR) is reported to be a potential PJI diagnostic biomarker, but its clinical value for diagnosing PJI is still uncertain. This study aims to provide additional evidence to support the effectiveness of PMR in accurately diagnosing PJI.

Methods

This study recruited 116 patients with PJI and 137 patients with aseptic loosening, divided them into PJI group and AL group. Collect subjects' preoperative laboratory indicators such as ESR, CRP, PLT, MPV, etc. The area under the curve (AUC) was calculated by plotting the receiver operating characteristic (ROC) curve to determine the diagnostic efficacy of PMR.

Results

ESR, CRP, PLT, and PLT/MPV were significantly increased in the PJI group, while MPV levels were decreased (both P< 0.001). The AUC of the PMR was 0.752, and the optimal cut-off value for diagnosing chronic PJI was determined to be 27.8 based on the Youden index. The sensitivity and specificity for diagnosing PJI were 79.3% and 47.9%, respectively, with a positive predictive value of 68.27%, a negative predictive value of 69.80%, and a diagnostic odds ratio of 4.97. The AUC (0.752) of the ratio biomarker was lower than that of ESR (0.825) and CRP (0.900). After predictive model calculation, the combination of PMR, CRP, and ESR had an AUC value of 0.910, with a sensitivity of 84.5% and a specificity of 84.7%, showing good discriminative ability.

Conclusion

Compared with traditional biomarkers ESR and CRP, the value of the PMR for diagnosing PJI is not significant, but it can be used as an auxiliary indicator for PJI diagnosis in combination with other indicators (P<0.001).