Volume 4, Issue 3

This report describes the anesthetic management of four elderly patients with hip fractures complicated by different types of severe cardiac disease, including severe mitral stenosis, post–myocardial infarction status, severe pulmonary hypertension, and acute exacerbation of chronic heart failure. All patients underwent individualized, ultrasound-guided precision anesthesia strategies, incorporating ultrasound-guided vascular access, nerve blocks, neuraxial anesthesia, and dynamic perioperative assessment using transthoracic echocardiography. Management followed a pathophysiology-oriented approach, emphasizing multimodal analgesia and multidisciplinary collaboration. All four patients completed the perioperative period uneventfully. This report aims to explore individualized anesthetic strategies for extremely high-risk patients in the era of visualization-based medicine.

Objective: Periprosthetic joint infection (PJI) is a serious complication after total joint arthroplasty. Because diagnosis remains difficult, readily available serum biomarkers may provide a practical adjunct. We evaluated whether combining conventional inflammatory markers with cell-count-derived indices improved diagnostic performance compared with individual markers. Methods: This single-center retrospective cohort study included 176 patients who underwent hip or knee revision between May 2017 and March 2022. Eighty-six patients were diagnosed with PJI and 90 with aseptic loosening (AL). PJI was defined according to the Musculoskeletal Infection Society (MSIS) criteria. Preoperative C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), and pan-immune-inflammation value (PIV) were compared between groups. Receiver operating characteristic (ROC) analyses were performed for individual markers and logistic-regression-based combinations. Results: CRP, ESR, PLR, NLR, and PIV were significantly higher in the PJI group, whereas LMR was significantly lower (all P<0.005). ESR (AUC=0.843, 95% CI: 0.781-0.894) and CRP (AUC=0.833, 95% CI: 0.769-0.885) showed the highest discrimination. The AUCs for PLR, PIV, NLR, and LMR were 0.729, 0.697, 0.682, and 0.628, respectively. CRP+ESR achieved an AUC of 0.856 (95% CI: 0.795-0.904), and CRP+ESR+PLR achieved an AUC of 0.860 (95% CI: 0.800-0.908). The three-marker model increased sensitivity to 86.05% but reduced specificity to 73.33%, indicating a modest numerical gain in discrimination with a sensitivity-specificity trade-off. Conclusions: The combined use of CRP, ESR, and PLR should be considered a supplementary tool for current PJI diagnostic criteria, rather than a substitute.