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Complete Blood Count Ratios Predict Adverse Events After Total Joint Arthroplasty. | LitMetric

Complete Blood Count Ratios Predict Adverse Events After Total Joint Arthroplasty.

J Am Acad Orthop Surg

From the Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA (Jones), and the Department of Orthopaedic Surgery, Keck School of Medicine of the University of Southern California, Los Angeles, CA (Wier, Chen, Liu, Palmer, Mayfield, Heckmann).

Published: December 2024

AI Article Synopsis

  • The study evaluates the relationship between complete blood count-based ratios (CBRs) like NLR, MLR, PLR, and SII with postoperative complications, hospital length of stay (LOS), and mortality in patients undergoing total joint arthroplasty.
  • Using a large database, the research identified specific threshold values for these CBRs that are linked to increased risk of complications and prolonged LOS after surgery.
  • The findings highlight the significance of CBRs in predicting surgical outcomes, which can potentially guide preoperative assessments and improve patient management.

Article Abstract

Introduction: Complete blood count-based ratios (CBRs), including neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), platelet-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) are biomarkers associated with the proinflammatory surgical stress response. This study sought to determine whether preoperative CBRs are associated with postoperative complications, protracted hospital length of stay (LOS), and mortality after total joint arthroplasty, as well as establish threshold values for these outcomes for use in future investigations.

Methods: The Premier Healthcare Database was retrospectively queried for adult patients who underwent primary elective total hip arthroplasty or total knee arthroplasty (TKA). Approximate cut-point values for CBRs were identified by bootstrap simulation using the Youden index. Multivariable adjusted restricted cubic spline models using the predicted cut-point value as the threshold for odds of outcomes were created to identify a final threshold value associated with increased adjusted odds ratio (aOR) of study outcomes.

Results: A total of 32,868 total joint arthroplasties (THA: 12,807, TKA: 20,061) were identified. All measures predicted odds of aggregate postoperative complications (THA: NLR TV: 4.60 [aOR = 2.35], PLR TV: 163.4 [aOR = 1.32], MLR TV: 0.40 [aOR = 2.02], SII TV: 977.00 [aOR = 1.54]; TKA: NLR TV: 3.7 [aOR = 1.69], MLR TV: 0.41 [aOR = 1.62], PLR TV: 205.10 [aOR = 1.43], SII TV: 1,013.10 [aOR = 1.62]; all P < 0.05). A MLR > 0.40 [aOR = 1.54] P < 0.001) was associated with LOS ≥3 days after total hip arthroplasty while an NLR > 13.1 [aOR = 1.38] and an MLR > 0.41[aOR = 1.29] were associated with LOS ≥3 days after total knee arthroplasty (both P < 0.001). No association between inflammatory markers and inpatient mortality was observed.

Conclusion: Given CBRs' ability to both predict outcomes and identify patients with a proinflammatory phenotype, the findings of this study provide a framework for future investigations aimed at identifying and treating high-risk patients with immune-modulating therapies. Continued work to validate these findings by applying TVs to interventional clinical trials is needed before wide clinical adoption.

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Source
http://dx.doi.org/10.5435/JAAOS-D-24-00184DOI Listing

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