Value-based Healthcare: Increasing Value by Reducing Implant-related Health Care Costs

In Vivo Assessment of a Triple Periodic Minimal Surface Based Biomimmetic Gyroid as an Implant Material in a Rabbit Tibia Model

Biomimetic approaches to implant construction are a rising frontier in implantology. Triple Periodic Minimal Surface (TPMS)-based additively manufactured gyroid structures offer a mean curvature of zero, rendering this structure an ideal porous architecture. Previous studies have demonstrated the ability of these structures to effectively mimic the mechanical cues required for optimal implant construction. The porous nature of gyroid materials enhances bone ingrowth, thereby improving implant stability within the body. This enhancement is attributed to the increased surface area of the gyroid structure, which is approximately 185% higher than that of a dense material of the same form factor. This larger surface area allows for enhanced cellular attachment and nutrient circulation facilitated by the porous channels. This study aims to evaluate the biological performance of a gyroid-based Ti6Al-4V implant material compared to a dense alloy counterpart. Cellular viability was assessed using the lactate dehydrogenase (LDH) assay, which demonstrated that the gyroid surface allowed marginally higher viability than dense material. The in vivo integration was studied over 6 weeks using a rabbit tibia model and characterized using X-ray, micro-CT, and histopathological examination. With a metal volume of 8.1%, the gyroid exhibited a bone volume/total volume (BV/TV) ratio of 9.6%, which is 11-fold higher than that of dense metal (0.8%). Histological assessments revealed neovascularization, in-bone growth, and the presence of a Haversian system in the gyroid structure, hinting at superior osteointegration.

Anemia Severity and the Risks of Postoperative Complications Following Total Ankle Arthroplasty

BACKGROUND

Although studies have demonstrated the effect of anemia severity on postoperative complications after arthroplasties of the shoulder, hip, and knee, no studies have investigated the effect on total ankle arthroplasty (TAA). The objective was to determine the influence of preoperative anemia severity on complications following TAA.

METHODS

The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) was queried from 2006 to 2019 for patients undergoing TAA. Utilizing the World Health Organization (WHO) definitions of anemia, patients were stratified into 3 cohorts: nonanemia (hematocrit >36% for women, >39% for men), mild anemia (hematocrit 33%-36% for women, 33%-39% for men), and moderate to severe anemia (hematocrit <33% for both women and men). Demographics, comorbidities, length of stay, and short-term (30-day) postoperative complications were compared between groups. Bivariate analyses, including χ2 and analysis of variance, and multivariable logistical regression were performed.

RESULTS

After exclusion, 1490 patients (1313 nonanemia [88.1%], 154 mild anemia [10.3%], and 23 moderate/severe anemia [1.6%]) were included. Increasing severity of anemia was associated with an increased average hospital length of stay (1.84 vs 2.19 vs 2.78 days, P < .001) and rate of reoperation (0.38% vs 3.90% vs 4.35%, P < .001). There was a statistically significant increase in wound disruptions (0.15% vs 1.95% vs 4.35%, P = .001), minor complications (1.52% vs 4.55% vs 8.70%, P = .008), major complications (1.98% vs 5.84% vs 4.35%, P < .033), and any complications (3.50% vs 10.39% vs 13.04%, P = .001) between groups. Multivariate analysis identified mild and moderate/severe anemia as a predictor of reoperation and extended length of stay (P ≤ .033).

DISCUSSION

Preoperative anemia is a modifiable risk factor for medical and surgical complications within 30 days of TAA. Medical optimization prior to surgical intervention is necessary in patients undergoing TAA.

LEVEL OF EVIDENCE

Level III: Retrospective comparative study.

Outcomes and Cost Comparison Between Generic and Conventional Cephalomedullary Nails in the Treatment of Peritrochanteric Femur Fractures

INTRODUCTION

Although generic orthopaedic implants have been available for several years, there has been slow adoption of this cost-saving option. We hypothesize equivalent outcomes between generic and conventional cephalomedullary nails (CMN) in the treatment of peritrochanteric femur fractures.

METHODS

We evaluated 419 patients undergoing CMN for peritrochanteric femur fracture with a minimum 6-month follow-up. Demographic data, radiographic assessment, and clinical outcomes were compared.

RESULTS

Ninety patients were treated with generic implants and 329 patients with conventional implants. The overall complication rate was 7.0%, with a revision surgery rate of 5.4%. No significant differences were seen in demographic variables or surgical factors. Although there was an increased incidence of postoperative infections with conventional nails (P = 0.045), no significant differences were seen in other complications.

CONCLUSION

At our institution, generic nails cost approximately 38% less than their conventional counterparts. There seems to be no increased rate of implant-associated complications with the use of generic CMNs, although allowing for notable cost savings.

Thresholds for meaningful improvement in WOMAC scores need to be adjusted to patient characteristics after hip and knee replacement

PURPOSE

To calculate unstratified and patient-specific meaningful improvement (MI) and patient acceptable symptom states (PASS) for the WOMAC total score in patients after total hip (THR) or total knee replacement (TKR).

METHODS

A retrospective observational cohort study. Anchor-based receiver operator characteristics curves were used to estimate MI and PASS thresholds.

RESULTS

Recovery paths were specific to individual characteristics of patients. An unstratified 12-months MI threshold of 28.1 (PASS: 13.3) and 17.8 (PASS: 15.8) for patients after THR and TKR, respectively, would unfairly detect critical recovery paths.

CONCLUSIONS

Thresholds for treatment success need to be as patient-specific as possible.

Machine Learning Predicts Femoral and Tibial Implant Size Mismatch for Total Knee Arthroplasty

Background

Despite reasonable accuracy with preoperative templating, the search for an optimal planning tool remains an unsolved dilemma. The purpose of the present study was to apply machine learning (ML) using preoperative demographic variables to predict mismatch between templating and final component size in primary total knee arthroplasty (TKA) cases.

Methods

This was a retrospective case-control study of primary TKA patients between September 2012 and April 2018. The primary outcome was mismatch between the templated and final implanted component sizes extracted from the operative database. The secondary outcome was mismatch categorized as undersized and oversized. Five supervised ML algorithms were trained using 6 demographic features. Prediction accuracies were obtained as a metric of performance for binary mismatch (yes/no) and multilevel (undersized/correct/oversized) classifications.

Results

A total of 1801 patients were included. For binary classification, the best-performing algorithm for predicting femoral and tibial mismatch was the stochastic gradient boosting model (area under the curve: 0.76/0.72, calibration intercepts: 0.05/0.05, calibration slopes: 0.55/0.7, and Brier scores: 0.20/0.21). For multiclass classification, the best-performing algorithms had accuracies of 83.9% and 82.9% for predicting the concordance/mismatch of the femoral and tibial implant, respectively. Model predictions of greater than 51.0% and 47.9% represented high-risk thresholds for femoral and tibial sizing mismatch, respectively.

Conclusions

ML algorithms predicted templating mismatch with good accuracy. External validation is necessary to confirm the performance and reliability of these algorithms. Predicting sizing mismatch is the first step in using ML to aid in the prediction of final TKA component sizes. Further studies to optimize parameters and predictions for the algorithms are ongoing.