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Orthopaedic Proceedings
Vol. 105-B, Issue SUPP_12 | Pages 82 - 82
23 Jun 2023
Halvorson RT Khattab K Ngwe H Ornowski J Akkaya Z Matthew RP Souza R Bird A Lotz J Vail TP Bailey JF
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Patients demonstrate distinct trajectories of recovery after THA. The purpose of this study was to assess the impact of adjacent muscle quality on postoperative hip kinematics. We hypothesized that patients with better adjacent muscle quality (less fatty infiltration) would have greater early biomechanical improvement.

Adults undergoing primary THA were recruited. Preoperative MRI was obtained and evaluated via Scoring Hip Osteoarthritis with MRI Scores (SHOMRI, Lee, 2015). Muscle quality was assessed by measuring fat fraction [FF] from water-fat sequences. Biomechanics were assessed preoperatively and six weeks postoperatively during a staggered stance sit-to-stand using the Kinematic Deviation Index (KDI, Halvorson, 2022). Spearman's rho was used to assess correlations between muscle quality and function.

Ten adults (5M, 5F) were recruited (average age: 60.1, BMI: 23.79, SHOMRI: 40.6, KDI: 2.96). Nine underwent a direct anterior approach and one a posterior approach. Preoperatively, better biomechanical function was very strongly correlated with lower medius FF (rho=0.89), strongly correlated with lower FF in the minimus (rho=0.75) and tensor fascia lata (TFL) FF (rho=0.70), and weakly correlated with SHOMRI (rho=0.29). At six weeks, greater biomechanical improvement was strongly correlated with lower minimus FF (rho=0.63), moderately correlated with medius FF (rho=0.59), and weakly correlated with TFL FF (rho=0.26) and SHOMRI (rho=0.39). Lastly, medius FF was moderately correlated with SHOMRI (rho=0.42) with negligible correlations between SHOMRI and FF in the minimus and TFL.

These findings suggest adjacent muscle quality may be related to postoperative function following THA, explaining some of the variability and supporting specialized muscle rehabilitation or regeneration therapy to improve outcomes.


Orthopaedic Proceedings
Vol. 102-B, Issue SUPP_10 | Pages 53 - 53
1 Oct 2020
Roberts H Barry J Vail TP Kandemir U Rogers S Ward D
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Introduction

While interdisciplinary protocols and expedited surgical treatment improve management of geriatric hip fractures, the impact of such interventions on patients undergoing specifically arthroplasty for femoral neck fracture (FNF) has not been well studied. The aim of this study is to evaluate the efficacy of an interdisciplinary hip fracture protocol for patients undergoing arthroplasty for acute FNF.

Methods

In 2017, our tertiary care institution implemented a standardized interdisciplinary hip fracture protocol. We conducted a retrospective review of adult patients who underwent hemiarthroplasty (HA) or total hip arthroplasty (THA) for FNF from July 2012 – March 2020, and compared patient characteristics, hospitalization characteristics, and outcomes between those treated before and after protocol implementation.


The Bone & Joint Journal
Vol. 102-B, Issue 6 Supple A | Pages 101 - 106
1 Jun 2020
Shah RF Bini SA Martinez AM Pedoia V Vail TP

Aims

The aim of this study was to evaluate the ability of a machine-learning algorithm to diagnose prosthetic loosening from preoperative radiographs and to investigate the inputs that might improve its performance.

Methods

A group of 697 patients underwent a first-time revision of a total hip (THA) or total knee arthroplasty (TKA) at our institution between 2012 and 2018. Preoperative anteroposterior (AP) and lateral radiographs, and historical and comorbidity information were collected from their electronic records. Each patient was defined as having loose or fixed components based on the operation notes. We trained a series of convolutional neural network (CNN) models to predict a diagnosis of loosening at the time of surgery from the preoperative radiographs. We then added historical data about the patients to the best performing model to create a final model and tested it on an independent dataset.


Orthopaedic Proceedings
Vol. 101-B, Issue SUPP_12 | Pages 73 - 73
1 Oct 2019
Sershon RA Fillingham Y Abdel MP Malkani AL Schwarzkopf R Padgett DE Vail TP Nam D Nahhas CR Culvern C Valle CJD
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Background

The purpose of this multicenter, randomized clinical trial was to determine the optimal dosing regimen of tranexamic acid (TXA) to minimize perioperative blood loss for revision total hip arthroplasty (THA).

Methods

Six centers prospectively randomized 155 revisions to one of four regimens: 1g of intravenous (IV) TXA prior to incision, a double dose regimen of 1g IV TXA prior to incision and 1g IV TXA during wound closure, a combination of 1g IV TXA prior to incision and 1g intraoperative topical TXA, or three doses of 1950mg oral TXA administered 2 hours preoperatively, 6 hours postoperatively, and on the morning of postoperative day one. Randomization was based upon revision subgroups to ensure equivalent group distribution, including: femur only, acetabulum only, both component, explant/spacer, and second stage reimplantation. Patients undergoing an isolated modular exchange were excluded. An a priori power analysis (alpha = 0.05; beta = 0.80) determined 40 patients per group were required to identify a 1g/dL difference in postoperative hemoglobin reduction between groups. Per-protocol analysis involved an analysis of variance, Fisher's exact tests, and two one-sided t-tests for equivalence.


Orthopaedic Proceedings
Vol. 101-B, Issue SUPP_11 | Pages 71 - 71
1 Oct 2019
Vail TP Shah RF Bini SA
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Background

Implant loosening is a common cause of a poor outcome and pain after total knee arthroplasty (TKA). Despite the increase in use of expensive techniques like arthrography, the detection of prosthetic loosening is often unclear pre-operatively, leading to diagnostic uncertainty and extensive workup. The objective of this study was to evaluate the ability of a machine learning (ML) algorithm to diagnose prosthetic loosening from pre-operative radiographs, and to observe what model inputs improve the performance of the model.

Methods

754 patients underwent a first-time revision of a total joint at our institution from 2012–2018. Pre-operative X-Rays (XR) were collected for each patient. AP and lateral X-Rays, in addition to demographic and comorbidity information, were collected for each patient. Each patient was determined to have either loose or fixed prosthetics based on a manual abstraction of the written findings in their operative report, which is considered the gold standard of diagnosing prosthetic loosening. We trained a series of deep convolution neural network (CNN) models to predict if a prosthesis was found to be loose in the operating room from the pre-operative XR. Each XR was pre-processed to segment the bone, implant, and bone-implant interface. A series of CNN models were built using existing, proven CNN architectures and weights optimized to our dataset. We then integrated our best performing model with historical patient data to create a final model and determine the incremental accuracy provided by additional layers of clinical information fed into the model. The models were evaluated by its accuracy, sensitivity and specificity.


Orthopaedic Proceedings
Vol. 101-B, Issue SUPP_12 | Pages 25 - 25
1 Oct 2019
Vail TP Shah R Bini S
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Background

80% of health data is recorded as free text and not easily accessible for use in research and QI. Natural Language Processing (NLP) could be used as a method to abstract data easier than manual methods. Our objectives were to investigate whether NLP can be used to abstract structured clinical data from notes for total joint arthroplasty (TJA).

Methods

Clinical and hospital notes were collected for every patient undergoing a primary TJA. Human annotators reviewed a random training sample(n=400) and test sample(n=600) of notes from 6 different surgeons and manually abstracted historical, physical exam, operative, and outcomes data to create a gold standard dataset. Historical data collected included pain information and the various treatments tried (medications, injections, physical therapy). Physical exam information collected included ROM and the presence of deformity. Operative information included the angle of tibial slope, angle of tibial and femoral cuts, and patellar tracking for TKAs and approach and repair of external rotators for THAs. In addition, information on implant brand/type/size, sutures, and drains were collected for all TJAs. Finally, the occurrence of complications was collected. We then trained and tested our NLP system to automatically collect the respective variables. Finally, we assessed our automated approach by comparing system-generated findings against the gold standard.


The Bone & Joint Journal
Vol. 101-B, Issue 6_Supple_B | Pages 77 - 83
1 Jun 2019
Roberts HJ Tsay EL Grace TR Vail TP Ward DT

Aims

Increasingly, patients with bilateral hip arthritis wish to undergo staged total hip arthroplasty (THA). With the rise in demand for arthroplasty, perioperative risk assessment and counselling is crucial for shared decision making. However, it is unknown if complications that occur after a unilateral hip arthroplasty predict complications following surgery of the contralateral hip.

Patients and Methods

We used nationwide linked discharge data from the Healthcare Cost and Utilization Project between 2005 and 2014 to analyze the incidence and recurrence of complications following the first- and second-stage operations in staged bilateral total hip arthroplasty (BTHAs). Complications included perioperative medical adverse events within 30 to 60 days, and infection and mechanical complications within one year. Conditional probabilities and odds ratios (ORs) were calculated to determine whether experiencing a complication after the first stage of surgery increased the risk of developing the same complication after the second stage.


Orthopaedic Proceedings
Vol. 92-B, Issue SUPP_I | Pages 29 - 29
1 Mar 2010
Bolognesi MP Viens NA Marchant MH Vail TP Cook C
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Purpose: As the prevalence of diabetes mellitus (DM) in people over 60 years of age is expected to increase, the number of diabetic patients who undergo total hip and knee arthroplasty should increase concordantly. In general, patients with DM have significantly increased risk for adverse events following arthroplasty. The goal of this study was to determine whether the quality of glycemic control affected the incidence of perioperative complications in the hospital following joint replacement.

Method: From 1988 to 2003, the Nationwide Inpatient Survey (NIS) recognized 65,769 patients who had DM and underwent joint replacement surgery. In this retrospective study, bivariate and multivariate analyses compared patients with uncontrolled (n=2,872) and not uncontrolled (n=62,897) DM regarding common surgical and systemic complications, mortality, and hospital course alterations. Glycemic control was determined by physicians’ assessments based upon the American Diabetes Association guidelines using a combination of patients’ self-monitoring of blood-glucose testing, the hemoglobin A1C, and related complications.

Results: Patients with uncontrolled DM routinely had an increased length of stay and increased inflation-adjusted costs after surgery (p< 0.001). Uncontrolled patients also had significant increases in the incidence of stroke, pneumonia, urinary tract infection, post-operative hemorrhage, wound infection, and death (p< 0.001).

Conclusion: Patients with well-managed glycemic control have fewer comorbidities in general. Patients with uncontrolled DM exhibited significantly increased risks for surgical and systemic complications, higher mortality, increased length of stay, and higher hospital charges during the index hospitalization following arthroplasty. The consequences are increased cost, greater burden on the healthcare system, and greater risk to these patients.