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The Bone & Joint Journal
Vol. 101-B, Issue 7_Supple_C | Pages 17 - 21
1 Jul 2019
Schroer WC LeMarr AR Mills K Childress AL Morton DJ Reedy ME

Aims

To date, no study has demonstrated an improvement in postoperative outcomes following elective joint arthroplasty with a focus on nutritional intervention for patients with preoperative hypoalbuminaemia. In this prospective study, we evaluated differences in the hospital length of stay (LOS), rate of re-admission, and total patient charges for a malnourished patient study population who received a specific nutrition protocol before surgery.

Patients and Methods

An analytical report was extracted from the electronic medical record (EMR; Epic, Verona, Wisconsin) of a five-hospital network joint arthroplasty patient data set between 2014 and 2017. A total of 4733 patients underwent joint arthroplasty and had preoperative measurement of albumin levels: 2220 at four hospitals and 2513 at the study hospital. Albumin ≤ 3.4 g/l, designated as malnutrition, was found in 543 patients (11.5%). A nutritional intervention programme focusing on a high-protein, anti-inflammatory diet was initiated in January 2017 at one study hospital. Hospital LOS, re-admission rate, and 90-day charges were compared for differential change between patients in study and control hospitals for all elective hip and knee arthroplasty patients, and for malnourished patients over time as the nutrition intervention was implemented.


The Bone & Joint Journal
Vol. 106-B, Issue 2 | Pages 158 - 165
1 Feb 2024
Nasser AAHH Sidhu M Prakash R Mahmood A

Aims. Periprosthetic fractures (PPFs) around the knee are challenging injuries. This study aims to describe the characteristics of knee PPFs and the impact of patient demographics, fracture types, and management modalities on in-hospital mortality. Methods. Using a multicentre study design, independent of registry data, we included adult patients sustaining a PPF around a knee arthroplasty between 1 January 2010 and 31 December 2019. Univariate, then multivariable, logistic regression analyses were performed to study the impact of patient, fracture, and treatment on mortality. Results. Out of a total of 1,667 patients in the PPF study database, 420 patients were included. The in-hospital mortality rate was 6.4%. Multivariable analyses suggested that American Society of Anesthesiologists (ASA) grade, history of peripheral vascular disease (PVD), history of rheumatic disease, fracture around a loose implant, and cerebrovascular accident (CVA) during hospital stay were each independently associated with mortality. Each point increase in ASA grade independently correlated with a four-fold greater mortality risk (odds ratio (OR) 4.1 (95% confidence interval (CI) 1.19 to 14.06); p = 0.026). Patients with PVD have a nine-fold increase in mortality risk (OR 9.1 (95% CI 1.25 to 66.47); p = 0.030) and patients with rheumatic disease have a 6.8-fold increase in mortality risk (OR 6.8 (95% CI 1.32 to 34.68); p = 0.022). Patients with a fracture around a loose implant (Unified Classification System (UCS) B2) have a 20-fold increase in mortality, compared to UCS A1 (OR 20.9 (95% CI 1.61 to 271.38); p = 0.020). Mode of management was not a significant predictor of mortality. Patients managed with revision arthroplasty had a significantly longer length of stay (median 16 days; p = 0.029) and higher rates of return to theatre, compared to patients treated nonoperatively or with fixation. Conclusion. The mortality rate in PPFs around the knee is similar to that for native distal femur and neck of femur fragility fractures. Patients with certain modifiable risk factors should be optimized. A national PPF database and standardized management guidelines are currently required to understand these complex injuries and to improve patient outcomes. Cite this article: Bone Joint J 2024;106-B(2):158–165


The Bone & Joint Journal
Vol. 105-B, Issue 9 | Pages 971 - 976
1 Sep 2023
Bourget-Murray J Piroozfar S Smith C Ellison J Bansal R Sharma R Evaniew N Johnson A Powell JN

Aims. This study aims to determine difference in annual rate of early-onset (≤ 90 days) deep surgical site infection (SSI) following primary total knee arthroplasty (TKA) for osteoarthritis, and to identify risk factors that may be associated with infection. Methods. This is a retrospective population-based cohort study using prospectively collected patient-level data between 1 January 2013 and 1 March 2020. The diagnosis of deep SSI was defined as per the Centers for Disease Control/National Healthcare Safety Network criteria. The Mann-Kendall Trend test was used to detect monotonic trends in annual rates of early-onset deep SSI over time. Multiple logistic regression was used to analyze the effect of different patient, surgical, and healthcare setting factors on the risk of developing a deep SSI within 90 days from surgery for patients with complete data. We also report 90-day mortality. Results. A total of 39,038 patients underwent primary TKA for osteoarthritis during the study period. Of these, 275 patients developed a deep SSI within 90 days of surgery, representing a cumulative incidence of 0.7%. The annual infection rate did not significantly decrease over the seven-year study period (p = 0.162). Overall, 13,885 (35.5%) cases were excluded from the risk analysis due to missing data. Risk factors associated with early-onset deep SSI included male sex, American Society of Anesthesiologists grade ≥ 3, blood transfusion, acute length of stay, and surgeon volume < 30 TKAs/year. Early-onset deep SSI was not associated with increased 90-day mortality. Conclusion. This study establishes a reliable baseline infection rate for early-onset deep SSI after TKA for osteoarthritis using robust Infection Prevention and Control surveillance data, and identifies several potentially modifiable risk factors. Cite this article: Bone Joint J 2023;105-B(9):971–976


The Bone & Joint Journal
Vol. 102-B, Issue 9 | Pages 1183 - 1193
14 Sep 2020
Anis HK Strnad GJ Klika AK Zajichek A Spindler KP Barsoum WK Higuera CA Piuzzi NS

Aims. The purpose of this study was to develop a personalized outcome prediction tool, to be used with knee arthroplasty patients, that predicts outcomes (lengths of stay (LOS), 90 day readmission, and one-year patient-reported outcome measures (PROMs) on an individual basis and allows for dynamic modifiable risk factors. Methods. Data were prospectively collected on all patients who underwent total or unicompartmental knee arthroplasty at a between July 2015 and June 2018. Cohort 1 (n = 5,958) was utilized to develop models for LOS and 90 day readmission. Cohort 2 (n = 2,391, surgery date 2015 to 2017) was utilized to develop models for one-year improvements in Knee Injury and Osteoarthritis Outcome Score (KOOS) pain score, KOOS function score, and KOOS quality of life (QOL) score. Model accuracies within the imputed data set were assessed through cross-validation with root mean square errors (RMSEs) and mean absolute errors (MAEs) for the LOS and PROMs models, and the index of prediction accuracy (IPA), and area under the curve (AUC) for the readmission models. Model accuracies in new patient data sets were assessed with AUC. Results. Within the imputed datasets, the LOS (RMSE 1.161) and PROMs models (RMSE 15.775, 11.056, 21.680 for KOOS pain, function, and QOL, respectively) demonstrated good accuracy. For all models, the accuracy of predicting outcomes in a new set of patients were consistent with the cross-validation accuracy overall. Upon validation with a new patient dataset, the LOS and readmission models demonstrated high accuracy (71.5% and 65.0%, respectively). Similarly, the one-year PROMs improvement models demonstrated high accuracy in predicting ten-point improvements in KOOS pain (72.1%), function (72.9%), and QOL (70.8%) scores. Conclusion. The data-driven models developed in this study offer scalable predictive tools that can accurately estimate the likelihood of improved pain, function, and quality of life one year after knee arthroplasty as well as LOS and 90 day readmission. Cite this article: Bone Joint J 2020;102-B(9):1183–1193


The Bone & Joint Journal
Vol. 105-B, Issue 10 | Pages 1086 - 1093
1 Oct 2023
Kolin DA Sculco PK Gonzalez Della Valle A Rodriguez JA Ast MP Chalmers BP

Aims

Blood transfusion and postoperative anaemia are complications of total knee arthroplasty (TKA) that are associated with substantial healthcare costs, morbidity, and mortality. There are few data from large datasets on the risk factors for these complications.

Methods

We retrospectively reviewed the records of TKA patients from a single tertiary care institution from February 2016 to December 2020. There were a total of 14,901 patients in this cohort with a mean age of 67.9 years (SD 9.2), and 5,575 patients (37.4%) were male. Outcomes included perioperative blood transfusion and postoperative anaemia, defined a priori as haemoglobin level < 10 g/dl measured on the first day postoperatively. In order to establish a preoperative haemoglobin cutoff, we investigated a preoperative haemoglobin level that would limit transfusion likelihood to ≤ 1% (13 g/dl) and postoperative anaemia likelihood to 4.1%. Risk factors were assessed through multivariable Poisson regression modelling with robust error variance.


The Bone & Joint Journal
Vol. 103-B, Issue 6 Supple A | Pages 45 - 50
1 Jun 2021
Kerbel YE Johnson MA Barchick SR Cohen JS Stevenson KL Israelite CL Nelson CL

Aims

It has been shown that the preoperative modification of risk factors associated with obesity may reduce complications after total knee arthroplasty (TKA). However, the optimal method of doing so remains unclear. The aim of this study was to investigate whether a preoperative Risk Stratification Tool (RST) devised in our institution could reduce unexpected intensive care unit (ICU) transfers and 90-day emergency department (ED) visits, readmissions, and reoperations after TKA in obese patients.

Methods

We retrospectively reviewed 1,614 consecutive patients undergoing primary unilateral TKA. Their mean age was 65.1 years (17.9 to 87.7) and the mean BMI was 34.2 kg/m2 (SD 7.7). All patients underwent perioperative optimization and monitoring using the RST, which is a validated calculation tool that provides a recommendation for postoperative ICU care or increased nursing support. Patients were divided into three groups: non-obese (BMI < 30 kg/m2, n = 512); obese (BMI 30 kg/m2 to 39.9 kg/m2, n = 748); and morbidly obese (BMI > 40 kg/m2, n = 354). Logistic regression analysis was used to evaluate the outcomes among the groups adjusted for age, sex, smoking, and diabetes.


The Bone & Joint Journal
Vol. 103-B, Issue 10 | Pages 1578 - 1585
1 Oct 2021
Abram SGF Sabah SA Alvand A Price AJ

Aims

To compare rates of serious adverse events in patients undergoing revision knee arthroplasty with consideration of the indication for revision (urgent versus elective indications), and compare these with primary arthroplasty and re-revision arthroplasty.

Methods

Patients undergoing primary knee arthroplasty were identified in the national Hospital Episode Statistics (HES) between 1 April 1997 to 31 March 2017. Subsequent revision and re-revision arthroplasty procedures in the same patients and same knee were identified. The primary outcome was 90-day mortality and a logistic regression model was used to investigate factors associated with 90-day mortality and secondary adverse outcomes, including infection (undergoing surgery), pulmonary embolism, myocardial infarction, and stroke. Urgent indications for revision arthroplasty were defined as infection or fracture, and all other indications (e.g. loosening, instability, wear) were included in the elective indications cohort.


The Bone & Joint Journal
Vol. 103-B, Issue 8 | Pages 1358 - 1366
2 Aug 2021
Wei C Quan T Wang KY Gu A Fassihi SC Kahlenberg CA Malahias M Liu J Thakkar S Gonzalez Della Valle A Sculco PK

Aims

This study used an artificial neural network (ANN) model to determine the most important pre- and perioperative variables to predict same-day discharge in patients undergoing total knee arthroplasty (TKA).

Methods

Data for this study were collected from the National Surgery Quality Improvement Program (NSQIP) database from the year 2018. Patients who received a primary, elective, unilateral TKA with a diagnosis of primary osteoarthritis were included. Demographic, preoperative, and intraoperative variables were analyzed. The ANN model was compared to a logistic regression model, which is a conventional machine-learning algorithm. Variables collected from 28,742 patients were analyzed based on their contribution to hospital length of stay.


The Bone & Joint Journal
Vol. 102-B, Issue 6 Supple A | Pages 31 - 35
1 Jun 2020
Sloan M Sheth NP Nelson CL

Aims

Rates of readmission and reoperation following primary total knee arthroplasty (TKA) are under scrutiny due to new payment models, which penalize these negative outcomes. Some risk factors are more modifiable than others, and some conditions considered modifiable such as obesity may not be as modifiable in the setting of advanced arthritis as many propose. We sought to determine whether controlling for hypoalbuminaemia would mitigate the effect that prior authors had identified in patients with obesity.

Methods

We reviewed the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database for the period of January 2008 to December 2016 to evaluate the rates of reoperation and readmission within 30 days following primary TKA. Multivariate logistic regression modelling controlled for preoperative albumin, age, sex, and comorbidity status.


The Bone & Joint Journal
Vol. 101-B, Issue 7_Supple_C | Pages 28 - 32
1 Jul 2019
Springer BD Roberts KM Bossi KL Odum SM Voellinger DC

Aims

The aim of this study was to observe the implications of withholding total joint arthroplasty (TJA) in morbidly obese patients

Patients and Methods

A total of 289 morbidly obese patients with end-stage osteoarthritis were prospectively followed. There were 218 women and 71 men, with a mean age of 56.3 years (26.7 to 79.1). At initial visit, patients were given information about the risks of TJA in the morbidly obese and were given referral information to a bariatric clinic. Patients were contacted at six, 12, 18, and 24 months from initial visit.


The Bone & Joint Journal
Vol. 101-B, Issue 7_Supple_C | Pages 64 - 69
1 Jul 2019
Wodowski AJ Pelt CE Erickson JA Anderson MB Gililland JM Peters CL

Aims

The Bundled Payments for Care Improvement (BPCI) initiative has identified pathways for improving the value of care. However, patient-specific modifiable and non-modifiable risk factors may increase costs beyond the target payment. We sought to identify risk factors for exceeding our institution’s target payment, the so-called ‘bundle busters’.

Patients and Methods

Using our data warehouse and Centers for Medicare and Medicaid Services (CMS) data we identified all 412 patients who underwent total joint arthroplasty and qualified for our institution’s BPCI model, between July 2015 and May 2017. Episodes where CMS payments exceeded the target payment were considered ‘busters’ (n = 123). Risk ratios (RRs) were calculated using a modified Poisson regression analysis.