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Orthopaedic Proceedings
Vol. 103-B, Issue SUPP_14 | Pages 5 - 5
1 Nov 2021
DeMik D Carender C Glass N Brown T Bedard N Callaghan J
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Reported incidence of blood transfusion following primary and revision total hip arthroplasty (pTHA, rTHA) has decreased considerably compared to historical rates. However, it is not known if further adoption of techniques to limit transfusions has resulted in further reduction on a large scale. The purpose of this study was to assess recent trends in blood transfusions and contemporary risk factors for transfusions using a large, national database.

The American College of Surgeons National Surgical Quality Improvement Program was queried to identify patients undergoing pTHA and rTHA between 2011 to 2019. pTHA for fracture, infection, tumor, and bilateral procedures were excluded. Only aseptic rTHA were included. Annual incidence of transfusions and proportion of patients with optimized preoperative hematocrit (HCT) (defined as ≥33%) were assessed. Risk factors for transfusion were evaluated with 2018 and 2019 data using multivariate analyses.

234,352 pTHA and 16,322 rTHA were included. Transfusion following pTHA decreased from 21.4% in 2011 to 2.5% in 2019 and from 33.5% in 2011 to 12.0% in 2019 for rTHA (p<0.0001). Patients with optimized HCT increased for pTHA (96.7% in 2011 vs 98.1% in 2019, p<0.0001) and did not change for rTHA (91.5% in 2011 vs 91.6% in 2019, p=0.27). Decreased HCT was most strongly associated with transfusions, with each three-point change corresponding to odds ratio of 1.90 and 1.78 for pTHA and rTHA, respectively. Increased age, female sex, history of bleeding disorders or preoperative transfusion, ASA score ≥3, non-spinal anesthesia, and longer operative times were also associated with increased odds for transfusion.

Incidence of blood transfusion has continued to decrease following pTHA and rTHA. Despite care improvements, transfusions still occur in certain high-risk patients. While transfusion in pTHA may have reached the lower asymptote, further reduction in rTHA may be possible through further improvements in preoperative optimization and surgical technique.


Orthopaedic Proceedings
Vol. 100-B, Issue SUPP_11 | Pages 6 - 6
1 Aug 2018
Callaghan J DeMilk D Bedard N Dowdle S Elkins J Brown T Gao Y
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Obesity has previously been demonstrated to be an independent risk factor for increased complications following total hip (THA) and total knee arthroplasty (TKA). The purpose of this study was to compare the effects of obesity and BMI to determine whether the magnitude of the effect was similar for both procedures.

We queried the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) database to identify patients who underwent primary THA or TKA between 2010 and 2014. Patients were stratified by procedure and classified as non-obese, obese, or morbidly obese according to BMI. Thirty-day rates of wound complications, deep infection, total complications, and reoperation were compared using univariate and multivariate logistic regression analyses.

We identified 64,648 patients who underwent THA and 97,137 patients who underwent TKA. Obese THA patients had significantly higher rates of wound complications (1.53% vs 0.96%), deep infection (0.31% vs 0.17%), reoperation rate (2.11% vs 1.02%), and total complications (5.22% vs. 4.63%) compared to TKA patients. Morbidly obese patients undergoing THA were also found to have significantly higher rates of wound complications (3.25% vs 1.52%), deep infection (0.84% vs 0.23%), reoperation rate (3.65% vs 1.60%), and total complications (7.36% vs. 5.57%). Multivariate regression analysis identified increasingly higher odds of each outcome measure as BMI increased.

This study demonstrates the impact of obesity on postoperative complications is more profound for THA than TKA. This emphasizes the importance of considering patient comorbidities in the context of the specific procedure (hips and knees should be analyzed independently) when assessing risks of surgery.


Orthopaedic Proceedings
Vol. 100-B, Issue SUPP_1 | Pages 31 - 31
1 Jan 2018
Bedard N Pugely A McHugh M Lux N Bozic K Callaghan J
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Use of large databases for orthopaedic research has increased exponentially. Each database represents unique patient populations and vary in methodology of data acquisition. The purpose of this study was to evaluate differences in reported demographics, comorbidities and complications following total hip arthroplasty (THA) amongst four commonly used databases.

Patients who underwent primary THA during 2010–2012 were identified within National Surgical Quality Improvement Programs (NSQIP), Nationwide Inpatient Sample (NIS), Medicare Standard Analytic Files (MED) and Humana Claims Database (HAC). NSQIP definitions for comorbidities and surgical complications were queried in NIS, MED, and HAC using coding algorithms. Age, sex, comorbidities, inpatient and 30-day postoperative complications were compared (NIS has inpatient data only).

Primary THAs from each database were 22,644 (HAC), 371,715 (MED), 188,779 (NIS) and 27,818 (NSQIP). Age and gender distribution were similar between databases. There was variability in the prevalence of comorbidities and complications depending upon the database and duration of post-operative follow-up. HAC and MED had twice the prevalence of COPD, coagulopathy and diabetes than NSQIP. NSQIP had more than twice the obesity than NIS. HAC had more than twice the rates of 30-day complications at all endpoints compared to NSQIP and more than twice the DVTs, strokes and deep infection as MED at 30-days post-op. Comparison of inpatient and 30-day complications rates demonstrated more than twice the amount of infections and DVTs are captured when analysis is extended from inpatient stay to 30-days post-op.

Amongst databases commonly used in orthopaedic research, there is considerable variation in complication rates following THA depending upon the database. It will be important to consider these differences when critically evaluating database research. Additionally, with the advent of bundled payments, these differences must be considered in risk adjustment models.