Impact of Gender on 30-Day Complications After Primary Total Joint Arthroplasty

Robinson, Jonathan; Shin, John I.; Dowdell, James; Moucha, Calin S.; Chen, Darwin D.

doi:10.1016/j.arth.2017.03.001

Cited by 47 publications

(39 citation statements)

References 40 publications

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“…This was a consistent finding in our study for both THA and TKA. Our findings are also consistent with that of Robinson et al [7]. Using the ACS-NSQIP database between 2012 and 2014, the authors found a similar differential effect of gender by the procedure type.…”

Section: Discussionsupporting

confidence: 93%

“…The authors found that males had increased risk of 30-day wound infections, readmissions, reoperations, and mortality. In another study by the same group using the Nationwide Inpatient Sample from 2002 to 2011, Robinson et al [7] showed that male gender was associated with increased risks of infection, MI, acute kidney injury, pneumonia, sepsis, wound dehiscence, and mortality. Only the rates of urinary tract infection (UTI) and blood transfusion were higher among females.…”

Section: Discussionmentioning

confidence: 99%

“…When it comes to the influence of gender on the postoperative TJA outcomes, there remains a significant amount of variability depending on the research methodology, time interval, and assessed outcomes [4,[6][7][8]. Recently, Basques et al published 2 reports [6,9] on gender differences in TJA outcomes using 2 separate national databases.…”

Section: Introductionmentioning

confidence: 99%

“…However, neither study was stratified by procedure type (total hip arthroplasty [THA] or total knee arthroplasty [TKA]). Other studies have identified gender differences in postoperative complications that were variable depending on the procedure type (THA or TKA) [7]. To date, there remains a lack of clarity on this topic.…”

Section: Introductionmentioning

confidence: 99%

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Gender and Total Joint Arthroplasty: Variable Outcomes by Procedure Type

et al. 2020

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Background: Recent reports on the influence of gender on the outcomes of total joint arthroplasty were limited by either lack of longitudinal data or absent stratification by total hip arthroplasty (THA) or total knee arthroplasty (TKA). As a result, there remains a lack of clarity on this topic. Methods: The American College of Surgeons National Surgical Quality Improvement Program was queried for all primary, elective THAs and TKAs performed between 2011 and 2017. Differences in demographics, comorbidity profiles, operative time, hospital length of stay (LOS), and 30-day outcomes were compared between male and female patients. Multivariate analyses were performed separately for THA and TKA. Results: A total of 418,885 patients were analyzed; 59.1% were females. Compared with males, females were likely to be older, have a higher body mass index, identify as nonwhite, and require preoperative functional assistance (P < .001). Females had lower rates of diabetes, hypertension, anemia, and kidney disease but a higher rate of chronic steroid use (P < .001). They were also likely to have shorter operative times for both THA and TKA (P < .001). After controlling for the aforementioned differences, female gender was an independent risk factor for readmission, reoperation, and wound infection after THA (P < .001). In contrast, male sex was an independent risk factor for readmission, reoperation, and overall complications after TKA (P < .001). Regardless of the procedure, females were 64%e82% more likely to require an LOS >2 days than males. Discussion: A variable effect of gender was observed on the postetotal joint arthroplasty LOS and outcomes depending on the procedure type (THA or TKA). Differences attributed to gender should be accounted for in risk-stratification models. Future studies are also needed to elucidate the underlying causes of gender differences in joint arthroplasty.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Gender and Total Joint Arthroplasty: Variable Outcomes by Procedure Type

et al. 2020

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“…Total knee replacement (TKR) has traditionally been seen as a highly demanding surgery associated with major blood loss in patients belonging to older age group often having comorbidities. Older age group, male gender and pre-existing cardiac disease increase the risk [1][2][3][4][5] of complications after TKR surgery. Clinically signicant complications like myocardial infarction (MI), pulmonary embolism (PE), deep vein thrombosis (DVT) and death are known to occur following total knee arthroplasty (TKA) with an overall frequency of 6 2.2 %.…”

Section: Introduction: -mentioning

confidence: 99%

Robotic Technology Can Be a Useful Tool in TKR in a Post-Cabg Patient: A Case Report and Literature Review

Agrawal

Kale

Vaidya

2020

ijsr

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Background: - Total knee replacement (TKR) is a major surgery associated with complications like pulmonary embolism, myocardial infarction, deep vein thrombosis and death. Associated risk factors like old age, male gender, pre-existing cardiac disease increase the risk of these post-operative complications. Use of robotic technology leads to reduced blood loss, decreased risk of pulmonary embolism and related complications. In our study, we evaluated the use of this technology in a patient undergoing total knee replacement, post coronary artery bypass grafting surgery. Case Presentation: - An 85y old male patient, known case of hypertension, diabetes mellitus, ischaemic heart disease, who had undergone coronary artery bypass grafting (12 years back), presented with severe osteoarthritis in left knee, and was operated for total knee replacement surgery using robotic technology. The procedure was uneventful with satisfactory recovery of the patient. Use of robotic technology, along with good perioperative planning and its execution can help achieve successful outcomes in patients with cardiopulmonary risk factors.

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Prediction of Early Adverse Events After THA: A Comparison of Different Machine‐Learning Strategies Based on 262,356 Observations From the Nordic Arthroplasty Register Association (NARA) Dataset

Venäläinen,

Panula,

Eskelinen

et al. 2024

ACR Open Rheumatology

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ObjectivePreoperative risk prediction models can support shared decision‐making before total hip arthroplasties (THAs). Here, we compare different machine‐learning (ML) approaches to predict the six‐month risk of adverse events following primary THA to obtain accurate yet simple‐to‐use risk prediction models.MethodsWe extracted data on primary THAs (N = 262,356) between 2010 and 2018 from the Nordic Arthroplasty Register Association dataset. We benchmarked a variety of ML algorithms in terms of the area under the receiver operating characteristic curve (AUROC) for predicting the risk of revision caused by periprosthetic joint infection (PJI), dislocation or periprosthetic fracture (PPF), and death. All models were internally validated against a randomly selected test cohort (one‐third of the data) that was not used for training the models.ResultsThe incidences of revisions because of PJI, dislocation, and PPF were 0.8%, 0.4%, and 0.3%, respectively, and the incidence of death was 1.2%. Overall, Lasso regression with stable iterative variable selection (SIVS) produced models using only four to five input variables but with AUROC comparable to more complex models using all 32 variables available. The SIVS‐based Lasso models based on age, sex, preoperative diagnosis, bearing couple, fixation, and surgical approach predicted the risk of revisions caused by PJI, dislocations, and PPF, as well as death, with AUROCs of 0.61, 0.67, 0.76, and 0.86, respectively.ConclusionOur study demonstrates that satisfactory predictive potential for adverse events following THA can be reached with parsimonious modeling strategies. The SIVS‐based Lasso models may serve as simple‐to‐use tools for clinical risk assessment in the future.

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Impact of Gender on 30-Day Complications After Primary Total Joint Arthroplasty

Cited by 47 publications

References 40 publications

Gender and Total Joint Arthroplasty: Variable Outcomes by Procedure Type

Gender and Total Joint Arthroplasty: Variable Outcomes by Procedure Type

Robotic Technology Can Be a Useful Tool in TKR in a Post-Cabg Patient: A Case Report and Literature Review

Prediction of Early Adverse Events After THA: A Comparison of Different Machine‐Learning Strategies Based on 262,356 Observations From the Nordic Arthroplasty Register Association (NARA) Dataset

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