Predictive factors for length of hospital stay following primary total knee replacement in a total joint replacement centre in Hong Kong

Lo, CK; Lee, QJ; Wong, YC

doi:10.12809/hkmj166113

Cited by 9 publications

(10 citation statements)

References 17 publications

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“…The key finding was that LoS was significantly associated with patient surgical and management factors. Patient age at surgery and the presence of comorbidities have been extensively reported as factors affecting LoS 4,5,10 and this was supported by the present findings. However, we also found that the time to first mobilization, discharge destination other than home, and the presence of complications also extended LoS.…”

Section: Discussionsupporting

confidence: 90%

“…13 We found that an in-patient complication was associated with LoS, in agreement with other recent analyses. 10,14 Similarly, discharge destination other than home has also been previously reported, 14,15 but not as extensively as patient age and comorbidities. Similarly, case-control studies and other comparative designs have demonstrated the superiority of computer navigated TKA 16 and local analgesia infiltration, 17 although surgical approach may not affect LoS 18 however, positive effects of less invasive incisions (e.g., mini-subvastus) have been noted in individual comparative studies.…”

Section: Discussionmentioning

confidence: 64%

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Factors Affecting Hospital Length of Stay following Total Knee Replacement: A Retrospective Analysis in a Regional Hospital

Scholes¹,

Cowley²,

Ebrahimi³

et al. 2019

J Knee Surg

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In an effort to reduce hospital length of stay (LoS) following total knee arthroplasty (TKA), patient management strategies have evolved over time. The aims of this study were threefold: first, to quantify the reduction in LoS for TKA in a regional hospital; second, to identify the patient, surgical and management factors associated with hospital LoS; and lastly, to assess the change in complications incidence and hospital readmission as a function of LoS. A retrospective chart review was conducted on a consecutive series of primary and revision TKAs from January 2012 to March 2018. Factors describing patient demographics, as well as preoperative, intraoperative, surgical, and postoperative management, were extracted from paper and electronic medical records by a team of reviewers. Multivariate linear regression was performed to assess the association between these factors and LoS. In total, 362 procedures were included, which were reduced to 329 admissions once simultaneous bilateral procedures were taken into account. Median LoS reduced significantly (p = 0.001) from 6 to 2 days over the period of review. A stepwise regression analysis identified patient characteristics (age, gender, comorbidities, discharge barriers), perioperative management (anesthesia type), surgical characteristics (approach, alignment method), and postoperative management (mobilization timing, postoperative narcotic use, complication prior to discharge) as factors explaining 58.3% of the variance in LoS. Representation to emergency (6%) and hospital readmission (3%) remained low for the reviewed period. Efforts to reduce hospital LoS following TKA within a regional hospital setting can be achieved over time without significant increases in the rate or severity of complications or representation to acute care and subsequent readmission. The findings establish the role of patient, surgical and management factors in the context of agreed discharge criteria between care providers.

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Section: Discussionsupporting

confidence: 90%

Section: Discussionmentioning

confidence: 64%

Factors Affecting Hospital Length of Stay following Total Knee Replacement: A Retrospective Analysis in a Regional Hospital

Scholes¹,

Cowley²,

Ebrahimi³

et al. 2019

J Knee Surg

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“…Our patients had a mean LOS of 2.64 daysdlower than published estimates, which have reported a mean LOS ranging from 3.17 days to 6.8 days for TKA [5,7,8,34]. This median LOS is also lower than published estimates in similar literature looking at risk factors associated with prolonged LOS [22,35].…”

Section: Discussioncontrasting

confidence: 60%

“…Despite recent reports of decreasing LOS for TKA in the United States, LOS remains high in other parts of the world. A recent study published in 2017 of a cohort of 1622 patients from Hong Kong receiving TKA was identified as having a mean LOS of 6.8 days after the procedure [5]. In a study using data from the National Health Institute in the United Kingdom, the mean hospital LOS remained high at 5.4 days [6].…”

mentioning

confidence: 99%

Modifiable, Postoperative Risk Factors for Delayed Discharge Following Total Knee Arthroplasty: The Influence of Hypotension and Opioid Use

Anastasio

Farley

Boden

et al. 2020

The Journal of Arthroplasty

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Keywords:total knee arthroplasty opioid hypotension modifiable risk factors length of stay anemia a b s t r a c t Background: We sought to identify independent modifiable risk factors for delayed discharge after total knee arthroplasty (TKA) that have been previously underrepresented in the literature, particularly postoperative opioid use, postoperative laboratory abnormalities, and the frequency of hypotensive events. Methods: Data from 1033 patients undergoing TKA for primary osteoarthritis of the knee between June 2012 and August 2014 at an academic orthopedic specialty hospital were reviewed. Patient demographics, comorbidities, inpatient opioid medication, postoperative hypotensive events, and abnormalities in laboratory values, all occurring on postoperative day 0 or 1, were collected. Multivariate logistic regression analysis was performed to identify independent risk factors for a prolonged length of stay (LOS) >3 days. Results: The average age of patients undergoing primary TKA in our cohort was 65.9 (standard deviation, 9.1) years, and 61.7% were women. The mean LOS for all patients was 2.64 days (standard deviation, 1.14; range, 1-9). And 15.3% of patients had a LOS >3 days. On multivariate logistic regression analysis, nonmodifiable risk factors associated with a prolonged LOS included nonwhite race (odds ratio [OR], 2.01), single marital status (OR, 1.53), and increasing age (OR, 1.47). Modifiable risk factors included every 5 postoperative hypotensive events (OR, 1.31), 10-mg increases in oral morphine equivalent consumption (OR, 1.04), and postoperative laboratory abnormalities (hypocalcemia: OR, 2.15; low hemoglobin: OR, 2.63). Conclusion: This study identifies potentially modifiable factors that are associated with increased LOS after TKA. Doubling down on efforts to control the narcotic use and to use opioid alternatives when possible will likely have efficacy in reducing LOS. Attempts should be made to correct laboratory abnormalities and to be cognizant of patient opioid use, age, and race when considering potential avenues to reduce LOS.

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“…However, to our knowledge, fast-track arthroplasty has been rarely applied in Chinese hospitals, and few studies have focused on the LOS after TKA in the Chinese population. Lo CK et al reviewed 1,622 primary total knee replacements performed in Hong Kong and the mean length of hospital stay was 6.8 days (9). It is highly necessary to generalize the use of fast-track arthroplasty in China, and a predictive system for LOS will be the starting point.…”

Section: Introductionmentioning

confidence: 99%

To Predict the Length of Hospital Stay After Total Knee Arthroplasty in an Orthopedic Center in China: The Use of Machine Learning Algorithms

Han

Liu

et al. 2021

Front. Surg.

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Background and Objectives: Total knee arthroplasty (TKA) is widely performed to improve mobility and quality of life for symptomatic knee osteoarthritis patients. The accurate prediction of patients' length of hospital stay (LOS) can help clinicians for rehabilitation decision-making and bed assignment planning, which thus makes full use of medical resources.Methods: Clinical characteristics were retrospectively collected from 1,298 patients who received TKA. A total of 36 variables were included to develop predictive models for LOS by multiple machine learning (ML) algorithms. The models were evaluated by the receiver operating characteristic (ROC) curve for predictive performance and decision curve analysis (DCA) for clinical values. A feature selection approach was used to identify optimal predictive factors.Results: The areas under the ROC curve (AUCs) of the nine models ranged from 0.710 to 0.766. All the ML-based models performed better than models using conventional statistical methods in both ROC curves and decision curves. The random forest classifier (RFC) model with 10 variables introduced was identified as the best predictive model. The feature selection indicated the top five predictors: tourniquet time, distal femoral osteotomy thickness, osteoporosis, tibia component size, and post-operative values of Hb within 24 h.Conclusions: By analyzing clinical characteristics, it is feasible to develop ML-based models for the preoperative prediction of LOS for patients who received TKA, and the RFC model performed the best.

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Predictive factors for length of hospital stay following primary total knee replacement in a total joint replacement centre in Hong Kong

Cited by 9 publications

References 17 publications

Factors Affecting Hospital Length of Stay following Total Knee Replacement: A Retrospective Analysis in a Regional Hospital

Factors Affecting Hospital Length of Stay following Total Knee Replacement: A Retrospective Analysis in a Regional Hospital

Modifiable, Postoperative Risk Factors for Delayed Discharge Following Total Knee Arthroplasty: The Influence of Hypotension and Opioid Use

To Predict the Length of Hospital Stay After Total Knee Arthroplasty in an Orthopedic Center in China: The Use of Machine Learning Algorithms

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