The effect of body mass index and preoperative weight loss in people with obesity on postoperative outcomes to 6 months following total hip or knee arthroplasty: a retrospective study

Pavlovic, Natalie; Harris, Ian A.; Boland, Robert; Brady, Bernadette; Genel, Furkan; Naylor, Justine

doi:10.1186/s42836-023-00203-5

Cited by 3 publications

(1 citation statement)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Sled et al [10] proposed a landmark-based method for assessing Hip knee ankle angle (HKA) using customized software, addressing common issues in similar methods. In clinical practice, measurement accuracy can be influenced by factors such as body position [11][12][13] (like loading, flexion, or rotation of lower limbs), image quality [7], and reader experience [14][15][16]. Even with software assistance, deviations caused by hardware facilities and use can also affect the measurement, which leads to inter-and intra-reader variability and unsatisfied reliability [17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Automatic measurement of lower limb alignment in portable devices based on deep learning for knee osteoarthritis

Yang,

Ren,

Xin

et al. 2024

J Orthop Surg Res

View full text Add to dashboard Cite

Background For knee osteoarthritis patients, analyzing alignment of lower limbs is essential for therapy, which is currently measured from standing long-leg radiographs of anteroposterior X-ray (LLR) manually. To address the time wasting, poor reproducibility and inconvenience of use caused by existing methods, we present an automated measurement model in portable devices for assessing knee alignment from LLRs. Method We created a model and trained it with 837 conforming LLRs, and tested it using 204 LLRs without duplicates in a portable device. Both manual and model measurements were conducted independently, then we recorded knee alignment parameters such as Hip knee ankle angle (HKA), Joint line convergence angle (JCLA), Anatomical mechanical angle (AMA), mechanical Lateral distal femoral angle (mLDFA), mechanical Medial proximal tibial angle (mMPTA), and the time required. We evaluated the model’s performance compared with manual results in various metrics. Result In both the validation and test sets, the average mean radial errors were 2.778 and 2.447 (P<0.05). The test results for native knee joints showed that 92.22%, 79.38%, 87.94%, 79.82%, and 80.16% of the joints reached angle deviation<1° for HKA, JCLA, AMA, mLDFA, and mMPTA. Additionally, for joints with prostheses, 90.14%, 93.66%, 86.62%, 83.80%, and 85.92% of the joints reached that. The Chi-square test did not reveal any significant differences between the manual and model measurements in subgroups (P>0.05). Furthermore, the Bland-Altman 95% limits of agreement were less than ± 2° for HKA, JCLA, AMA, and mLDFA, and slightly more than ± 2 degrees for mMPTA. Conclusion The automatic measurement tool can assess the alignment of lower limbs in portable devices for knee osteoarthritis patients. The results are reliable, reproducible, and time-saving.

show abstract

Section: Introductionmentioning

confidence: 99%

Automatic measurement of lower limb alignment in portable devices based on deep learning for knee osteoarthritis

Yang,

Ren,

Xin

et al. 2024

J Orthop Surg Res

View full text Add to dashboard Cite

show abstract

Glucagon-Like Peptide-1 Receptor Agonists Decrease Medical and Surgical Complications in Morbidly Obese Patients Undergoing Primary TKA

Kim,

LaValva,

Parks

et al. 2024

Journal of Bone and Joint Surgery

View full text Add to dashboard Cite

Background: Weight optimization methods in morbidly obese patients with a body mass index (BMI) of ≥40 kg/m2 undergoing total knee arthroplasty (TKA) have shown mixed results. The purpose of this study was to evaluate the effect of perioperative use of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) in patients with a BMI of ≥40 kg/m2 undergoing primary TKA. Methods: Using an administrative claims database, patients with morbid obesity undergoing primary TKA were stratified into GLP-1 RA use for 3 months before and after the surgical procedure (treatment group) and GLP-1 RA non-use (control group), and were matched on the basis of patient age, gender, diagnosis of type-2 diabetes mellitus, and Charlson Comorbidity Index (CCI). In addition, these groups were compared with a contemporaneous cohort of patients undergoing TKA with a BMI of 35.0 to 39.9 kg/m2. Outcomes including infection, complications, revision, and readmission were compared between the matched cohorts. Results: There were significant decreases in the rates of 90-day periprosthetic joint infection (PJI) (1.0% compared with 1.8%; p = 0.037), any medical complications (10.6% compared with 12.7%; p = 0.033), pulmonary embolism (<0.4% compared with 0.6%; p = 0.050), and readmissions (5.3% compared with 8.9%; p < 0.001) in patients with a BMI of ≥40 kg/m2 who were taking GLP-1 RA versus the control group who were not. There were no differences in the 2-year rates of surgical complications (p > 0.05) between these groups. Compared with obese patients (BMI of 35.0 to 39.9 kg/m2), patients who had a BMI of ≥40 kg/m2 and were taking a GLP-1 RA did not have increased rates of infection or 90-day or 2-year complications (p > 0.05). Conclusions: GLP-1 RA administration for at least 90 days prior to and after primary TKA in patients with a BMI of ≥40 kg/m2 was associated with reductions in the risks of 90-day PJI, any medical complications, and readmission. Additionally, the reduced complication rate that was achieved was similar to that of obese patients with a BMI of 35.0 to 39.9 kg/m2 undergoing TKA. Randomized clinical trials are needed to define the true effect of these agents on clinical outcomes following TKA. Level of Evidence: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

show abstract

Influencing factors on the quality of recovery after total knee arthroplasty: development of a predictive model

Shan,

Shi,

Zhang

2024

Front. Med.

View full text Add to dashboard Cite

IntroductionTotal Knee Arthroplasty (TKA) is a widely performed procedure that significantly benefits patients with severe knee degeneration. However, the recovery outcomes post-surgery can vary significantly among patients. Identifying the factors influencing these outcomes is crucial for improving patient care and satisfaction.MethodsIn this retrospective study, we analyzed 362 TKA cases performed between January 1, 2018, and July 1, 2022. Multivariate logistic regression was employed to identify key predictors of recovery within the first year after surgery.ResultsThe analysis revealed that Body Mass Index (BMI), age-adjusted Charlson Comorbidity Index (aCCI), sleep quality, Bone Mineral Density (BMD), and analgesic efficacy were significant predictors of poor recovery (p < 0.05). These predictors were used to develop a clinical prediction model, which demonstrated strong predictive ability with an Area Under the Receiver Operating Characteristic (AUC) curve of 0.802. The model was internally validated.DiscussionThe findings suggest that personalized postoperative care and tailored rehabilitation programs based on these predictors could enhance recovery outcomes and increase patient satisfaction following TKA.

show abstract

The effect of body mass index and preoperative weight loss in people with obesity on postoperative outcomes to 6 months following total hip or knee arthroplasty: a retrospective study

Cited by 3 publications

References 49 publications

Automatic measurement of lower limb alignment in portable devices based on deep learning for knee osteoarthritis

Automatic measurement of lower limb alignment in portable devices based on deep learning for knee osteoarthritis

Glucagon-Like Peptide-1 Receptor Agonists Decrease Medical and Surgical Complications in Morbidly Obese Patients Undergoing Primary TKA

Influencing factors on the quality of recovery after total knee arthroplasty: development of a predictive model

Contact Info

Product

Resources

About