Effect of body mass index on duration of total knee replacement surgery: A prospective cross sectional study

Abbas, Zamin; Hafeez, Sohail; Naseem, Ali; Habib, Yasir; Mumtaz, Hassan

doi:10.1016/j.amsu.2022.104637

Cited by 3 publications

(1 citation statement)

References 16 publications

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“…We concur with the other studies on negative impact of gender on complications. 23,24 Duration of surgery influences complications in any surgery and joint arthroplasty should be an exception. Yasunaga et al (2009) 25 suggested that with the average operating time was 127 AE 47 min; they had postoperative complications of 9.8%.…”

Section: Discussionmentioning

confidence: 99%

The effect of obesity on the outcome of total knee replacement (TKR)

Al-Omran

2022

F1000Res

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Background: The objective of this study was to look for the outcome of TKR in obese individuals. Methods: The data of all patients who had undergone primary TKR between 2005 and 2015 were collected from the QuadruMed Patient Care System and crosschecked with the operating room. The biometric data of age, gender, weight and postoperative follow up, any complications were collected from the medical charts. Patients were classified as per the BMI (Body Mass Index). BMI is classified as per the WHO classification of 2000 Results Two hundred and four patients fulfilled the criteria for inclusion. The demographic data is given in Table 2. The average age 59.8±9.3 years. Right side was operated in 103 and left in 101 patients. The average BMI was 35.88±7.47 (Range 21.95-54.78); mean duration of surgery was 163.37±29.9 (Range 88-250) minutes. The range of follow up was 5-14 years with the average of 7.49±2.56 years. There were 18 (8.8%) complications. One hundred and three (50.5%) of the patients belonged to Class II Obesity (BMI ≥36Kg/M2). Between class II obesity and Class III obesity (BMI ≥41Kg/M2, the later had 94.4% of the complications. The level of satisfaction was similar in all the groups at 80%. High BMI and longer duration of surgery were important and statistically significant risk factors (p <0.0001 and <0.009) for complications during TKA. Post operative data on VAS, Modified Knee Scoring Score and WOMAC grading, showing low scores of all the assessment in the patients with higher BMI. Conclusions: Our analysis shows that our patients with Class III obesity had over 90% of the complications and we believe that patients in this BMI range should seek ways to reduce their body weight to avoid complications and long-term morbidity.

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Section: Discussionmentioning

confidence: 99%

The effect of obesity on the outcome of total knee replacement (TKR)

Al-Omran

2022

F1000Res

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Predicting duration of surgery in hip and knee arthroplasty with machine learning: Operational factors are important.

Nejad,

Matthiesen,

Dukovska-Popovska

et al. 2024

Preprint

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Total hip arthroplasty (THA) and total knee arthroplasty (TKA) are among the most common surgeries in the healthcare system which highly consume hospital resources. An accurate prediction of the duration of surgery (DOS) can improve operating room scheduling and subsequently enhance hospital resource allocation efficiency. Currently, hospitals generally rely on historical data average or surgeons’ experience for DOS prediction which are prone to inaccuracy and personal bias. Besides, not enough attention has been paid to DOS prediction for these surgeries in the literature. This paper aims to develop machine learning (ML) models to predict surgery duration for patients undergoing hip and knee arthroplasty based on clinical and operational factors. Clinical and operational factors (n = 3,233) were extracted from Aalborg University Hospital’s database from 2017 to 2020. Three ML models (Extreme Gradient Boosting (XGBoost), Multilayer Perceptron, and Support Vector Machine) were developed and their performances were evaluated and compared with a baseline model. XGBoost demonstrated the best performance among all models (Mean Absolute Error = 12.86, Root Mean Squared Error = 16.67, Buffer Accuracy = 68.73). Furthermore, all models performed better than the baseline model. Analyzing feature importances indicated that the surgeon, temporal factors, and surgery type are the most contributing factors for predicting DOS. To conclude, machine learning models can improve the accuracy of DOS prediction for TKA and THA surgeries compared to the current methods. As an ensemble learning method, XGBoost can better deal with health data complexities related to DOS. Besides medical features, operational factors have a significant contribution to predicting DOS.

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Factors Affecting Operating Room Scheduling Accuracy for Primary and Revision Total Knee Arthroplasty: A Retrospective Study

Cardillo,

Garry,

Katzman

et al. 2024

Orthopedics

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Background: Optimizing operating room (OR) scheduling accuracy is important for improving OR efficiency and maximizing value of total knee arthroplasty (TKA). However, data on factors that may impact TKA OR scheduling accuracy are limited. Materials and Methods: A retrospective review of 7655 knee arthroplasties (6999 primary TKAs and 656 revision TKAs) performed between January 2020 and May 2023 was conducted. Patient baseline characteristics, surgeon experience (years in practice), as well as actual vs scheduled OR times were collected. Actual OR times that were at least 15% shorter or longer than scheduled OR times were considered to be clinically important. Logistic regression analyses were employed to assess the influence of specific patient and surgeon factors on OR scheduling inaccuracies. Results: Using adjusted odds ratio, patients with primary TKA who had a lower body mass index ( P <.001) were independently associated with overestimation of scheduled surgical time. Conversely, younger age ( P <.001), afternoon procedure start time ( P <.001), surgeons with less than 10 years of experience ( P =.037), and higher patient body mass index ( P <.001) were associated with underestimation of scheduled surgical time. For revision TKA, female sex ( P =.021) and morning procedure start time ( P =.038) were associated with overestimation of scheduled surgical time, while surgeons with less than 10 years of experience ( P =.014) and patients who underwent spinal/epidural/block anesthesia ( P =.038) were associated with underestimation of scheduled surgical time. Conclusion: This study highlights patient, surgeon, and intraoperative variables that impact the accuracy of scheduling for TKA procedures. Health systems should take these variables into consideration when creating OR schedules to fully optimize resources and available space. [ Orthopedics . 202x;4x(x):xx–xx.]

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Effect of body mass index on duration of total knee replacement surgery: A prospective cross sectional study

Cited by 3 publications

References 16 publications

The effect of obesity on the outcome of total knee replacement (TKR)

The effect of obesity on the outcome of total knee replacement (TKR)

Predicting duration of surgery in hip and knee arthroplasty with machine learning: Operational factors are important.

Factors Affecting Operating Room Scheduling Accuracy for Primary and Revision Total Knee Arthroplasty: A Retrospective Study

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