Louisa T.M.A. Mulder MSc , Danielle D.P. Berghmans PhD , Peter Z. Feczko MD, PhD , Sander M.J. van Kuijk PhD , Rob A. de Bie PhD , Antoine F. Lenssen PhD
{"title":"全膝关节置换术后院内身体功能延迟恢复的预测","authors":"Louisa T.M.A. Mulder MSc , Danielle D.P. Berghmans PhD , Peter Z. Feczko MD, PhD , Sander M.J. van Kuijk PhD , Rob A. de Bie PhD , Antoine F. Lenssen PhD","doi":"10.1016/j.arrct.2024.100321","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><p>To identify patients at high risk of delayed in-hospital functional recovery after knee replacement surgery by developing and validating a prediction model, including a combination of preoperative physical fitness parameters and patient characteristics.</p></div><div><h3>Design</h3><p>Retrospective cohort study using binary logistic regression.</p></div><div><h3>Setting</h3><p>University hospital, orthopedic department.</p></div><div><h3>Participants</h3><p>260 adults (N=260) (≥18y) with knee osteoarthritis awaiting primary unilateral total knee arthroplasty and assessed during usual care between 2016 and 2020.</p></div><div><h3>Intervention</h3><p>Not applicable.</p></div><div><h3>Main Outcome Measures</h3><p>Time to reach in-hospital functional independence (in days), measured by the modified Iowa Level of Assistance Scale. A score of 0 means completely independent. Potential predictor variables are a combination of preoperative physical fitness parameters and patient characteristics.</p></div><div><h3>Results</h3><p>Binary logistic regression modeling was applied to develop the initial model. A low de Morton Mobility Index (DEMMI), walking aid use indoors, and a low handgrip strength (HGS) were the most important predictors of delayed in-hospital recovery. This model was internally validated and had an optimism-corrected <em>R</em><sup>2</sup> of 0.07 and an area under curve of 61.2%. The probability of a high risk of delayed in-hospital recovery is expressed by the following equation:</p><p><span><math><mrow><msub><mi>P</mi><mrow><mi>h</mi><mi>i</mi><mi>g</mi><mi>h</mi><mi>r</mi><mi>i</mi><mi>s</mi><mi>k</mi></mrow></msub><mo>=</mo><mrow><mi>(</mi><mn>1</mn><mo>/</mo><mrow><mo>(</mo><mn>1</mn><mo>+</mo><msup><mrow><mi>e</mi></mrow><mrow><mo>(</mo><mo>−</mo><mo>(</mo><mn>2.638</mn><mo>−</mo><mn>0.193</mn><mo>×</mo><mi>D</mi><mi>E</mi><mi>M</mi><mi>M</mi><mi>I</mi><mo>+</mo><mn>0.879</mn><mo>×</mo><mi>i</mi><mi>n</mi><mi>d</mi><mi>o</mi><mi>o</mi><mi>r</mi><mi>w</mi><mi>a</mi><mi>l</mi><mi>k</mi><mi>i</mi><mi>n</mi><mi>g</mi><mi>a</mi><mi>i</mi><mi>d</mi><mo>−</mo><mn>0.007</mn><mo>×</mo><mi>H</mi><mi>G</mi><mi>S</mi><mo>)</mo><mo>)</mo></mrow></msup><mo>)</mo></mrow><mi>)</mi></mrow><mo>×</mo><mn>100</mn><mo>%</mo></mrow></math></span>.</p></div><div><h3>Conclusions</h3><p>The model has a low predictive value and a poor discriminative ability. However, there is a positive association between preoperative physical fitness and postoperative recovery of physical function. The validity of our model to distinguish between high and low risk, based on preoperative fitness values and patient characteristics, is limited.</p></div>","PeriodicalId":72291,"journal":{"name":"Archives of rehabilitation research and clinical translation","volume":"6 1","pages":"Article 100321"},"PeriodicalIF":1.9000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2590109524000041/pdfft?md5=5852e7f52b28f2fec37ae4256c993373&pid=1-s2.0-S2590109524000041-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Predicting Delayed In-Hospital Recovery of Physical Function After Total Knee Arthroplasty\",\"authors\":\"Louisa T.M.A. Mulder MSc , Danielle D.P. Berghmans PhD , Peter Z. Feczko MD, PhD , Sander M.J. van Kuijk PhD , Rob A. de Bie PhD , Antoine F. Lenssen PhD\",\"doi\":\"10.1016/j.arrct.2024.100321\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objective</h3><p>To identify patients at high risk of delayed in-hospital functional recovery after knee replacement surgery by developing and validating a prediction model, including a combination of preoperative physical fitness parameters and patient characteristics.</p></div><div><h3>Design</h3><p>Retrospective cohort study using binary logistic regression.</p></div><div><h3>Setting</h3><p>University hospital, orthopedic department.</p></div><div><h3>Participants</h3><p>260 adults (N=260) (≥18y) with knee osteoarthritis awaiting primary unilateral total knee arthroplasty and assessed during usual care between 2016 and 2020.</p></div><div><h3>Intervention</h3><p>Not applicable.</p></div><div><h3>Main Outcome Measures</h3><p>Time to reach in-hospital functional independence (in days), measured by the modified Iowa Level of Assistance Scale. A score of 0 means completely independent. Potential predictor variables are a combination of preoperative physical fitness parameters and patient characteristics.</p></div><div><h3>Results</h3><p>Binary logistic regression modeling was applied to develop the initial model. A low de Morton Mobility Index (DEMMI), walking aid use indoors, and a low handgrip strength (HGS) were the most important predictors of delayed in-hospital recovery. This model was internally validated and had an optimism-corrected <em>R</em><sup>2</sup> of 0.07 and an area under curve of 61.2%. The probability of a high risk of delayed in-hospital recovery is expressed by the following equation:</p><p><span><math><mrow><msub><mi>P</mi><mrow><mi>h</mi><mi>i</mi><mi>g</mi><mi>h</mi><mi>r</mi><mi>i</mi><mi>s</mi><mi>k</mi></mrow></msub><mo>=</mo><mrow><mi>(</mi><mn>1</mn><mo>/</mo><mrow><mo>(</mo><mn>1</mn><mo>+</mo><msup><mrow><mi>e</mi></mrow><mrow><mo>(</mo><mo>−</mo><mo>(</mo><mn>2.638</mn><mo>−</mo><mn>0.193</mn><mo>×</mo><mi>D</mi><mi>E</mi><mi>M</mi><mi>M</mi><mi>I</mi><mo>+</mo><mn>0.879</mn><mo>×</mo><mi>i</mi><mi>n</mi><mi>d</mi><mi>o</mi><mi>o</mi><mi>r</mi><mi>w</mi><mi>a</mi><mi>l</mi><mi>k</mi><mi>i</mi><mi>n</mi><mi>g</mi><mi>a</mi><mi>i</mi><mi>d</mi><mo>−</mo><mn>0.007</mn><mo>×</mo><mi>H</mi><mi>G</mi><mi>S</mi><mo>)</mo><mo>)</mo></mrow></msup><mo>)</mo></mrow><mi>)</mi></mrow><mo>×</mo><mn>100</mn><mo>%</mo></mrow></math></span>.</p></div><div><h3>Conclusions</h3><p>The model has a low predictive value and a poor discriminative ability. However, there is a positive association between preoperative physical fitness and postoperative recovery of physical function. The validity of our model to distinguish between high and low risk, based on preoperative fitness values and patient characteristics, is limited.</p></div>\",\"PeriodicalId\":72291,\"journal\":{\"name\":\"Archives of rehabilitation research and clinical translation\",\"volume\":\"6 1\",\"pages\":\"Article 100321\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2024-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2590109524000041/pdfft?md5=5852e7f52b28f2fec37ae4256c993373&pid=1-s2.0-S2590109524000041-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Archives of rehabilitation research and clinical translation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2590109524000041\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"REHABILITATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archives of rehabilitation research and clinical translation","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590109524000041","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"REHABILITATION","Score":null,"Total":0}
Predicting Delayed In-Hospital Recovery of Physical Function After Total Knee Arthroplasty
Objective
To identify patients at high risk of delayed in-hospital functional recovery after knee replacement surgery by developing and validating a prediction model, including a combination of preoperative physical fitness parameters and patient characteristics.
Design
Retrospective cohort study using binary logistic regression.
Setting
University hospital, orthopedic department.
Participants
260 adults (N=260) (≥18y) with knee osteoarthritis awaiting primary unilateral total knee arthroplasty and assessed during usual care between 2016 and 2020.
Intervention
Not applicable.
Main Outcome Measures
Time to reach in-hospital functional independence (in days), measured by the modified Iowa Level of Assistance Scale. A score of 0 means completely independent. Potential predictor variables are a combination of preoperative physical fitness parameters and patient characteristics.
Results
Binary logistic regression modeling was applied to develop the initial model. A low de Morton Mobility Index (DEMMI), walking aid use indoors, and a low handgrip strength (HGS) were the most important predictors of delayed in-hospital recovery. This model was internally validated and had an optimism-corrected R2 of 0.07 and an area under curve of 61.2%. The probability of a high risk of delayed in-hospital recovery is expressed by the following equation:
.
Conclusions
The model has a low predictive value and a poor discriminative ability. However, there is a positive association between preoperative physical fitness and postoperative recovery of physical function. The validity of our model to distinguish between high and low risk, based on preoperative fitness values and patient characteristics, is limited.
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