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Modeling Patient Satisfaction After Arthroscopic Partial Meniscectomy Using Knee Injury and Osteoarthritis Scores (KOOS) Measured With Error- [electronic resource]
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Modeling Patient Satisfaction After Arthroscopic Partial Meniscectomy Using Knee Injury and Osteoarthritis Scores (KOOS) Measured With Error- [electronic resource]
자료유형  
 학위논문
Control Number  
0016933738
International Standard Book Number  
9798380260732
Dewey Decimal Classification Number  
616.7
Main Entry-Personal Name  
Harvey, Tucker J.
Publication, Distribution, etc. (Imprint  
[S.l.] : University of Pittsburgh., 2022
Publication, Distribution, etc. (Imprint  
Ann Arbor : ProQuest Dissertations & Theses, 2022
Physical Description  
1 online resource(95 p.)
General Note  
Source: Dissertations Abstracts International, Volume: 85-03, Section: B.
General Note  
Advisor: Carlson, Jenna;Buchanich, Jeanine;Brooks, Maria;Youk, Ada.
Dissertation Note  
Thesis (M.Sc.)--University of Pittsburgh, 2022.
Restrictions on Access Note  
This item must not be sold to any third party vendors.
Summary, Etc.  
요약Pain and reduced function resulting from tears of the meniscus can cause disability, compounded by a risk of osteoarthritis. The Knee Injury and Osteoarthritis Score (KOOS) is a tool for quantifying pain and functional deficits, but scores can vary even without underlying biological change. Arthroscopic Partial Meniscectomy (APM) is a minimally invasive surgery used to repair meniscal tears, but it's hypothesized that using improvements in KOOS pain or function sub-scores alone is too simplistic to determine whether patients are satisfied with their post-operative results. This project modelled post-operative satisfaction using KOOS and baseline demographic characteristics, while accounting for the intra-subject variability of KOOS. Logistic regression was used to model satisfaction with KOOS and demographic covariates. A backwards-selection technique with bootstrapping was used to quantify variable importance. Age, education, race, and mental health were identified as important covariates for a reduced model. A multiple imputation technique was used to simulate KOOS uncertainty, in which other covariates were used to impute potentially true values of the erroneously-measured variables using background information about the distribution of errors. This was followed by regression of satisfaction on these imputed values and computation of corrected regression coefficient estimates. Minor changes to regression coefficient estimates and odds ratios resulted, but the associated confidence intervals generally overlapped with the uncorrected estimates. While the effect of KOOS pain on satisfaction marginally decreased, the effect of KOOS function increased. Individuals who were worse off (high pain and low function) at baseline, and those whose pain and function improved the most, had the highest probability of satisfaction. More research is needed to exactly explain the effect estimates for demographic predictors. Additionally, simulation studies would be useful to determine the performance of this measurement error correction method, as would a study of KOOS using validation data. This project has public health implications in educating clinicians and patients about what factors are important in determining satisfaction after APM, specifically how KOOS should be used. There are considerable ethical and financial benefits to more effectively identifying ideal candidates for surgery, while ruling out those unlikely to benefit.
Subject Added Entry-Topical Term  
Osteoarthritis.
Subject Added Entry-Topical Term  
Arthritis.
Subject Added Entry-Topical Term  
Surgery.
Subject Added Entry-Topical Term  
Body mass index.
Subject Added Entry-Topical Term  
Normal distribution.
Subject Added Entry-Topical Term  
Knee.
Subject Added Entry-Topical Term  
Feature selection.
Subject Added Entry-Topical Term  
Pain.
Subject Added Entry-Topical Term  
Probability.
Subject Added Entry-Topical Term  
Surgical outcomes.
Subject Added Entry-Topical Term  
Clinical outcomes.
Subject Added Entry-Topical Term  
Patient satisfaction.
Subject Added Entry-Topical Term  
Health care management.
Subject Added Entry-Topical Term  
Health sciences.
Subject Added Entry-Topical Term  
Medicine.
Added Entry-Corporate Name  
University of Pittsburgh.
Host Item Entry  
Dissertations Abstracts International. 85-03B.
Host Item Entry  
Dissertation Abstract International
Electronic Location and Access  
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Control Number  
joongbu:643728
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