Dataset Information

The association of parity with osteoarthritis and knee replacement in the multicenter osteoarthritis study.

ABSTRACT: We evaluated the association of parity to both risk of knee replacement (KR) and knee osteoarthritis (OA).The NIH-funded Multicenter Osteoarthritis Study (MOST) is a longitudinal observational study of persons age 50-79 years with either symptomatic knee OA or at elevated risk of disease. Baseline and 30-month knee radiographic OA (ROA) was defined as Kellgren/Lawrence (K/L) grade ?2 or KR. Women were grouped based by number of births: 0; 1 (reference group); 2; 3; 4; and 5 or more. We examined the relation of parity to the incidence over 30 months of ROA and KR using a Poisson regression model. Generalized estimating equations (GEE) were used to control for correlation between two knees within a subject. We adjusted for age, BMI, race, education, occupation, baseline estrogen use, clinical site, injury, and for KR analyses WOMAC pain and use of pain medication.Among 1618 women who reported parity information, mean age was 62.6 years, mean BMI 30.7 kg/m(2), mean WOMAC pain subscale score 3.7 at baseline. There were 115 KRs and 134 cases of incident knee ROA over 30 months. The relative risk of incident KR was 2.7 times as high (95% CI: 1.0, 7.3) and relative risk of incident knee ROA was 2.6 times as high (95% CI: 1.2, 5.3) among women with five to 12 children compared with those with one birth.Parity in women at risk for OA is associated with both incident ROA and KR, particularly for those with more than four children.

SUBMITTER: Wise BL

PROVIDER: S-EPMC3855897 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The association of parity with osteoarthritis and knee replacement in the multicenter osteoarthritis study.

Wise B L BL Niu J J Zhang Y Y Felson D T DT Bradley L A LA Segal N N Keysor J J Nevitt M M Lane N E NE

Osteoarthritis and cartilage 20130909 12

<h4>Objective</h4>We evaluated the association of parity to both risk of knee replacement (KR) and knee osteoarthritis (OA).<h4>Design</h4>The NIH-funded Multicenter Osteoarthritis Study (MOST) is a longitudinal observational study of persons age 50-79 years with either symptomatic knee OA or at elevated risk of disease. Baseline and 30-month knee radiographic OA (ROA) was defined as Kellgren/Lawrence (K/L) grade ≥2 or KR. Women were grouped based by number of births: 0; 1 (reference group); 2; ...[more]

PMID: 24029601

Similar Datasets

Project description:BackgroundSome of the poor functional outcomes of knee arthroplasty may be due to pain in the contralateral, unreplaced knee. We investigated the relationship between the preoperative pain status of the contralateral knee and the risk of a poor postoperative functional outcome in patients who underwent knee arthroplasty.MethodsWe analyzed data on 271 patients in the Multicenter Osteoarthritis Study who had undergone knee arthroplasty since the time of enrollment. Eighty-six percent of these patients were white, 72% were female, and the mean age was sixty-seven years. The severity of pain in the knee contralateral to the one that was replaced was measured before the knee arthroplasty with use of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain scale, with the scores being grouped into four categories (0, 1 to 4, 5 to 9, and 10 to 20). Poor post-arthroplasty function six months or more after surgery was determined with use of the Patient Acceptable Symptom State (PASS) outcome tool and a clinical performance measure of walking speed. We evaluated the relationship between contralateral pain severity and the functional outcomes with use of Poisson regression.ResultsSeventy-two (27%) of 264 patients demonstrated poor post-arthroplasty function by failing to attain the threshold PASS score, and seventy-six (30%) of 250 subjects had a slow walking speed. As the pre-arthroplasty pain in the contralateral knee increased, there was a steady increase in the proportion with poor post-arthroplasty function (p < 0.0001 for PASS and p = 0.04 for slow walking speed). Compared with patients who had no pre-arthroplasty pain in the contralateral knee, those in the highest category of contralateral pain severity had 4.1 times the risk (95% confidence interval, 1.5 to 11.5) of having poor self-reported post-arthroplasty function. Patients in whom both knees had been replaced at the time of outcome collection were less likely to have poor self-reported function than those in whom only one knee had been replaced.ConclusionsPreoperative pain in the contralateral knee is strongly associated with self-reported post-arthroplasty functional outcome and may therefore be a useful indicator of prognosis or a potential target of perioperative intervention.Level of evidencePrognostic Level II. See Instructions for Authors for a complete description of levels of evidence.

Project description:Reduced external knee adduction moments in the second half of stance after total hip replacement have been reported in hip osteoarthritis patients. This reduction is thought to shift the load from the medial to the lateral knee compartment and as such increase the risk for knee osteoarthritis. The knee adduction moment is a surrogate for the load distribution between the medial and lateral compartments of the knee and not a valid measure for the tibiofemoral contact forces which are the result of externally applied forces and muscle forces. The purpose of this study was to investigate whether the distribution of the tibiofemoral contact forces over the knee compartments in unilateral hip osteoarthritis patients 1 year after receiving a primary total hip replacement differs from healthy controls. Musculoskeletal modeling on gait was performed in OpenSim using the detailed knee model of Lerner et al. (2015) for 19 patients as well as for 15 healthy controls of similar age. Knee adduction moments were calculated by the inverse dynamics analysis, medial and lateral tibiofemoral contact forces with the joint reaction force analysis. Moments and contact forces of patients and controls were compared using Statistical Parametric Mapping two-sample t-tests. Knee adduction moments and medial tibiofemoral contact forces of both the ipsi- and contralateral leg were not significantly different compared to healthy controls. The contralateral leg showed 14% higher medial tibiofemoral contact forces compared to the ipsilateral (operated) leg during the second half of stance. During the first half of stance, the lateral tibiofemoral contact force of the contralateral leg was 39% lower and the ratio 32% lower compared to healthy controls. In contrast, during the second half of stance the forces were significantly higher (39 and 26%, respectively) compared to healthy controls. The higher ratio indicates a changed distribution whereas the increased lateral tibiofemoral contact forces indicate a higher lateral knee joint loading in the contralateral leg in OA patients after total hip replacement (THR). Musculoskeletal modeling using a detailed knee model can be useful to detect differences in the load distribution between the medial and lateral knee compartment which cannot be verified with the knee adduction moment.

Project description:Background The methods for assessing knee osteoarthritis (OA) do not provide enough comprehensive information to make robust and accurate outcome predictions. Purpose To develop a deep learning (DL) prediction model for risk of OA progression by using knee radiographs in patients who underwent total knee replacement (TKR) and matched control patients who did not undergo TKR. Materials and Methods In this retrospective analysis that used data from the OA Initiative, a DL model on knee radiographs was developed to predict both the likelihood of a patient undergoing TKR within 9 years and Kellgren-Lawrence (KL) grade. Study participants included a case-control matched subcohort between 45 and 79 years. Patients were matched to control patients according to age, sex, ethnicity, and body mass index. The proposed model used a transfer learning approach based on the ResNet34 architecture with sevenfold nested cross-validation. Receiver operating characteristic curve analysis and conditional logistic regression assessed model performance for predicting probability and risk of TKR compared with clinical observations and two binary outcome prediction models on the basis of radiographic readings: KL grade and OA Research Society International (OARSI) grade. Results Evaluated were 728 participants including 324 patients (mean age, 64 years ± 8 [standard deviation]; 222 women) and 324 control patients (mean age, 64 years ± 8; 222 women). The prediction model based on DL achieved an area under the receiver operating characteristic curve (AUC) of 0.87 (95% confidence interval [CI]: 0.85, 0.90), outperforming a baseline prediction model by using KL grade with an AUC of 0.74 (95% CI: 0.71, 0.77; P < .001). The risk for TKR increased with probability that a person will undergo TKR from the DL model (odds ratio [OR], 7.7; 95% CI: 2.3, 25; P < .001), KL grade (OR, 1.92; 95% CI: 1.17, 3.13; P = .009), and OARSI grade (OR, 1.20; 95% CI: 0.41, 3.50; P = .73). Conclusion The proposed deep learning model better predicted risk of total knee replacement in osteoarthritis than did binary outcome models by using standard grading systems. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Richardson in this issue.

Dataset Information

The association of parity with osteoarthritis and knee replacement in the multicenter osteoarthritis study.

Publications

The association of parity with osteoarthritis and knee replacement in the multicenter osteoarthritis study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure