Phenotypes in Osteoarthritis

Dório, Murillo; Deveza, Leticia A

doi:10.1016/j.cger.2021.11.002

Cited by 12 publications

(9 citation statements)

References 63 publications

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“…For instance, Moser et al (2020) identified diverse knee phenotypes based on knee alignment and recommended personalised TKA realignment for improved outcomes. By identifying distinct patient phenotypes, researchers can investigate the underlying variables that contribute to disease progression, prognosis, and outcomes (Dório & Deveza, 2022). While the prognostic value of the phenotypes identified in this study are yet to be determined, these phenotypes may aid in refining patient selection, targeted preoperative interventions, and enhancing shared decision-making with patients presenting for surgical review of OA.…”

Section: Discussionmentioning

confidence: 99%

“…While phenotyping has the potential to offer significant benefits to orthopaedic research and clinical practice, caution is necessary in regards to the phenotypes themselves and the analytical approaches used to develop them (Dório & Deveza, 2022). A number of different phenotypes could be identified based on the variables included in the model irrespective of their true relevance for phenotyping.…”

Section: Discussionmentioning

confidence: 99%

“…Phenotyping is an emerging field in orthopaedic research that offers a more nuanced understanding of patient heterogeneity and has the potential to guide management decisions (29). While this study focused on PROMs, previous research has explored OA phenotypes has attempted to group patients with OA into phenotypes based on gait kinematics (20,21), joint aspirate metabolomics (22), pain groups (23), functional knee characteristics (24), structural characteristics, and prognosis (25) While phenotyping has the potential to offer significant benefits to orthopaedic research and clinical practice, caution is necessary in regards to the phenotypes themselves and the analytical approaches used to develop them (18). A number of different phenotypes could be identified based on the variables included in the model irrespective of their true relevance for phenotyping.…”

Section: Discussionmentioning

confidence: 99%

“…Knee OA is a disease with marked heterogeneity in terms of pathology, progression, demographics, and treatment response, which likely contributes to the difficulty in predicting outcomes (Dório & Deveza, 2022). The question has been raised whether the variability in patients with OA might be explained by the existence of discrete subgroups or phenotypes (Driban et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

“…However, these findings and approaches have yet to achieve clinically significant reliability (17). Knee OA's marked heterogeneity in pathology, progression, demographics, and treatment response likely complicates outcome prediction, prompting consideration of whether patient variability can be explained by discrete subgroups or phenotypes (18,19). Phenotypes refer to groups of patients with similar characteristics, such as demographics, clinical presentation, disease progression, and treatment response.…”

Section: Introductionmentioning

confidence: 99%

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Multidimensional analysis of preoperative patient-reported outcomes identifies distinct phenotypes in patients booked for total knee arthroplasty: Secondary analysis of the SHARKS registry in a metropolitan hospital department

McGill,

Scholes,

Torbey

et al. 2023

Preprint

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AimsTraditional research on total knee arthroplasty (TKA) has predominantly utilised individual preoperative patient-reported outcome measures (PROMs) to predict postoperative satisfaction. The objective of this study was to leverage the power of machine learning to simultaneously analyse multiple PROMs, thus unveiling unique patient phenotypes within this heterogeneous population. This study aimed to identify phenotypes in patients scheduled for TKA using multidimensional analysis of preoperative PROMs and evaluate their correlation with patient characteristics.MethodsPatients booked for primary TKA between 2017 and 2021 at a metropolitan public hospital were enrolled in the clinical quality registry (SHARKS) maintained by the orthopaedics department. The registry collected demographic and clinical data, including PROMs such as the Veterans Rand 12 (VR-12) and Oxford Knee Score (OKS). The imputed data was used for the primary analysis, which involved clustering patients based on their responses to VR-12 and OKS subscale scores using a k-means clustering algorithm. A k value of 4 was chosen to identify four distinct phenotypes. ANOVA was used to compare average scores in each cluster. Relationships between phenotype and patient age, sex, body mass index (BMI), and laterality were determined using nominal logistic regressionResultsThere were 389 patients and 450 primary knees included in the study (49.6% females and 50.4% males). The cluster analysis categorised patients into four distinct phenotypes based on VR-12 PCS, VR-12 MCS, OKS-F, and OKS-P scores. Patients in phenotype 3 (Mild symptoms with good mental health) reported superior physical function, less pain, and higher mental and general health scores, while those in phenotype 2 (Severe symptoms with poor mental health) experienced the greatest knee pain, impairment, and poorer physical and mental health. Notably, phenotype 4 (Moderate symptoms with good mental health) patients reported high mental health scores despite significant knee pain and physical health impairment. Patient characteristics were significantly associated with phenotype. Patients in theSevere symptoms with poor mental healthphenotype were significantly more likely to be younger, female, have a higher BMI, and exhibit bilateral OA compared to those in theMild symptoms with good mental healthphenotype (P<0.05).ConclusionsThis preliminary study employed a multidimensional data analysis method to identify phenotypes in OA patients based on commonly used PROMs. These phenotypes demonstrated significant associations with patient demographics. A key advantage of this approach is the capability to identify patterns that may not be discernible when interpreting PROMs independently. The use of cluster analysis demonstrates potential for developing prognostic models in joint replacement and warrants further research to improve clinical decision-making and patient outcomes.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multidimensional analysis of preoperative patient-reported outcomes identifies distinct phenotypes in patients booked for total knee arthroplasty: Secondary analysis of the SHARKS registry in a metropolitan hospital department

McGill,

Scholes,

Torbey

et al. 2023

Preprint

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Effect of l‐Carnitine Supplementation on Osteoarthritis: A Systematic Review

Kou,

Li,

Wang

et al. 2024

Molecular Nutrition Food Res

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ScopeComprehensive assessment of l‐carnitine's safety and effectiveness in reducing inflammatory markers in osteoarthritis (OA) patients.Methods and resultsJournal articles on l‐carnitine for OA are gathered using computer searches of PubMed, Embase, the Cochrane Library, and Web of Science. The kind of literature that is found is restricted to clinical randomized controlled trials (RCTs). The Cochrane Handbook risk of bias assessment tool RevMan 5.4 software is used to conduct a meta‐analysis. The systematic assessment comprises eight trials totaling 619 patients; the included studies’ quality is mediocre. The study's findings demonstrate that OA patients’ Western Ontario and McMaster University (WOMAC) function improves and that treatment efficacy outperforms that of the control group (mean difference [MD] = −7.75, 95% CI [−14.63, −0.86]; Z = 2.21; p = 0.03), WOMAC total (MD = −10.24, 95% CI [−18.97, −1.51]; Z = 2.30; p = 0.02), and visual analogue scale (VAS) pain (MD = −14.01, 95% CI [−16.16, −11.85]; Z = 12.74; p < 0.00001). The studies that are methodically reviewed also discover heterogeneity, which may have resulted from the created pooled data and requires more analysis.ConclusionIn patients with OA, l‐carnitine effectively decreases clinical signs and symptoms, inflammatory markers, pain, and stiffness indicators, and significantly improves WOMAC and VAS scores.

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Cholesterol, systemic inflammation, interleukin-1β, and osteoarthritis risk — aligning animal models with specific patient endotypes provides novel insights

Little

2023

Osteoarthritis and Cartilage

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Phenotypes in Osteoarthritis

Cited by 12 publications

References 63 publications

Multidimensional analysis of preoperative patient-reported outcomes identifies distinct phenotypes in patients booked for total knee arthroplasty: Secondary analysis of the SHARKS registry in a metropolitan hospital department

Multidimensional analysis of preoperative patient-reported outcomes identifies distinct phenotypes in patients booked for total knee arthroplasty: Secondary analysis of the SHARKS registry in a metropolitan hospital department

Effect of l‐Carnitine Supplementation on Osteoarthritis: A Systematic Review

Cholesterol, systemic inflammation, interleukin-1β, and osteoarthritis risk — aligning animal models with specific patient endotypes provides novel insights

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