Total knee replacement in osteoarthritis patients on reducing the risk of major adverse cardiac events: a 18-year retrospective cohort study

Association between knee osteoarthritis and mortality: a serial propensity score-matched cohort study

BACKGROUND/AIMS

The association between symptomatic knee osteoarthritis (OA) and higher cardiovascular disease (CVD) mortality is established; however, findings from studies that utilized regression analysis were limited, attributed to the strong association between OA and metabolic risk factors. This study aimed to evaluate the association between knee OA and mortality through propensity score matching.

METHODS

This was a cohort study including Korean National Health and Nutrition Examination Survey (2010-2013) participants aged ≥ 50 years. By linking the survey data to cause of death data (through 2019) from Statistics Korea, mortality and cause-specific mortality data were obtained. Radiographic knee OA (ROA) was defined as bilateral Kellgren-Lawrence grade ≥ 2. Propensity score matching (1:1) was conducted between asymptomatic ROA, knee pain, and symptomatic ROA groups and normal groups, balancing the confounding factors. Time to death was analyzed using Cox proportional hazard modeling.

RESULTS

A higher CVD mortality was observed in the symptomatic ROA group, but not in others; the risk estimates were asymptomatic ROA (hazard ratio [HR] 1.12; 95% confidence interval [CI] 0.77-1.65), knee pain (HR 0.61; 95% CI 0.27-1.38), and symptomatic ROA (HR 1.39; 95% CI 0.89-2.17). No association was found between the all-cause/cancer mortality and other groups.

CONCLUSION

When propensity score matching controls metabolic risk factor imbalances, the association between symptomatic knee OA and higher CVD mortality was weaker compared to results of prior studies that used regression adjustment. The results may be more precise estimates of the total risk of knee OA for mortality in Koreans.

Deep Learning-Based CT Imaging to Evaluate the Therapeutic Effects of Acupuncture and Moxibustion Therapy on Knee Osteoarthritis

The study was aimed at analyzing the application value of deep learning-based computed tomography (CT) in evaluating the effect of acupuncture for knee osteoarthritis (KOA). Specifically, 124 patients with KOA were selected in the test group (warm acupuncture and moxibustion) and the control group (simple acupuncture), with 62 cases in each group. Deep learning-based CT scanning was performed before and after treatment to compare the Lequesne-Mery, Visual Analog Scale (VAS), Western Ontario and McMaster Universities (WOMAC), Hospital Special Surgery (HSS), and Knee Society Score (KSS) scores as well as the overall effective rate. The results showed that the trabecular thickness, quantity, bone mineral density (BMD), connection density, structural model index, and articular cartilage thickness were different significantly between the two groups (P < 0.05). After treatment, the Lequesne-Mery was 4.78, the VAS was 0.87, and the WOMAC score was 14.89 of the test group, which were reduced (P < 0.05). The KSS and HSS scores of the test group were improved significantly after treatment (P < 0.05). The total effective rate of the test group was 85.48%, and that of the control group was 51.61%; the former was significantly higher than the latter (P < 0.05). In conclusion, acupuncture could improve the clinical effect on KOA patients, and CT scanning under deep learning algorithm could evaluate the clinical effect of acupuncture for KOA.