Do Knee Pain Phenotypes Have Different Risks of Total Knee Replacement?

Education level has an effect on the recovery of total knee arthroplasty: a retrospective study

OBJECTIVE

This study aimed to observe the relationship between education level and outcomes after total knee arthroplasty (TKA).

METHODS

One thousand two hundred sixty four patients after TKA in our hospital from April 2016 to April 2020 were reviewed. These patients were divided into 4 groups (A who were illiterate, B who had elementary school degree, C who had junior high school degree, D who had senior high school degree or higher) by the educational level, which was blinded to the observers. The postoperative outcomes of KSS score, pain, joint extension and flexion function were observed 1 year after discharged from hospital.

RESULTS

Among 1253 patients met the inclusion criteria, the average age was 68.63 years, the average body mass was 57.73 kg. There are no distinctions among 4 groups one day after the surgery. However, the outcomes of the follow up were that, the KSS score was: 77.84 ± 10.635; 80.70 ± 8.956; 87.92 ± 8.123;91.27 ± 8.262, with significant differences (P < 0.05). The mean VAS scores were: 1.97 ± 1.60; 2.07 ± 1.66; 1.197 ± 1.5265, 1.044 ± 1.4662. Patients in Group C and D had significantly less pain than that in Group A and B (P < 0.05). The knee flexion range of motion (ROM) was: 91.21 ± 11.69°; 91.77 ± 11.95°; 102.12 ± 11.38°; 109.96 ± 10.64°, Group D performed best, with significant differences (P < 0.05). The knee extension ROM were: - 2.41 ± 4.49°; - 0.91 ± 2.82°; - 0.83 ± 2.87°; - 0.35 ± 1.60°, with significant difference between Group D and the others (P < 0.05).

CONCLUSION

Education level affects the outcomes such as VAS score, KSS score, the extension and flexion ROM of the knee after TKA. The patients with higher education level have better outcomes.

Association of Pain Phenotypes with Risk of Falls and Incident Fractures

Objective: To compare whether falls risk score and incident fracture over 10.7 years were different among three previously identified pain phenotypes. Methods: Data on 915 participants (mean age 63 years) from a population-based cohort study were studied at baseline and follow-ups at 2.6, 5.1 and 10.7 years. Three pain phenotypes were previously identified using the latent class analysis: Class 1: high prevalence of emotional problems and low prevalence of structural damage; Class 2: high prevalence of structural damage and low prevalence of emotional problems; Class 3: low prevalence of emotional problems and low prevalence of structural damage. Fractures were self-reported and falls risk score was measured using the Physiological Profile Assessment. Generalized estimating equations model and linear mixed-effects model were used to compare differences in incident fractures and falls risk score over 10.7 years between pain phenotypes, respectively. Results: There were 3 new hip, 19 vertebral, and 121 non-vertebral fractures, and 138 any site fractures during 10.7-year follow-up. Compared with Class 3, Class 1 had a higher risk of vertebral (relative risk (RR) = 2.44, 95% CI: 1.22-4.91), non-vertebral fractures (RR = 1.20, 95% CI: 1.01-1.42), and any site fractures (RR = 1.24, 95% CI: 1.04-1.46) after controlling for covariates, bone mineral density and falls risk score. Class 2 had a higher risk of non-vertebral and any site fracture relative to those in Class 3 (non-vertebral: RR = 1.41, 95% CI: 1.17-1.71; any site: RR = 1.44, 95% CI: 1.20-1.73), but not vertebral fracture. Compared with Class 3, Class 1 had a higher falls risk score at baseline (β = 0.16, 95% CI: 0.09-0.23) and over 10.7-year (β = 0.03, 95% CI: 0.01-0.04). Conclusions: Class 1 and/or Class 2 had a higher risk of incident fractures and falls risk score than Class 3, highlighting that targeted preventive strategies for fractures and falls are needed in pain population.

Translating clinical and patient-reported data to tailored shared decision reports with predictive analytics for knee and hip arthritis

Introduction

New informatics tools can transform evidence-based information to individualized predictive reports to serve shared decisions in clinic. We developed a web-based system to collect patient-reported outcomes (PROs) and medical risk factors and to compare responses to national registry data. The system generates predicted outcomes for individual patients and a report for use in clinic to support decisions. We present the report development, presentation, and early experience implementing this PRO-based, shared decision report for knee and hip arthritis patients seeking orthopedic evaluation.

Methods

Iterative patient and clinician interviews defined report content and visual display. The web-system supports: (a) collection of PROs and risk data at home or in office, (b) automated statistical processing of responses compared to national data, (c) individualized estimates of likely pain relief and functional gain if surgery is elected, and (d) graphical reports to support shared decisions. The system was implemented at 12 sites with 26 surgeons in an ongoing cluster randomized trial.

Results

Clinicians and patients recommended that pain and function as well as clinical risk factors (e.g., BMI, smoking) be presented to frame the discussion. Color and graphics support patient understanding. To date, 7891 patients completed the assessment before the visit and 56% consented to study participation. Reports were generated for 98% of patients and 68% of patients recalled reviewing the report with their surgeon.

Conclusions

Informatics solutions can generate timely, tailored office reports including PROs and predictive analytics. Patients successfully complete the pre-visit PRO assessments and clinicians and patients value the report to support shared surgical decisions.

Electronic supplementary material

The online version of this article (10.1007/s11136-020-02557-8) contains supplementary material, which is available to authorized users.