Severity of Diabetes Mellitus and Total Hip or Knee Replacement: A Population-Based Case-Control Study

The microbiota-metabolic syndrome axis as a promoter of metabolic osteoarthritis

The relation between obesity and osteoarthritis (OA) development has been traditionally explained as consequence of the excessive joint effort derived of overweight. However, in the last two decades a metabolic OA has been suggested through diverse molecular mechanism implying metabolic syndrome, although more investigation must be conducted to elucidate it. Metabolic syndrome is responsible of the release of diverse inflammatory cytokines, specially the increased adipokine in obesity, causing a chronic low-grade inflammatory status that alters the joint homeostasis. In this scenario, the microbiota dysbiosis contribute by worsening the low-grade chronic inflammation or causing metabolic disorders mediated by endotoxemia generated by an increased lipopolysaccharides intake. This results in joint inflammation and cartilage degradation, which contributes to the development of OA. Also, the insulin resistance provoked by type 2 Diabetes contributes to the OA development. When intake patterns are considered, some coincidences can be pointed between the food patterns associated to the metabolic syndrome and the food patterns associated to OA development. Therefore, these coincidences support the idea of a molecular mechanism of the OA development caused by the molecular mechanism generated under the metabolic syndrome status. This review points the relation between metabolic syndrome and OA, showing the connected molecular mechanisms between both pathologies as well as the shared dietary patterns that promote or prevent both pathologies.

Is postoperative glucose variability associated with adverse outcomes following shoulder arthroplasty?

BACKGROUND

Postoperative infection after shoulder arthroplasty is a devastating complication. Multiple patient risk factors have been associated with postoperative infection, including increased body mass index and diabetes. Although the association between preoperative glucose control and infection has been established, little is known about the effect of perioperative glycemic control on outcomes following shoulder arthroplasty. The purpose of this study was to investigate the association between postoperative glycemic variability and short-term complications after total shoulder arthroplasty (TSA) and reverse total shoulder arthroplasty (RTSA).

METHODS

A retrospective study was performed at a large, single-specialty center from January 2015 to December 2018. Patients were included if they underwent primary TSA or RTSA with a minimum of 90 days' follow-up and had a minimum of 1 serum glucose value obtained per day of the hospital stay or had ≥3 measurements obtained during the hospital admission period. The primary outcome variable was postoperative infection per accepted definitions of surgical-site infection or periprosthetic joint infection. Secondary outcome variables included stiffness, periprosthetic fracture, periprosthetic dislocation, and reoperation.

RESULTS

In total, 1074 TSAs or RTSAs (in 1032 patients) met the eligibility criteria. The mean patient age was 69.9 ± 8.4 years, and 40.3% of patients had a preoperative diagnosis of diabetes mellitus. Of the patients, 670 (62%) had a calculable coefficient of variation. A younger patient age (median, 65 years [interquartile range (IQR), 13.5 years] vs. 71 years [IQR, 11.0 years]; P = .02) and a preoperative diagnosis of diabetes mellitus (P = .01) showed statistically significant associations with postoperative infection. The first in-hospital glucose measurement beyond the reference tertile of 70-140 mg/dL showed a statistically significant association with postoperative infection, with a median of 128.0 mg/dL (IQR, 43 mg/dL) vs. 167.5 mg/dL (IQR, 37.0 mg/dL; P = .01), whereas the second and third glucose measurements showed no association with postoperative infection. We found no associations between the coefficient of variation and reoperations or complications including surgical-site infection, periprosthetic joint infection, death, postoperative infection, periprosthetic fracture, or stiffness.

CONCLUSION

We found an association between a preoperative diagnosis of diabetes mellitus and postoperative infection following shoulder arthroplasty. We also found that an elevated first glucose measurement is associated with the development of postoperative infection. In-hospital glycemic control, as well as preoperative glycemic control and optimization, may be beneficial for reducing postoperative infections following shoulder arthroplasty.

Impact of Diabetes on 90-Day Episodes of Care After Elective Total Joint Arthroplasty Among Medicare Beneficiaries

BACKGROUND

In an effort to improve quality and reduce costs, reimbursement for total knee arthroplasty (TKA) and total hip arthroplasty (THA) in the United States is being based on the value of care provided, with adjustments for some qualifying comorbidities, including diabetes in its most severe form and excluding many diabetes codes. The aims of this study were to examine the effects of diabetes on elective TKA or THA complications and readmission risks among Medicare beneficiaries.

METHODS

Complication (n = 521,230) and readmission (n = 515,691) data were extracted from Medicare files in 2013 and 2014. Diabetes status (no diabetes, controlled-uncomplicated diabetes, controlled-complicated diabetes, and uncontrolled diabetes) was identified with ICD-9 (International Classification of Diseases, 9th Revision) codes. TKA or THA complications and readmission odds based on diabetes status were estimated using logistic regression and adjusted for sociodemographic and clinical characteristics, including comorbidities.

RESULTS

Compared with no diabetes, the odds ratio (OR) of TKA complications was significantly higher for uncontrolled diabetes (1.29, 95% confidence interval [CI] = 1.06 to 1.57). The OR of THA complications was significantly higher for controlled-complicated diabetes (1.45, 95% CI = 1.17 to 1.80). The OR of readmission was significantly higher for all diabetes groups (1.21 to 1.48 for TKA, 1.20 to 1.70 for THA).

CONCLUSIONS

Readmission odds were higher in all diabetes categories. The uncontrolled-diabetes group had the greatest TKA readmission and complication odds. The controlled-complicated diabetes group had the greatest THA readmission and complication odds. The findings suggest that including diabetes and associated systemic complications in cost adjustments in alternative payment models for arthroplasty should be considered.

LEVEL OF EVIDENCE

Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Metabolic syndrome, hypertension, and hyperglycemia were positively associated with knee osteoarthritis, while dyslipidemia showed no association with knee osteoarthritis

OBJECTIVE

Metabolic syndrome (MetS) is a clustering of at least three of the following four medical conditions: obesity, hypertension, dyslipidemia, and hyperglycemia. We aimed to discover the relationships between these diseases and osteoarthritis (OA) of the knee.

METHODS

We searched four databases (EMBASE, PubMed, Cochrane Library, and MEDLINE), as well as articles on websites and conference materials. Study effect estimates and their 95% confidence intervals (CIs) were extracted and calculated. Sensitivity analyses were undertaken to determine inter-study heterogeneity. Finally, we tested for publication bias to determine whether the outcome of the meta-analysis was robust.

RESULTS

A total of 1609 articles were identified, 40 of which were included. In radiological studies, the relationships with OA were increased for people with the following diseases: metabolic syndrome (OR 1.418, 95% CI 1.162 to 1.730), hypertension (OR 1.701, 95% CI 1.411 to 2.052), and hyperglycemia (OR 1.225, 95% CI 1.054 to 1.424). In symptomatic studies, the outcomes were similar in metabolic syndrome (OR 1.174, 95% CI 1.034 to 1.332) and hypertension (OR 1.324, 95% CI 1.186 to 1.478) studies, while there were no associations in hyperglycemia (OR 0.975, 95% CI 0.860 to 1.106) studies. There was no correlation between dyslipidemia and OA, whether in radiological studies (OR 1.216, 95% CI 0.968 to 1.529) or symptomatic studies (OR 1.050, 95% CI 0.961 to 1.146).

CONCLUSIONS

In both studies, metabolic syndrome and hypertension were positively associated with knee OA, and dyslipidemia showed no correlations. Hyperglycemia was associated with OA in radiological studies, while results were reversed in symptomatic studies. Key Points • The hypothesis that metabolic syndrome and its components increase the risk for knee osteoarthritis is attractive; thus, this meta-analysis may help us find out the answer. • There were lots of large-scale studies here, and the total participants were considerable; and this meta-analysis was relatively robust because of reasonable heterogeneity and publication bias. • Targeted education and effective management of risk factors may be helpful for reducing the prevalence of knee osteoarthritis.

Treat-to-target strategy for knee osteoarthritis. International technical expert panel consensus and good clinical practice statements

Background:

In this work, we aimed to establish a clinical target in the management of knee osteoarthritis (KOA) and to propose good clinical practice (GCP) statements for carrying out a treat-to-target strategy.

Methods:

A steering committee of seven experts had formulated a provisional set of recommendations that were exposed for discussion and modification to a technical expert panel (TEP) of 25 multidisciplinary experts from Europe, North America, South America and Asia. The level of evidence and strength of each recommendation was discussed. The TEP formulated overarching principles and GCP statements based on the level of agreement for each item with a vote using a 10-point numerical scale.

Results:

Two overarching principles and 10 GCP statements were formulated by the TEP. These GCP statements suggest: treatment should achieve clinical improvement bringing the patient to the Patient Acceptable Symptom State (PASS); pharmacological and nonpharmacological treatment should begin as early as possible, with an early diagnosis of symptomatic KOA; the patient should be evaluated every 3–6 months; risk factors of KOA progression should be identified and managed with patients at the beginning of the treatment and monitored regularly; treatment should be adapted according to patient phenotype and disease severity; healthy lifestyle must be promoted and monitored. The level of agreement average ranged from 8.7 to 9.6 on scale.

Conclusions:

The proposed overarching principles and GCP statements have the aim of involving patients, general practitioners and multidisciplinary specialists in sharing a therapeutic treat-to-target strategy for KOA management based on the best evidence and expert opinions.

Causal Factors for Knee, Hip, and Hand Osteoarthritis: A Mendelian Randomization Study in the UK Biobank

OBJECTIVE

There is no curative treatment for osteoarthritis (OA), which is the most common form of arthritis. This study was undertaken to identify causal risk factors of knee, hip, and hand OA.

METHODS

Individual-level data from 384,838 unrelated participants in the UK Biobank study were analyzed. Mendelian randomization (MR) analyses were performed to test for causality for body mass index (BMI), bone mineral density (BMD), serum high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglyceride levels, type 2 diabetes, systolic blood pressure (BP), and C-reactive protein (CRP) levels. The primary outcome measure was OA determined using hospital diagnoses (all sites, n = 48,431; knee, n = 19,727; hip, n = 11,875; hand, n = 2,330). Odds ratios (ORs) with 95% confidence intervals (95% CIs) were calculated.

RESULTS

MR analyses demonstrated a robust causal association of genetically determined BMI with all OA (OR per SD increase 1.57 [95% CI 1.44-1.71]), and with knee OA and hip OA, but not with hand OA. Increased genetically determined femoral neck BMD was causally associated with all OA (OR per SD increase 1.14 [95% CI 1.06-1.22]), knee OA, and hip OA. Low systolic BP was causally associated with all OA (OR per SD decrease 1.55 [95% CI 1.29-1.87]), knee OA, and hip OA. There was no evidence of causality for the other tested metabolic factors or CRP level.

CONCLUSION

Our findings indicate that BMI exerts a major causal effect on the risk of OA at weight-bearing joints, but not at the hand. Evidence of causality of all OA, knee OA, and hip OA was also observed for high femoral neck BMD and low systolic BP. However, we found no evidence of causality for other metabolic factors or CRP level.

Type 2 diabetes mellitus and osteoarthritis

OBJECTIVES

Type 2 diabetes mellitus (T2DM) and osteoarthritis (OA) are common diseases that frequently co-exist, along with overweight/obesity. While the mechanical impact of excess body weight on joints may explain lower limb OA, we sought to explore whether T2DM is linked to OA outside of excess weight and whether T2DM may play a role in OA pathophysiology. The consequence of T2DM on OA outcomes is a question of research interest.

METHODS

We conducted a critical review of the literature to explore the association between T2DM and OA, whether any association is site-specific for OA, and whether the presence of T2DM impacts on OA outcomes. We also reviewed the literature to assess the safety of anti-OA treatments in patients with T2DM.

RESULTS

T2DM has a pathogenic effect on OA through 2 major pathways involving oxidative stress and low-grade chronic inflammation resulting from chronic hyperglycemia and insulin resistance. T2DM is a risk factor for OA progression and has a negative impact on arthroplasty outcomes. Evidence is mounting for safety concerns with some of the most frequently prescribed anti-OA medications, including paracetamol, non-steroidal anti-inflammatory drugs, and corticosteroid injections, while other anti-OA medications may be safely prescribed in OA patients with T2DM, such as glucosamine and intra-articular hyaluronic acid.

CONCLUSIONS

Future research is needed to better understand whether diabetes control and prevention can modulate OA occurrence and progression. The selection of therapy to treat OA symptoms in patients with T2DM may require careful consideration of the evidence based to avoid untoward safety issues.

Impact of the definition of osteoarthritis and of the timing of its onset on the association between type 2 diabetes mellitus and osteoarthritis: Clinical Practice Research Datalink

AIMS

In a previous case-control study in a large primary care database, the Clinical Practice Research Datalink (CPRD), type 2 diabetes mellitus (T2DM) was associated with a decreased rate of total joint replacement (TJR). As this was in contrast to the hypothesis, selection bias due to the used definition of osteoarthritis (OA) or misclassification of the onset of OA were raised as possible explanations. We therefore aimed to explore the effect of the definition of OA, and hypothesized timing of its onset on the association between T2DM and OA.

METHODS

All patients using a non-insulin anti-hyperglycaemic drug (NIAD) between 1989 and 2012 in the CPRD were included and matched to unexposed patients. Cox proportional hazard models were fitted estimating the risk of TJR or OA in T2DM patients compared to patients without T2DM. These analyses were repeated in sensitivity scenarios and joint-specific analyses. To assess whether misclassification of onset of OA may affect the association, analyses were repeated with addition of a latency period of up to 10 years after start of follow-up.

RESULTS

The use of TJR as a proxy for OA (hazard ratio (HR) = 0.74; 95% Confidence Interval (CI) = 0.70-0.78) resulted in a HR that was approximately 0.2 lower than when OA diagnostic codes were used (HR = 0.93; 95% CI = 0.90-0.95). The joint-specific subgroup analyses, sensitivity scenarios, and latency analyses showed similar results.

CONCLUSION

When examining the association between T2DM and OA, the use of TJR as a proxy for OA resulted in a 20% lower estimate than the OA diagnosis.

Risk of Incident Osteoarthritis of the Hand in Statin Initiators: A Sequential Cohort Study

OBJECTIVE

To investigate the association between statin therapy initiation and incident hand osteoarthritis (OA).

METHODS

We performed a propensity score-matched cohort study using data from the UK-based Clinical Practice Research Datalink. Statin initiators had ≥1 statin prescription between 1996 and 2015 and were matched 1:1 on their propensity score to noninitiators within 10 sequential 2-year cohort entry blocks. After a 180-day run-in period, patients were followed in an as-treated approach until a recorded diagnosis of hand OA or until censoring (change in exposure status, development of an exclusion criterion, or maximum follow-up of 5.5 years). We applied Cox proportional hazard regression to calculate hazard ratios (HRs) with 95% confidence intervals (95% CIs) overall and in subgroups of sex, age, statin dose, statin agent, preexisting dyslipidemia, and treatment duration. To compare results, we ran all analyses with negative and positive control outcomes and assessed generalized OA as a secondary outcome. We further performed the overall analysis with an active comparator (topical glaucoma therapy initiators).

RESULTS

Among 233,608 statin initiators and the same number of noninitiators, we observed an overall HR for hand OA of 0.98 (95% CI 0.88-1.09). The observed null result remained unchanged in all subgroups. Results were highly similar for generalized OA and negative control outcomes. In addition, the active comparator analysis showed a null result with an HR for hand OA of 0.85 (95% CI 0.56-1.29). Previously known associations with positive control outcomes were observed.

CONCLUSION

There was no association between statin initiation and incident hand OA in this study.

Type 2 diabetes patients have accelerated cartilage matrix degeneration compared to diabetes free controls: data from the Osteoarthritis Initiative

PURPOSE

Osteoarthritis (OA) and diabetes mellitus (DM) share common risk factors with a potential underlying relationship between both diseases. The purpose of this study was to investigate the longitudinal effects of DM on cartilage deterioration over 24-months with MR-based T2 relaxation time measurements.

METHODS

From the Osteoarthritis Initiative (OAI) cohort 196 diabetics were matched in small sets for age, sex, BMI and Kellgren-Lawrence score with 196 non-diabetic controls. Knee cartilage semi-automatic segmentation was performed on 2D multi-slice multi-echo spin-echo sequences. Texture of cartilage T2 maps was obtained via grey level co-occurrence matrix analysis. Linear regression analysis was used to compare cross-sectional and changes in T2 and texture parameters between the groups.

RESULTS

Both study groups were similar in age (63.3 vs 63.0 years, P = 0.70), BMI (30.9 vs 31.2 kg/m2, P = 0.52), sex (female 53.6% vs 54.1%, P = 0.92) and KL score distribution (P = 0.97). In diabetics, except for the patella, all compartments showed a significantly higher increase in mean T2 values when compared to non-diabetic controls. Global T2 values increased almost twice as much; 1.77ms vs 0.98ms (0.79ms [CI: 0.39,1.19]) (P < 0.001). Additionally, global T2 values showed a significantly higher increase in the bone layer (P = 0.006), and in a separate analysis of the texture parameters, diabetics also showed consistently higher texture values (P < 0.05), indicating a more disordered cartilage composition.

CONCLUSION

Cartilage T2 values in diabetics show a faster increase with a consistently more heterogeneous cartilage texture composition. DM seems to be a risk factor for developing early OA with an accelerated degeneration of the articular cartilage in the knee.

Metabolic syndrome as a risk factor for total hip or knee replacement due to primary osteoarthritis: a prospective cohort study (the HUNT study and the Norwegian Arthroplasty Register)

Objective

Biochemical changes associated with obesity may accelerate osteoarthritis beyond the effect of mechanical factors. This study investigated whether metabolic syndrome and its components (visceral obesity, hypertension, dyslipidemia and insulin resistance) were risk factors for subsequent total hip replacement (THR) or total knee replacement (TKR) due to primary osteoarthritis.

Design

In this prospective cohort study, data from the second survey of the Nord-Trøndelag Health Study 2 (HUNT2) were linked to the Norwegian Arthroplasty Register for identification of the outcome of THR or TKR. The analyses were stratified by age (<50, 50–69.9 and ≥70 years) and adjusted for gender, body mass index, smoking, physical activity and education.

Results

Of the 62,661 participants, 12,593 (20.1%) were identified as having metabolic syndrome, and we recorded 1,840 (2.9%) THRs and 1,111 (1.8%) TKRs during a mean follow-up time of 15.4 years. Cox regression analyses did not show any association between full metabolic syndrome and THR or TKR, except in persons <50 years with metabolic syndrome who had a decreased risk of THR (hazard ratio [HR] 0.58, 95% CI 0.40–0.83). However, when including only participants whose exposure status did not change during follow-up, this protective association was no longer significant. Increased waist circumference was associated with increased risk of TKR in participants <50 years (HR 1.62, 95% CI 1.10–2.39) and 50–69.9 years (HR 1.43, 95% CI 1.14–1.80). Hypertension significantly increased the risk of TKR in participants <50 years (HR 1.38, 95% CI 1.05–1.81), and this risk was greater for men.

Conclusion

This study found an increased risk of TKR in men <50 years with hypertension and persons <70 years with increased waist circumference. Apart from this, neither metabolic syndrome nor its components were associated with increased risk of THR or TKR due to primary osteoarthritis.

Prevalence of type 2 diabetes and impaired fasting glucose in patients affected by rheumatoid arthritis: Results from a cross-sectional study

Although the better management of rheumatoid arthritis (RA) has significantly improved the long-term outcome of affected patients, a significant proportion of these may develop associated comorbidities including cardiometabolic complications. However, it must be pointed out that a comprehensive cardiometabolic evaluation is still poorly integrated into the management of RA patients, due to a limited awareness of the problem, a lack of appropriate clinical studies, and optimal strategies for cardiovascular (CV) risk reduction in RA. In addition, although several studies investigated the possible association between traditional CV risk factors and RA, conflicting results are still available.On this basis, we planned this cross-sectional study, aimed at investigating the prevalence of type 2 diabetes (T2D) and impaired fasting glucose (IFG) in RA patients compared with age- and gender- matched control individuals. Furthermore, we analyzed the role of both traditional and RA-related CV risk factors in predicting T2D and IFG.We observed an increased prevalence of T2D in RA patients when compared with age- and gender-matched controls. Regression analyses demonstrated that the presence of high blood pressure (HBP), a longer disease duration, and exposure to corticosteroids (CCS) were significantly associated with an increased likelihood of being classified as T2D. In addition, we observed an increased prevalence of IFG in RA patients when compared with age- and gender-matched controls. Regression analyses demonstrated that a higher body mass index (BMI), the presence of metabolic syndrome (MetS), higher levels of total cholesterol, the presence of radiographic damage, and higher serum levels of C-reactive protein (CRP) were significantly associated with an increased likelihood of presenting IFG.In this cross-sectional study, we observed an increased prevalence of T2D and IFG in an Italian cohort of RA patients when compared with age- and gender-matched control individuals. Interestingly, both RA-specific features, such as disease duration, CCS exposure, and radiographic damage, and traditional CV risk factors, such as HBP and MetS, were significantly associated with glucose metabolism abnormalities.

Metabolic syndrome-associated osteoarthritis

PURPOSE OF REVIEW

Interest in the metabolic syndrome-associated osteoarthritis phenotype is increasing. Here, we summarize recently published significant findings.

RECENT FINDINGS

Meta-analyses confirmed an association between type 2 diabetes and osteoarthritis and between cardiovascular diseases and osteoarthritis. Recent advances in the study of metabolic syndrome-associated osteoarthritis have focused on a better understanding of the role of metabolic diseases in inducing or aggravating joint damage. In-vivo models of obesity, diabetes, or dyslipidemia have helped to better decipher this association. They give emerging evidence that, beyond the role of common pathogenic mechanisms for metabolic diseases and osteoarthritis (i.e., low-grade inflammation and oxidative stress), metabolic diseases have a direct systemic effect on joints. In addition to the impact of weight, obesity-associated inflammation is associated with osteoarthritis severity and may modulate osteoarthritis progression in mouse models. As well, osteoarthritis synovium from type 2 diabetic patients shows insulin-resistant features, which may participate in joint catabolism. Finally, exciting data are emerging on the association of gut microbiota and circadian rhythm and metabolic syndrome-associated osteoarthritis.

SUMMARY

The systemic role of metabolic syndrome in osteoarthritis pathophysiology is now better understood, but new avenues of research are being pursued to better decipher the metabolic syndrome-associated osteoarthritis phenotype.

Osteoarthritis and type 2 diabetes mellitus: What are the links?

Osteoarthritis (OA) is the most frequent joint disorder and one of the leading cause of disability. During a long time, it was considered as the consequence of aging and mechanical stress on cartilage. Recent advances in the knowledge of OA have highlighted that it is a whole joint disease with early modifications of synovium and subchondral bone but also that it is associated with obesity and metabolic syndrome through systemic mechanisms. In the past year, type 2 diabetes has been described in two meta-analyzes as an independent risk factor for OA. In vivo models of diabetes corroborated epidemiological studies. Indeed, diabetic rodents display a spontaneous and a more severe experimental OA than their non-diabetic counterparts, which can be partially prevented by diabetes treatment (insulin, pioglitazone). The negative impact of diabetes on joints could be explain by the induction of oxidative stress and pro-inflammatory cytokines but also by advanced age products accumulation in joint tissues exposed to chronic high glucose concentration. Insulin resistance might also impair joint tissue because of a local insulin resistance of diabetic synovial membrane but also by the systemic low grade inflammation state related to obesity and insulin resistant state.