Multidisciplinary Intervention Before Joint Replacement Surgery May Improve Outcomes for People with Osteoarthritis and Metabolic Syndrome: A Cohort Study

Abstract

Background:

Metabolic syndrome has been associated with poorer outcomes in the immediate postoperative period following joint replacement surgery for osteoarthritis. The aim of this study was to determine whether a multidisciplinary, preoperative intervention would minimize postoperative differences between people with and without metabolic syndrome who underwent joint replacement surgery for osteoarthritis.

Method:

A retrospective cohort study of older adults with multiple comorbidities (n = 230) attending a preoperative intervention service before lower limb joint replacement surgery. The intervention aimed to optimize the patient's health and functional reserve before surgery through weight loss, physical activity and medical management. Patient outcomes were adverse events, discharge destination and function. Health service outcomes were length of stay, hospital readmissions and emergency department presentations over a 2-year follow-up.

Results:

Two-thirds of participants (n = 151) had metabolic syndrome. There were no significant differences between those with and without metabolic syndrome in terms of discharge destination or adverse events during the acute hospital admission. There were no differences in function during rehabilitation but people with metabolic syndrome had significantly more adverse events (P = 0.037) during rehabilitation. In the 2 years following surgery, there were no differences in hospital readmission rates but people with metabolic syndrome had a higher observed frequency of potentially avoidable emergency department presentations (P = 0.066).

Conclusions:

Providing a preoperative intervention may help minimize differences between people with and without metabolic syndrome in the immediate postoperative period. However, having a diagnosis of metabolic syndrome may still adversely affect some long-term health service outcomes following joint replacement surgery.

Introduction

Metabolic syndrome is a group of risk factors (central obesity, hypertension, raised triglycerides, lowered high-density lipoprotein (HDL) cholesterol, and/or raised fasting glucose) that commonly occur together to raise the risk of chronic diseases.¹ Compared with people without metabolic syndrome, people with metabolic syndrome are twice as likely to develop cardiovascular disease,² have an increased risk of developing some cancers,³ and have double the health care utilization and costs.⁴ A recent systematic review reported a bidirectional relationship between metabolic syndrome and osteoarthritis whereby having metabolic syndrome was associated with an increased risk of osteoarthritis and having osteoarthritis was associated with an increased risk of metabolic syndrome.⁵ This is hypothesized to be due to common low-grade systemic inflammation present in both osteoarthritis and metabolic syndrome.⁶

Approximately one quarter of all adults have metabolic syndrome⁷ and it is unclear whether prevalence is higher in people with osteoarthritis due to differing definitions and study designs.⁵ In an Australian study, 26% of participants (n = 1222, mean age 72 years) who underwent joint replacement surgery for osteoarthritis had metabolic syndrome.⁸ In the Malmo Diet and Cancer study, prevalence was 30% in people with severe osteoarthritis (n = 209, mean age 58 years)⁹ and in the NHANES III study, prevalence was 59% in people with osteoarthritis (n = 975, mean age 70 years).¹⁰ The broad range in results and the differing populations means the prevalence of metabolic syndrome in older adults with osteoarthritis is still largely unknown.

The occurrence of metabolic syndrome in people with osteoarthritis is important as its presence may be associated with poorer outcomes and increased in-hospital complications for people with osteoarthritis.^11,12 A recent systematic review, including 10 cohort studies (9 retrospective, 1 prospective), found people with metabolic syndrome had higher postoperative complication rates after hip and knee joint replacement surgery and higher 30-day readmission rates.¹² However, the level of control of metabolic risk factors may be an important factor in postoperative outcomes. A retrospective study found people with metabolic syndrome (n = 133) who had uncontrolled components (e.g., hypertension, glucose control) had a significantly higher risk of postoperative complications than those with controlled metabolic syndrome.¹³ In a prospective study of people with diabetes and prediabetes (n = 228), better hyperglycemia control through medical management before knee joint replacement surgery was associated with reduced postoperative complications.¹⁴ In addition, previous research has found that preoperative, multidisciplinary interventions for patients with multimorbidity before hip and knee arthroplasties may improve postoperative outcomes.^15
–17 Therefore, preoperative interventions may be an effective way to reduce complications for people with metabolic syndrome who require joint replacement surgery for osteoarthritis. However, the effect of preoperative interventions has not been explored in people with metabolic syndrome and osteoarthritis and there is little data on longer term outcomes such as health care utilization.

Therefore, our primary aim was to determine whether a multidisciplinary preoperative intervention would minimize differences between people with and without metabolic syndrome in postoperative patient and health service outcomes following lower limb joint arthroplasty for osteoarthritis. Second, we aimed to describe the prevalence and characteristics of metabolic syndrome in patients waiting for lower limb joint replacement surgery due to osteoarthritis.

Materials and Methods

Study design

A retrospective, cohort study of people attending a multidisciplinary screening and intervention service [Proactive Intervention and Medical assessment in the Elderly (PRIME)] before lower limb joint replacement surgery for osteoarthritis. Participants with metabolic syndrome were compared with control participants without metabolic syndrome. The research was approved by hospital and university Human Research and Ethics Committees before commencement (HREC/53649/Austin-2019).

Participants

Participants were eligible to participate if they attended PRIME between 2010 and 2016 (to allow for 2-year follow-up) and were deemed appropriate for lower limb joint replacement surgery.

To be eligible for the PRIME service, patients needed to have been referred for planned elective joint replacement surgery, be 65 years or older, and have significant comorbidities (e.g., poorly controlled diabetes) or functional problems (e.g., history of falls) (Table 1).

Table 1.

Referral Criteria for Proactive Intervention and Medical Assessment in the Elderly

To be accepted into PRIME, patients must have been at least 65 years of age, planning to have elective surgery and have at least one of the following:

Poorly controlled diabetes

Poorly controlled hypertension

Recent history of myocardial infarction

Unstable angina

Unstable or undiagnosed cardiac arrhythmia

Current treatment for congestive cardiac failure

Significant shortness of breath

Chronic renal or liver failure

Significant peripheral vascular disease

Previous stroke or other chronic neurological disease

On long-term anticoagulation

Chronic lung disease

Poor nutritional status

Two or more falls

Significant memory problems or dementia

Requiring assistance with more than two activities of daily living or likely to need complex discharge planning

PRIME, Proactive Intervention and Medical assessment in the Elderly.

As metabolic syndrome is often not diagnosed or recorded, the presence of metabolic syndrome was determined from patient health records based on international definitions.¹ Participants must have had at least 3 of the 5 common criteria for clinical diagnosis of metabolic syndrome: (1) Abdominal obesity according to elevated waist circumference using population and country-specific definitions. Body mass index (BMI) >25 kg/m² was used to indicate central obesity if waist circumference was not available; (2) Elevated triglycerides ≥1.7 mmol/L or on drug therapy for elevated triglycerides; (3) Reduced HDL cholesterol <1.0 mmol/L for males or <1.3 mmol/L for females or on drug therapy for reduced HDL cholesterol; (4) Elevated blood pressure systolic ≥130 and/or diastolic ≥85 mmHg or on antihypertensive drug therapy; and/or (5) Elevated fasting glucose ≥5.6 mmol/L or on drug therapy for elevated glucose. HbA1c levels indicating diabetes (>6.4%) or prediabetes (5.7%–6.4%)¹⁸ were used when fasting glucose was not available.

Participants who attended the PRIME service were identified from hospital records and screened for eligibility. Participants were assessed according to metabolic syndrome criteria and then classified as having or not having metabolic syndrome. These groups were then compared.

The sample size was dependent on the total number of eligible patients who attended the PRIME service between June 2010 (when it commenced) and December 2016.

Setting

The setting was a large public health network in metropolitan Melbourne, Australia. Participants attended outpatient appointments at a community branch of the hospital network, had their joint replacement surgery at one acute hospital, and their inpatient rehabilitation at one of two subacute sites within the health network.

Intervention

All participants received multidisciplinary input from the PRIME service before joint replacement surgery. The PRIME service provides multidisciplinary assessment and intervention for patients 65 years of age or older, who are planning to have elective surgery and are considered to have an increased postoperative risk of adverse outcomes. The PRIME service has two aims: (1) to assess the suitability of patients for surgery; and (2) to optimize the patient's health and functional reserve before surgery. Participants had a comprehensive preoperative multidisciplinary health assessment and had subsequent individualized management plans implemented based on the comprehensive assessment [see Table 2 for intervention details described according to the Template for Intervention Description and Replication checklist (TIDieR)¹⁹]. The individualized management plans often included exercise, physical activity advice, nutritional advice for weight loss, and medication optimization. The PRIME intervention addressed all the components required to manage metabolic syndrome, even though metabolic syndrome was not formally diagnosed or targeted by the intervention.

Table 2.

Template for Intervention Description and Replication Description of Intervention

TIDieR criteria	Intervention
Brief name	PRIME: Proactive Intervention and Medical assessment in the Elderly
Why/aim of the intervention	(1) To assess the suitability of patients for surgery; and (2) To optimize the patient's health and functional reserve before surgery.
What	Multidisciplinary assessment and intervention for patients 65 years of age or older, who were planning to have elective surgery and were considered to have an increased postoperative risk of adverse outcomes.
Procedures	Patients were only seen preoperatively. No follow-up appointments were made following surgery. Medical/Nursing Assessment and Intervention A comprehensive medical assessment to identify chronic medical conditions, including liaising with specialists, the patient may have been in contact with previously, and referral for relevant investigations. Medical management involved optimization of medication and included liaising with the patient's general practitioner and referral to specialist clinics when required. Allied Health Assessment and Intervention All patients had a physiotherapy assessment, which focused on mobility and the patient's participation in activity or exercise. The aim of the physiotherapy intervention was to address functional deficits and improve activity levels and fitness. As required, patients had a nutritional screen and review by a dietician. Appropriate intervention was completed depending on nutritional status and BMI
Who provided the intervention	The PRIME multidisciplinary team comprised a geriatrician, nurse practitioner, physiotherapist, and dietitian. Geriatrician: Highly experienced geriatrician with more than 10 years expertise in geriatric presurgical management and general medicine. Nurse practitioner: Senior nurse with more than 40 years' experience with a focus on improving clients' elective surgery journeys. Physiotherapist: Senior physiotherapist with postgraduate clinical Masters qualification and more than 10 years of musculoskeletal clinical experience supported by junior physiotherapists. Dietician: Junior dietician with no specific additional training.
How was it delivered	The initial appointments were 2-hr, individual, face-to-face appointments. At this appointment, patients were assessed by at least two members, and up to all four members of the team if required. Review appointments were made with the individual team members as appropriate.
Where did it occur	Participants attended outpatient appointments at a community branch of a large public health network in metropolitan Melbourne, Australia.
When and how much was delivered	All participants attended an initial appointment. Review appointments were made with individual team members as appropriate. Interventions were highly individualized and were dependent on the patient's motivations and values. Example physiotherapy options included: home exercise program only; twice-weekly, 6-week group exercise program; and individual appointments. Dietary interventions were often an initial education session focusing on portion size and healthy eating +/− follow-up sessions as required.
Tailoring of intervention for individuals	All participants received individualized care based upon their complex care needs.
Modifications during the course of the study	No changes throughout the intervention period.
How well/intervention adherence	All participants attended their initial PRIME appointment and were deemed eligible for surgery.

BMI, body mass index; TIDieR, Template for Intervention Description and Replication checklist.

Outcomes

Demographic details (age, gender, country of birth, comorbidity, smoking status) were recorded. The primary outcomes were classified as patient health outcomes or health service outcomes.

Patient health outcomes were outcomes measured in relation to the participants' joint replacement surgery. Adverse events (e.g., wound infections, anemia, delirium, hypotension) during acute and rehabilitation inpatient admissions that were documented in the hospital risk management database were recorded. Discharge destination from the acute inpatient health service was recorded as either home (with or without support) or subacute inpatient rehabilitation. Functional independence measure (FIM)²⁰ on admission to and discharge from inpatient rehabilitation (if applicable) was extracted from medical records.

Health service outcomes included: length of stay (acute inpatient and rehabilitation inpatient); readmissions within 28 days of discharge from hospital; readmissions within 60 days of discharge from hospital; hospitalizations within 2 years; emergency department presentations; and potentially avoidable emergency department presentations within 2 years of discharge. Potentially avoidable presentations to an emergency department were defined as those where the patient: was triaged as a category 4 or 5 (less urgent, defined as moderate or minimal acuity) on the Australasian Triage Scale²¹; did not arrive by ambulance, police, or correctional vehicle; and was not admitted to hospital, not referred to another hospital, and did not die.²²

Data analysis

Mean differences and 95% confidence intervals (95% CI) were calculated for between-group effects for continuous outcomes (length of stay, functional independence). Relationships between demographic factors and outcomes were explored using point biserial correlations (for one continuous and one dichotomous outcome e.g., gender) and bivariate correlations (for continuous outcomes). A Pearson's r value of 0.1 to 0.29 was considered weak, 0.3 to 0.49 was considered moderate and 0.5 to 1 was considered strong correlation.²³

Risk ratios (RR) and 95% confidence intervals were calculated to assess between-group differences in dichotomous outcomes for health care use (having or not having a readmission, an admission to subacute rehabilitation and an emergency department presentation).The nonparametric Kruskal–Wallis test was used to determine if groups differed in the total number of adverse events, emergency department presentations, and hospital admissions, considering that data were skewed and an individual could have more than one presentation or admission.²³ In addition, incidence rate ratios (IRRs) and 95% confidence intervals were calculated using Poisson's regression to compare the rates of incidences (adverse events) when the length of data collection differed (i.e., based on length of stay for acute and rehabilitation settings). Two-way analysis of variance was used to assess the interaction effects of older age (65 or more years), elevated BMI (>25 kg/m²), and high Charlson Comorbidity Index score (≥5) with metabolic syndrome presence on any significantly different health service outcomes.

Results

Participants

Between 2010 and 2016, 415 patients attended the PRIME service with hip and knee problems. Of these, 232 were eligible to participate as they progressed to hip or knee joint replacement surgery between 2010 and 2016. Others were not eligible because they were deemed inappropriate surgical candidates (n = 26), declined surgical interventions (n = 22), required other surgery (n = 30), had joint replacement surgery after 2016 (n = 13), or did not progress to surgery (n = 92) because they were either lost to follow-up, had surgery at another health service, or completed conservative physiotherapy management. Two participants were subsequently excluded as they had insufficient data to diagnose the presence or absence of metabolic syndrome (Fig. 1), therefore 230 participants were included.

FIG. 1.

Flow of participants through the study. PRIME, Proactive Intervention and Medical assessment in the Elderly.

There were a number of statistically significant but weak correlations present between demographic factors and health service outcomes (Table 3). There was a positive, statistically significant moderate correlation between age and rehabilitation length of stay (r = 0.38, P < 0.001).

Table 3.

Correlation Between Demographic Factors and Outcomes

	Patient and health service outcomes, Pearson's r (P)
Demographic variables	Acute hospital length of stay	Acute hospital adverse events	Rehabilitation length of stay	Rehabilitation FIM score on admission	Rehabilitation FIM score on discharge	Rehabilitation adverse events	Total emergency department presentations over 2 years	Potentially avoidable emergency department presentations over 2 years	Total hospital admissions over 2 years
Female gender n = 139 (60%)	0.055 (0.404)	−0.117 (0.076)	0.052 (0.547)	0.085 (0.329)	−0.047 (0.589)	−0.148 (0.087)	−0.005 (0.946)	−0.014 (0.830)	−0.015 (0.824)
Age (years) Mean 71 (SD 10)	0.236 (<0.001)^a	0.212 (0.001)^a	0.380 (<0.001)^a	−0.294 (0.001)^a	−0.217 (0.012)^a	0.158 (0.068)	0.203 (0.002)^a	0.169 (0.010)^a	0.149 (0.025)^a
Charlson Comorbidity Index Mean 4.1 (SD 2.6)	0.142 (0.032)^a	0.180 (0.006)^a	0.068 (0.452)	−0.281 (0.001)^a	−0.180 (0.038)^a	0.145 (0.092)	0.139 (0.036)^a	0.054 (0.420)	0.230 (<0.001)^a
BMI ≥25 kg/m² n = 204 (89%)	−0.088 (0.213)	−0.093 (0.185)	−0.214 (0.016)^a	0.149 (0.104)	0.075 (0.414)	−0.020 (0.822)	−0.091 (0.195)	−0.085 (0.226)	−0.062 (0.380)
Current smoker n = 33 (14%)	−0.045 (0.498)	0.077 (0.245)	−0.005 (0.955)	0.046 (0.600)	0.079 (0.366)	−0.155 (0.186)	0.019 (0.773)	−0.017 (0.798)	0.028 (0.669)

Denotes statistically significant correlation (P < 0.05).

FIM, functional independence measure; SD, standard deviation.

Of the participants, 151 (66%) had metabolic syndrome and 79 did not. People with metabolic syndrome were a mean age of 72 (standard deviation, SD 8) years, 54% were female, and 95% were overweight or obese (BMI >25 kg/m²). People without metabolic syndrome were a mean age of 69 (SD 11) years, 72% were female, and 77% were overweight or obese. Participants with metabolic syndrome were on average 3 years older (95% CI: 0–6) and had a Charlson Comorbidity Index score of 0.9 points (95% CI: 0.2–1.7) higher than those without metabolic syndrome (Table 4).

Table 4.

Participant Characteristics

	Metabolic syndrome	No metabolic syndrome	P
n	151	79
Surgery location			0.162
Knee joint replacement surgery, n = (%)	102 (68)	46 (58)
Hip joint replacement surgery, n = (%)	49 (32)	33 (42)
Gender			0.009^a
Males, n = (%)	69 (46)	22 (28)
Females, n = (%)	82 (54)	57 (72)
Age, mean (SD)	72 (8)	69 (11)	0.026^a
Charlson comorbidity index score, mean (SD)	4.4 (2.6)	3.4 (2.6)	0.009^a
BMI ≥25, n = (%)	143 (95)	61 (77)	<0.001^a
Smoking status, n = (%)			0.161
Nonsmoker	92 (61)	52 (66)
Smoker	16 (11)	17 (22)
Exsmoker	43 (28)	10 (13)

Denotes statistically significant values (P < 0.05).

In-hospital patient health outcomes

Following preoperative intervention, there were no significant differences between groups in terms of discharge destination, rehabilitation admission, intensive care unit admission, or FIM score in rehabilitation (Table 4). People with metabolic syndrome were not more likely to have an adverse event during their acute hospitalization (RR: 1.29, 95% CI: 0.93–1.79, P = 0.12) or inpatient rehabilitation (RR: 1.25, 95% CI: 0.94–1.66, P = 0.13).

Considering an individual may have more than one adverse event, there were no significant differences between groups for the number of adverse events that occurred during the acute hospital admission (P = 0.093). When accounting for acute hospital length of stay, there were still no differences between groups (IRR: 1.4, 95% CI: 0.89–2.19, P = 0.145). During the rehabilitation admission, people with metabolic syndrome had significantly more adverse events (P = 0.037). There were no interaction effects between Charlson Comorbidity Index score severity [F(1, 131) = 0.749, P = 0.388], older age [F(1, 131) = 0.032, P = 0.858], or elevated BMI [F(1, 119) = 0.017, P = 0.898] and metabolic syndrome for rehabilitation adverse events. To account for differences in rehabilitation length of stay, IRRs were also calculated and people with metabolic syndrome had an observed adverse event rate 47% higher than those without metabolic syndrome (IRR: 1.47, 95% CI: 0.98–2.23, P = 0.066).

Health service outcomes

Following preoperative intervention, there were no differences between groups in terms of in-hospital health service outcomes, that is, acute or rehabilitation length of stay (Table 4). For longer term health service outcomes there were no differences between groups for 30- or 60-day readmissions, hospitalizations, or emergency department presentations. In the 2 years following surgery, 29% (44/150) of participants with metabolic syndrome had a potentially avoidable emergency department presentation compared with 18% (14/79) of participants without metabolic syndrome (RR: 1.66, 95% CI: 0.97–2.83, P = 0.065) and had a higher observed frequency of potentially avoidable emergency department presentations (P = 0.066). However, between-group differences were not statistically significant (Table 5).

Table 5.

Patient and Health Service Outcomes, Mean (Standard Deviation)

	Metabolic syndrome	No metabolic syndrome	P
Acute hospital length of stay, days	5.7 (3.5)	5.2 (2.6)	0.167
Participants who had an acute adverse event, n = (%)	74 (49)	29 (37)
Acute adverse events	1.3 (1.9)	0.9 (1.6)	0.093
Rehabilitation length of stay, days	16.5 (8.9)	16.3 (9.9)	0.457
Rehabilitation FIM score on admission	84.6 (15.9)	87.2 (11.9)	0.299
Rehabilitation FIM score at discharge	105.7 (14.7)	109.11 (10.9)	0.135
Rehabilitation adverse events	1.6 (1.6)	1.1 (1.4)	0.037^a
Total emergency department presentations over 2 years	1.3 (1.9)	1.1 (1.9)	0.382
Potentially avoidable emergency department presentations over 2 years	0.4 (0.8)	0.3 (0.7)	0.066
Total hospital admissions over 2 years	1.5 (2.3)	1.5 (2.3)	0.960

Denotes statistically significant values (P < 0.05).

Discussion

There was a high prevalence (66%) of metabolic syndrome in this at-risk group of older adults with osteoarthritis who proceeded to joint replacement surgery. There were no differences between people with and without metabolic syndrome who participated in the PRIME intervention in terms of immediate postoperative patient and health service outcomes. However, those with metabolic syndrome may have been more likely to have adverse events during rehabilitation and may have been more at risk of having potentially avoidable emergency department presentations in the 2 years following joint replacement surgery.

Contrary to the results of our study (where participants received a multidisciplinary preoperative intervention that included individualized exercise and nutritional advice and medical management), participants with metabolic syndrome in other similar-sized retrospective studies who did not receive preoperative intervention had twice as many adverse events during their acute hospital stay as those without metabolic syndrome.^13,24 Similar to our study, participants with metabolic syndrome in other studies had significantly more comorbidities than those without metabolic syndrome^13,25 and were on average, 3 years older.^13,24 Even though overall rates of adverse events in our study were much higher than the other studies^13,24 potentially due to the older, at-risk population or better reporting of adverse events in medical records, acute postoperative differences between people with and without metabolic syndrome were not significant in our study.

The observed lack of significant differences between groups with and without metabolic syndrome in the immediate postoperative period in our study may have been due to the PRIME preoperative, multidisciplinary intervention provided to participants in both groups which aimed to optimize patients' health and functional reserve before surgery. Previous research has found that participants who consulted their primary care practitioner for management of hyperglycemia before knee joint replacement surgery had significantly fewer postoperative complications compared with those who did not (P = 0.02).¹⁴ For people with osteoarthritis, preoperative exercise intervention may reduce pain before surgery and increase activity following surgery.¹⁵ The multidisciplinary presurgery intervention provided to participants in the current study addressed weight loss, medication optimization, diabetes control, and increased physical activity levels and therefore may have minimized the negative impact of metabolic syndrome and therefore minimized any differences in outcomes between groups after surgery. Further research is required to confirm these results but metabolic risk factors, such as hyperglycemia, hypertension, dyslipidemia, and obesity, may need to be controlled before admission for surgery to improve outcomes and reduce adverse events (and subsequent costs) following surgery.

Longer term follow-up showed differences may have been emerging between groups with a higher observed incidence of potentially avoidable emergency department presentations. The PRIME service only managed people presurgery and did not review people postsurgery, hence the effects of the intervention may not have been maintained. Dietary and physical activity changes, exercise compliance, and medication control all require significant patient engagement and sustained behavior change. These beneficial behavior changes have been found to diminish over time when support is not provided.²⁶ Because osteoarthritis is not just a single joint condition, ongoing lifestyle change may be important following joint replacement surgery and follow-up community intervention may be required to optimize joint replacement outcomes, especially for those with metabolic syndrome. A community-based multidisciplinary self-management intervention for people with metabolic syndrome has been found to improve patient outcomes and reduce emergency department presentations.²⁷ Such interventions may be appropriate to sustain or boost behavior change to maintain effects and reduce health care burden.

A limitation of this study is the retrospective design, which limited our sample size and was reliant on recorded data for determining the presence of metabolic syndrome. The study found a high prevalence of metabolic syndrome in the sample, therefore, there was a small group of participants without metabolic syndrome, which may have contributed to the low precision in estimates of effect (wide confidence intervals). However, the study does provide preliminary data to suggest that it may be important to consider management of metabolic syndrome both before and after joint replacement surgery to improve outcomes. Future research may consider a randomized controlled trial design to evaluate the effect of providing multidisciplinary preoperative intervention for people with metabolic syndrome scheduled to undergo joint replacement surgery.

Conclusion

This research provides preliminary data to suggest that providing a multidisciplinary intervention that included dietary and physical activity advice for weight loss, exercise, and medical management before lower limb joint replacement surgery for osteoarthritis may minimize differences between people with and without metabolic syndrome in immediate postoperative patient and health service outcomes. However, having a diagnosis of metabolic syndrome may still adversely affect long-term health service outcomes following joint replacement surgery.

Footnotes

Acknowledgments

The authors would like to thank the Northern Health Foundation, Dr. Yana Sunderland and the PRIME staff for their contributions to the project.

Author Disclosure Statement

No conflicting financial interests exist.

Funding Information

This project was funded by a 2018 Northern Health Small Research Grant, courtesy of the Northern Health Foundation

References

Alberti

, Eckel

, Grundy

, et al. Harmonizing the metabolic syndrome: A joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation, 2009; 120:1640–1645.

Gami

, Witt

, Howard

, et al. Metabolic syndrome and risk of incident cardiovascular events and death: A systematic review and meta-analysis of longitudinal studies. J Am Coll Cardiol, 2007; 49:403–414.

Esposito

, Chiodini

, Colao

, et al. Metabolic syndrome and risk of cancer: A systematic review and meta-analysis. Diabetes Care, 2012; 35:2402–2411.

Boudreau

, Malone

, Raebel

, et al. Health care utilization and costs by metabolic syndrome risk factors. Metab Syndr Relat Disord, 2009; 7:305–314.

Liu

, Zhu

, Chen

, et al. Bidirectional association between metabolic syndrome and osteoarthritis: A meta-analysis of observational studies. Diabetol Metab Syndr, 2020; 12:38.

Courties

, Semman

, Berenbaum

. Metabolic syndrome-associated osteoarthritis. Curr Opin Rheumatol, 2017; 29:214–222

Saklayen

. The global epidemic of the metabolic syndrome. Curr Hypertens Rep, 2018; 20:12.

Hussain

, Wang

, Cicuttini

, et al. Incidence of total knee and hip replacement for osteoarthritis in relation to the metabolic syndrome and its components: A prospective cohort study. Semin Arthritis Rheum, 2014; 43:429–436

Engstrom

, Gerhardsson de Verdier

, Rollof

, et al. C-reactive protein, metabolic syndrome and incidence of severe hip and knee osteoarthritis. A population-based cohort study. Osteoarthritis Cartilage, 2009; 17:168–173.

10.

Puenpatom

, Victor

. Increased prevalence of metabolic syndrome in individuals with osteoarthritis: An analysis of NHANES III data. Postgrad Med, 2009; 121:9–20.

11.

Gandhi

, Razak

, Davey

, Mahomed

. Metabolic syndrome and the functional outcomes of hip and knee arthroplasty. J Rheumatol, 2010; 37:1917–1922.

12.

Guofeng

, Chen

, Rong

, et al. Patients with metabolic syndrome have a greater rate of complications after arthroplasty: A systematic review and meta-analysis. Bone Joint Res, 2020; 9:120–129.

13.

Zmistowski

, Dizdarevic

, Jacovides

, et al. Patients with uncontrolled components of metabolic syndrome have increased risk of complications following total hoint arthroplasty. J Arthroplasty, 2013; 28:904–907.

14.

Reátegui

, Tornero

, Popescu

, et al. Postoperative hyperglycaemia control reduces postoperative complications in patients subject to total knee arthroplasty. Knee, 2017; 24:128–136.

15.

Wallis

, Taylor

. Pre-operative interventions (non-surgical and non-pharmacological) for patients with hip or knee osteoarthritis awaiting joint replacement surgery–a systematic review and meta-analysis. Osteoarthritis Cartilage, 2011; 19:1381–1395.

16.

Brimblecombe

, Lim

, Sunderland

. Preoperative comprehensive geriatric assessment: Outcomes in elective lower limb joint replacement surgery for complex older adults. J Am Geri Soc, 2014; 62:1396–1398

17.

Harari

, Hopper

, Dhesi

, et al. Proactive care of older people undergoing surgery (‘POPS’): Designing, embedding, evaluating and funding a comprehensive geriatric assessment service for older elective surgical patients. Age Ageing, 2007; 36:190–196.

18.

American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care, 2010; 33:S62–S69.

19.

Hoffmann

, Glasziou

, Boutron

, et al. Better reporting of interventions: Template for intervention description and replication (TIDieR) checklist and guide. BMJ, 2014; 348:g1687.

20.

Hamilton

, Granger

. Disability outcomes following inpatient rehabilitation for stroke. Phys Ther, 1994; 74:494–503

21.

Australasian College for Emergency Medicine. Guidelines on the implementation of the Australasian Triage Scale in emergency departments. Version 4, 2016. Accessed at https://acem.org.au/Content-Sources/Advancing-Emergency-Medicine/Better-Outcomes-for-Patients/Triage on February 10, 2021.

22.

Australian Institute of Health and Welfare. National healthcare agreement: PI 19-Selected potentially avoidable GP-type presentations to emergency departments, 2014. Accessed at http://meteor.aihw.gov.au/content/index.phtml/itemId/517646 on February 10, 2021.

23.

Pallant

SPSS survival manual: A step by step guide to data analysis using SPSS. Maidenhead: Open University Press/McGraw-Hill; 2010.

24.

Gage

, Schwarzkopf

, Abrouk

, et al. Impact of metabolic syndrome on perioperative complication rates after total joint arthroplasty surgery. J Arthroplasty, 2014; 29:1842–1845.

25.

Gonzalez Della Valle

, Chiu

, Ma

, et al. The metabolic syndrome in patients undergoing knee and hip arthroplasty: Trends and in-hospital outcomes in the United States. J Arthroplasty, 2012; 27:1743–1749.

26.

Ory

, Smith

, Mier

, et al. The science of sustaining health behavior change: The health maintenance consortium. Am J Health Behav, 2010; 34:647–659.

27.

Peiris

, Taylor

, Hull

, et al. A group lifestyle intervention program is associated with reduced emergency department presentations for people with metabolic syndrome: A retrospective case-control study. Metab Syndr Relat Disord, 2018; 16:110–116.