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Musculoskeletal diseases

Pharmacology Systematic review/meta‐analysis 14 February 2022 Free

Efficacy, safety, and dose‐dependence of the analgesic effects of opioid therapy for people with osteoarthritis: systematic review and meta‐analysis

Opioid medications may provide very small benefits for people with osteoarthritis, but also increase the risk of adverse events

Christina Abdel Shaheed · Wasim Awal · Geoffrey Zhang · Stephen E Gilbert · Daniel Gallacher · Andrew McLachlan · Richard O Day · Giovanni E Ferreira · Caitlin MP Jones · Harbeer Ahedi · Mamata Tamrakar · Fiona M Blyth · Fiona Stanaway · Christopher G Maher

Mja2 51392
Musculoskeletal diseases Research letters 7 June 2021 Free

Impact of pre‐surgery hospital transfer on time to surgery and 30‐day mortality for people with hip fractures

Australians have around 19 000 hip fractures each year,1 and the estimated cost to the health care system was $445 million in 2015–16.2 Surgery within 48 hours of initial presentation to hospital is widely accepted as a clinically meaningful indicator of best practice care, and is supported by the Australian Hip Fracture Care Clinical Care Standard when there are no clinical contraindications.3 However, timely access to emergency orthopaedic hip fracture surgery is difficult in a country as large and geographically diverse as Australia; patients admitted to remote or regional hospitals that do not provide orthopaedic surgery must be transferred to larger regional centres. In a retrospective population study, we evaluated the impact of pre‐surgery hospital transfer and time to surgery on 30‐day mortality for people aged 65 years or more who underwent surgical interventions for fall‐related hip fractures in NSW public hospitals during 1 January 2011 – 31 December 2018. Hospitalisation data from the NSW Admitted Patient Data Collection and deaths data from the NSW Registry of Births, Deaths and Marriages were linked to provide person‐level records. Time to surgery (in calendar days) was estimated from the date of admission for the first episode of care to the date of surgery. Comorbid conditions during the preceding year were identified with the Charlson Comorbidity Index (CCI). Multilevel multivariable logistic regression models were fitted to assess the influence of patient‐level factors (age, sex, comorbidity) and process factors (transfer status, time to surgery) on 30‐day mortality. Operating hospitals were included as a random effect to account for variation between hospitals. Adjusted odds ratios (aORs) with 95% confidence intervals (CIs) were calculated and residual variation (variance partition coefficient) assessed. All analyses were performed in SAS Enterprise Guide 7.1 and MLwiN 3.02 (http://www.bristol.ac.uk/cmm/software/mlwin). The NSW Population and Health Services Research Ethics Committee approved the study (HREC/17/CIPHS/45). Of 36 956 patients who underwent hip fracture repair procedures in 36 hospitals, 3916 (10.6%) were transferred from peripheral hospitals to operating hospitals for surgery; 1579 were transferred on the day of presentation (40.3%), 1875 the following day (47.9%), and 462 patients (11.8%) spent at least two days at the admitting hospital before being transferred. Larger proportions of transferred patients than of patients admitted directly to operating hospitals were men (29.4% v 27.8%), under 85 years of age (50.9% v 48.4%), or had CCI scores of 1 or more (60.2% v 56.3%). The proportion of transferred patients who underwent surgery within 48 hours of presentation was smaller than for directly admitted patients (53.9% v 72.4%) (Box). In multilevel models adjusted for inter‐hospital variation, transfer was associated with higher risk of 30‐day mortality than direct admission (aOR, 1.15; 95% CI, 1.01–1.32), but after adjusting for age, sex, and comorbidity, neither transfer (aOR, 1.10; 95% CI, 0.95–1.28) nor delayed surgery (> 2 days v ≤ 2 days: aOR, 0.99; 95% CI, 0.89–1.11) significantly influenced mortality. The most influential factor was comorbidity (CCI ≥ 3 v CCI < 3: aOR, 4.89; 95% CI, 4.32–5.54). The discrimination of our fully adjusted model was adequate (area under the curve, 0.73), and 1.8% of residual variation in 30‐day mortality was attributable to differences between hospitals. In our large study of NSW people with hip fractures, we found that transfer from non‐operating to operating hospitals, after adjusting for patient and hospital characteristics, was not associated with higher 30‐day mortality, despite increasing the time between initial presentation and surgery. This is contrary to the findings of earlier, single centre studies in Australia.4,5,6 However, our study was the first to control for several key person‐level factors that increase the risk of death, and our findings suggest that time to surgery may be less important for health outcomes than these factors when other dimensions of care quality are equal. More research is required to understand the interplay between the effects of patient demographic characteristics, pre‐injury health status, and the quality of hip fracture care on 30‐day mortality for patients. Box – Characteristics of patients with hip fractures, by pre‐surgery transfer, New South Wales, 2011–2018* table#t1 tbody td:nth-child(n+2) P. Pleft { text-align: center; } Not transferred Transferred Number of people 33 040 (89.4%) 3916 (10.6%) Sex Women 23 866 (72.2%) 2766 (70.6%) Men 9174 (27.8%) 1150 (29.4%) Age at admission (years) 65–74 4684 (14.2%) 535 (13.7%) 75–84 11 311 (34.2%) 1458 (37.2%) ≥ 85 17 045 (51.6%) 1923 (49.1%) Weighted Charlson Comorbidity Index score 0 14 437 (43.7%) 1556 (39.7%) 1–2 12 667 (38.3%) 1595 (40.7%) ≥ 3 5936 (18.0%) 765 (19.5%) Time to transfer (days) 0 1579 (40.3%) 1 1875 (47.9%) ≥ 2 462 (11.8%) Time to surgery (days) 0 12 991 (39.3%) 739 (18.9%) 1 10 939 (33.1%) 1370 (35.0%) ≥ 2 9110 (27.6%) 1807 (46.1%) Length of stay (days), mean (SD) Total 27.5 (21.9) 26.8 (20.5) Acute care 11.9 (8.5) 12.8 (9.0) 30‐day deaths 2172 (6.6%) 288 (7.4%) SD = standard deviation. * Linked hospitalisation and deaths data.

Lara A Harvey · Ian A Harris · Rebecca J Mitchell · Adrian Webster · Ian D Cameron · Louisa R Jorm · Hannah Seymour · Pooria Sarrami · Jacqueline CT Close

Mja2 51083
Rehabilitation Letters 3 May 2021 Free

Discharge destination and patient‐reported outcomes after inpatient treatment for isolated lower limb fractures

To the Editor: In their observational study, Kimmel and colleagues1 examined the impact of inpatient rehabilitation (IPR) for isolated lower limb injuries on functional outcomes in working‐aged people using inverse probability of treatment weighting (IPTW) propensity score analysis. It concerns us that the study lacks real clinical perspectives in disability management. Firstly, the authors assumed exchangeability in the baseline characteristics of patients discharged home and patients admitted to IPR. Exchangeability of the samples is a prerequisite for IPTW propensity score analysis.2,3 However, this is a flawed assumption in the Australasian context, where patients discharged home are medically stable, have minimal physical disability and have sufficient psychological coping skills. In contrast, patients admitted to IPR are deemed unsafe to be discharged home, with greater disability, home hazards, or inadequate support. IPR addresses complex therapy and care needs while alleviating pressure on acute beds. Secondly, the study examined disability and returning to work without considering all relevant determinants of health and functioning as listed in the World Health Organization’s International Classification of Functioning, Disability and Health. Rather than IPR resulting in a poorer functional outcome through hospital‐related complications, it is our experience that persons who require IPR will have a higher physical, functional, psychological, personal and social complexity or vulnerability, which may result in the observed long term disability. Thirdly, the study identified adverse 12‐month outcomes in patients discharged home. This control group were physically and functionally fit for discharge home, but 67% reported suboptimal recovery on the extended Glasgow Outcomes Scale (GOS‐E) and 16% failed to return to work at 12‐month follow‐up. Given that return to previous jobs plateaus by 6–12 months,4 gaps in care may aggravate problems by preventing timely access to multidisciplinary interventions to address the medical, psychological, physical, occupational and social impact of a traumatic injury. Finally, we encourage the authors to present the 12‐month follow‐up data in the Victorian Orthopaedic Trauma Outcomes Registry (VOTOR) for pain scores, anxiety and/or depression, and other domains of the EuroQol EQ‐5D‐3L Scale.4 Pain perception and depressive symptoms are known predictors for functioning and returning to work following an orthopaedic trauma and likely confounded the results.5

Pearl Chung · Mark Haran

Mja2 51017
Musculoskeletal diseases Letters 6 April 2020 Free

Time to recognise gout as a chronic disease

To the Editor: In August 2019, the Australian Institute of Health and Welfare (AIHW) released a report on chronic musculoskeletal conditions in Australia.1 In the report, the prevalence of gout is estimated at 0.8% (equating to 187 000 people), based on self‐reported survey data. This rate is much smaller than previously reported in Australia. Recent South Australian population‐based studies using “self‐reported doctor diagnosed gout” as the case definition reported the prevalence of gout as being between 5.2% and 6.8%.2 Thus, the rate of self‐reported gout detailed in the AIHW report is incongruous with published data and appears to be unusually low. The reported prevalence of gout in the AIHW document is based on the 2017–18 National Health Survey, in which participants were asked to self‐report doctor‐ or nurse‐diagnosed gout and whether the gout was current and expected to last for 6 months or more. Participants who did not identify as having current or long term gout did not have their condition recorded in the survey. Given that for most patients gout manifests as an intermittently flaring disease, with most flares lasting 7–10 days, respondents would likely not report their gout to be “current” or “likely to last 6 months” unless they have a clear understanding that gout is a chronic disease of monosodium urate crystal deposition. Many people with gout have not received this information from their health care providers and view the disease as present only when they are experiencing a flare.3 The chronic nature of the disease is reflected in the current definition of gout as “current or prior clinically evident disease”, as agreed by international gout experts.4 Gout is a systemic disease and an established independent risk factor for renal and cardiovascular disease. Like many chronic diseases, flares of gout and their long term consequences can be prevented with daily medication. However, both international and Australian evidence demonstrates that gout is inadequately treated, that persistence to urate‐lowering therapies is low, with suboptimal outcomes for patients.2 Under‐reporting and under‐recognition of gout and its burden on society is likely to contribute to undertreating and failure to manage it as a chronic disease — in contrast to other chronic conditions such as diabetes, in which the need for optimal disease management is well accepted. It is important that the burden of gout in Australia is understood and accurately measured to allow optimal use of limited health resources, reduce burden on society, and improve outcomes for people with this condition. Quality data are required but must be generated with appropriate definitions. We suggest that a validated case definition, such as “self‐reported gout” or “urate‐lowering therapies use”, be used in future Australian epidemiological studies.5

Helen I Keen · Philip C Robinson · Nicola Dalbeth · Catherine Hill

Mja2 50512
Ageing Letters 13 January 2020 Free

Sarcopenia: a deserving recipient of an Australian ICD‐10‐AM code

To the Editor: In July 2019, sarcopenia — a progressive and generalised skeletal muscle condition involving loss of skeletal muscle mass and function1 — was awarded a code in the International Classification of Diseases, tenth revision, Australian modification (ICD‐10‐AM). This recognition has arrived 30 years after Irwin Rosenberg first described the condition in 1989.2 Sarcopenia is independently associated with poor quality of life, falls, fractures, institutionalisation and mortality.1 About 13–19% of community‐dwelling older adults may have this condition, and prevalence is highest among those living in residential care.1 All individuals experience declines in muscle mass and function during ageing, but only those who meet the criteria described in the Box are considered to have sarcopenia. The definition currently promoted by the Australian and New Zealand Society for Sarcopenia and Frailty Research is the initial European Working Group on Sarcopenia in Older People definition,3 which was adopted after a Delphi consensus.5 Measures of muscle strength and physical performance such as grip strength, chair stands and gait speed are cost‐effective and easy to perform in clinical practice. Obtaining measures of muscle and lean mass may be challenging outside of the research setting. Therefore, in individuals with low muscle strength or physical performance, in the absence of other potential causes (eg, osteoarthritis), sarcopenia should be suspected and safe and effective interventions can be offered. Patients with, or at risk of, sarcopenia should be recommended exercise therapy, in particular, progressive resistance training.1 This type of training prescribed by treating clinicians can be implemented by allied health professionals, including exercise physiologists and physiotherapists. Protein supplementation can prevent loss of muscle, but this is most beneficial when combined with progressive resistance training.1 A number of randomised controlled trials are underway examining different therapeutics for the treatment of sarcopenia.1 With the advent of the ICD‐10‐AM code, primary care clinicians, allied health staff, and members of the public will begin observing sarcopenia diagnoses on medical correspondence. Hospital funding models may adjust in line with the ICD‐10‐AM code and in recognition of the increased complexity and risk of complications that comes with caring for patients with sarcopenia. An understanding of this condition, its implications and treatment is key in providing evidence‐based care to patients living with sarcopenia. Box – Diagnostic tools and measurements to diagnose sarcopenia* using the initial European Working Group on Sarcopenia in Older People (EWGSOP) definition†3 Component Thresholds and equipment Low muscle strength Hand grip strength using dynamometer: Men: < 30 kg Women: < 20 kg Low physical performance Men and women over 4 m course: Gait speed: ≤ 0.8 m/s Low lean mass ALM using whole‐body DXA (adjusted for height, m2): Men: < 7.26 kg/m2 Women: < 5.50 kg/m2 ALM = appendicular lean mass; DXA = dual x‐ray absorptiometry. * Diagnosis of sarcopenia is based on low lean mass and low physical performance or muscle strength. † The EWGSOP have developed a revised definition for sarcopenia (known as EWGSOP2);4 however, this has not yet been recommended for use in Australia.

Jesse Zanker · David Scott · Sharon L Brennan‐Olsen · Gustavo Duque

Mja2 50432
Musculoskeletal diseases Narrative reviews 18 February 2019 Free

Selecting and optimising patients for total knee arthroplasty

The minimum requirement for TKA must be prolonged clinically important symptoms in the presence of clinical signs that allow attribution of those symptoms to local pathology affecting articular surfaces and knee alignment. If, after reasonable attempts at non‐operative treatment, symptoms are sufficiently severe to justify the risks, a person is considered suitable for surgery. Optimisation to attenuate surgical risks should be attempted in all TKA candidates, although high level evidence is lacking for certain important factors. Pre‐operative interventional trials, with the aim of improving post‐operative TKA outcomes, are particularly needed in the areas of patient expectation, diabetes, obesity and vascular disease.

Sam Adie · Ian Harris · Alwin Chuan · Peter Lewis · Justine M Naylor

Mja2 12109
Rehabilitation Letters 4 February 2019 Free

Predictors of inpatient rehabilitation after total knee replacement: an analysis of private hospital claims data

To the Editor: Schilling and colleagues1 state that the Australasian Rehabilitation Outcomes Centre (AROC) — the national rehabilitation clinical quality registry for Australia and New Zealand — does not routinely collect data on post‐surgery outcomes for private total knee replacement (TKR) recipients. This statement is factually incorrect. All private inpatient rehabilitation services in Australia are members of AROC and routinely submit data (including functional outcomes as assessed by a functional independence measure) describing all episodes of rehabilitation they provide. More specifically, over the period described by Schilling and colleagues,1 AROC received data on outcomes for 93 278 TKRs receiving private rehabilitation. If we restrict the AROC data to match the study data (patients aged 40–89, single TKR, first admission), AROC received data describing 76 847 privately rehabilitated TKRs. In rehabilitation, the Australian National Subacute and Non‐Acute Patient Classification2 is routinely used to classify episodes into resource‐homogeneous groups. In interrogating the AROC TKR data, we concur with Schilling et al1 that the average length of stay in rehabilitation has been declining, with this decline accelerating over the past 5 years. Concurrent with the decline in length of stay, the functional change achieved (both absolute and relative) during rehabilitation has been increasing, and has in fact accelerated over the past 5 years. Achieving more functional change in a shorter length of stay shows that services are becoming more efficient while also continuing to produce positive outcomes for their patients. Moreover, it is also factually incorrect that AROC does not collect data outside of the inpatient setting. In fact, AROC also runs an ambulatory benchmarking initiative, and while coverage is not 100%, it is growing. There are currently 35 private ambulatory rehabilitation services that participate and routinely provide data describing their ambulatory rehabilitation outcomes. In conclusion, we suggest that while the authors provide an interesting analysis, it is incomplete, given that they did not include function — the key driver of cost and outcomes in rehabilitation — as one of the variables they used.

Frances Simmonds · John H Olver

Rehabilitation Letters 4 February 2019 Free

Predictors of inpatient rehabilitation after total knee replacement: an analysis of private hospital claims data

To the Editor: In reply to Shilling and colleagues,1 the Rehabilitation Medicine Society of Australia and New Zealand refers the authors and readers to our position statement regarding referral for rehabilitation in the home after total knee replacement (TKR).2 Shilling and colleagues1 state that the most important determinant for referral to inpatient rehabilitation was the hospital where the TKR took place. Independent researchers might be more circumspect, considering there is no acknowledgement that Medibank Private did not fund rehabilitation in the home nationally during the study period nor whether their data included outpatient rehabilitation carried out as “same day rehabilitation”, usually coded as inpatient. Also, disturbingly, some of the literature is misrepresented. The unblinded Canadian randomised controlled trial3 comparing a publicly funded combination of rehabilitation in the home and hospital‐based outpatient therapy with inpatient rehabilitation is not generalisable to privately insured Australian patients. Moreover, the Australian randomised controlled trial4 showing equivalent outcomes for the same two groups excluded patients who were appropriately referred for inpatient rehabilitation on the basis of numerous patient factors. The present study included few patient factors and not clinically relevant factors, such as obesity, ability to walk after TKR, or complications.1 Finally, while no patient safety or outcome data were included, the choice to include the dollar value of the previous year's private hospital claims seems gratuitous — are those patients with higher cost to insurers more likely to use inpatient rehabilitation, or perhaps they were just sicker? It is interesting that no reference is made to the 2017 study that found that referrals to inpatient rehabilitation were directly influenced by preferences of the patient, the surgeon, therapists, discharge planners, insurers and others.5

Steven G Faux · Lee Laycock

Rehabilitation Letters 4 February 2019 Free

Predictors of inpatient rehabilitation after total knee replacement: an analysis of private hospital claims data

To the Editor: In their recent article and media release, Schilling and colleagues1 concluded that after total knee replacement (TKR) “some inpatient rehabilitation is low value care”. The research was funded by Medibank Private. The article comes at a time of increasing interest in rehabilitation in the home (RITH) for TKR and other rehabilitation problems. Despite widely proclaimed opinions, there is limited high level evidence regarding outcomes for inpatient rehabilitation versus ambulatory rehabilitation. In research examining the benefits of RITH, higher complexity patients are often excluded from the studies.2 One of the limitations of this article is that important “patient‐related factors … including obesity, pre‐operative physical and mental health … functional performance” and others, “were not available”. A significant gap in the current debate is an almost total absence of nuanced thinking regarding which patients are clinically indicated and safe to have RITH. The authors’ conclusion is only a relatively minor aspect of the real problem, which is to ensure the best outcome for the patient. That is, we must confidently identify the right rehabilitation program, at the right time and in the right place. The Australasian Faculty of Rehabilitation Medicine3 is committed to ensuring high quality rehabilitation medicine services. We believe that: while many patients with uncomplicated TKR may be appropriate for RITH, there are many others for whom RITH is inappropriate or unsafe; the appropriate setting for TKR rehabilitation should be determined on evidence‐based clinical indicators and minimum safety standards;4 all patients with TKR (apart from the most uncomplicated cases) require referral to and assessment by or on behalf of a rehabilitation medicine physician (or other appropriately trained physician); and some ambulatory rehabilitation programs may be appropriate for TKR and other rehabilitation, but they must be evidence‐based, interdisciplinary, led by a rehabilitation medicine physician and adequately resourced, and not simply seen as a cheaper panacea for a struggling system. To achieve the best outcome for patients, decisions must be individualised and patient‐centred and they should start with a referral to a rehabilitation medicine physician, who can determine the right rehabilitation program, at the right time and in the right place. There are circumstances in which RITH is an alternative to inpatient rehabilitation for appropriately selected patients.4 Let's ensure, however, that we do not throw the baby out with the bathwater.

Timothy J Geraghty · Andrew M D Cole · Gregory Bowring

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