Abstract
Introduction: Sarcopenia is highly prevalent in older inpatients. However, it is unclear if sarcopenia is documented routinely in geriatric rehabilitation. This study aimed to investigate the documentation of sarcopenia in medical records among geriatric rehabilitation patients. Methods: Geriatric rehabilitation inpatients in a statewide hospital in VIC, Australia, were included. Patient characteristics, muscle measurements, and medical records at admission and discharge were collected. Sarcopenia was defined using the European Working Group on Sarcopenia in Older People 2 (EWGSOP2). Patient characteristics were compared between the groups with documented and non-documented sarcopenia using the Wilcoxon rank-sum or chi-square test. Results: Of 1,890 geriatric rehabilitation inpatients (aged 83.4 [interquartile range: 77.6–88.4] years, 56.3% female), muscle measurements were available in 1,334 patients at admission. The prevalence of sarcopenia was 20.8% (n = 278). Sarcopenia was documented in 68 out of 1,890 patients; 23 of them did not have muscle mass or muscle strength measured. Forty-five patients with muscle measurements available were documented with sarcopenia either at discharge from acute admissions (n = 9), on rehabilitation admission (n = 25), or at discharge from rehabilitation (n = 26). Of these 45 patients, 8 patients had sarcopenia following the EWGSOP2 criteria. Compared with patients without sarcopenia documented, patients documented with sarcopenia had lower body mass index and sarcopenia screening (Strength, Assistance in Walking, Rise from a Chair, Climb Stairs, Falls History [SARC-F]) scores and higher Clinical Frailty Scale (CFS) scores and were likely to come from nursing homes. Conclusions: Documentation of sarcopenia was lower than the prevalence of sarcopenia in geriatric rehabilitation inpatients. Sarcopenia was incorrectly documented as data on muscle measurement were missing to define sarcopenia. Practitioners likely used clinical impressions to document sarcopenia, rather than the formal diagnostic criteria.
Introduction
Geriatric rehabilitation provides multidisciplinary, patient-centred interventions to optimise functional recovery following a functional and physical decline related to an acute event and/or chronic conditions [1]. In Australia, older patients cleared for their medical conditions are being referred for geriatric rehabilitation [2]. Patients admitted to geriatric rehabilitation will receive a Comprehensive Geriatric Assessment (CGA) to develop an interdisciplinary care plan to meet their goals; the emphasis focuses on intervening obstacles to the patients’ return to an optimal level of independence or accessing ongoing support. Patients in VIC, Australia, are generally admitted to the geriatric rehabilitation wards for 28 days with some flexibility to allow patients to get an appropriate level of care post-discharge [2].
Geriatric rehabilitation patients often have several comorbidities [3]. Sarcopenia is one common comorbidity with a high prevalence ranging from 18.6% to 37.9% [4, 5]. This prevalence necessitates recognising and managing this disease as part of the multidisciplinary therapeutic interventions [1]. If left unrecognised and untreated, sarcopenia has high personal, social, and cost burdens to patients and health systems [6]. Furthermore, sarcopenia is associated with future hospitalisation and mortality post-discharge and should therewith be communicated to the medical practitioners caring for patients in the community after discharge from geriatric rehabilitation [7, 8].
Sarcopenia is an important geriatric condition, and to facilitate physicians making the diagnosis, the International Classification Disease-10 has accepted sarcopenia as a disease since 2016 [9, 10]. Therefore, sarcopenia is expected to be recognised equally to any other disease, and muscle strength, muscle mass, and physical performance should be assessed as part of geriatric rehabilitation routine practice [5]. Like other diseases, documentation of sarcopenia is important as it is the main means of communication with other clinicians outside of geriatric rehabilitation. It is unclear if clinicians document sarcopenia in geriatric rehabilitation inpatients. Known barriers to identifying sarcopenia include lack of knowledge, availability of equipment, time constraints, and patients’ comorbidities rendering assessment difficult [11‒13]. Although multiple definitions of sarcopenia exist, posing another challenge [12], the European Working Group on Sarcopenia in Older People 2 (EWGSOP2) has been promoted as the operational definition of sarcopenia for clinical use in the country of this study [6, 14]. This study aimed to investigate the documentation of sarcopenia in medical records, compared with the actual prevalence of sarcopenia in geriatric rehabilitation inpatients.
Methods
Study Design
This is a sub-study from the Restoring Health of Acutely Unwell Adults (RESORT) project, an observational, prospective longitudinal cohort of patients admitted to the geriatric rehabilitation wards at the Royal Melbourne Hospital, a statewide tertiary hospital in VIC, Australia. Inpatients admitted to geriatric rehabilitation during the recruitment period from 16 October 2017 to 18 March 2020 were recruited. Patients were excluded if they were receiving palliative care on admission, were transferred to acute care before consenting to the study, or lacked the capacity to provide informed consent with no nominated proxy available. All included patients underwent a CGA by a multidisciplinary team of physicians, nurses, physiotherapists, occupational therapists, and dieticians within 48 h of admission [15].
The Melbourne Health Research Ethics Committee approved this study (HERC/17/MH/103). The study was conducted following the Declaration of Helsinki [16]. All participants or their nominated proxies gave written informed consent to participate in the study.
Data Collection and Storage
Study data were collected and stored using REDCap electronic data capture tools hosted at the studied institution [17]. As part of CGA, all data were collected within 48 h of admission to geriatric rehabilitation. Patient characteristics were collected from medical records or reported by the patient, the carer, or a researcher assisting the patient. Characteristics included age, sex, ethnicity, living situation before admission, persons living with patients, receiving home services, smoking status, and chronic comorbidities. Patients who lived in their own homes or rental units were considered in the community. Sources of admission to rehabilitation wards and length of stay in acute admissions and geriatric rehabilitation wards were extracted from medical records.
Body mass index (BMI) was calculated by weight divided by height squared, expressed in kg/m2. Height was measured using a stadiometer or was estimated from knee height using the Chumlea equation for Caucasians for patients unable to stand [18]. Weight was evaluated using a standing or seated scale or a weighted hoist depending on the ambulatory status. The Strength, Assistance in Walking, Rise from a Chair, Climb Stairs, Falls History (SARC-F) questionnaire was added to the CGA in July 2018 [19]. The total score ranges from 0 to 10 points, with higher scores indicating a higher risk of sarcopenia; a cutoff score of 4 points or higher defines the risk of sarcopenia. The Clinical Frailty Scale (CFS) was used by physicians to grade frailty from 1 to 9 points, representing very fit to terminally ill [20]. The Malnutrition Screening Tool (MST) was used by nurses to assess and classify malnutrition from 0 to 5 points [21]. A score of 2 or above indicates moderate to high risk of malnutrition. Patients who did not complete any tools were missing in their data and were not included in statistical analyses on those tools.
All muscle measurements were performed by trained healthcare professionals on admission to geriatric rehabilitation. Muscle strength was assessed by measuring handgrip strength in three attempts on both hands, alternating between right and left, instructing patients in a sitting position to bend the elbow at 90° to the body and squeeze with maximum effort with a handheld dynamometer (JAMAR, Sammons Preston, Inc., Boling-Brook, IL, USA) [22]. The maximum value in kg was used. The results were classified as abnormal (n = 81) if there were medical reasons impacting or hindering patients’ completion of all attempts, such as fractures or hemiparesis affecting performance on one side; these patients were still included in the operational definition for sarcopenia, with their best results typically on the unaffected limb used. The data were missing if patients refused, had language barriers, or had medical conditions hindering their participation, such as cognitive impairments or substantial pain or weakness. Physical performance was measured by the Short Physical Performance Battery (SPPB) on two attempts with scores from 0 to 4 points for each of the standing balance test, the timed chair stand test, and the timed 4-metre walk test to measure gait speed (m/s), giving a total score between 0 and 12 points with higher scores indicating better physical performance [23]. The data were missing if the patients refused or had language barriers.
Direct segmental multifrequency bio-electrical impedance analysis (InBody S10, Biospace Co., Ltd., Seoul, South Korea) was used by trained nursing staff to measure body composition. BIA was performed in the morning; patients were asked to remain still in a supine position, with arms not touching the trunk and legs apart for at least 10–15 min during the measurement. When recommended by an automated message from the device, remeasurements were conducted. This may be caused by movement during the measurement, inaccurate posture, or suboptimal conductivity due to dry skin or body lotion use as indicated by the manufacturer. Since geriatric rehabilitation patients were medically stable, the hydration statuses were at their baseline; 2 patients who required dialysis for their kidney disease had their BIA done after their dialysis. BIA was not performed when patients declined or contraindications were present [24], including (1) an electronic medical device or implant such as a pacemaker, (2) cast, dressing, or bandages interfering with the placing of the electrodes, (3) amputation, (4) contact isolation, (5) other medical reasons such as delirium, agitation, fracture limiting optimal positioning. Appendicular lean mass (ALM) was recorded in kg; ALM index (ALMI) was defined as ALM divided by height squared and expressed in kg/m2.
Evaluation of Sarcopenia
Sarcopenia was defined using the EWGSOP2 definition since it has been promoted for clinical use [14]. The definition confirmed sarcopenia as having both low muscle mass and muscle strength [6]. Muscle mass was low when ALMI was <7.0 kg/m2 for males or <5.5 kg/m2 for females; muscle strength was low with handgrip strength <27 kg for males or <16 kg for females, or chair stand time >15 s. Sarcopenia was considered severe when physical performance was poor, defined as gait speed ≤0.8 m/s or SPPB ≤8 points [6].
The documentation of sarcopenia as a diagnosis or comorbidity was evaluated at three time points: at discharge from acute admission, on admission to geriatric rehabilitation, and at discharge from geriatric rehabilitation. The acute admission data were of the patients admitted to geriatric rehabilitation wards only, whereas discharged acute hospital patients not transferred to geriatric rehabilitation were excluded from the data. Generally, upon becoming medically stable in an acute hospital, patients who required functional recovery were referred for geriatric rehabilitation [2]. The patients were waitlisted for geriatric rehabilitation and remained inpatients in acute wards until their beds were made available; the time between acute wards and geriatric rehabilitation may have depended on delayed access [2], patients’ recovery from acute illness, and consent for transfer. The documentation of sarcopenia was extracted from medical records, which were discharge summaries from acute admissions, rehabilitation admission notes, and rehabilitation discharge summaries. The documenting process was completed by healthcare professionals and was independent of the researcher’s evaluation of the actual prevalence of sarcopenia. Therefore, the documentation was used to reflect the clinicians’ utilisation of the EWGSOP2 definition.
Statistical Analyses
Data were analysed using Stata Release 18 (StataCorp, College Station, TX, USA). Continuous variables were expressed as medians and interquartile ranges; categorical variables were described as frequencies (n) and proportions (%). Documented sarcopenia was compared with sarcopenia according to the EWGSOP2 definition using cross tabulation. Patient characteristics were compared between the documented and non-documented groups of sarcopenia using the Wilcoxon rank-sum test for continuous variables and the chi-square test or one-sided Fisher’s exact test (if n <5) for categorical variables [25]. Two-sided p < 0.05 was considered statistically significant.
Results
Patient Characteristics and Prevalence of Sarcopenia
The cohort comprised 2,246 consecutive patients eligible for recruitment; 356 met exclusion criteria (Fig. 1). Patient characteristics of the included 1,890 patients (median [interquartile range] age 83.4 [77.6, 88.4] years, 56.3% female) are shown in Table 1. Most patients were of European ethnicity (87.6%) and were living in the community prior to admission (91.2%) rather than nursing homes (2.7%). About half were living alone (42.2%) or with a partner or children (52.3%) and were receiving home services (54.1%). Most patients were admitted from acute wards (96.8%), while 60 patients came from other sources (directly from patients’ accommodation n = 2, transferred from external care and other subacute wards n = 58). The median length of stay in acute admissions was 7.2 (4.1–12.5) days, and in geriatric rehabilitation, it was 19.9 (13.1, 31.0) days. Patients’ comorbidities, BMI, SARC-F, CFS, and MST scores are shown in Table 1.
Patients documented with sarcopenia from the RESORT cohort * Sarcopenia was defined using the EWGSOP2 definition [14].
Patients documented with sarcopenia from the RESORT cohort * Sarcopenia was defined using the EWGSOP2 definition [14].
Patient characteristics and sarcopenia measures at geriatric rehabilitation admission (N = 1,890)
Variables . | N . | Total . |
---|---|---|
Patient characteristics | ||
Age, median [IQR], years | 1,890 | 83.4 [77.6–88.4] |
Female | 1,890 | 1,065 (56.3) |
Ethnicity | 1,824 | |
European/Caucasian | 1,598 (87.6) | |
Asian | 92 (5.0) | |
Living situation prior to admission | 1,890 | |
Community-dwelling | 1,724 (91.2) | |
Nursing homes | 51 (2.7) | |
Persons living with patients | 1,884 | |
Living alone | 795 (42.2) | |
With partner or children | 985 (52.3) | |
Receiving home services | 1,815 | 982 (54.1) |
Chronic comorbidities | 1,890 | |
Cardiac disease (MI, CCF) | 713 (37.7) | |
Hypertension | 1,323 (70.0) | |
Stroke | 621 (32.9) | |
COPD | 342 (18.1) | |
Dementia | 474 (25.1) | |
Diabetes | 682 (36.1) | |
Chronic kidney disease | 564 (29.8) | |
Osteoporosis | 560 (29.6) | |
Cognitive impairment | 1,231 (65.1) | |
Visual impairment | 593 (31.4) | |
Urine incontinence | 1,048 (56.1) | |
Admitted from acute care | 1,890 | 1,830 (96.8) |
Length of acute admission, median [IQR], days | 1,830 | 7.2 [4.1–12.5] |
Length of rehabilitation stay, median [IQR], days | 1,890 | 19.9 [13.1–31.0] |
BMI, median [IQR], kg/m2 | 1,838 | 25.9 [22.5–30.2] |
SARC-F score, median [IQR]a | 876 | 7.0 [5.0–8.0] |
CFS score, median [IQR] | 1,716 | 6.0 [5.0–7.0] |
MST score, median [IQR] | 1,863 | 1.0 [0.0–2.0] |
Sarcopenia components (EWGSOP2) | ||
Low muscle mass | 1,367 | 331 (24.2) |
Low muscle strength | 1,832 | 1,350 (73.7) |
Low physical performance | 1,811 | 1,740 (96.1) |
Prevalence of sarcopenia (EWGSOP2) | ||
Sarcopenia | 1,334 | 278 (20.8) |
Severe sarcopenia | 1,318 | 262 (19.9) |
Variables . | N . | Total . |
---|---|---|
Patient characteristics | ||
Age, median [IQR], years | 1,890 | 83.4 [77.6–88.4] |
Female | 1,890 | 1,065 (56.3) |
Ethnicity | 1,824 | |
European/Caucasian | 1,598 (87.6) | |
Asian | 92 (5.0) | |
Living situation prior to admission | 1,890 | |
Community-dwelling | 1,724 (91.2) | |
Nursing homes | 51 (2.7) | |
Persons living with patients | 1,884 | |
Living alone | 795 (42.2) | |
With partner or children | 985 (52.3) | |
Receiving home services | 1,815 | 982 (54.1) |
Chronic comorbidities | 1,890 | |
Cardiac disease (MI, CCF) | 713 (37.7) | |
Hypertension | 1,323 (70.0) | |
Stroke | 621 (32.9) | |
COPD | 342 (18.1) | |
Dementia | 474 (25.1) | |
Diabetes | 682 (36.1) | |
Chronic kidney disease | 564 (29.8) | |
Osteoporosis | 560 (29.6) | |
Cognitive impairment | 1,231 (65.1) | |
Visual impairment | 593 (31.4) | |
Urine incontinence | 1,048 (56.1) | |
Admitted from acute care | 1,890 | 1,830 (96.8) |
Length of acute admission, median [IQR], days | 1,830 | 7.2 [4.1–12.5] |
Length of rehabilitation stay, median [IQR], days | 1,890 | 19.9 [13.1–31.0] |
BMI, median [IQR], kg/m2 | 1,838 | 25.9 [22.5–30.2] |
SARC-F score, median [IQR]a | 876 | 7.0 [5.0–8.0] |
CFS score, median [IQR] | 1,716 | 6.0 [5.0–7.0] |
MST score, median [IQR] | 1,863 | 1.0 [0.0–2.0] |
Sarcopenia components (EWGSOP2) | ||
Low muscle mass | 1,367 | 331 (24.2) |
Low muscle strength | 1,832 | 1,350 (73.7) |
Low physical performance | 1,811 | 1,740 (96.1) |
Prevalence of sarcopenia (EWGSOP2) | ||
Sarcopenia | 1,334 | 278 (20.8) |
Severe sarcopenia | 1,318 | 262 (19.9) |
Data are displayed as n (%) unless stated otherwise.
MI, myocardial infarction; CCF, congestive cardiac failure; COPD, chronic obstructive pulmonary disease; BMI, body mass index; SARC-F, Strength, Assistance in Walking, Rise from a Chair, Climb Stairs, Falls History; CFS, Clinical Frailty Scale; MST, Malnutrition Screening Tool; EWGSOP2, European Working Group on Sarcopenia in Older People 2.
aThe SARC-F questionnaire was added to the Comprehensive Geriatric Assessment (CGA) in July 2018.
The prevalence of sarcopenia using the EWGSOP2 definition is shown in Table 1. Applying the EWGSOP2 criteria [6], the prevalence of low muscle mass was 24.2% (n = 331 of 1,367 patients completing BIA), low muscle strength was 73.7% (n = 1,350 of 1,832 patients), and low physical performance was 96.1% (n = 1,740 of 1,811 patients with data available). In 1,334 patients whose data on muscle measures were available to apply the EWGSOP2 criteria [6], the prevalence of sarcopenia was 20.8% (n = 278), and severe sarcopenia was 19.9% (n = 262).
Documentation of Sarcopenia
Out of 1,890 patients, 68 patients (3.6%) were documented with sarcopenia; 23 of them did not have muscle mass or muscle strength measured (Fig. 1). Of the other 45 patients documented with sarcopenia who had available muscle measurement data using the EWGSOP2 definition, 9 patients were documented at discharge from acute admission, 25 patients were documented on admission to geriatric rehabilitation, and 26 patients were documented at discharge from geriatric rehabilitation (Table 2; Fig. 2). Of these 45 patients, eight had sarcopenia according to the EWGSOP2 definition (n = 4 at discharge from acute admission, n = 8 at geriatric rehabilitation admission, n = 2 at geriatric rehabilitation discharge), whereas the other 37 patients did not have sarcopenia by this definition (Table 2; Fig. 2). Five patients had overlapping documentation at all three time points (Fig. 2). Figure 3 shows the patients documented with sarcopenia following the EWGSOP2 algorithm for diagnosis of sarcopenia. Of 107 cases of confirmed sarcopenia, 4 patients were correctly documented.
Number of geriatric rehabilitation patients having sarcopenia by applying the EWGSOP2 definition and documentation of sarcopenia at three time points
. | Sarcopenia . | No sarcopenia . | Total . |
---|---|---|---|
Discharge from acute admission | |||
Documented | 4 | 5 | 9 |
Not documented | 261 | 1,023 | 1,284 |
Total | 265 | 1,028 | 1,293 |
Geriatric rehabilitation admission | |||
Documented | 8 | 17 | 25 |
Not documented | 270 | 1,039 | 1,309 |
Total | 278 | 1,056 | 1,334 |
Geriatric rehabilitation discharge | |||
Documented | 2 | 24 | 26 |
Not documented | 276 | 1,032 | 1,308 |
Total | 278 | 1,056 | 1,334 |
. | Sarcopenia . | No sarcopenia . | Total . |
---|---|---|---|
Discharge from acute admission | |||
Documented | 4 | 5 | 9 |
Not documented | 261 | 1,023 | 1,284 |
Total | 265 | 1,028 | 1,293 |
Geriatric rehabilitation admission | |||
Documented | 8 | 17 | 25 |
Not documented | 270 | 1,039 | 1,309 |
Total | 278 | 1,056 | 1,334 |
Geriatric rehabilitation discharge | |||
Documented | 2 | 24 | 26 |
Not documented | 276 | 1,032 | 1,308 |
Total | 278 | 1,056 | 1,334 |
Data are displayed as n (%).
Number of geriatric rehabilitation patients having sarcopenia by applying the EWGSOP2 definition and documented sarcopenia at three time points. A total of 1,334 patients whose data were available using the EWGSOP2 definition were evaluated. Patients documented with sarcopenia: at discharge from acute admission (red, sarcopenic: n = 4, non-sarcopenic: n = 5), on admission to geriatric rehabilitation (white, sarcopenic: n = 8, non-sarcopenic: n = 17), and at discharge from geriatric rehabilitation (blue, sarcopenic: n = 2, non-sarcopenic: n = 24). Overlapping documentation at all time points: sarcopenic: n = 2, non-sarcopenic: n = 3.
Number of geriatric rehabilitation patients having sarcopenia by applying the EWGSOP2 definition and documented sarcopenia at three time points. A total of 1,334 patients whose data were available using the EWGSOP2 definition were evaluated. Patients documented with sarcopenia: at discharge from acute admission (red, sarcopenic: n = 4, non-sarcopenic: n = 5), on admission to geriatric rehabilitation (white, sarcopenic: n = 8, non-sarcopenic: n = 17), and at discharge from geriatric rehabilitation (blue, sarcopenic: n = 2, non-sarcopenic: n = 24). Overlapping documentation at all time points: sarcopenic: n = 2, non-sarcopenic: n = 3.
Patients with documented sarcopenia according to the EWGSOP2 algorithm for diagnosis of sarcopenia (N = 1,890). * The SARC-F questionnaire was added to the Comprehensive Geriatric Assessment (CGA) in July 2018.
Patients with documented sarcopenia according to the EWGSOP2 algorithm for diagnosis of sarcopenia (N = 1,890). * The SARC-F questionnaire was added to the Comprehensive Geriatric Assessment (CGA) in July 2018.
Patient Characteristics between Documented and Non-Documented Groups
Patients who were documented with sarcopenia had lower SARC-F scores compared with patients who had no sarcopenia documented (Table 3). At geriatric rehabilitation admission, patients who had sarcopenia documented had lower BMI and higher CFS scores compared with those with no documented sarcopenia. At geriatric rehabilitation discharge, patients coming from nursing homes were more likely to be documented with sarcopenia. Analysis of all other patient characteristics was shown in online supplementary Table 1 (for all online suppl. material, see https://doi.org/10.1159/000543620). There was no difference in most variables, except patients with chronic kidney disease and urinary incontinence were more likely to be documented with sarcopenia at geriatric rehabilitation admission and discharge, respectively.
Patient characteristics compared between patients with documented sarcopenia and patients with no documentation of sarcopenia
Variables . | N . | Acute admission . | Rehabilitation admission . | Rehabilitation discharge . | ||||||
---|---|---|---|---|---|---|---|---|---|---|
documented, n = 18 . | not documented, n = 1,812 . | p value . | documented, n = 45 . | not documented, n = 1,845 . | p value . | documented, n = 38 . | not documented, n = 1,852 . | p value . | ||
Age, years | 1,890 | 83.6 [78.5–87.8] | 83.4 [77.6–88.4] | 0.65a | 84.3 [77.8–91.1] | 83.4 [77.6–88.4] | 0.50a | 85.7 [78.5–91.1] | 83.4 [77.6–88.4] | 0.14a |
Female, n (%) | 1,890 | 12 (66.7) | 1,017 (56.1) | 0.37b | 23 (51.1) | 1,042 (56.5) | 0.47b | 21 (55.3) | 1,044 (56.4) | 0.89b |
BMI, kg/m2 | 1,838 | 24.0 [20.6–27.5] | 25.9 [22.5–30.2] | 0.25a | 22.9 [19.7–26.0] | 26.0 [22.6–30.2] | <0.001a | 24.8 [22.1–27.0] | 25.9 [22.5–30.2] | 0.10a |
Came from nursing homes, n (%) | 1,890 | 2 (11.1) | 47 (2.59) | 0.08c | 3 (6.7) | 48 (2.6) | 0.12c | 4 (10.5) | 47 (2.5) | 0.018c |
SARC-F scored | 876 | 5.5 [2.0–6.5] | 7.0 [5.0–8.0] | 0.028a | 6.0 [3.5–8.0] | 7.0 [5.0–8.0] | 0.007a | 5.0 [2.0–7.0] | 7.0 [5.0–8.0] | <0.001a |
CFS score | 1,716 | 6.5 [6.0–7.0] | 6.0 [5.0–7.0] | 0.18a | 7.0 [6.0–7.0] | 6.0 [5.0–7.0] | <0.001a | 6.0 [5.0–7.0] | 6.0 [5.0–7.0] | 0.27a |
MST score | 1,863 | 0.0 [0.0–2.0] | 1.0 [0.0–2.0] | 0.50a | 0.0 [0.0–2.0] | 1.0 [0.0–2.0] | 0.15a | 1.0 [0.0–2.0] | 1.0 [0.0–2.0] | 0.88a |
SPPB | 1,789 | 0.0 [0.0–3.0] | 1.0 [0.0–4.0] | 0.40a | 0.0 [0.0–3.0] | 1.0 [0.0–4.0] | 0.18a | 0.0 [0.0–3.0] | 1.0 [0.0–4.0] | 0.06a |
Variables . | N . | Acute admission . | Rehabilitation admission . | Rehabilitation discharge . | ||||||
---|---|---|---|---|---|---|---|---|---|---|
documented, n = 18 . | not documented, n = 1,812 . | p value . | documented, n = 45 . | not documented, n = 1,845 . | p value . | documented, n = 38 . | not documented, n = 1,852 . | p value . | ||
Age, years | 1,890 | 83.6 [78.5–87.8] | 83.4 [77.6–88.4] | 0.65a | 84.3 [77.8–91.1] | 83.4 [77.6–88.4] | 0.50a | 85.7 [78.5–91.1] | 83.4 [77.6–88.4] | 0.14a |
Female, n (%) | 1,890 | 12 (66.7) | 1,017 (56.1) | 0.37b | 23 (51.1) | 1,042 (56.5) | 0.47b | 21 (55.3) | 1,044 (56.4) | 0.89b |
BMI, kg/m2 | 1,838 | 24.0 [20.6–27.5] | 25.9 [22.5–30.2] | 0.25a | 22.9 [19.7–26.0] | 26.0 [22.6–30.2] | <0.001a | 24.8 [22.1–27.0] | 25.9 [22.5–30.2] | 0.10a |
Came from nursing homes, n (%) | 1,890 | 2 (11.1) | 47 (2.59) | 0.08c | 3 (6.7) | 48 (2.6) | 0.12c | 4 (10.5) | 47 (2.5) | 0.018c |
SARC-F scored | 876 | 5.5 [2.0–6.5] | 7.0 [5.0–8.0] | 0.028a | 6.0 [3.5–8.0] | 7.0 [5.0–8.0] | 0.007a | 5.0 [2.0–7.0] | 7.0 [5.0–8.0] | <0.001a |
CFS score | 1,716 | 6.5 [6.0–7.0] | 6.0 [5.0–7.0] | 0.18a | 7.0 [6.0–7.0] | 6.0 [5.0–7.0] | <0.001a | 6.0 [5.0–7.0] | 6.0 [5.0–7.0] | 0.27a |
MST score | 1,863 | 0.0 [0.0–2.0] | 1.0 [0.0–2.0] | 0.50a | 0.0 [0.0–2.0] | 1.0 [0.0–2.0] | 0.15a | 1.0 [0.0–2.0] | 1.0 [0.0–2.0] | 0.88a |
SPPB | 1,789 | 0.0 [0.0–3.0] | 1.0 [0.0–4.0] | 0.40a | 0.0 [0.0–3.0] | 1.0 [0.0–4.0] | 0.18a | 0.0 [0.0–3.0] | 1.0 [0.0–4.0] | 0.06a |
Numbers are given as median [IQR] unless otherwise stated.
BMI, body mass index; SARC-F, Strength, Assistance in Walking, Rise from a Chair, Climb Stairs, Falls History; CFS, Clinical Frailty Scale; MST, Malnutrition Screening Tool; SPPB, Short Physical Performance Battery.
Patients who did not complete any tools were missing in their data and were not included in statistical analyses on those tools.
Bold values indicate statistically significant results (p < 0.05).
p values were retrieved from the tests.
aWilcoxon rank-sum test.
bChi-square test.
cOne-sided Fisher’s exact test.
dThe SARC-F questionnaire was added to the Comprehensive Geriatric Assessment (CGA) in July 2018.
Discussion
In this prospective cohort study of inpatients admitted to the geriatric rehabilitation wards, sarcopenia prevalence was high, but documentation of the disease was low, and there was no agreement with the actual prevalence. Patients with documentation of sarcopenia had higher scores on SARC-F or CFS, lower BMI, or came from nursing homes.
Poor documentation of sarcopenia implies that sarcopenia has not been recorded in routine clinical practice in geriatric rehabilitation, despite the availability of muscle mass, muscle strength, and physical performance measures in a cohort of high needs for diagnosis [5]. Sarcopenia was, therefore, not the priority of treatment goals set by the clinicians. It should be noted that while muscle measurements may not have occurred during acute admissions [26], the high proportion of patients documented with sarcopenia but did not have this condition supported an incorrect documenting process. Surveys in Australia, New Zealand, the Netherlands, and the UK also showed that most healthcare professionals did not diagnose sarcopenia as part of their routine practice [11, 27, 28], despite the willingness of older individuals to start treatment [29, 30].
Several barriers to identifying sarcopenia are known [11, 12]. Many patients who did not undergo BIA were possibly due to the staff’s lack of time, other priorities, or incapability to perform the measurement [24, 31]. Other reasons included medical conditions that contraindicate or limit the measurement, technical issues, or patients’ refusal to undergo the measurement(s) [24]. However, this RESORT cohort had a BIA completion rate of 77.1% of patients at admission and 63.2% at discharge, indicating good feasibility of BIA in routine clinical practice in geriatric rehabilitation inpatients [24]. Other barriers were patients’ other comorbidities taking priority in treatment goals or the clinicians’ lack of knowledge or time to diagnose sarcopenia in clinical practice [3, 11, 26, 28].
Sarcopenia was incorrectly documented in patients with missing data on muscle measurements required for diagnosis and in patients without sarcopenia. Therefore, the documentation was presumably based on other factors rather than the formal diagnostic criteria. This study found tools such as SARC-F, CFS, and BMI, and coming from nursing homes were different between the documented and non-documented groups. Hence, clinicians may have predominantly used their clinical impressions and screening tools to identify sarcopenia. Similarly, a survey of healthcare professionals indicated that often formal diagnostic algorithms or tools to diagnose sarcopenia are not being used [27]. Interestingly, SARC-F scores were lower in those documented than those not documented with sarcopenia, which is in line with the relatively poor validity of the tool [32, 33]. While the CFS has been validated in screening for frailty and there are close links between frailty and sarcopenia [34], this tool is not intended to screen for or diagnose sarcopenia. Similarly, BMI and accommodation may provide a clinical impression of the patient’s body composition and physical function but do not constitute diagnostic criteria for sarcopenia. However, as the nursing home sample size was small, its implication was limited. Finally, there was no between-group difference in the SPPB scores, which measure physical performance. Since the SPPB has demonstrated feasibility in clinical practice and has been recognised as a part of the EWGSOP2 definition for severe sarcopenia [23, 35, 36], this finding further supports the poor utilisation of a validated tool to evaluate sarcopenia in clinical settings.
The findings from this study have important clinical and research implications. While geriatric rehabilitation should be a well-equipped environment to identify and manage sarcopenia owing to its multidisciplinary teams, facility, and expertise in geriatric medicine [1], patients with sarcopenia are most likely undocumented. Patients are at risk of not receiving ongoing treatment post-discharge due to the lack of communication with clinicians in the community. The aim of functional recovery may not serve these patients well since they have an ongoing, untreated risk of falls, physical disability, and mortality [6, 37, 38]. This risk necessitates clinicians’ awareness and prioritising sarcopenia. Future research should focus on implementation strategies for sarcopenia documentation in geriatric rehabilitation. Qualitative studies are needed for a more nuanced exploration into the barriers at practitioner and patient levels.
When documenting sarcopenia, it is recommended to classify the sarcopenia case where possible, including primary or secondary and acute or chronic [6, 26]. Most sarcopenia cases in geriatric rehabilitation inpatients would be secondary sarcopenia due to their multiple comorbidities predisposing them to the disease [3, 6]. Classifying sarcopenia as acute or chronic is more difficult because geriatric rehabilitation inpatients share several risk factors for both, including their comorbidities and acute illnesses prior to admission. Furthermore, the 6-month cutoff point to distinguish between acute and chronic sarcopenia may be difficult to utilise due to the lack of prior case-finding and follow-ups [11, 27, 28]. Clinicians should also focus on identifying and treating the reversible secondary causes besides nutrition supplementation and resistance exercise when managing secondary sarcopenia. Ongoing re-evaluation of sarcopenia and the predisposing factors are important for the treatment process, requiring ongoing documentation of sarcopenia.
This study has several strengths. It is one of the few studies indicating the documentation of sarcopenia in clinical practice. Since studies on this topic mainly used standardised surveys of health professionals [11, 27, 28], utilisation of medical records has the advantage of a more objective exploration into the identification of sarcopenia. Other strengths include a large sample size, controlled selection bias where possible, and inpatient geriatric rehabilitation settings which are better equipped to intervene with sarcopenia. Limitations include the attrition rate from the patients not undergoing muscle assessments, mainly due to the completion rate of BIA, yet it was deemed an acceptable rate [24]. Additionally, the small number of patients documented with sarcopenia in a single-centre study may have limited the statistical power of the statistical analysis. Finally, although we proposed the documentation practice and the possible barriers impacting the documentation of sarcopenia, we had insufficient data to evaluate them.
In conclusion, this study found lower documentation of sarcopenia than the prevalence of sarcopenia in geriatric rehabilitation inpatients. Sarcopenia was incorrectly documented in patients with missing data on muscle measurements that are required for the diagnosis of sarcopenia. Practitioners likely used clinical impressions to document sarcopenia, rather than the formal diagnostic criteria. Patients are at risk of not receiving ongoing treatment post-discharge due to the lack of communication with clinicians in the community.
Acknowledgements
The authors thank the multidisciplinary team members of the Royal Melbourne Hospital, Royal Park Campus, involved in the RESORT cohort for their clinical work and the @AgeMelbourne team for their role in the data collection.
Statement of Ethics
The Melbourne Health Research Ethics Committee approved this study (HERC/17/MH/103). The study was conducted following the Declaration of Helsinki. All participants or their nominated proxies gave written informed consent to participate in the study.
Conflict of Interest Statement
The authors declare no conflict of interest.
Funding Sources
This work was supported by the University of Melbourne (unrestricted grant received by Prof. Andrea B. Maier) and the Medical Research Future Fund (MRFF) provided by the Melbourne Academic Centre for Health (MACH). The funders had no role in the study design, data collection, and the preparation of this article.
Author Contributions
Study conception and design: T.D., C.H.S., E.M.R., and A.B.M. Data collection: C.H.S. and E.M.R. Data curation: E.M.R. and L.G. Data analysis and interpretation: T.D. and A.B.M. Prepared the manuscript: T.D. Revised and approved the final manuscript: all authors.
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.