Frailty in older patients with atrial fibrillation in Vietnam: a comparison between the physical frailty phenotype and the Clinical Frailty Scale

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There is limited evidence on the prevalence of frailty and its impact on health outcomes in older adults with atrial fibrillation (AF) in Vietnam. This study aimed to (1) Examine the prevalence of frailty in older hospitalised patients with AF, using the frailty phenotype (Fried’s criteria) and the Clinical Frailty Scale (CFS), and (2) Compare the associations of these frailty definitions with hospitalisation. Methods . Adults aged 65 or older with AF attending the outpatient clinics of Thong Nhat Hospital, Ho Chi Minh City, Vietnam, from December 2022 to September 2023 were included in this study. Frailty was defined as having ≥3/5 of Fried’s criteria or a CFS≥4. All participants were followed up for 9 months, recording hospitalizations. Results . There were 305 participants. They had a mean age of 76.7 (SD 7.8), 40% were female. The prevalence of frailty was 34% according to Fried’s criteria, and 88% according to the CFS (Kappa coefficient 0.14, 95%CI 0.09–0.19). The hospitalisation rate during follow up was 28.8%, higher in frail participants compared to the non-frail. The sensitivity and specificity for predicting hospitalisation were 95.3% and 15.0% for CFS≥4, and 44.2% and 69.5% for Fried’s criteria, respectively. Frailty defined as CFS≥4 was significantly associated with increased hospitalisation (adjusted OR 3.72, 95%CI 1.23–11.31, p=0.020). A weaker association was observed with frailty defined by Fried’s criteria (adjusted OR 1.64, 95%CI 0.95–2.84, p=0.077). Similar results were obtained when frailty was analysed as a continuous score: adjusted ORs 1.39 (95%CI 1.05–1.83, p=0.022) for each higher number of CFS categories, and 1.24 (95%CI 1.00 – 1.53, p=0.051) for each unit higher Fried’s score. Conclusion . Frailty was highly prevalent among older patients with AF. There was a poor correlation between the two frailty criteria when identifying frail and non-frail participants in the cohort using the cut-offs. Despite this, both measures of frailty worked well as predictors of hospitalisation, and using the suggested cutoff of CFS≥4 is more likely to accurately identify future hospitalisations. Further studies are needed to compare the predictive values of these two frailty definitions in older adults in Vietnam. frailty frailty phenotype Clinical Frailty Scale atrial fibrillation geriatric cardiology Vietnam Figures Figure 1 Figure 2 Background Atrial fibrillation (AF) is the most prevalent arrhythmia worldwide and significantly contributes to the risk of stroke. The prevalence and incidence of AF increase significantly with age. 1 , 2 AF particularly affects older adults and poses an increasing burden on the healthcare systems. 3 , 4 AF-related strokes tend to be more severe and often leading to chronic disability or death. Additionally, AF-related strokes incur higher healthcare costs compared to non-AF strokes. 3 AF is a common condition in older hospitalised patients in Vietnam. Previous studies reported that AF was present in 4–8% in older hospitalised patients. 5 , 6 A recent study of 2038 patients (mean age 66 years, SD 13) hospitalized with ischemic stroke or transient ischemic attack found that 18.1% of them had AF. 7 However, there is limited evidence on the prevalence of frailty and its impact on health outcomes in this population. As the population ages, both the prevalence and significance of frailty in clinical settings are increasing. 8 Frailty is a complex geriatric syndrome caused by multisystem impairments, resulting in increased vulnerability to stressors and a higher risk of functional disabilities. 9 Various physiological factors have been shown to contribute to the progression of frailty, including the cardiovascular systems and thrombotic pathways. 10 , 11 Research has provided substantial evidence linking frailty with cardiovascular diseases, including AF. 12 , 13 For older adults with AF, frailty can adversely affect their treatment and health outcomes. 14 – 16 Therefore, it is important to understand the impact of frailty in this population. However, despite the considerable interest in frailty research, a "gold" standard for frailty has yet to be established. 17 Researchers have developed more than sixty different assessment tools to evaluate and categorize frailty, but a consensus remains elusive due to the varying criteria and results produced by each tool. 17 , 18 The frailty phenotype ( Fried’s frailty criteria) has been predominantly used in both clinical and experimental research, but this approach can be challenging for older patients who are often bedridden due to acute illnesses. 19 The Clinical Frailty Scale (CFS) offers an alternative by summarizing the overall fitness or frailty level of older individuals, and has demonstrated its potential as a strong predictor of mortality in several study populations. 20 – 22 This frailty approach may be more practical for research in older hospitalized patients, especially in resource-limited clinical settings. 20 Therefore, this study aimed to (1) to examine the prevalence of frailty in older hospitalised patients with AF, using the frailty phenotype and the CFS, and (2) to compare the association of frailty defined by the frailty phenotype and frailty defined by the CFS with hospitalisation in this population. Methods Study design and population A prospective, observational study was conducted at the outpatient clinics of Thong Nhat Hospital in Ho Chi Minh City from December 2022 to September 2023 to examine the prevalence of frailty in older patients with AF. Older patients aged ≥ 60 diagnosed with AF who visited the clinics during the study period were recruited. AF was defined by medical history and confirmed with a 12-lead ECG. Patients with valvular heart disease or having an ischemic stroke within the past 2 weeks were excluded. All participants were assessed for frailty using the physical frailty phenotype and the CFS. (Table 1 ) The physical frailty phenotype includes 5 components: unintentional weight loss, weakness, exhaustion, slowness and low physical activity. Participants with three or more of these components were identified as being frail. 19 The CFS Frailty was assessed using the CFS version 2.0. 17 , 23 The CFS score ranges from 1–9, and a score of 4 or greater indicates frailty status. 23 , 24 For the purpose of the current study, only participants aged 65 or above were included as the CFS is not validated in adults younger than 65 years. Table 1 Participant characteristics Variables All (n = 305) Frailty defined by ≥ 3 Fried’s criteria Frailty defined by the Clinical Frailty Scale ≥ 4 Non-frail (n = 200) Frail (n = 105) P value Non-frail (n = 38) Frail (n = 267) P value Age, years 76.7 (7.8) 74.5 (7.0) 80.7 (7.8) < 0.001 69.9 (4.8) 77.6 (7.7) < 0.001 Sex Female 123 (40.3) 70 (35.0) 53 (50.5) 0.009 10 (26.3) 113 (42.3) 0.060 Male 182 (59.7) 130 (65.0) 52 (49.5) 28 (73.7) 154 (57.7) Level of education Illiterate 25 (8.2) 13 (6.5) 12 (11.4) 0.066 2 (5.3) 23 (8.6) 0.372 Primary school 69 (22.6) 41 (20.5) 28 (26.7) 10 (26.3) 59 (22.1) Secondary/High school 98 (32.1) 74 (37.0) 24 (22.9) 13 (34.2) 85 (31.8) Higher education 68 (22.3) 46 (23.0) 22 (21.0) 11 (28.9) 57 (21.3) Unknown 45 (14.8) 26 (13.0) 19 (18.1) 2 (5.3) 43 (16.1) Carer None (Living alone) 10 (3.3) 9 (4.5) 1 (1.0) 0.025 2 (5.3) 8 (3.0) 0.243 Spouse 148 (48.5) 106 (53.0) 42 (40.0) 23 (60.5) 125 (46.8) Children 142 (46.6) 82 (41.0) 60 (57.1) 13 (34.2) 129 (48.3) Other relatives 5 (1.6) 3 (1.5) 2 (1.9) 0 (0) 5 (1.9) Marital status Married 214 (70.2) 158 (79.0) 56 (53.3) < 0.001 33 (86.8) 181 (67.8) 0.063 Never married 3 (1.0) 2 (1.0) 1 (1.0) 0 (0) 3 (1.1) Divorced/separated 9 (3.0) 7 (3.5) 2 (1.9) 2 (5.3) 7 (2.6) Widowed 79 (25.9) 33 (16.5) 46 (43.8) 3 (7.9) 76 (28.5) Smoking Never smoke 242 (79.3) 162 (81.0) 80 (76.2) 0.335 24 (63.2) 218 (81.6) 0.028 Currently smoking 20 (6.6) 14 (7.0) 6 (5.7) 5 (13.2) 15 (5.6) Used to smoke 43 (14.1) 24 (12.0) 19 (18.1) 9 (23.7) 34 (12.7) BMI, kg/m 2 Underweight (BMI < 18.5) 17 (5.6) 7 (3.5) 10 (9.5) 0.003 1 (2.6) 16 (6.0) 0.209 Normal (BMI 18.5–22.9) 103 (33.8) 59 (29.5) 44 (41.9) 9 (23.7) 94 (35.2) Overweight and obese (BMI ≥ 23.0) 185 (60.7) 134 (67.0) 51 (48.6) 28 (73.7) 157 (58.8) Comorbidities : Hypertension 284 (93.1) 185 (92.5) 99 (94.3) 0.558 33 (86.8) 251 (94.0) 0.103 Dyslipidemia 263 (86.2) 169 (84.5) 94 (89.5) 0.226 31 (81.6) 232 (86.9) 0.374 Ischemic heart disease 167 (54.8) 110 (55.0) 57 (54.3) 0.905 14 (36.8) 153 (57.3) 0.018 Diabetes 103 (33.8) 67 (33.5) 36 (34.3) 0.890 10 (26.3) 93 (34.8) 0.299 GERD 68 (22.3) 45 (22.5) 23 (21.9) 0.906 10 (26.3) 58 (21.7) 0.524 Osteoarthritis 67 (22.0) 38 (19.0) 29 (27.9) 0.076 4 (10.5) 63 (23.7) 0.092 Heart failure 48 (15.7) 17 (8.5) 31 (29.5) < 0.001 3 (7.9) 45 (16.9) 0.232 Ischemic stroke/TIA 26 (8.5) 13 (6.5) 13 (12.4) 0.081 1 (2.6) 25 (9.4) 0.223 Chronic kidney disease 21 (6.9) 10 (5.0) 11 (10.5) 0.073 0 (0) 21 (7.9) 0.088 Chronic hepatitis 18 (5.9) 13 (6.5) 5 (4.8) 0.541 3 (7.9) 15 (5.6) 0.710 Osteoporosis 13 (4.3) 6 (3.0) 7 (6.7) 0.132 1 (2.6) 12 (4.5) 0.713 Peripheral vascular disease 8 (2.6) 4 (2.0) 4 (3.8) 0.454 2 (5.3) 6 (2.3) 0.602 Cancer 6 (2.0) 3 (1.5) 3 (2.9) 0.668 1 (2.6) 5 (1.9) 0.99 COPD/chronic bronchitis 9 (3.0) 3 (1.5) 6 (5.7) 0.068 1 (2.6) 8 (3.0) 0.99 Falls/fractures 4 (1.3) 9 (0) 4 (3.8) 0.014 0 (0) 4 (1.5) 0.99 Number of comorbidities (excluding atrial fibrillation) 3.7 (1.3) 3.5 (1.3) 4.0 (1.3) < 0.001 3.1 (1.5) 3.7 (1.3) 0.004 CHA₂DS₂-VASc Score 4.1 (1.3) 3.8 (1.2) 4.6 (1.3) < 0.001 3.1 (1.3) 4.3 (1.2) < 0.001 HASBLED score 1.5 (0.6) 1.5 (0.6) 1.5 (0.7) 0.445 1.3 (0.6) 1.5 (0.6) 0.076 Anticoagulation treatment None 36 (11.8) 22 (11.0) 14 (13.3) 0.778 6 (15.8) 30 (11.2) 0.618 Vitamin K antagonists 73 (23.9) 47 (23.5) 26 (24.8) 10 (26.3) 63 (23.6) Direct oral anticoagulants 196 (64.3) 131 (65.5) 65 (61.9) 22 (57.9) 174 (65.2) Continuous data are presented as mean (standard deviation). Categorical data are shown as n (%). BMI: body mass index. COPD: chronic obstructive pulmonary disease. GERD: gastroesophageal reflux disease. TIA: transient ischemic attack Data were collected from patient interviews and medical records. Information obtained included demographic characteristics, lifestyles, height, weight, medical history, blood test results, medications and comorbidities. The study was approved by the Ethics Committee of the University of Medicine and Pharmacy at Ho Chi Minh City (Reference Number 1027/HDDD-DHYD, dated 09/12/2022) and the Ethics Committee of Thong Nhat Hospital (Reference Number 87/2022/BVTN-HĐYĐ, dated 25/11/2022). Informed consent was obtained from all participants. This study was conducted in accordance with the Declaration of Helsinki. Outcome The study outcome was hospitalisation for ny cause. Hospitalisation information was obtained from patient medical records and by making phone calls to the participants or their caregivers. All participants were followed up for 9 months. Sample size estimation Based on the local data, we estimated that the rate of all-cause hospitalisation in older patients with AF in 9 months would be around 20%. Assuming an absolute difference of 20% in hospitalisation rate between non-frail and frail patients (20% in the non-frail and 40% in the frail), we estimated that at least 82 frail and 82 non-frail patients with AF would be needed in this study to detect a significant difference in hospitalisation rates (with a power of 80%, 2-sided test, alpha = 0.05). Statistical analysis Study population characteristics are presented as mean and standard deviation (SD) for continuous variables, or frequencies and percentages for categorical variables. Comparisons in general characteristics and hospitalisation rates between frail and non-frail participants were conducted using chi-square tests or Fisher's exact tests for binary variables, and Student’s t-tests for continuous variables. The kappa statistic was used to quantify the agreement between frailty defined by Fried’s frailty criteria and the CFS. The degrees of agreement were defined according to the Kappa coefficient values: ≤0.20 (poor), 0.21 to 0.40 (fair), 0.41 to 0.60 (moderate), 0.61 to 0.80 (good), and ≥ 0.81 (very good). 27 , 28 Logistic regression was used to examine the association between frailty and hospitalisation, adjusted for sex, number of comorbidities (excluding AF), CHA₂DS₂-VASc Score, HASBLED score and anticoagulant treatment. The results are presented as odds ratios (OR) and 95% confidence intervals (CI). P values < 0.05 were considered statistically significant. Data were analysed in SPSS Statistics 27.0. Results A total of 305 participants aged ≥ 65 years were included in this study. They had a mean age of 76.7 years (SD 7.8), 40.3% were female and 59.7% were male. Table 1 presents the participant characteristics. Frail participants were significantly older. They had higher CHA₂DS₂-VASc score, and more comorbidities. There was no significant difference in use of anticoagulant treatment between frail and non-frail participants. Figure 2 shows the distribution of the Fried’s score and CFS categories. The prevalence of frailty was 34.4% (105/305) according to Fried’s criteria, and 87.5% (267/305) according to the CFS. Table 2 presents the overlap between these two frailty criteria; the Kappa coefficient value was 0.14 (95% CI 0.09–0.19). Table 2 Agreement between frailty defined by Fried’s criteria and by the Clinical Frailty Scale Non-frail (< 3 Fried’s criteria) (n = 200) Frail (≥ 3/5 Fried’s criteria) (n = 105) Non-frail (CFS < 4) (n = 38) 38 0 Frail (CFS ≥ 4) (n = 267) 162 105 Kappa coefficient = 0.14. CFS: Clinical Frailty Scale The relationship between frailty and all-cause hospitalisation During the follow up, 28.8% of the participants admitted to hospitals. The hospitalisation rate was 31.2% in participants with CFS ≥ 4 versus 11.1% in participants with CFS < 4 (p = 0.013), and 36.9% in participants with 3/5 Fried’s criteria compared to 24.5% in those with < 3 criteria (p = 0.024). The sensitivity and specificity of CFS ≥ 4 for predicting hospitalisation were 95.3% and 15.0%, respectively. The sensitivity of having 3/5 Fried’s criteria for hospitalisation was 44.2%, while its specificity was 69.5%. In the logistic models, frailty defined as CFS ≥ 4 was significantly associated with increased hospitalisation (adjusted OR 3.72, 95%CI 1.23–11.31, p = 0.020). A weaker association was observed with frailty defined by Fried’s criteria; (adjusted OR 1.64, 95%CI 0.95–2.84, p = 0.077). (Table 3 ) Similar results were obtained when frailty was analysed as a continuous score: adjusted ORs for hospitalisation were 1.39 (95%CI 1.05–1.83, p = 0.022) for each higher number of CFS categories, and 1.24 (95%CI 1.00–1.53, p = 0.051) for each unit higher Fried’s score. (Table 4 ). Table 3 Association between (binary) frailty and all-cause hospitalisation Frailty defined by Fried frailty phenotype Frailty defined by CFS ≥ 4 Odds ratios for hospitalisation (95% CI) P value Odds ratios for hospitalisation (95% CI) P value Crude (unadjusted) model 1.80 (1.08–3.02) 0.025 3.62 (1.24–10.58) 0.019 Adjusted model* 1.64 (0.95–2.84) 0.077 3.72 (1.23–11.31) 0.020 *Adjusted for sex, number of comorbidities (excluding AF), CHA₂DS₂-VASc Score, HASBLED score, anticoagulant treatment Table 4 Association between continuous frailty scores and all-cause hospitalisation Fried’s frailty score (from 1 to 5) CFS score (from 1 to 9) Odds ratios for hospitalisation (95% CI) P value Odds ratios for hospitalisation (95% CI) P value Crude (unadjusted) model 1.26 (1.03–1.53) 0.024 1.40 (1.08–1.81) 0.011 Adjusted model* 1.24 (1.00–1.53) 0.051 1.39 (1.05–1.83) 0.022 *Adjusted for sex, number of comorbidities (excluding AF), CHA₂DS₂-VASc Score, HASBLED score, anticoagulant treatment Discussion In this study, frailty was highly prevalent among older patients with AF. There was a large difference in prevalence depending on whether Fried’s criteria (34.4%) or the CFS (87.5%) was used to define frailty. There was poor agreement between these two terms, with a Kappa statistic of 0.14. 27 , 28 The prevalence of frailty defined by Fried’s criteria in our study is consistent with findings from a systematic review published in 2022, which found that approximately 40% of adults with AF globally experienced frailty (prevalence ranging from 30–50%, depending on the frailty assessment used, n = 1,187,651). 29 Our findings are in line with previous studies which found that the CFS tends to identify a higher prevalence of frailty than Fried’s method. A cohort study of 12,237 patients aged 75 years or older in the UK revealed that the prevalence of frailty defined by the CFS ≥ 4 was 82.5% compared to 65% using the hospital frailty risk score, with a poor agreement between these two frailty assessment tools (kappa coefficient 0.15, 95% CI 0.14–0.16). 30 A cohort study of 473 hospitalized patients aged 65 or older in Taiwan also reported that the prevalence of frailty determined by the CFS was 70.2%. 31 This disparity in frailty prevalence may reflect different methodologies in assessing frailty. Fried’s criteria primarily emphasize physical aspects, and relies mostly on objective measurements of weight, muscle strength, walking speed, and physical activity level, while the CFS relies more on the clinician’s judgement and patients’ report of their daily activities and symptoms. Additionally, the subjective nature of the CFS and its reliance on clinician judgment could also contribute to its inconsistency with Fried’s criteria. Another possible explanation is that the CFS captures a wider spectrum of frailty, potentially including individuals in milder stages of frailty, which may not be as readily identified by Fried’s frailty criteria. The poor agreement between two commonly used frailty criteria in identifying frail patients in this study raises a significant question about the reliability and consistency of frailty assessments in clinical settings. Identifying frailty accurately is crucial for tailoring interventions that improve patient outcomes. Different criteria might capture divergent aspects of frailty, potentially leading to varied and possibly conflicting assessments. This discrepancy can lead to variations in frailty identification, subsequently influencing treatment plans and prognostic outlooks. It is imperative to further investigate why these criteria yield different results and explore the development of a more unified and comprehensive assessment framework. It is important to select frailty assessment tools carefully based on specific clinical goals, whether for rapid screening or detailed evaluation. The CFS has been shown to correlate well with overall health impairments and is often used for comprehensive assessments in older adults. 32 The simplicity and comprehensiveness of CFS make it suitable for outpatient clinics and chronic care management. On the other hand, Fried’s frailty phenotype is more effective in detecting physical vulnerability, and is still useful for in-depth assessments to design specific interventions such as rehabilitation and nutritional programs. 33 Our finding on the association between frailty and hospitalisation in older patients with AF is consistent with studies in other populations. In a study using data from 2369 patients (mean age 73 years) in the Swiss Atrial Fibrillation Cohort Study, frailty was shown to be associated with a higher risk of unplanned hospitalisation (adjusted HR 3.59, 95% CI 2.78–4.63). 34 Frailty often leads to adverse outcomes in AF patients by increasing their vulnerability to complications and exacerbating existing comorbidities. 35 Our study found that frailty defined by the CFS had a stronger association with hospitalisation than Fried’s frailty criteria. This difference may suggest a stronger prognostic value of the CFS in clinical settings, where disease burden and functional activities are more important. The CFS is the more sensitive in assessing frailty in the older patients with AF. A systematic review published in 2022 analyzed 23 studies, involving a total of 504,719 AF participants aged 65 and older from different geographical locations worldwide, also reported a great heterogeneity among different (in this case, 17) validated frailty measures. 36 This review showed that Fried’s frailty phenotype predicted adverse outcomes with highly heterogeneous results and did not show a significant difference in oral anticoagulant prescription rates between frail and non-frail patients. In contrast, the deficit accumulation model, which conceptualizes frailty as the accumulation of multiple health deficits, did reveal such differences. 36 To the best of our knowledge, this is the first study on the prevalence of frailty in older adults with AF in Vietnam, using both the frailty phenotype and CFS. Our study provides data specific to Vietnamese patients with AF, where research on frailty in this population remains limited. Despite the strength, this study has several limitations. The measurements of frailty, including the CFS were conducted by only one researcher. In addition, the study was conducted at a single hospital. Therefore, the findings may not be generalisable for all older adults with AF in Vietnam and should be interpreted with caution. Conclusion Frailty was highly prevalent among older patients with AF. There was a weak correlation between the two frailty criteria when identifying frail and non-frail participants in the cohort using the established cut-offs. Despite this poor correlation, both measures of frailty worked well as predictors of hospitalisation, and using the suggested cutoff of CFS ≥ 4 is more likely to accurately identify future hospitalisations. Further studies are needed to compare the predictive values of these two frailty definitions in older adults in Vietnam. Declarations Ethics approval and consent to participate. The study was approved by the Ethics Committee of the University of Medicine and Pharmacy at Ho Chi Minh City (Reference Number 1027/HDDD-DHYD, dated 09/12/2022) and the Ethics Committee of Thong Nhat Hospital (Reference Number 87/2022/BVTN-HĐYĐ, dated 25/11/2022). Informed consent was obtained from all participants. Consent for publication. Not applicable. Availability of data and materials. The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests. The authors declare that they have no competing interests. Funding. This study did not receive any funding. Authors' contributions. TVN and TNN conceived the study. TVN and HQN designed the study protocol, led the ethics application and conducted recruitment. TVN and TNN conducted the statistical analyses and led the manuscript writing. All authors were involved in data interpretation. The manuscript was revised for important scientific content by all authors. All authors approved the final version of the manuscript. Acknowledgements. We thank all participants for their participation in this study. Clinical trial number. Not applicable. References Heeringa J, van der Kuip DA, Hofman A, et al. Prevalence, incidence and lifetime risk of atrial fibrillation: the Rotterdam study. Eur Heart J Apr. 2006;27(8):949–53. 10.1093/eurheartj/ehi825 . Lake FR, Cullen KJ, de Klerk NH, McCall MG, Rosman DL. Atrial fibrillation and mortality in an elderly population. Aust N Z J Med Aug. 1989;19(4):321–6. 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J Am Med Dir Assoc Mar. 2020;21(3):300–e3072. 10.1016/j.jamda.2019.12.012 . Tran DV, Lee AH, Au TB, Nguyen CT, Hoang DV. Reliability and validity of the International Physical Activity Questionnaire-Short Form for older adults in Vietnam. Health Promot J Austr Aug. 2013;24(2):126–31. 10.1071/he13012 . Zhu Y, Liu Z, Wang Y, et al. Agreement between the frailty index and phenotype and their associations with falls and overnight hospitalizations. Arch Gerontol Geriatr Sep-Oct. 2016;66:161–5. 10.1016/j.archger.2016.06.004 . Nguyen AT, Nguyen TX, Nguyen TN, et al. The impact of frailty on prolonged hospitalization and mortality in elderly inpatients in Vietnam: a comparison between the frailty phenotype and the Reported Edmonton Frail Scale. Clin Interv Aging. 2019;14:381–8. 10.2147/cia.S189122 . Proietti M, Romiti GF, Raparelli V, et al. Frailty prevalence and impact on outcomes in patients with atrial fibrillation: A systematic review and meta-analysis of 1,187,000 patients. Ageing Res Rev Aug. 2022;79:101652. 10.1016/j.arr.2022.101652 . Alshibani A, Coats T, Maynou L, Lecky F, Banerjee J, Conroy S. A comparison between the clinical frailty scale and the hospital frailty risk score to risk stratify older people with emergency care needs. BMC Emerg Med. 2022/10/25 2022;22(1):171. 10.1186/s12873-022-00730-5 Lin JW, Lin PY, Wang TY, Chen YJ, Yen DH, Huang HH. The Association Between Frailty Evaluated by Clinical Frailty Scale and Mortality of Older Patients in the Emergency Department: A Prospective Cohort Study. Clin Interv Aging. 2024;19:1383–92. 10.2147/cia.S472991 . Church S, Rogers E, Rockwood K, Theou O. A scoping review of the Clinical Frailty Scale. BMC Geriatr Oct. 2020;7(1):393. 10.1186/s12877-020-01801-7 . Xue QL. The frailty syndrome: definition and natural history. Clin Geriatr Med Feb. 2011;27(1):1–15. 10.1016/j.cger.2010.08.009 . Gugganig R, Aeschbacher S, Leong DP, et al. Frailty to predict unplanned hospitalization, stroke, bleeding, and death in atrial fibrillation. Eur Heart J Qual Care Clin Outcomes Jan. 2021;25(1):42–51. 10.1093/ehjqcco/qcaa002 . Savelieva I, Fumagalli S, Kenny RA, et al. EHRA expert consensus document on the management of arrhythmias in frailty syndrome, endorsed by the Heart Rhythm Society (HRS), Asia Pacific Heart Rhythm Society (APHRS), Latin America Heart Rhythm Society (LAHRS), and Cardiac Arrhythmia Society of Southern Africa (CASSA). EP Europace. 2023;25(4):1249–76. 10.1093/europace/euac123 . Presta R, Brunetti E, Polidori MC, Bo M. Impact of frailty models on the prescription of oral anticoagulants and on the incidence of stroke, bleeding, and mortality in older patients with atrial fibrillation: a systematic review. Ageing Res Rev Dec. 2022;82:101761. 10.1016/j.arr.2022.101761 . Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5992248","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":424042416,"identity":"727093db-30f0-4c40-b9b4-24fb0991719b","order_by":0,"name":"Tan Van Nguyen","email":"","orcid":"","institution":"University of Medicine and Pharmacy at Ho Chi Minh City","correspondingAuthor":false,"prefix":"","firstName":"Tan","middleName":"Van","lastName":"Nguyen","suffix":""},{"id":424042417,"identity":"58dc44d1-4776-42e3-97a8-1abf1d425abc","order_by":1,"name":"Huy Quoc Nguyen","email":"","orcid":"","institution":"University of Medicine and Pharmacy at Ho Chi Minh City","correspondingAuthor":false,"prefix":"","firstName":"Huy","middleName":"Quoc","lastName":"Nguyen","suffix":""},{"id":424042418,"identity":"5b0731bc-a34f-4d5a-89c6-c6e90efe0d73","order_by":2,"name":"Lilin Chen","email":"","orcid":"","institution":"The Hong Kong Polytechnic University","correspondingAuthor":false,"prefix":"","firstName":"Lilin","middleName":"","lastName":"Chen","suffix":""},{"id":424042419,"identity":"62516ae4-d1ac-48a1-9b57-fededa3aaf65","order_by":3,"name":"Mark Woodward","email":"","orcid":"","institution":"George Institute for Global Health","correspondingAuthor":false,"prefix":"","firstName":"Mark","middleName":"","lastName":"Woodward","suffix":""},{"id":424042420,"identity":"a15e81f1-e9ec-42f4-b16c-2284fdfe9d55","order_by":4,"name":"Tu Ngoc Nguyen","email":"data:image/png;base64,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","orcid":"","institution":"George Institute for Global Health","correspondingAuthor":true,"prefix":"","firstName":"Tu","middleName":"Ngoc","lastName":"Nguyen","suffix":""}],"badges":[],"createdAt":"2025-02-09 12:08:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5992248/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5992248/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12877-026-07065-x","type":"published","date":"2026-02-02T15:56:57+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":78248970,"identity":"09d40c4b-70e3-4cff-aad7-a71842c74b67","added_by":"auto","created_at":"2025-03-11 09:41:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":130593,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFried’s Frailty criteria and the Clinical Frailty Scale\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5992248/v1/baf75fdab26a787bdcd1aea1.png"},{"id":78246824,"identity":"7cb344b8-34a8-484a-95ad-4238d4564ee6","added_by":"auto","created_at":"2025-03-11 09:33:26","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":145726,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe distribution of the Clinical Frailty Scale (left) and Fried’s frailty phenotype (right)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5992248/v1/8ad7074d32f166c113081a7a.jpeg"},{"id":102233957,"identity":"b97cd2dc-8628-42b3-acff-f94a651f063a","added_by":"auto","created_at":"2026-02-09 16:00:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1448235,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5992248/v1/500f5624-11b5-47d7-b125-cdb38e600521.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Frailty in older patients with atrial fibrillation in Vietnam: a comparison between the physical frailty phenotype and the Clinical Frailty Scale","fulltext":[{"header":"Background","content":"\u003cp\u003eAtrial fibrillation (AF) is the most prevalent arrhythmia worldwide and significantly contributes to the risk of stroke. The prevalence and incidence of AF increase significantly with age.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e AF particularly affects older adults and poses an increasing burden on the healthcare systems.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e AF-related strokes tend to be more severe and often leading to chronic disability or death. Additionally, AF-related strokes incur higher healthcare costs compared to non-AF strokes.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAF is a common condition in older hospitalised patients in Vietnam. Previous studies reported that AF was present in 4\u0026ndash;8% in older hospitalised patients.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e A recent study of 2038 patients (mean age 66 years, SD 13) hospitalized with ischemic stroke or transient ischemic attack found that 18.1% of them had AF.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e However, there is limited evidence on the prevalence of frailty and its impact on health outcomes in this population. As the population ages, both the prevalence and significance of frailty in clinical settings are increasing.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e Frailty is a complex geriatric syndrome caused by multisystem impairments, resulting in increased vulnerability to stressors and a higher risk of functional disabilities.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Various physiological factors have been shown to contribute to the progression of frailty, including the cardiovascular systems and thrombotic pathways.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Research has provided substantial evidence linking frailty with cardiovascular diseases, including AF.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e For older adults with AF, frailty can adversely affect their treatment and health outcomes.\u003csup\u003e\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Therefore, it is important to understand the impact of frailty in this population. However, despite the considerable interest in frailty research, a \"gold\" standard for frailty has yet to be established.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Researchers have developed more than sixty different assessment tools to evaluate and categorize frailty, but a consensus remains elusive due to the varying criteria and results produced by each tool.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e The frailty phenotype ( Fried\u0026rsquo;s frailty criteria) has been predominantly used in both clinical and experimental research, but this approach can be challenging for older patients who are often bedridden due to acute illnesses.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e The Clinical Frailty Scale (CFS) offers an alternative by summarizing the overall fitness or frailty level of older individuals, and has demonstrated its potential as a strong predictor of mortality in several study populations.\u003csup\u003e\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e This frailty approach may be more practical for research in older hospitalized patients, especially in resource-limited clinical settings.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eTherefore, this study aimed to (1) to examine the prevalence of frailty in older hospitalised patients with AF, using the frailty phenotype and the CFS, and (2) to compare the association of frailty defined by the frailty phenotype and frailty defined by the CFS with hospitalisation in this population.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and population\u003c/h2\u003e \u003cp\u003eA prospective, observational study was conducted at the outpatient clinics of Thong Nhat Hospital in Ho Chi Minh City from December 2022 to September 2023 to examine the prevalence of frailty in older patients with AF. Older patients aged\u0026thinsp;\u0026ge;\u0026thinsp;60 diagnosed with AF who visited the clinics during the study period were recruited. AF was defined by medical history and confirmed with a 12-lead ECG. Patients with valvular heart disease or having an ischemic stroke within the past 2 weeks were excluded. All participants were assessed for frailty using the physical frailty phenotype and the CFS. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) The physical frailty phenotype includes 5 components: unintentional weight loss, weakness, exhaustion, slowness and low physical activity. Participants with three or more of these components were identified as being frail.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e The CFS Frailty was assessed using the CFS version 2.0.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e The CFS score ranges from 1\u0026ndash;9, and a score of 4 or greater indicates frailty status.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e For the purpose of the current study, only participants aged 65 or above were included as the CFS is not validated in adults younger than 65 years.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParticipant characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;305)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eFrailty defined by \u0026ge;\u0026thinsp;3 Fried\u0026rsquo;s criteria\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eFrailty defined by the Clinical Frailty Scale\u0026thinsp;\u0026ge;\u0026thinsp;4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-frail\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFrail\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;105)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNon-frail\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eFrail\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;267)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76.7 (7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.5 (7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80.7 (7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e69.9 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e77.6 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e123 (40.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70 (35.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53 (50.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (26.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e113 (42.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e182 (59.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130 (65.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52 (49.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28 (73.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e154 (57.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eLevel of education\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (11.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23 (8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.372\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69 (22.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (20.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (26.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (26.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e59 (22.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary/High school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98 (32.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74 (37.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 (22.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13 (34.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e85 (31.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68 (22.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46 (23.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11 (28.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e57 (21.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 (14.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (18.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43 (16.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eCarer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone (Living alone)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.243\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpouse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e148 (48.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106 (53.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42 (40.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23 (60.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e125 (46.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChildren\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142 (46.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82 (41.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60 (57.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13 (34.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e129 (48.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther relatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (1.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e214 (70.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e158 (79.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56 (53.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33 (86.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e181 (67.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced/separated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79 (25.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (16.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46 (43.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 (7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e76 (28.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever smoke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e242 (79.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e162 (81.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80 (76.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.335\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24 (63.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e218 (81.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrently smoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (6.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (13.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15 (5.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUsed to smoke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (14.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (12.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (18.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9 (23.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e34 (12.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eBMI, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderweight (BMI\u0026thinsp;\u0026lt;\u0026thinsp;18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16 (6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.209\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal (BMI 18.5\u0026ndash;22.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e103 (33.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59 (29.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44 (41.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9 (23.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e94 (35.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight and obese (BMI\u0026thinsp;\u0026ge;\u0026thinsp;23.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e185 (60.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e134 (67.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51 (48.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28 (73.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e157 (58.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidities\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e284 (93.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e185 (92.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99 (94.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33 (86.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e251 (94.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e263 (86.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e169 (84.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94 (89.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31 (81.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e232 (86.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.374\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e167 (54.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110 (55.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57 (54.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14 (36.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e153 (57.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e103 (33.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67 (33.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (34.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.890\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (26.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e93 (34.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.299\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGERD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68 (22.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (22.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23 (21.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (26.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e58 (21.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.524\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOsteoarthritis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67 (22.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (19.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (27.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e63 (23.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.092\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 (15.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31 (29.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 (7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e45 (16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.232\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic stroke/TIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25 (9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.223\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic kidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (6.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21 (7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic hepatitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (5.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 (7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.710\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOsteoporosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12 (4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.713\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeripheral vascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.602\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD/chronic bronchitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFalls/fractures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of comorbidities (excluding atrial fibrillation)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.7 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.5 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.0 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.1 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.7 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHA₂DS₂-VASc Score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.1 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.8 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.6 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.1 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.3 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHASBLED score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.5 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.5 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.3 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.5 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eAnticoagulation treatment\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (11.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6 (15.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30 (11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.618\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitamin K antagonists\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73 (23.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (24.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (26.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e63 (23.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect oral anticoagulants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e196 (64.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e131 (65.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65 (61.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22 (57.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e174 (65.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eContinuous data are presented as mean (standard deviation). Categorical data are shown as n (%). BMI: body mass index. COPD: chronic obstructive pulmonary disease. GERD: gastroesophageal reflux disease. TIA: transient ischemic attack\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eData were collected from patient interviews and medical records. Information obtained included demographic characteristics, lifestyles, height, weight, medical history, blood test results, medications and comorbidities.\u003c/p\u003e \u003cp\u003e The study was approved by the Ethics Committee of the University of Medicine and Pharmacy at Ho Chi Minh City (Reference Number 1027/HDDD-DHYD, dated 09/12/2022) and the Ethics Committee of Thong Nhat Hospital (Reference Number 87/2022/BVTN-HĐYĐ, dated 25/11/2022). Informed consent was obtained from all participants. This study was conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e \n\u003ch3\u003eOutcome\u003c/h3\u003e\n\u003cp\u003eThe study outcome was hospitalisation for ny cause. Hospitalisation information was obtained from patient medical records and by making phone calls to the participants or their caregivers. All participants were followed up for 9 months.\u003c/p\u003e\n\u003ch3\u003eSample size estimation\u003c/h3\u003e\n\u003cp\u003eBased on the local data, we estimated that the rate of all-cause hospitalisation in older patients with AF in 9 months would be around 20%. Assuming an absolute difference of 20% in hospitalisation rate between non-frail and frail patients (20% in the non-frail and 40% in the frail), we estimated that at least 82 frail and 82 non-frail patients with AF would be needed in this study to detect a significant difference in hospitalisation rates (with a power of 80%, 2-sided test, alpha\u0026thinsp;=\u0026thinsp;0.05).\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStudy population characteristics are presented as mean and standard deviation (SD) for continuous variables, or frequencies and percentages for categorical variables. Comparisons in general characteristics and hospitalisation rates between frail and non-frail participants were conducted using chi-square tests or Fisher's exact tests for binary variables, and Student\u0026rsquo;s t-tests for continuous variables.\u003c/p\u003e \u003cp\u003eThe kappa statistic was used to quantify the agreement between frailty defined by Fried\u0026rsquo;s frailty criteria and the CFS. The degrees of agreement were defined according to the Kappa coefficient values: \u0026le;0.20 (poor), 0.21 to 0.40 (fair), 0.41 to 0.60 (moderate), 0.61 to 0.80 (good), and \u0026ge;\u0026thinsp;0.81 (very good).\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e Logistic regression was used to examine the association between frailty and hospitalisation, adjusted for sex, number of comorbidities (excluding AF), CHA₂DS₂-VASc Score, HASBLED score and anticoagulant treatment. The results are presented as odds ratios (OR) and 95% confidence intervals (CI). P values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant. Data were analysed in SPSS Statistics 27.0.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 305 participants aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years were included in this study. They had a mean age of 76.7 years (SD 7.8), 40.3% were female and 59.7% were male. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the participant characteristics. Frail participants were significantly older. They had higher CHA₂DS₂-VASc score, and more comorbidities. There was no significant difference in use of anticoagulant treatment between frail and non-frail participants.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the distribution of the Fried\u0026rsquo;s score and CFS categories. The prevalence of frailty was 34.4% (105/305) according to Fried\u0026rsquo;s criteria, and 87.5% (267/305) according to the CFS. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the overlap between these two frailty criteria; the Kappa coefficient value was 0.14 (95% CI 0.09\u0026ndash;0.19).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAgreement between frailty defined by Fried\u0026rsquo;s criteria and by the Clinical Frailty Scale\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-frail (\u0026lt;\u0026thinsp;3 Fried\u0026rsquo;s criteria)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrail (\u0026ge;\u0026thinsp;3/5 Fried\u0026rsquo;s criteria)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;105)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-frail (CFS\u0026thinsp;\u0026lt;\u0026thinsp;4) (n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrail (CFS\u0026thinsp;\u0026ge;\u0026thinsp;4) (n\u0026thinsp;=\u0026thinsp;267)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eKappa coefficient\u0026thinsp;=\u0026thinsp;0.14. CFS: Clinical Frailty Scale\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eThe relationship between frailty and all-cause hospitalisation\u003c/h2\u003e \u003cp\u003eDuring the follow up, 28.8% of the participants admitted to hospitals. The hospitalisation rate was 31.2% in participants with CFS\u0026thinsp;\u0026ge;\u0026thinsp;4 versus 11.1% in participants with CFS\u0026thinsp;\u0026lt;\u0026thinsp;4 (p\u0026thinsp;=\u0026thinsp;0.013), and 36.9% in participants with 3/5 Fried\u0026rsquo;s criteria compared to 24.5% in those with \u0026lt;\u0026thinsp;3 criteria (p\u0026thinsp;=\u0026thinsp;0.024). The sensitivity and specificity of CFS\u0026thinsp;\u0026ge;\u0026thinsp;4 for predicting hospitalisation were 95.3% and 15.0%, respectively. The sensitivity of having 3/5 Fried\u0026rsquo;s criteria for hospitalisation was 44.2%, while its specificity was 69.5%.\u003c/p\u003e \u003cp\u003eIn the logistic models, frailty defined as CFS\u0026thinsp;\u0026ge;\u0026thinsp;4 was significantly associated with increased hospitalisation (adjusted OR 3.72, 95%CI 1.23\u0026ndash;11.31, p\u0026thinsp;=\u0026thinsp;0.020). A weaker association was observed with frailty defined by Fried\u0026rsquo;s criteria; (adjusted OR 1.64, 95%CI 0.95\u0026ndash;2.84, p\u0026thinsp;=\u0026thinsp;0.077). (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) Similar results were obtained when frailty was analysed as a continuous score: adjusted ORs for hospitalisation were 1.39 (95%CI 1.05\u0026ndash;1.83, p\u0026thinsp;=\u0026thinsp;0.022) for each higher number of CFS categories, and 1.24 (95%CI 1.00\u0026ndash;1.53, p\u0026thinsp;=\u0026thinsp;0.051) for each unit higher Fried\u0026rsquo;s score. (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between (binary) frailty and all-cause hospitalisation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eFrailty defined by Fried frailty phenotype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eFrailty defined by CFS\u0026thinsp;\u0026ge;\u0026thinsp;4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOdds ratios for hospitalisation (95% CI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eOdds ratios for hospitalisation (95% CI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP \u003cb\u003evalue\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrude (unadjusted) model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.80 (1.08\u0026ndash;3.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.62 (1.24\u0026ndash;10.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdjusted model*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.64 (0.95\u0026ndash;2.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.72 (1.23\u0026ndash;11.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Adjusted for sex, number of comorbidities (excluding AF), CHA₂DS₂-VASc Score, HASBLED score, anticoagulant treatment\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between continuous frailty scores and all-cause hospitalisation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eFried\u0026rsquo;s frailty score (from 1 to 5)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eCFS score (from 1 to 9)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOdds ratios for hospitalisation (95% CI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eOdds ratios for hospitalisation (95% CI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP \u003cb\u003evalue\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrude (unadjusted) model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.26 (1.03\u0026ndash;1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.40 (1.08\u0026ndash;1.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdjusted model*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.24 (1.00\u0026ndash;1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.39 (1.05\u0026ndash;1.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Adjusted for sex, number of comorbidities (excluding AF), CHA₂DS₂-VASc Score, HASBLED score, anticoagulant treatment\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, frailty was highly prevalent among older patients with AF. There was a large difference in prevalence depending on whether Fried\u0026rsquo;s criteria (34.4%) or the CFS (87.5%) was used to define frailty. There was poor agreement between these two terms, with a Kappa statistic of 0.14.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe prevalence of frailty defined by Fried\u0026rsquo;s criteria in our study is consistent with findings from a systematic review published in 2022, which found that approximately 40% of adults with AF globally experienced frailty (prevalence ranging from 30\u0026ndash;50%, depending on the frailty assessment used, n\u0026thinsp;=\u0026thinsp;1,187,651).\u003csup\u003e29\u003c/sup\u003e Our findings are in line with previous studies which found that the CFS tends to identify a higher prevalence of frailty than Fried\u0026rsquo;s method. A cohort study of 12,237 patients aged 75 years or older in the UK revealed that the prevalence of frailty defined by the CFS\u0026thinsp;\u0026ge;\u0026thinsp;4 was 82.5% compared to 65% using the hospital frailty risk score, with a poor agreement between these two frailty assessment tools (kappa coefficient 0.15, 95% CI 0.14\u0026ndash;0.16).\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e A cohort study of 473 hospitalized patients aged 65 or older in Taiwan also reported that the prevalence of frailty determined by the CFS was 70.2%.\u003csup\u003e31\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThis disparity in frailty prevalence may reflect different methodologies in assessing frailty. Fried\u0026rsquo;s criteria primarily emphasize physical aspects, and relies mostly on objective measurements of weight, muscle strength, walking speed, and physical activity level, while the CFS relies more on the clinician\u0026rsquo;s judgement and patients\u0026rsquo; report of their daily activities and symptoms. Additionally, the subjective nature of the CFS and its reliance on clinician judgment could also contribute to its inconsistency with Fried\u0026rsquo;s criteria. Another possible explanation is that the CFS captures a wider spectrum of frailty, potentially including individuals in milder stages of frailty, which may not be as readily identified by Fried\u0026rsquo;s frailty criteria. The poor agreement between two commonly used frailty criteria in identifying frail patients in this study raises a significant question about the reliability and consistency of frailty assessments in clinical settings. Identifying frailty accurately is crucial for tailoring interventions that improve patient outcomes. Different criteria might capture divergent aspects of frailty, potentially leading to varied and possibly conflicting assessments. This discrepancy can lead to variations in frailty identification, subsequently influencing treatment plans and prognostic outlooks. It is imperative to further investigate why these criteria yield different results and explore the development of a more unified and comprehensive assessment framework. It is important to select frailty assessment tools carefully based on specific clinical goals, whether for rapid screening or detailed evaluation. The CFS has been shown to correlate well with overall health impairments and is often used for comprehensive assessments in older adults.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e The simplicity and comprehensiveness of CFS make it suitable for outpatient clinics and chronic care management. On the other hand, Fried\u0026rsquo;s frailty phenotype is more effective in detecting physical vulnerability, and is still useful for in-depth assessments to design specific interventions such as rehabilitation and nutritional programs.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eOur finding on the association between frailty and hospitalisation in older patients with AF is consistent with studies in other populations. In a study using data from 2369 patients (mean age 73 years) in the Swiss Atrial Fibrillation Cohort Study, frailty was shown to be associated with a higher risk of unplanned hospitalisation (adjusted HR 3.59, 95% CI 2.78\u0026ndash;4.63).\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e Frailty often leads to adverse outcomes in AF patients by increasing their vulnerability to complications and exacerbating existing comorbidities.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e Our study found that frailty defined by the CFS had a stronger association with hospitalisation than Fried\u0026rsquo;s frailty criteria. This difference may suggest a stronger prognostic value of the CFS in clinical settings, where disease burden and functional activities are more important. The CFS is the more sensitive in assessing frailty in the older patients with AF. A systematic review published in 2022 analyzed 23 studies, involving a total of 504,719 AF participants aged 65 and older from different geographical locations worldwide, also reported a great heterogeneity among different (in this case, 17) validated frailty measures.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e This review showed that Fried\u0026rsquo;s frailty phenotype predicted adverse outcomes with highly heterogeneous results and did not show a significant difference in oral anticoagulant prescription rates between frail and non-frail patients. In contrast, the deficit accumulation model, which conceptualizes frailty as the accumulation of multiple health deficits, did reveal such differences.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, this is the first study on the prevalence of frailty in older adults with AF in Vietnam, using both the frailty phenotype and CFS. Our study provides data specific to Vietnamese patients with AF, where research on frailty in this population remains limited. Despite the strength, this study has several limitations. The measurements of frailty, including the CFS were conducted by only one researcher. In addition, the study was conducted at a single hospital. Therefore, the findings may not be generalisable for all older adults with AF in Vietnam and should be interpreted with caution.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eFrailty was highly prevalent among older patients with AF. There was a weak correlation between the two frailty criteria when identifying frail and non-frail participants in the cohort using the established cut-offs. Despite this poor correlation, both measures of frailty worked well as predictors of hospitalisation, and using the suggested cutoff of CFS\u0026thinsp;\u0026ge;\u0026thinsp;4 is more likely to accurately identify future hospitalisations. Further studies are needed to compare the predictive values of these two frailty definitions in older adults in Vietnam.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate.\u0026nbsp;\u003c/strong\u003eThe study was approved by the Ethics Committee of the University of Medicine and Pharmacy at Ho Chi Minh City (Reference Number 1027/HDDD-DHYD, dated 09/12/2022) and the Ethics Committee of Thong Nhat Hospital (Reference Number 87/2022/BVTN-HĐYĐ, dated 25/11/2022). Informed consent was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication.\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials.\u0026nbsp;\u003c/strong\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests.\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding.\u0026nbsp;\u003c/strong\u003eThis study did not receive any funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions.\u0026nbsp;\u003c/strong\u003eTVN and TNN conceived the study. TVN and HQN designed the study protocol, led the ethics application and conducted recruitment. TVN and TNN conducted the statistical analyses and led the manuscript writing. All authors were involved in data interpretation. The manuscript was revised for important scientific content by all authors. All authors approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements.\u0026nbsp;\u003c/strong\u003eWe thank all participants for their participation in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number.\u003c/strong\u003e Not applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHeeringa J, van der Kuip DA, Hofman A, et al. Prevalence, incidence and lifetime risk of atrial fibrillation: the Rotterdam study. Eur Heart J Apr. 2006;27(8):949\u0026ndash;53. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/eurheartj/ehi825\u003c/span\u003e\u003cspan address=\"10.1093/eurheartj/ehi825\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLake FR, Cullen KJ, de Klerk NH, McCall MG, Rosman DL. Atrial fibrillation and mortality in an elderly population. 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Ageing Res Rev Dec. 2022;82:101761. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.arr.2022.101761\u003c/span\u003e\u003cspan address=\"10.1016/j.arr.2022.101761\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"frailty, frailty phenotype, Clinical Frailty Scale, atrial fibrillation, geriatric cardiology, Vietnam","lastPublishedDoi":"10.21203/rs.3.rs-5992248/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5992248/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e. There is limited evidence on the prevalence of frailty and its impact on health outcomes in older adults with atrial fibrillation (AF) in Vietnam. This study aimed to (1) Examine the prevalence of frailty in older hospitalised patients with AF, using the frailty phenotype (Fried’s criteria) and the Clinical Frailty Scale (CFS), and (2) Compare the associations of these frailty definitions with hospitalisation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e. Adults aged 65 or older with AF attending the outpatient clinics of Thong Nhat Hospital, Ho Chi Minh City, Vietnam, from December 2022 to September 2023 were included in this study. Frailty was defined as having ≥3/5 of Fried’s criteria or a CFS≥4. All participants were followed up for 9 months, recording hospitalizations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e. There were 305 participants. They had a mean age of 76.7 (SD 7.8), 40% were female. The prevalence of frailty was 34% according to Fried’s criteria, and 88% according to the CFS (Kappa coefficient 0.14, 95%CI 0.09–0.19). The hospitalisation rate during follow up was 28.8%, higher in frail participants compared to the non-frail. The sensitivity and specificity for predicting hospitalisation were 95.3% and 15.0% for CFS≥4, and 44.2% and 69.5% for Fried’s criteria, respectively. Frailty defined as CFS≥4 was significantly associated with increased hospitalisation (adjusted OR 3.72, 95%CI 1.23–11.31, p=0.020). A weaker association was observed with frailty defined by Fried’s criteria (adjusted OR 1.64, 95%CI 0.95–2.84, p=0.077). Similar results were obtained when frailty was analysed as a continuous score: adjusted ORs 1.39 (95%CI 1.05–1.83, p=0.022) for each higher number of CFS categories, and 1.24 (95%CI 1.00 – 1.53, p=0.051) for each unit higher Fried’s score.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e. Frailty was highly prevalent among older patients with AF. There was a poor correlation between the two frailty criteria when identifying frail and non-frail participants in the cohort using the cut-offs. Despite this, both measures of frailty worked well as predictors of hospitalisation, and using the suggested cutoff of CFS≥4 is more likely to accurately identify future hospitalisations. Further studies are needed to compare the predictive values of these two frailty definitions in older adults in Vietnam.\u003c/p\u003e","manuscriptTitle":"Frailty in older patients with atrial fibrillation in Vietnam: a comparison between the physical frailty phenotype and the Clinical Frailty Scale","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-11 09:33:20","doi":"10.21203/rs.3.rs-5992248/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-10T17:37:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-03T18:47:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-31T19:37:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-29T17:28:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"195836801139658651519220517626603531228","date":"2025-03-29T17:16:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"141847949933406073539178166353745596849","date":"2025-03-28T19:41:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"139876822237188029692473049345499483911","date":"2025-03-27T15:19:01+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-27T02:00:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"276372436207894157995574394616572797467","date":"2025-03-07T23:17:34+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-02T13:22:30+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-02-18T09:12:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-02-13T14:44:03+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-02-13T14:42:40+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2025-02-09T11:54:07+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fb09ac6c-0bd7-4a4d-9463-39a2225de40f","owner":[],"postedDate":"March 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-09T16:00:03+00:00","versionOfRecord":{"articleIdentity":"rs-5992248","link":"https://doi.org/10.1186/s12877-026-07065-x","journal":{"identity":"bmc-geriatrics","isVorOnly":false,"title":"BMC Geriatrics"},"publishedOn":"2026-02-02 15:56:57","publishedOnDateReadable":"February 2nd, 2026"},"versionCreatedAt":"2025-03-11 09:33:20","video":"","vorDoi":"10.1186/s12877-026-07065-x","vorDoiUrl":"https://doi.org/10.1186/s12877-026-07065-x","workflowStages":[]},"version":"v1","identity":"rs-5992248","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5992248","identity":"rs-5992248","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}