Impact of Physical and Cognitive Frailty on Long-Term Mortality in Older Patients undergoing Elective Non-cardiac Surgery

Min-Jie Low; Zhen Yi Liau; Jun Leong Cheong; Pui San Loh; Ina Ismiarti Shariffuddin; Hui Min Khor

doi:10.4235/agmr.24.0163

Ann Geriatr Med Res > Volume 29(1); 2025 > Article

Low, Liau, Cheong, Loh, Shariffuddin, and Khor: Impact of Physical and Cognitive Frailty on Long-Term Mortality in Older Patients undergoing Elective Non-cardiac Surgery

Original Article

Annals of Geriatric Medicine and Research 2025;29(1):111-118.

Published online: January 17, 2025

DOI: https://doi.org/10.4235/agmr.24.0163

Impact of Physical and Cognitive Frailty on Long-Term Mortality in Older Patients undergoing Elective Non-cardiac Surgery

Min-Jie Low¹, Zhen Yi Liau¹, Jun Leong Cheong², Pui San Loh², Ina Ismiarti Shariffuddin², Hui Min Khor¹

¹Department of Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia

²Department of Anaesthesiology, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia

Corresponding Author: Hui Min Khor, MBBS Department of Medicine, Faculty of Medicine, Universiti Malaya, 59100 Kuala Lumpur, Malaysia
E-mail: hmkhor@ummc.edu.my

Received October 5, 2024 Revised December 31, 2024 Accepted January 11, 2025

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

Older adults undergoing surgery frequently have multiple comorbidities and reduced physical and cognitive reserves. This study aims to assess the effect of physical and cognitive frailty on long-term mortality in older patients undergoing elective non-cardiac surgery in a tertiary center.

Methods

Patients aged ≥65 years old admitted to surgical wards at the University of Malaya Medical Centre were recruited. Physical frailty and cognitive status were assessed using the Fried Frailty Index (FFI) and the Montreal Cognitive Assessment, respectively. Patients were stratified into six groups based on their frailty and cognitive status: Group 1, normal cognition and non-frail (reference group); Group 2, normal cognition and frail; Group 3, mild cognitive impairment (MCI) and non-frail; Group 4, MCI and frail; Group 5, dementia and non-frail; and Group 6, dementia and frail.

Results

A total of 406 patients with a mean FFI score of 1.1±1.2 were recruited. Predictors of mortality include male sex (hazard ratio [HR]=1.96; 95% confidence interval [CI], 1.14–3.37; p=0.015), presence of active malignancy (HR=3.86; 95% CI, 2.14–6.95; p<0.001), and high FFI scores (1.8±1.2 vs. 1.0±1.1; p=0.013). Compared to Group 1, long-term mortality risk was significantly increased in Group 4 (HR=3.17; 95% CI, 1.36–7.38) and Group 6 (HR=3.91; 95% CI, 1.62–9.43) patients.

Conclusion

The combination of physical frailty and cognitive impairment was associated with long-term mortality risk among older patients who underwent elective non-cardiac surgery. This highlights the importance of assessing physical frailty and cognitive function of all older surgical patients to guide targeted intervention, especially for those with impairments which may be potentially reversible.

Key Words: Frailty, Cognition, Surgery, Aged, Mortality

INTRODUCTION

With the population ageing and the growing expectations towards healthcare and quality of life in later years, the demand for surgical procedures amongst the older population is increasing. In England, one in five individuals aged 75 years and above underwent surgery in 2015, compared to one in 10 people aged 15–59 years.¹⁾ Surgery is often necessary for older patients and has been well proven to be beneficial in several aspects including improved life expectancy and symptom relief.²⁾ However, many of these patients are burdened with multiple comorbidities, geriatric syndromes and poorer physical and cognitive reserves. Consequently, older patients suffer from increased surgical risks, perioperative complications as well as poorer operative outcomes compared to younger patients.^2,³⁾ Multiple studies have identified specific predictors of adverse surgical outcomes in older patients, including physical frailty, cognitive ability, and preoperative functional and nutrition status.^4,⁵⁾

Conventionally, physical frailty and cognitive impairment have been studied independently, and both have proven to be significant predictors of adverse health and surgical outcomes.^6,⁷⁾ Fried et al.⁸⁾ developed and operationalised the frailty phenotype and defined frailty as a syndrome characterised by three or more of the following five criteria: unintentional weight loss, self-reported exhaustion, weakness, slowness, and low physical activity. A systematic review and meta-analysis by Panayi et al.⁷⁾ concluded that frailty is a strong predictor of post-surgical morbidity and mortality, with frail patients having approximately twice the risk of major complications and four times risk of mortality. On the other hand, older patients with cognitive impairment have an increased predisposition to developing adverse outcomes including postoperative delirium, which leads to 7-fold higher 5-year mortality risk.⁹⁾ In recent years, the understanding of frailty has expanded beyond its predominantly physical construct, leading to the advent of the concept and operational definition of cognitive frailty, which is the presence of physical frailty and mild cognitive impairment without concurrent dementia.¹⁰⁾

An increasing number of studies have demonstrated a positive association between the presence of both physical frailty and cognitive impairment with adverse health outcomes in the older population. The French Three-City Study and the Singapore Longitudinal Ageing Studies concluded that the presence of cognitive impairment and frailty in community-dwelling older adults without dementia leads to increased mortality and a higher risk of functional disability.^11,¹²⁾ In one systematic review and meta-analysis, cognitive frailty was found to be a significant predictor of all-cause mortality in community-dwelling older adults and to be better than frailty alone.¹³⁾ Recognising cognitive frailty as a heterogeneous and potentially reversible clinical syndrome is thought to improve the identification and subsequent early intervention of older patients who are at a higher risk of adverse surgical outcomes. While studies on cognitive frailty are predominantly conducted in the community, there are limited studies on older people undergoing surgery. Hence, this study aims to determine the association between physical and cognitive frailty with long-term mortality among older surgical patients undergoing elective non-cardiac surgery in a tertiary center.

MATERIALS AND METHODS

Study Design and Setting

This is a prospective cohort study which recruited patients aged 65 years and above who were admitted for elective non-cardiac surgery between August 2019 and January 2020 at the University of Malaya Medical Centre, Kuala Lumpur. The exclusion criteria included patients with emergency surgery, severe cognitive impairment, and refusal to complete the questionnaire. This study was approved by the University of Malaya Medical Research Ethics Committee (MREC ID No. 2019614-7519; ClinicalTrial.gov ID U111-1237-9788).

Clinical Characteristics

Baseline socio-demographic data, residence status, and comorbidities such as diabetes mellitus, hypertension, chronic kidney disease, active malignancy, and stroke were assessed. The diagnosis of heart diseases includes ischemic heart disease, congestive cardiac failure, and atrial fibrillation, chronic lung disease encompasses conditions such as bronchial asthma and chronic obstructive airway disease. Perioperative data including details of surgical admission ward, type of surgery, and anaesthesia, were collected. The type of surgery was classified as major or minor. Major surgeries were defined as those associated with significant intraoperative or postoperative complications, such as substantial blood loss, intensive care unit admissions, prolonged operation duration, extended hospital stay, or those involving a major body cavity. Anaesthesia type was categorised into general, regional, or local anaesthesia. Nutritional status was assessed using the Mini Nutritional Assessment-Short Form to identify the patients who have or are at risk of malnutrition.¹⁴⁾ Depression screening was conducted using the Geriatric Depression Scale.¹⁵⁾ Patient recruitment was conducted by two trained research assistants, who performed patient interviews and assessments upon 24 hours of admission to the surgical wards, during office hours.

Frailty Assessment

Frailty status was evaluated before surgery using the Fried Frailty Index (FFI),⁸⁾ which consists of five components: unintentional weight loss, self-reported exhaustion, weakness, slow walking speed, and low physical activity. The criteria used in this study have been adapted to the following cutoffs:

- Unintentional weight loss was defined as self-reported weight loss of more than 5 kg in the previous year.

- Weakness was assessed using handgrip strength measured with an electronic hand dynamometer. Patients performed the test three times with their dominant hand, and the highest value was obtained. Poor grip strength was defined as grip strength in the lowest 20% of the study population.

- Self-reported exhaustion was identified through two questions: (1) Do you feel full of energy? With a response of “No,” and (2) During the past 4 weeks, how often have you rested in bed during the day? With the response of “Every day” or “Every week.”

- Slow walking speed was assessed using the Timed Up and Go (TUG) test, with slow gait speed defined as those in the slowest 20% (TUG >19 seconds) or individuals who are unable to walk.

- Low physical activity was defined as requiring assistance from another person to perform any of the following task: shopping, walking outdoors, dressing, or toileting.

Patients with three or more of the above components were considered frail, while those with one or two components were considered pre-frail. A score of zero is considered non-frail.

Cognitive Assessment

Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA).¹⁶⁾ Based on validation studies conducted in Malaysia and Singapore,^17,¹⁸⁾ the cutoff scores were identified as 23 and above for no cognitive impairment, 16–22 for mild cognitive impairment (MCI), and 15 and below for dementia.

Assessment of Postoperative Delirium

The presence of delirium was assessed using the 4-Abbreviation Test (4AT), where patients were screened daily from day 0 to day 5 (or day of discharge, whichever came first) postoperatively. The 4AT contains four items: alertness, the Abbreviated Mental Test 4 (AMT4), attention, and acute change or fluctuating course. The score ranges from 0–12: scores ≥4 are considered positive for delirium, scores 1–3 indicate possible cognitive impairment, and score 0 suggest delirium or severe cognitive impairment is unlikely.¹⁹⁾ Postoperative delirium is identified if the patient scores ≥4 on the 4AT on any of the assessment days.

Outcome Measures

Post-discharge mortality data was collected up to December 31, 2021 from the National Death Registry Department after recruitment, from which 1-year mortality and overall mortality were calculated.

Statistical Analyses

The IBM SPSS Statistics version 27.0 (IBM, Armonk, NY, USA) was used for data analyses. Descriptive statistics were generated for all variables, with continuous variables presented as mean±standard deviation and categorical variables as frequency and percentage. The Cox proportional hazards model was employed to identify potential confounding factors influencing survival outcomes. Multivariate logistic regression was done after eliminating variables with p≥0.1 to determine strong predictors of mortality. Patients were then stratified into six groups based on the combination of their physical frailty and cognitive status. Physical frailty has been dichotomized to either frail (pre-frail and frail patients) or non-frail. Cognitive status was identified as either normal cognition, mild cognitive impairment, or dementia. The hazard ratio and survival rates of these six groups were then evaluated, which include Group 1, normal cognition and non-frail; Group 2, normal cognition and frail; Group 3, MCI and non-frail; Group 4, MCI and frail; Group 5, dementia and non-frail; and Group 6, dementia and frail. Group 4 patients were also classified as having cognitive frailty according to the definition from the International Academy on Nutrition and Aging and the International Association of Gerontology and Geriatrics.¹⁰⁾

RESULTS

A total of 514 patients were admitted for elective surgery during the study period. Of those, 109 did not meet the inclusion criteria (Fig. 1). As a result, 406 patients were included in the analysis. Demographic and clinical characteristics of the patients are shown in Table 1. The mean age of the patients was 75.1±5.8 years, and 219 (53.9%) were women. The majority of patients were from the general orthopaedic ward (25.6%), followed by general surgery (23.4%) and ophthalmology (20.2%). More than half of the patients underwent general anaesthesia (n=218; 53.7%) during surgery. The mean MoCA score was 20.4±5.8 among all the patients. Using the FFI, 56 (13.8%) patients were found to be frail, 185 (45.6%) pre-frail, and 165 (40.6%) non-frail.

The median follow-up of patients who were living was 806 days (interquartile range [IQR], 763–835), and of deceased patients was 344 days (IQR, 108–509). The 1-year mortality rate was 8.6% (n=35) with a total of 63 deaths at the end of the study period. Table 2 highlights the significant predictors of long-term mortality following elective surgery. From the adjusted Cox proportional hazard analysis, men (hazard ratio [HR]=1.96; 95% confidence interval [CI], 1.14–3.37; p=0.015), the presence of malignancy (HR=3.86; 95% CI, 2.14–6.95; p<0.001) and physical frailty (HR=1.38; 95% CI, 1.07–1.77; p=0.013) were independent predictors of long-term mortality.

Patients were categorized into six groups with different combinations of physical and cognitive status as shown in Table 3. The largest patient group comprised individuals with MCI and frailty, accounting for 24.9%, whilst the smallest group included patients with dementia but no frailty, representing 4.18%. Patients with MCI and frailty had a high risk of mortality (HR=3.17; 95% CI, 1.36–7.38; p<0.01), as were patients with dementia and frailty (HR=3.91; 95% CI, 1.62–9.43; p<0.01). After adjusting for the type of surgery these two groups remained predictive of mortality, despite an attenuation in risk as shown in Table 3. On the other hand, following the inclusion of other confounders of mortality, specifically sex and the presence of malignancy, Group 4 (MCI and frail), Group 5 (dementia and non-frail), and Group 6 (dementia and frail) demonstrated a stepwise increase in risk. Notably, none of the Group 5 patients underwent major surgery. The differences in survival between groups with different combinations of cognitive and frailty status are illustrated in Fig. 2.

DISCUSSION

More than half of the patients in this study were either pre-frail or frail. This study demonstrated that the effect of physical frailty was more pronounced when it coexisted with cognitive impairment, resulting in higher mortality risk in patients with mild cognitive impairment and dementia but not in those with normal cognition. Patients with cognitive frailty represented the largest category in the study with increased long-term mortality, followed by the cohort with dementia and frailty, which was considered the most vulnerable group of patients in this study.

Cognitive impairment is known to contribute to poor surgical outcomes, including mortality, though most study factors were determined as moderate to severe cognitive impairment.^20,²¹⁾ Recent studies have shown an inter-relationship between frailty and cognitive decline. Buchman et al. found that common neuropathologies (e.g., Alzheimer disease pathology, macroinfarcts, and nigral neuronal loss) contribute to progressive physical frailty in old age, even in individuals who were not clinically diagnosed with dementia, Parkinson disease, or stroke.²²⁾ The effects of physical frailty on cognitive function were also demonstrated in several studies.^23-²⁵⁾ Our findings corroborate with results from longitudinal studies conducted across three continents: France, Singapore, and Peru, which showed that the presence of both cognitive impairment and cognitive frailty was a stronger predictor of mortality than either condition alone.^11,^12,²⁶⁾

Similar observations were reported in a prospective study by Makhani et al.²⁷⁾ on 330 surgical patients undergoing major surgery, which demonstrated a four times higher risk of death and poorer survival in patients with both physical frailty and cognitive impairment compared to robust patients. Additionally, a recent study on a Chinese population undergoing elective orthopaedic or abdominal surgery under general anaesthesia showed that patients with cognitive frailty had the highest risk of postoperative complications, mobility disability, and prolonged hospitalisation, regardless of the type of surgery.²⁸⁾ In comparison, our study, which included a larger population of cognitive frailty patients across various surgical specialties, identified cognitive frailty as a significant predictor of mortality, even after adjusting for type of surgery, sex, and the presence of malignancy. Similarly, a study by Itagaki et al.²⁹⁾ investigating other adverse outcomes, such as postoperative delirium, found that the risk was higher in patients with cognitive frailty, whereas patients with mild cognitive impairment but without physical functional decline did not develop postoperative delirium. As manifestations of mild cognitive impairment are oftentimes subtle and prone to be underdiagnosed by attending doctors, this stresses the importance of comprehensive preoperative cognitive and frailty assessments to identify this vulnerable group of older patients so that interventions can be done to minimise adverse surgical outcomes. Preoperative assessments during outpatient clinic reviews provide an opportunity to identify individuals at risk and implement appropriate interventions

Our analysis found that the male sex and presence of active malignancy were significant predictors of mortality. The sex discrepancy in mortality that has been observed in the past century is multifactorial in nature—greater predisposition to cardiovascular diseases and preponderance of male smokers, comparatively passive health-seeking behavior such as indifference towards health problems, delay in seeking treatment, and poorer compliance to treatment, on top of other biopsychosocial differences.^30,³¹⁾ This reflects the need for a more global approach in public health policies to address such differences. Active malignancy and malignancy-related complications necessitate surgery in over one-fifth of our patients. Its impact on perioperative mortality differs with specific patient and disease factors, though advanced disease and low to lower-middle income status generally contribute to poorer outcomes.³²⁾

The implication of this study lies in identifying high-risk groups among older surgical patients through physical and cognitive functional assessments that are feasible to carry out in day-to-day ward practice. This lays the foundation for patient-centred perioperative care, whilst advocating objective and systematic decision-making in the context of healthcare resource allocation, especially in a developing country such as Malaysia, where manpower and funding are limited. Management to optimise cognitive and physical reserve of older surgical patients involves a multidisciplinary team consisting of the primary attending doctor, geriatricians, physiotherapists and dietitians, as well as multimodal intervention which includes multicomponent exercise programmes, cognitive training and nutritional supplementation.^33-³⁶⁾ Published and ongoing studies evaluate the benefits and effectiveness of these interventions to reduce cognitive frailty among community-dwelling seniors, though future studies should seek to better apply these interventions in the geriatric preoperative setting such that patients can be better prepared for surgery. Furthermore, research is also yet to establish better strategies to assess and identify cognitive frailty, as well as the reversibility of cognitive frailty, an increasingly important clinical question with the emergence of more evidenced-based intervention models.

This study has several strengths and limitations. Firstly, one of the strengths is having a considerably large cohort of patients, which reduces margins of error and enhances reliability of the findings. Secondly, despite being a single-centre study, the study population reflects a unique group of older surgical patients due to their multiracial and multilingual backgrounds, as well as the diversity of elective surgeries included. That said, being conducted in a tertiary center, this study may be less generalizable to local, more resource-limited institutions. Patients who were unable to ambulate were included in the study by identifying them as positive for slowness in the FFI. While immobility is a strong indicator of an older patient’s physical frailty status, this subjects the study to some degree of selection bias. Lastly, the study population was limited to elective surgeries with a significant proportion of patients undergoing ophthalmology procedures, which are less invasive compared to other surgical procedures. This may have introduced selection bias in the patient population, although efforts were made to analyse the data by adjusting for the type of surgery performed.

In conclusion, the combination of physical and cognitive frailty was strongly associated with long-term mortality among older patients who underwent surgery, with greater predictive value compared to cognitive or physical status alone. This study emphasizes the importance of comprehensive geriatric assessment of physical frailty and cognitive function for all older patients undergoing surgery to guide the prehabilitation efforts and improve surgical outcomes. Identifying these potentially reversible factors early can help optimize preoperative care, reduce risk of postoperative complications and long-term adverse outcomes.

ACKNOWLEDGMENTS

The authors are grateful to all the patients who participated in the research study.

CONFLICT OF INTEREST

The researchers claim no conflicts of interest.

FUNDING

The study was funded by the UMSC Care Grant (Grant No. UMG012C-2022).

AUTHOR CONTRIBUTIONS

Conceptualization, JLC; Data curation, MJL, ZYL; Funding acquisition, HMK; Investigation, PSL, IIS, JLC; Methodology, PSL, JLC; Project administration, JLC; Supervision, PSL,HMK; Writing–original draft, MJL, ZYL; Writing–review & editing, HMK, IIS.

Fig. 1.

Flow diagram of patient selection.

Fig. 2.

Survival curves for 6 different patient groups of combined cognitive and physical status. The number of patients at risk for each category is indicated at the bottom. MCI, mild cognitive impairment.

Table 1.

Demographic and clinical characteristics of participants

Variable	Value
Age (y)	75.1±5.8
Sex
Female	219 (53.9)
Male	187 (46.1)
Ethnicity
Malay	96 (23.7)
Chinese	223 (54.9)
Indian	83 (20.4)
Others	4 (1.0)
Residence
Living alone	29 (7.1)
Living with family	374 (92.1)
Nursing home	3 (0.7)
Comorbidities
Diabetes mellitus	162 (39.9)
Hypertension	292 (71.9)
Chronic kidney disease	48 (11.8)
Heart disease	105 (25.9)
Chronic lung disease	31 (7.6)
Malignancy	91 (22.4)
Stroke	28 (6.9)
Surgical admission unit
General surgery	95 (23.4)
Orthopaedic surgery	104 (25.6)
Vascular surgery	15 (3.7)
Urology	68 (16.7)
Ophthalmology	82 (20.2)
Gynaecology	19 (4.7)
ENT	23 (5.7)
Type of surgery
Minor	112 (27.6)
Major	294 (72.4)
Anaesthetic type
General anaesthesia	218 (53.7)
Regional	101 (24.9)
Local (including peripheral nerve block)	87 (21.4)
Postoperative delirium	36 (8.9)
FFI	1.1±1.2
Frailty category
Non-frail	165 (40.6)
Pre-frail	185 (45.6)
Frail	56 (13.8)
MOCA	20.4±5.8
MNA	11.4±2.8
GDS	3.5±2.8

Values are presented as mean±standard deviation or number (%).

ENT, ear, nose and throat; FFI, Fried Frailty Index; TUG, Timed Up and Go; MoCA, Montreal Cognitive Assessment; MNA, Mini Nutritional Assessment; GDS, Geriatric Depression Scale.

Table 2.

Predictors of mortality in older patients who underwent elective surgery

Variable	Alive	Dead	Unadjusted HR (95% CI)	p-value	Adjusted HR (95% CI)	p-value
Overall	343 (84.5)	63 (15.5)
Age (y)	75.1±5.8	75.2±5.9	1.00 (0.96–1.05)	0.852
Sex
Female	194 (56.6)	25 (39.7)	Reference
Male	149 (43.4)	38 (60.3)	1.84 (1.11–3.04)	0.018	1.96 (1.14–3.37)	0.015
Ethnicity
Malay	81 (23.6)	15 (23.8)	Reference
Chinese	185 (53.9)	38 (60.3)	1.11 (0.61–2.02)	0.732
Indian	73 (21.3)	10 (15.9)	0.76 (0.34–1.69)	0.499
Others	4 (1.2)	0 (0)
Residence
Nursing home	2 (0.6)	1 (1.6)	Reference
Living alone	23 (6.7)	6 (9.5)	0.63 (0.08–5.21)	0.665
Living with family	318 (92.7)	56 (88.9)	0.44 (0.06–3.21)	0.421
Comorbidities
Diabetes mellitus	135 (39.4)	27 (42.9)	1.15 (0.70–1.89)	0.588
Hypertension	245 (71.4)	47 (74.6)	1.19 (0.68–2.10)	0.543
Chronic kidney disease	35 (10.2)	13 (20.6)	2.07 (1.13–3.82)	0.019	1.52 (0.72–3.23)	0.270
Heart disease	89 (25.9)	16 (25.4)	0.98 (0.56–1.73)	0.950
Chronic lung disease	26 (7.6)	5 (7.9)	1.00 (0.40–2.50)	0.994
Malignancy	79 (23.0)	33 (52.4)	3.07 (1.86–5.04)	<0.001	3.86 (2.14–6.95)	<0.001
Stroke	21 (6.1)	7 (11.1)	1.85 (0.84–4.06)	0.126
Surgical admission unit
General surgery	80 (23.3)	15 (23.8)	1.03 (0.58–1.85)	0.900
Orthopedic surgery	84 (24.5)	20 (31.7)	1.43 (0.84–2.43)	0.189
Vascular surgery	10 (2.9)	5 (7.9)	2.36 (0.95–5.89)	0.065	2.79 (0.87–9.00)	0.09
Urology	56 (16.3)	12 (19.0)	1.16 (0.62–2.17)	0.646
Ophthalmology	75 (21.9)	7 (11.1)	0.47 (0.21–1.02)	0.056	0.76 (0.31–1.88)	0.550
Gynaecology	15 (4.4)	4 (6.3)	1.42 (0.52–3.91)	0.497
ENT	23 (6.7)	0 (0)	0.05 (0.00–4.33)	0.183
Type of surgery
Minor	255 (74.3)	39 (61.9)	Reference
Major	88 (25.7)	24 (38.1)	1.71 (1.03–2.84)	0.039	0.74 (0.38–1.43)	0.373
Anaesthetic type
General anaesthesia	182 (53.1)	36 (57.1)	1.16 (0.70–1.91)	0.564
Regional	83 (24.2)	18 (28.6)	1.25 (0.73–2.16)	0.419
Other anaesthesia	78 (22.7)	9 (14.3)	0.58 (0.29–1.18)	0.132
FFI	1.0±1.1	1.8±1.2	1.65 (1.37–2.00)	<0.001	1.38 (1.07–1.77)	0.013
MOCA	20.8±5.7	18.3±6.2	0.94 (0.90–0.98)	0.001	0.97 (0.93–1.02)	0.212
Postoperative delirium	25 (7.3)	11 (17.5)	2.35 (1.23–4.51)	0.010	1.11 (0.52–2.38)	0.783
MNA	11.6±2.5	9.8±3.4	0.81 (0.75–0.88)	<0.001	0.94 (0.84–1.04)	0.229
GDS	3.2±2.7	4.6±2.7	1.15 (1.07–1.24)	<0.001	1.05 (0.96–1.16)	0.270

Values are presented as number (%) or mean±standard deviation.

ENT, ear, nose and throat; FFI, Fried Frailty Index; MoCA, Montreal Cognitive Assessment; MNA, Mini Nutritional Assessment; GDS, Geriatric Depression Scale; HR, hazard ratio; CI, confidence interval.

Bold font indicates statistical significance (p<0.05).

Table 3.

Hazard ratio of cognitive function and frailty status of different patient groups

Patient group category	Unadjusted	Model 1	Model 2
Patient group category	HR (95% CI)	HR (95% CI)	HR (95% CI)
Group 1. Normal cognition + non-frail	Reference	Reference	Reference
Group 2. Normal cognition + frail	1.62 (0.62–4.25)	1.57 (0.60–4.12)	1.91 (0.72–5.04)
Group 3. MCI + non-frail	0.64 (0.17–2.47)	0.65 (0.17–2.52)	0.72 (0.19–2.80)
Group 4. MCI + frail (cognitive frailty)	3.17 (1.36–7.38)	3.05 (1.31–7.11)	3.61 (1.54–8.47)
Group 5. Dementia + non-frail	2.37 (0.61–9.18)	2.66 (0.68–10.41)	4.60 (1.15–18.45)
Group 6. Dementia + frail	3.91 (1.62–9.43)	3.71 (1.53–8.97)	4.82 (1.99–11.71)

MCI, mild cognitive impairment; HR, hazard ratio; CI, confidence interval.

Model 1, adjusted with type of surgery; Model 2, adjusted with type of surgery, male sex and presence of malignancy.

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