Cognitive frailty predicting death and disability in Chinese elderly

Association between malnutrition and cognitive frailty in older adults: A systematic review and meta-analysis

BACKGROUND

To systematically assess the association between cognitive frailty (CF) and malnutrition in older adults.

METHODS

8 databases were retrieved up until April 2023 by two reviewers in dependently, and meta-analysis was performed by Stata 16.0 software.

RESULTS

A total of 19 studies were meta-analyzed to assess the relationship between CF and malnutrition in older adults. The pooled prevalence of CF from 17 studies was 23 %, and the pooled prevalence of malnutrition among patients with CF from 12 studies was 57 %. Data from 13 studies on the association between CF and malnutrition unveiled a high risk of CF in older adults with malnutrition (OR = 3.77, 95 % CI: 2.49-5.69).

CONCLUSION

The prevalence of malnutrition is high in older adults with CF, and there is a significant delve into targeted treatment and preventive measures to ameliorate the quality of life of older adults.

Prevalence of cognitive frailty and its associated factors in a population of Iranian older adults

BACKGROUND

In recent years cognitive frailty has emerged as an important predictor of adverse health outcomes in older adults. Herein, we aimed to investigate the prevalence and associated factors of cognitive frailty in a population of community-dwelling older adults in Iran.

METHOD

This cross-sectional study was conducted as part of the second cycle of the Amirkola Health and Aging Project (AHAP). Physical frailty and cognitive impairment were evaluated using the FRAIL questionnaire and the mini-mental state examination (MMSE) respectively. Cognitive frailty was defined as co-existence of frailty and cognitive impairment without presence of dementia. Depression and disability were assessed using the Persian version of geriatric depression scale (GDS) and instrumental activities of daily living (IADL) questionnaire.

RESULTS

Overall 1775 individuals (47.1% female) with mean age of 69.7 ± 7.3 years were included in the final analysis. The prevalence of cognitive frailty was 12.0%. The prevalence of cognitive frailty among males and females was 4.3% and 20.7%, respectively. After adjusting for all possible confounders through binary logistic regression analysis, factors such as older age (OR 1.06, CI 1.03-1.09), female gender (OR 2.25, CI 1.42-3.57), illiteracy (OR 3.84, CI 2.03-8.29), more comorbidities (OR 1.21, CI 1.12-1.31), depression (OR 2.01, CI 1.40-2.86), and greater IADL disability (OR 1.68, CI 1.44-3.96), were independently and significantly associated with cognitive frailty.

CONCLUSION

In this population of Iranian older adults, prevalence of cognitive frailty was consistent with its estimated mean global prevalence. Age, gender, illiteracy, comorbidities, depression and IADL disability were associated with cognitive frailty. Further research is required to develop screening tools and prevention strategies.

Development and validation of a nomogram for predicting cognitive frailty in patients on maintenance haemodialysis

AIMS

This study aimed to construct a nomogram for predicting the risk of cognitive frailty in patients on maintenance haemodialysis.

DESIGN

An explorative cross-sectional design was adopted.

METHODS

From April 2022 to July 2022, 496 participants were recruited from five haemodialysis centres in Qingdao, Shandong Province, China. Participants with cognitive frailty were screened by Frailty Phenotype scale and Mini-Mental State Examination. Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate logistic regression were utilized to determine predictors. The predictive performance of the nomogram was validated by calibration and discrimination. Decision curve analysis was used to assess clinical utility. Internal validation was implemented using 1000 bootstrap samples to mitigate overfitting.

RESULTS

The prevalence of cognitive frailty was 17.5% (n = 87). Six risk predictors, namely health empowerment, alexithymia, age, educational level, marital status and dialysis vintage, were screened and used to develop a nomogram model. The nomogram had satisfactory discrimination and calibration, and decision curve analysis revealed considerable clinical utility.

CONCLUSIONS

A nomogram incorporated with the six risk predictors was developed, and it exhibited excellent prediction performance. The nomogram may strengthen the effective screening of patients at high risk of cognitive frailty.

IMPACT

This study established a tool for healthcare staff to predict cognitive frailty probability and identify risk factors in patients on maintenance haemodialysis. The nomogram can meet the needs of personalized care and precision medicine simultaneously.

PATIENT OR PUBLIC CONTRIBUTION

Data were collected from patients on maintenance haemodialysis by using questionnaire survey.

REPORTING METHOD

STROBE checklist was used.

Prediction Model for Cognitive Impairment among Disabled Older Adults: A Development and Validation Study

Disabled older adults exhibited a higher risk for cognitive impairment. Early identification is crucial in alleviating the disease burden. This study aims to develop and validate a prediction model for identifying cognitive impairment among disabled older adults. A total of 2138, 501, and 746 participants were included in the development set and two external validation sets. Logistic regression, support vector machine, random forest, and XGBoost were introduced to develop the prediction model. A nomogram was further established to demonstrate the prediction model directly and vividly. Logistic regression exhibited better predictive performance on the test set with an area under the curve of 0.875. It maintained a high level of precision (0.808), specification (0.788), sensitivity (0.770), and F1-score (0.788) compared with the machine learning models. We further simplified and established a nomogram based on the logistic regression, comprising five variables: age, daily living activities, instrumental activity of daily living, hearing impairment, and visual impairment. The areas under the curve of the nomogram were 0.871, 0.825, and 0.863 in the internal and two external validation sets, respectively. This nomogram effectively identifies the risk of cognitive impairment in disabled older adults.

Risk factors and a nomogram for predicting cognitive frailty in Chinese patients with lung cancer receiving drug therapy: A single-center cross-sectional study

BACKGROUND

To identify independent factors of cognitive frailty (CF) and construct a nomogram to predict cognitive frailty risk in patients with lung cancer receiving drug therapy.

METHODS

In this cross-sectional study, patients with lung cancer undergoing drug therapy from October 2022 to July 2023 were enrolled. The data collected includes general demographic characteristics, clinical data characteristics and assessment of tools for cognitive frailty and other factors. Logistic regression was harnessed to determine the influencing factors, R software was used to establish a nomogram model to predict the risk of cognitive frailty. The enhanced bootstrap method was employed for internal verification of the model. The performance of the nomogram was evaluated by using calibration curves, the area under the receiver operating characteristic curve, and decision curve analysis.

RESULTS

A total of 372 patients were recruited, with a cognitive frailty prevalence of 56.2%. Age, education background, diabetes mellitus, insomnia, sarcopenia, and nutrition status were identified as independent factors. Then, a nomogram model was constructed and patients were classified into high- and low-risk groups with a cutoff value of 0.552. The internal validation results revealed good concordance, calibration and discrimination. The decision curve analysis presented prominent clinical utility.

CONCLUSIONS

The prevalence of cognitive frailty was higher in lung cancer patients receiving drug therapy. The nomogram could identify the risk of cognitive frailty intuitively and simply in patients with lung cancer, so as to provide references for early screening and intervention for cognitive frailty at the early phases of drug treatment.

Risk factors of cognitive frailty in elderly chronic obstructive pulmonary disease patients and its implication for death: a cohort study

BACKGROUNDS

Cognitive frailty, a clinical syndrome with physical frailty and cognitive impairment, leads to mortality and other adverse health outcomes in older adults. This study aimed to investigate the prevalence of cognitive frailty, and its influencing factors, and follow its impact on short-term mortality in elderly chronic obstructive pulmonary disease patients, to provide a theoretical scientific reference basis for clinical intervention and management of cognitive frailty.

METHODS

A sample of 243 elderly chronic obstructive pulmonary disease patients in the respiratory department of a tertiary care hospital was conveniently sampled from November 2021 to February 2023, and the prevalence of cognitive frailty was investigated using the General Information Survey Scale, the Fried Phenotype Scale, the Mini-Mental State Examination, the Anxiety Self-Rating Scale, the Brief Geriatric Depression Scale, and the Mortality Record. The mortality was recorded by telephone follow-up after 6 months. A database was created and statistical analysis such as one-way analysis of variance, logistic regression analysis, Kaplan-Meier, and Cox survival analysis were used to analyze the data.

RESULTS

A total of 47 patients (19.3%) had cognitive frailty; there were statistical differences in the prevalence of cognitive frailty by medical payment type, physical exercise, and sleeping time (P < 0.05). During a 6-month follow-up, 38 patients (15.6%) died. Cox survival analysis showed that the risk of death in elderly chronic obstructive pulmonary disease patients in the cognitive frailty group was 3.212 times higher than that in the normal cognitive function and non-frailty group (95% CI 1.646-6.270, P = 0.001), and 5.266 times higher than that in the normal cognitive function and frailty group (95% CI 3.159-8.778, P < 0.001).

CONCLUSIONS

The prevalence of cognitive frailty in elderly chronic obstructive pulmonary disease patients is high, and clinical staff should pay attention to patients' medical burden and financial ability, and reduce the incidence of cognitive frailty by instructing patients to perform physical exercise and arrange sleep time. Cognitive frailty is an important risk factor for mortality within 6 months in elderly chronic obstructive pulmonary disease patients, and early intervention should be emphasised to reduce or delay cognitive frailty and mortality.

Relationship Between Cognitive Frailty and Mortality in Older Adults: A Systematic Review and Meta-Analysis

OBJECTIVE

To synthesize the pooled mortality risk estimate and determine whether cognitive frailty is a predictor of mortality.

DESIGN

A systematic review and meta-analysis.

SETTING AND PARTICIPANTS

The participants were community-dwelling older adults aged ≥60 years.

METHODS

PubMed, Web of Science, Embase, CINAHL, and the Cochrane Library databases were systematically searched. Two researchers independently screened potentially eligible literature, evaluated the quality of the included studies, and then extracted the data. We used STATA, version 15.0 to perform the all data.

RESULTS

Nineteen studies were included. The association between cognitive frailty and a higher risk of death was statistically significant [hazard ratio (HR), 2.01; 95% CI, 1.84-2.19; P < .001]. The outcomes indicated that cognitive frailty was a critical risk factor for predicting mortality (OR, 4.82; 95% CI, 1.59-14.57; P < .01). Based on different models of cognitive frailty, the results of subgroup analyses revealed that the risk of mortality was the highest in the Frail + mild cognitive impairment group (HR, 2.35; 95% CI, 2.05-2.70; P < .001). The subgroup analyses by region demonstrated that mortality risk was lowest in the European group (HR, 1.63; 95% CI, 1.4-1.87; P < .001).

CONCLUSIONS AND IMPLICATIONS

This study quantitatively portrays the pooled mortality risk estimate of cognitive frailty. The results suggest that in older adults, cognitive frailty can be a predictor of mortality. The findings could alert health care providers to pay more attention to cognitive frailty.

Prevalence and risk factors of cognitive frailty in community-dwelling older adults with diabetes: A systematic review and meta-analysis

AIMS

Cognitive frailty can increase the risk of adverse health outcomes in older adults. Estimates of the prevalence of cognitive frailty among older adults with diabetes varied widely in literature. This study aimed to conduct a systematic review and meta-analysis to assess the pooled prevalence of cognitive frailty and risk factors in community-dwelling older adults with diabetes, providing evidence for healthcare professionals to better understand the status of cognitive frailty and help develop effective interventions.

METHODS

Databases of PubMed, Web of Science, Cochrane Library, Embase, Cumulative Index of Nursing and Allied Health, Proquest, China National Knowledge Infrastructure and China Biology Medicine were searched from inception to February 10th, 2022. The reviewers independently selected studies, extracted data and assessed the quality of studies. Pooled prevalence of cognitive frailty and risk factors were estimated. Subgroup analysis, meta-regression analysis, sensitivity analysis and publication bias were also conducted.

RESULTS

A total of 15 studies with 6391 participants were included in this review. The pooled prevalence of cognitive frailty was 11% (95%CI = 7.9-14%) in community-dwelling older adults with diabetes. Pooled estimates showed that increasing age, higher level of HbA1c, shorter night sleep duration and depression were risk factors, and regular exercise was the protective factor of cognitive frailty in community-dwelling older adults with diabetes.

CONCLUSION

Cognitive frailty was common in community-dwelling older adults with diabetes. Routine screening of cognitive frailty and effective interventions should be implemented for this population in community settings.

REGISTRATION

PROSPERO ID CRD42021276973.

Institutional Residence Protects Against Cognitive Frailty: A Cross-Sectional Study

Based on the complex aging background, more and more older people have to live in an institution in later life in China. The prevalence of cognitive frailty (CF) is more higher in institutions than in communities. Rarely studies were conducted on the relationship between institutional residence and CF. Hence, this study were performed to determine the relationship between institutional residence (living in a nursing home) and CF in older adults. A total of 1004 older community residents and 111 older nursing home residents over 50 years of age from Hefei, Anhui Province, China were recruited. CF included physical frailty (PF) and mild cognitive impairment (MCI). PF was assessed using the Chinese version of the Fried frailty scale, MCI was assessed using the Montreal Cognitive Assessment, and the common associated factors including sedentary behavior, exercise, intellectual activity, comorbidity, medication, chronic pain, sleep disorders, nutritional status and loneliness were analyzed using regression logistic models. Multivariate regression logistic analysis showed that exercise (P = .019, odds ratio [OR] = 0.494, 95% confidence interval [CI]: 0.274-0.891), intellectual activity (P = .019, OR = 0.595, 95% CI: 0.380-0.932), medication use (P = .003, OR = 2.388, 95% CI: 1.339-4.258), chronic pain (P = .003, OR = 1.580, 95% CI: 1.013-2.465) and loneliness (P = .000, OR = 2.991, 95% CI: 1.728-5.175) were significantly associated with CF in community residents; however, only sedentary behavior (P = .013, OR = 3.851, 95% CI: 1.328-11.170) was significantly associated with CF in nursing home residents. Our findings suggest that nursing homes can effectively address many common risk factors for CF, including lack of exercise and intellectual activity, medication use, chronic pain, and loneliness, better than the community setting. Thus, residing in a nursing home is conducive to the intervention of CF.

Unhealthy oral status contributes to the older patients with cognitive frailty: an analysis based on a 5-year database

BACKGROUND

Oral health is associated with the onset and deterioration of cognitive function and physical frailty, which can be improved with appropriate interventions. However, far too little attention has been paid to oral health status of elderly with cognitive frailty. The objective of this study was to investigate the oral health status and potential risk factors of elderly hospitalized patients aged 60 years or older with cognitive frailty.

METHODS

The participants' assessment data derived from the Comprehensive Geriatric Assessment Database of hospitalized patients from The First Affiliated Hospital of Chongqing Medical University. Data were collected from April 2016 to December 2021. All participants underwent a face-to-face assessment conducted by professional evaluators. Physical frailty was defined by Fried's criteria. Cognitive function was assessed by Mini Mental State Examination (MMSE). The cognitive frailty is characterized by the simultaneous presence of at least 1 Fried's criteria and mild cognitive impairment according to Diagnostic and Statistical Manual of Mental Disorders 5th edition. The oral health was assessed according to 10-item Brief Oral Health Status Examination (BOHSE). The general demographic characteristics, BOHSE scores were compared between the cognitive frailty and non-cognitive frailty (control group). The score of BOHSE and ten items were included in the binary logistic regression analysis. The covariate characteristics were adjusted for a final model with a multivariate analysis.

RESULTS

A total of 425 patients (245 females) with cognitive frailty and 491 patients (283 females) with non-cognitive frailty were enrolled in this retrospective study. Univariate analysis showed statistically significant differences in age, education level, living arrangement, diabetes, Body Mass Index (BMI), Pittsburgh Sleep Quality Index (PSQI), depression between the two groups. The total BOHSE score of cognitive frailty was higher than that of the control group (4.35 ± 2.68 vs. 3.64 ± 2.60, Z = 4.07, P < 0.001). The average scores and the proportions of health changes and unhealthy states of tongue, mucosa tissue, gums, natural teeth, dentures, masticatory teeth and oral hygiene in cognitive frailty were greater than those of the control group (all P < 0.05). The binary logistical regression analysis showed that four or more natural teeth decayed or broken was independently associated with cognitive frailty after adjusting the age, gender, education level, living arrangement and BMI, PSQI, diabetes and depression (OR = 1.91, 95%CI: 1.20-3.07, P = 0.007). Additionally, while in the chewing position, those cases with a normal-occlusal-relationship number of less than 11 pairs had a higher risk of cognitive frailty than those with 12 pairs or more.

CONCLUSIONS

The oral health status of older hospitalized patients over 60 years with cognitive frailty was worse than that of patients with non-cognitive frailty. But only four or more natural teeth decayed or broken and a reduction in chewing pairs were independent risk factors for cognitive frailty.

Prevalence and possible factors of cognitive frailty in the elderly with hypertension and diabetes

BACKGROUND

Cognitive frailty is the coexistence of physical frailty and mild cognitive impairment. Research shows that cognitive frailty is related to an increased risk of hospitalization, mortality, disability, and dementia. Diabetes and hypertension are common risk factors for physical frailty and cognitive impairment. However, the factors influencing cognitive frailty in the elderly with hypertension and diabetes are still unclear. This study aimed to investigate the possible factors influencing cognitive frailty in the elderly with hypertension and diabetes.

METHODS

A cross-sectional study was conducted. We evaluated people over 60 years with hypertension and diabetes who underwent physical examination in Wuxi Xin'an Community Health Service Center. Frail scale, Montreal Cognitive Assessment-Basic and clinical dementia rating were used to assess cognitive frailty. We collected demographic characteristics, hypertension and diabetes-related laboratory indicators of the participants. We also used various scales to assess the overall health status of the elderly.

RESULTS

Approximately 20.8% of the participants were determined to have cognitive frailty in elderly adults with hypertension and diabetes. These participants were older, had a lower monthly income, and included a higher proportion of peasants. They also had a higher level of depression (p = 0.037), higher risk of falls (p = 0.000), higher risk of malnutrition (p = 0.002), poorer ability to perform activities of daily living (ADL) (p = 0.000), and less social support (p = 0.030). Multivariate regression analysis was used to further assess the factors for cognitive frailty. After adjusting for possible confounders, age and ADL score emerged as risk factors, whereas high monthly income decreased the risk of cognitive frailty.

CONCLUSION

Cognitive frailty is correlated with age, income, and ability to perform daily living activities in the elderly with diabetes and hypertension. Closer attention to the elderly who have low income and poor self-care ability may play an important role in the early prevention of cognitive frailty and even dementia.

Comparison of the prevalence and associated factors of cognitive frailty between elderly and middle-young patients receiving maintenance hemodialysis

PURPOSE

This study aimed at comparing the prevalence of cognitive frailty and explore the differences in the influencing factors between elderly and middle-young patients receiving maintenance hemodialysis (MHD).

METHODS

In this cross-sectional study, the frailty phenotype, mini-mental state examination, and clinical dementia rating were used to assess the current status of cognitive frailty in 852 patients receiving MHD from four hospitals in Lianyungang City and Xuzhou City, Jiangsu Province, China; the influencing factors were then analyzed for statistical significance.

RESULTS

Of the total 852 patients receiving MHD, 340 were classified into an elderly group (≥ 60 years) and 512 into a middle-young group (< 60 years). The prevalence of cognitive frailty was 35.9% and 8.8%, respectively. The results of multivariate logistic regression analysis showed that the independent factors of cognitive frailty were age (P < 0.001), education level (P = 0.010), nutritional status (P = 0.001), serum albumin level (P = 0.010), calf circumference (P = 0.024), and social support level (P < 0.001) in the elderly group and comorbidity status (P = 0.037), education level (P < 0.001), nutritional status (P = 0.008), serum creatinine level (P = 0.001), waist circumference (P < 0.001), and depression (P = 0.006) in the middle-young group.

CONCLUSION

The prevalence of cognitive frailty was significantly higher in the elderly group than in the middle-young group, and the influencing factors differed between the two populations.

Association between Cognitive Frailty and Adverse Outcomes among Older Adults: A Meta-Analysis

OBJECTIVES

This systematic review and meta-analysis aimed to pool the effect size of the association between cognitive frailty and adverse outcomes (e.g., falls, disability, and hospitalization) among older adults.

DESIGN

Systematic review and meta-analysis.

METHODS

PubMed, ScienceDirect, and Embase were searched from their respective inceptions to June 1, 2022. We extracted prospective cohort studies that reported the association between cognitive frailty and adverse outcomes. Random or fixed-effects models based on heterogeneity were used to pool the effect sizes of independent associations of cognitive frailty, frailty only, and cognitive impairment only with each adverse outcome.

RESULTS

Fifteen studies involving 49,122 older adults were included in the meta-analysis. Older adults with cognitive frailty had higher odds ratios (OR) for falls (1.82, 95% confidence interval [CI]: 1.29-2.58), disability (3.17, 95%CI: 2.24-4.48), and hospitalization (1.78, 95%CI: 1.48-2.14) compared with those without frailty and cognitive impairment. Older adults with frailty only demonstrated a high risk for falls (pooled OR 1.76, 95%CI: 1.25-2.48), disability (pooled OR 1.82, 95%CI: 1.43-2.33), and hospitalization (pooled OR 1.64, 95% CI: 1.45-1.85). The influence of cognitive impairment only on adverse outcomes was lower compared with cognitive frailty or frailty. Subgroup analyses showed that those with cognitive frailty (defined by the frailty phenotype plus Mini-Mental State Examination) were at greater risk for developing adverse outcomes.

CONCLUSION

Our findings indicate that cognitive frailty is an independent risk factor for adverse outcomes (e.g., falls, disability, and hospitalization). Early screening and comprehensive intervention may improve cognitive frailty and reduce the risk for adverse outcomes among older adults.