Both pre-frailty and frailty increase healthcare utilization and adverse health outcomes in patients with type 2 diabetes mellitus

Chao, Chia‐Ter; Wang, Jui; Chien, Kuo‐Liong

doi:10.1186/s12933-018-0772-2

Cited by 99 publications

(102 citation statements)

References 55 publications

(65 reference statements)

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“…More generally, frailty, regardless of how it is defined, is associated with incident falls, difficulty with activities of daily living, disability, hospitalisation and death 24. While T2DM itself is associated with an elevated risk of mortality and healthcare utilisation, frailty magnifies these risks 25. It is important to determine if there is an interaction between parameters of sleep, T2DM and individual components of frailty.…”

Section: Introductionmentioning

confidence: 99%

Rationale and design of a cross-sectional study to investigate and describe the chronotype of patients with type 2 diabetes and the effect on glycaemic control: the CODEC study

et al. 2019

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IntroductionA person’s chronotype is their entrained preference for sleep time within the 24 hours clock. It is described by the well-known concept of the ‘lark’ (early riser) and ‘owl’ (late sleeper). Evidence suggests that the ‘owl’ is metabolically disadvantaged due to the standard organisation of our society which favours the ‘lark’ and places physiological stresses on this chronotype. The aim of this study is to explore cardiometabolic health between the lark and owl in a population with an established metabolic condition - type 2 diabetes.MethodsThis cross-sectional, multisite study aims to recruit 2247 participants from both secondary and primary care settings. The primary objective is to compare glycaemic control between late and early chronotypes. Secondary objectives include determining if late-chronotype is associated with poorer cardiometabolic health and other lifestyle factors, including well-being, compared with early-chronotype; describing the prevalence of the five different chronotypes in this cohort and examining the trends in glycaemic control, cardiometabolic health, well-being and lifestyle factors across chronotype.AnalysisThe primary outcome (glycated haemoglobin (HbA1c)), linear regression analysis will compare HbA1c between early and late chronotypes, with and without adjustment for confounding variables. Chronotype will be modelled as a categorical variable with all five levels (from extreme-morning to extreme-late type), and as a continuous variable to calculate p for trend across the five categories. A number of models will be created; unadjusted through to adjusted with age, sex, ethnicity, body mass index, duration of diabetes, family history of diabetes, current medication and dietary habits. All secondary outcomes will be analysed using the same method.EthicsEthical approval from the West Midlands - Black Country Research Ethics Committee (16/WM/0457).DisseminationThe results will be disseminated through publication in peer-reviewed medical journal, relevant medical/health conferences and a summary report sent to patients.Trial registration number NCT02973412 (Pre-Results).

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Section: Introductionmentioning

confidence: 99%

Rationale and design of a cross-sectional study to investigate and describe the chronotype of patients with type 2 diabetes and the effect on glycaemic control: the CODEC study

et al. 2019

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“…Further studies on the effect of vitamin D on pre-frailty and frailty in ESRD patients and even those with other metabolic disorders are needed. 43,44 In this study, we found that those with high LFI-1 scores had a significantly higher mortality than those with low scores, but not for LFI-2. Several reasons may be responsible for this discrepancy in outcome predictability.…”

Section: Discussionmentioning

confidence: 47%

“…Serum 1,25‐(OH) 2 ‐D levels may be associated not only with frail phenotype but also with FI in elderly and in ESRD patients alike. Further studies on the effect of vitamin D on pre‐frailty and frailty in ESRD patients and even those with other metabolic disorders are needed …”

Section: Discussionmentioning

confidence: 99%

Applicability of laboratory deficit‐based frailty index in predominantly older patients with end‐stage renal disease under chronic dialysis: A pilot test of its correlation with survival and self‐reported instruments

2019

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Aim Laboratory deficit‐based frailty index (LFI) exhibited outcome‐prediction ability in the elderly, but not in those with end‐stage renal disease (ESRD). We hypothesized that LFI results might have outcome correlation and correlate closely with other instruments in ESRD patients. Methods We prospectively enroled ESRD patients between 2014 and 2015 and administered self‐report frailty instruments (Strawbridge questionnaire, Edmonton frail scale (EFS), Groningen frailty indicator (GFI), Tilburg frailty indicator, G8 questionnaire and FRAIL scale), and Cardiovascular Health Study (CHS) scale, with two types of LFI calculated. They were followed up until June 30, 2017. Correlations between the results of six instruments, CHS scale, and those of LFI were identified, followed by Kaplan–Meier survival analyses and logistic regression analyses to compare those with high and low LFI. Results The frailty prevalence was 33.3% (CHS), 78.8% Strawbridge questionnaire, 45.5% (EFS), 57.6% (GFI), 27.3% (Tilburg frailty indicator), 84.8% (G8) and 18.2% (FRAIL) among ESRD participants. LFI‐1 results were significantly correlated with those of LFI‐2 (P < 0.01), EFS (P = 0.04) and GFI (P < 0.01), while LFI‐2 results were not. Those with CHS or GFI‐identified frailty had significantly lower 1,25‐(OH)2‐D levels than those without. After 32.3 ± 5.4 months, patients with high LFI‐1 scores, but not LFI‐2, had a significantly higher mortality than those with lower scores. GFI and EFS scores were also independently associated with LFI‐1, while CHS scores exhibited borderline association only. Conclusion Among a group of predominantly older ESRD patients, LFI differentiates patients with good and poor outcomes, supporting its applicability in these patients.

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“…We selected patients with DM from the Longitudinal Cohort of Diabetes Patients (LCDP), a well-maintained cohort of patients with diabetes derived from an annual random selection of 120 000 patients with at least one diagnosis of diabetes from the National Health Insurance Database in Taiwan, between 2004 and 2010 7 8. This led to an initial cohort size of 840 000 during the study period.…”

Section: Methodsmentioning

confidence: 99%

“…Patients with DM are at a higher risk of exhibiting frailty, a degenerative trait characterized by a higher vulnerability to endogenous or environmental injuries, regardless of their age, likely due to the combinatorial effects of hyperglycemia-induced premature cellular senescence, chronic inflammation, and oxidative stress 6. Accumulating evidence indicates that frailty in patients with diabetes causes adverse outcomes ranging from effects on mortality and functional independence, to musculoskeletal degeneration, an increased risk of cardiovascular events, and renal failure 7 8. None of the existing studies has examined whether frailty may influence the probability of urolithiasis in patients with DM.…”

Section: Introductionmentioning

confidence: 99%

Frailty predicts a higher risk of incident urolithiasis in 525 368 patients with diabetes mellitus: a population-based study

Chao¹,

Wang

Hung³

et al. 2020

BMJ Open Diab Res Care

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ObjectivePatients with diabetes have an increased risk for urolithiasis, but the associated risk factors remain an active area of research. We investigated whether frailty influenced the probability of patients with diabetes developing urolithiasis.Research design and methodsUsing data from the Longitudinal Cohort of Diabetic Patients from 2004 to 2010, we identified those without and with frailty based on a validated, modified FRAIL scale. Patients were followed until they developed urolithiasis, and we used Kaplan-Meier and Cox proportional hazard regression analyses to examine the relationship between frailty, its severity, and the risk of urolithiasis, accounting for demographic profiles, comorbidities, frailty status changes over follow-up, and medications, with risk competition by mortality.ResultsAmong 525 368 patients with diabetes, 64.4% were not frail, while 28.5%, 6.6%, and 0.6% had 1, 2, and ≥3 FRAIL items at baseline. After 4.2 years of follow-up, 13.4% experienced incident urolithiasis. Cox proportional hazard regression analysis showed that patients with diabetes having at least one FRAIL criterion exhibited a significantly higher risk for urolithiasis compared with non-frail patients (for 1, 2, and ≥3 items, hazard ratio (HR)s: 1.04, 1.23, and 1.46; 95% confidence intervals (CIs) 0.99 to 1.09, 1.12 to 1.35, and 1.12 to 1.91, respectively). This increase in urolithiasis risk remained significant if we restricted analyses to renal stones or recurrent urolithiasis as the study outcomes.ConclusionsFrailty may pose a risk for incident urolithiasis in patients with diabetes. Treating frailty may potentially reduce their risk for urolithiasis.

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Both pre-frailty and frailty increase healthcare utilization and adverse health outcomes in patients with type 2 diabetes mellitus

Cited by 99 publications

References 55 publications

Rationale and design of a cross-sectional study to investigate and describe the chronotype of patients with type 2 diabetes and the effect on glycaemic control: the CODEC study

Rationale and design of a cross-sectional study to investigate and describe the chronotype of patients with type 2 diabetes and the effect on glycaemic control: the CODEC study

Applicability of laboratory deficit‐based frailty index in predominantly older patients with end‐stage renal disease under chronic dialysis: A pilot test of its correlation with survival and self‐reported instruments

Frailty predicts a higher risk of incident urolithiasis in 525 368 patients with diabetes mellitus: a population-based study

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