Kidney Function and Risk of Physical and Cognitive Impairment in Older Persons with Type 2 Diabetes at an Outpatient Clinic with Geriatric Assessment Implementation
Bibliographic record
Abstract
Cheng-Fu Lin,1,2 Hsiu-Chen Liu,3 Shih-Yi Lin1,4,5 1Center for Geriatrics & Gerontology, Taichung Veterans General Hospital, Taichung, 40705, Taiwan; 2Division of Occupational Medicine, Department of Emergency, Taichung Veterans General Hospital, Taichung, 40705, Taiwan; 3Department of Nursing, Taichung Veterans General Hospital, Taichung, 40705, Taiwan; 4School of Medicine, National Yang Ming Chiao Tung University, Taipei, 11221, Taiwan; 5Institute of Clinical Medicine, School of Medicine, National Yang Ming Chiao Tung University, Taipei, 11221, TaiwanCorrespondence: Shih-Yi LinCenter for Geriatrics & Gerontology, Taichung Veterans General Hospital, 1650 Taiwan Boulevard Sect. 4, Taichung, 40705, TaiwanTel +886-4-2359-2525#3390Fax +886-4-2359-5046Email sylin@vghtc.gov.twPurpose: Diabetes is associated with an increased risk of cognitive and physical functional decline that may impede disease self-management. By incorporating cognitive and physical function assessment, this study aimed to evaluate prevalence and factors associated with cognitive and physical dysfunction in older diabetic people.Methods: The cross-sectional study was performed from August 1, 2017 to November 30, 2018. The patients aged 65 years or older with type 2 diabetes mellitus were enrolled and the disease was routinely evaluated by blood hemoglobin A1c (A1C), blood pressure, lipids, and kidney function measured by estimated glomerular filtration rate (eGFR) and urinary albumin-creatinine rate (UACR). Besides, cognitive dysfunction through Mini-mental State Examination (MMSE), and functional disabilities by Activities of Daily Living (ADL) questionnaire were assessed simultaneously.Results: Among 863 patients (48.3% men) with a median age of 72.0 years (interquartile range or IQR: 67.0– 78.0 years), 159 (18.5%) had cognitive impairment assessed by MMSE, while 40 (4.6%) experienced at least one problem in ADL. With different A1C stratifications, it was shown that both MMSE and ADL scores were associated with glycemic control. Patients with impaired MMSE and ADL scores were older, had lower eGFR, lower blood pressure, and higher UACR levels. After adjustment of possible confounders, it was shown that age and eGFR predicted MMSE and ADL score impairment.Conclusion: By incorporating physical and cognitive function screening program into routine care at a diabetes outpatient clinic, our study found that both cognitive and physical function impairment were common in older diabetic patients, and their relevant factors, including older age, and lower eGFR. It was recommended that in older individuals with diabetes, particularly those with risk factors, an additional assessment of cognitive and physical functions can be integrated into routine clinical process to provide more comprehensive management plans.Keywords: diabetes, aged, outpatient, functional decline, cognitive impairment
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".