SAT-150 Usefulness of Point-of-Care Testing as a Tool in the Management of Patients with Diabetes
Bibliographic record
Abstract
Abstract D.M. Nascimento: None. G.M. Chichelero: None. L.R. Bahia: None. F. Malerbi: None. B.D. Schaan: None. Background: The use of technologies that allow the identification of chronic complications of diabetes mellitus and glycemic control, especially in areas with limited access to healthcare services is crucial for an early intervention and, consequently, for improving the quality of life. The application of point-of-care testing (POCT) for this purpose enables analyses outside the laboratory setting, ensuring real-time availability of results, thus assisting in decision-making. For this, it is necessary to assess its accuracy to avoid erroneous clinical decisions. Objective: To identify potential differences between POCT and laboratory hemoglobin A1c (HbA1c), creatinine (CREA), and albumin to creatinine ratio (ACR) in outpatients with diabetes. Methods: This is a cross sectional study, in which HbA1c and CREA were evaluated simultaneously in capillary and venous blood samples from patients with diabetes mellitus randomly selected from tertiary and primary care healthy units, by POCT (AfinionTM 2 Analyzer, Abbott Diagnostics Technologies AS, Oslo/Norway and i-STAT 1 Analyzer, Abbott Point of Care Inc., Ontario/Canada) and laboratory method (VariantTM II Turbo HbA1c Kit - 2.0, Bio-Rad Laboratories, Inc. California/USA and Alinity c System, Abbott Ireland Diagnostics Division, Longford/Ireland). Urine samples were also obtained and evaluated by POCT (AfinionTM 2 Analyzer, Abbott Diagnostics Technologies AS, Oslo/Norway) and laboratory method (Alinity c System, Abbott Ireland Diagnostics Division, Longford/Ireland). The intraclass correlation coefficient (ICC) was performed to calculate the inter-rater reliability for continuous variables and the Fleiss' Kappa coefficient (k) was used for categorical variables. Results: A total of 261 patients were included. Overall, participants were aged 65 ± 12.3 years, mainly women (53,6%), white (n = 205, 78.5%), with type 2 diabetes (n = 236, 90.4%), laboratory HbA1c > 7% (63,7%), and ACR < 30 mg/g (66.4%). The mean POCT and laboratory HbA1c was 7.9 ± 1.8 % and 7.8 ± 1.8%, respectively. The mean POCT and laboratory CREA was 1.0 ± 0.8 mg/dL and 1.1 ± 0.7 mg/dL, respectively. ACR was categorized in normal (< 30 mg/g) or increased (≥ 30mg/g). Agreement was high for HbA1c (ICC = 0.98), CREA (ICC = 0.99), and ACR (k = 0.96). Conclusion: Point-of-care testing demonstrated almost perfect agreement in assessment of glycemic control and renal impairment in patients with diabetes mellitus as compared to the gold standard laboratory method. Support: FAPERGS, FIPE, Brazilian Society of Diabetes Saturday, June 1, 2024
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".