What is the role of admission <scp>HbA1c</scp> in managing <scp>COVID</scp>‐19 patients?
Bibliographic record
Abstract
Some recent articles published in the Journal of Diabetes have raised concerns about the importance of checking glycosylated hemoglobin (HbA1c) upon hospital admission for coronavirus disease 2019 (COVID-19) patients.1-3 It is now undoubtedly clear that absolute hyperglycemia at the time of admission increases the risk of severe outcomes of COVID-19, independent of prior diabetes status,4, 5 and tight glycemic control improves the prognosis of these patients significantly.4, 5 However, the role of admission HbA1c, which reflects average glycemia over the preceding 2 to 3 months, in the management of COVID-19 patients remains uncertain. Some studies have shown a significant association between admission HbA1c and disease progression or mortality in COVID-19 patients, whereas a few others did not (Table 1). While the reasons for this discrepancy are not clear, most of these studies are constrained by a small number of patients,6, 7 a large proportion of missing HbA1c data,8 and inadequate adjustment of potential confounders.8, 9 Previous research has shown that background glycemia mediates the association between admission glucose and outcomes in patients with a variety of medical conditions.10-12 Thus, correcting admission glucose levels for background glycemia estimated by HbA1c, the so-called relative hyperglycemia predicts outcomes in acute health conditions better than absolute hyperglycemia,10, 13 albeit not yet proven in the COVID-19 context. Mortality Markers of inflammation and hypercoagulability, and oxygen saturation Higher mortality rate with increasing HbA1c levels: 9.8% in group A (n = 41, no diabetes and HbA1c ≤6.0%), 11.4% in group B (n = 44, no diabetes and HbA1c >6.0- < 6.5%), and 27.7% in group C (n = 47, diabetes and/or HbA1c ≥6.5%), P = .04 Negative correlation between HbA1c and SaO2 (r = −0.22, P = .01). Positive correlation between HbA1c and ferritin (r = 0.24, P = .01), CRP (r = 0.22, P = .01), fibrinogen (r = 0.27, P < .01), and ESR (r = 0.27, P < .01) Invasive mechanical ventilation or death within 7 days of admission Since HbA1c is relatively unaffected by the stress of acute illness,14 it may help identify newly diagnosed diabetes cases in COVID-19 patients. Newly diagnosed diabetes (new onset or previously undiagnosed) is now increasingly recognized as a common phenomenon in COVID-19 patients.15, 16 More importantly, COVID-19 patients with newly diagnosed diabetes appear to be at a greater risk for poor prognosis not only compared with those without diabetes but also individuals with known diabetes.17-19 To summarize, admission blood glucose is certainly a key biomarker to risk stratify and guide the clinical management of COVID-19 patients, with or without known diabetes. Thus, it is essential that all COVID-19 patients be screened for absolute hyperglycemia upon admission so that early and appropriate treatment can be initiated if required. While the role of admission HbA1c as a marker of COVID-19 severity is yet to be fully established, HbA1c assists in identifying patients with newly diagnosed diabetes.15, 20 These patients are a high-risk group and should be closely monitored for the emergence of cardiometabolic disorders in the long term.16 No funding received. None declared.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".