Prognosis of COVID-19 patients with type 2 diabetes
Bibliographic record
Abstract
Background: The pandemic of COVID-19, a disease caused by novel coronavirus SARS-CoV-2, is associated with significant morbidity and mortality. Recent data showed that hypertension, diabetes mellitus, cardiovascular diseases, and chronic obstructive pulmonary disease were the most prevalent comorbidities in COVID-19 patients. Additionally, data indicate that hypertension, diabetes and cardiovascular diseases are important risk factors for progression and unfavourable outcome in COVID-19 patients. Poorly controlled Type 2 diabetes mellitus was associated with severe progression of disease. Hence, large studies with comprehensive analysis of all risk factors and longer follow-up are necessary. Methods and analysis: A single-centre retrospective cross-sectional study of 300 patients that were SARS-CoV-2 positive from May to October 2020 was done. Data was entered into Microsoft excel data sheet and was analysed using SPSS 22 version software. Chi-square test or Fischer’s exact test (for 2x2 tables only) was used as test of significance for qualitative data. Independent t test was used as test of significance to identify the mean difference between two quantitative variables. ANOVA (Analysis of Variance) was used as test of significance to identify the mean difference between more than two quantitative variables. P value (Probability that the result is true) of <0.05 was considered as statistically significant after assuming all the rules of statistical tests. Data collected was analyzed in a group of patients who were sub divided into 2 groups diabetics and Non diabetics. The parameters studied included laboratory markers: D dimer, CRP, Lactate Dehydrogenase, Ferritin levels. To assess the glycemic control HbA1C levels were assessed. The outcome parameters considered were Oxygen requirement, assessing the requirement of intensive care and duration of stay in the hospital Conclusion: The patients with higher HbA1c values were found to have higher CRP and D-dimer values and required ICU shift and prolonged hospital stay. Hence, good control of diabetes will reduce the worsening of disease. In a country like India, where most of the population do not have health insurance cover proper control of diabetes, can reduce the burden on family. Hence, large studies with comprehensive analysis of all risk factors and longer follow-up are necessary.
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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 | 0.003 | 0.061 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".