Profiling of circulating serum exosomal microRNAs in elderly patients with infectious stress hyperglycaemia
Bibliographic record
Abstract
Abstract Background Early diagnosis of hospitalized elderly patients with infectious stress hyperglycaemia (ISH) is clinically important, especially under the global coronavirus disease 2019 (COVID‐19) pandemic, as without timely prevention and effective treatment, it is likely to deteriorate into septic shock, thus worsening patient survival and complications. Moreover, cumulative studies have showed that patients with COVID‐19 are reported to have a greater prevalence of hyperglycaemia. However, the underlying mechanism remained unknown. Aim and method Systematic screening of specific biomarkers of serum exosome‐derived microRNAs (sE‐miRNAs) from ISH patient has not yet been reported. In this study, sE‐miRNAs were derived from 10 elderly patients with ISH and 5 control patients with disease‐match without hyperglycaemia (non‐ISH). RNA sequencing identified that a total number of 49 sE‐miRNAs with differential expression between ISH and control group. Of which, top 22 miRNAs ranked by sensitivity × specificity were chosen for further research. Moreover, 7 out of 22 miRNAs that related to glucose metabolism or immune disorder were picked up for further validation in an independent cohort consisting of 52 participants (31 ISH and 21 non‐ISH). Result A validation analysis revealed that three miRNAs (hsa‐miR‐21‐5p, hsa‐miR‐335‐5p and hsa‐miR‐28‐3p) were statistically up‐regulated in exosomes from ISH patients. In the validation cohort and discovery cohort, the AUC of three individual miRNAs ranged from 0.73 to 0.88. A logistic model combining three miRNAs achieved an AUC of 0.96. Besides, sE‐miRNAs‐based signatures effectively characterized patients' poor clinical outcome. Survival curve analysis showed that hsa‐miR‐335‐5p, hsa‐miR‐28‐3p but not hsa‐miR‐21‐5p, were significantly closely related to mortality, and the combination of these three miRNAs could also predict patients outcome (p < .05). Conclusion This study depicted the circulating exosomal miRNAs change in ISH patient, which could be used as a promising biomarker to detect ISH at an early stage and predict patients clinical outcome.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".