U201Cqasc Europeu201D The First Results of The Study in Italy : Comparative Analysis of The Data Obtained From The Observational Study of Two Different Hospitals
Bibliographic record
Abstract
IntroductionApproximately 15 million people worldwide suffer a stroke each year. There is compelling evidence that improved patient outcomes are achieved through early intervention in acute stroke care, including thrombolysis, endovascular clot retrieval and access to specialised in-patient stroke units. Hyperglycaemia, swallowing dysfunction and elevated temperature are physiological variables known to be associated with poorer stroke outcomes. Optimal management of fever, hyperglycaemia and dysphagia have been identified in international guidelines as priorities for inpatient stroke management.The Quality in Acute Stroke Care (QASC) Trial, has shown, in the countries where the study was conducted, that multidisciplinary nurse-led interventions to manage fever, hyperglycaemia and swallow difficulties following acute stroke, significantly improved health outcomes. Results showed that supported implementation of the Fever, Sugar, Swallow (FeSS) Clinical Protocols resulted in 16% decreased death and dependency at 90-days, and in-hospital: reduced mean temperatures, reduced mean glucose levels and improved swallow screening management. There also was a non-significant reduction in length of stay by two days. Results were fast-tracked for publication in The Lancet, with a commentary, having won the Canadian Stroke Congress Award for Impact in 2011 and the 2012 American Heart Association Council on Cardiovascular Nursing Stroke Article of the year. The Italian study was conducted at the San Camillo Forlanini Hospital in Rome and at the Hospital of Avezzano, which are two very different hospitals for localization and approach to the Stroke.MethodWe proceeded, as envisaged by the International Protocol QASC, to the first phase of the study, which is the observational study, with the audit of 42 patient records of patients hospitalized in the two Centers during 2018 with diagnosis of acceptance of the ICD 10. For the cases at provisional intervals (six months) we will proceed to a new audit entitled
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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 | 0.043 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".