104 COMPARING THE OTTAWA 3DY AND 6CIT IN DETECTING COGNITIVE IMPAIRMENT IN OLDER PATIENTS SEEN BY AN EMERGENCY DEPARTMENT THERAPY TEAM
Bibliographic record
Abstract
Abstract Background Recognising cognitive impairment in the Emergency Department (ED) is important in order to optimise outcomes for patients and to carry out a holistic assessment. Currently the team screen routinely for delirium using the 4AT. Since 2016 the 03DY was used to screen for mild cognitive impairment however it was not being completed frequently in practice. In a busy ED setting where time and resources are limited, one brief tool is preferable. The purpose of this investigation is to determine the most accurate cognitive screening tool to identify cognitive impairment in older adults in ED. Methods A literature review was completed comparing recent articles which examined the O3DY and 6CIT. The search criteria for journal articles were: ● Published within the last 10 years. ● Published in English. ● Full text only. ● Database: CINAHL. Results Our investigation identified that the O3DY offered the greatest sensitivity to rule out cognitive impairment. The O3DY is quick to administer, requires no additional equipment or training, and can be completed at the patient’s bedside (BGS, 2020) which is particularly important within the ED. The 6CIT was shown to have poorer sensitivity for MCI diagnosis (Abdel-Aziz and Larner, 2014) and has a mathematical component which studies noted may not be appropriate for use in a busy clinical setting. Conclusion From this literature review, the O3DY has been identified as the most appropriate cognitive screening tool for our team to detect MCI in the ED. It is important to note that many of the articles reviewed highlighted that a single cognitive screen should not be used in isolation for the identification of cognitive impairment. It is unlikely that completing more than one cognitive screen is achievable in the ED however by implementing the most sensitive screening tool we can identify potential MCI and refer onwards.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".