The Challenge of Differentiating Delirium Tremens from Other Causes of Delirium in Hospitalized Patients: A Case Report & Review of the Challenge
Bibliographic record
Abstract
Alcohol withdrawal is a common presentation in patients with alcohol use disorder. If severe, alcohol withdrawal may present as delirium tremens (DT) characterized by confusion, agitation, disorientation and hallucinations, occuring approximately 48 hours after cessation of alcohol. Delirium tremens is associated with significant morbidity and mortality. Thus, it is important for clinicians to know how to diagnose and treat delirium tremens. We report on a case of delirium in a patient with a history of alcohol withdrawal in which there was a clinical question regarding the etiology of the delirium. Challenges in diagnosis and management of delirium tremens are discussed. Les symptômes de sevrage alcoolique sont fréquents chez les patients avec des troubles de consommation d'alcool. Un sevrage sévère peut être accompagné d'un délire alcoolique aigu, aussi appelé delirium tremens (DT), qui se caractérise par de la confusion, de l'agitation, de la désorientation et des hallucinations et qui apparaît environ 48 heures suivant la dernière consommation. Le DT est associé à une morbidité et une mortalité plus importante. Il est donc important que les cliniciens sachent comment diagnostiquer et traiter le DT. Nous faisons rapport d'un cas de delirium chez un patient avec des antécédents de sevrage alcoolique et chez qui la cause du delirium suscitait des questions d'ordre clinique. Les difficultés liées au diagnostic et à la gestion du DT sont discutées.
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 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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".