Delirium masquerading as depression
Bibliographic record
Abstract
OBJECTIVE: Despite the high prevalence of delirium in palliative care settings, this diagnosis is frequently missed, particularly in patients with hypoactive delirium. These patients are also commonly misdiagnosed with depression because of the overlap in symptoms between the two diagnoses. Failure to promptly diagnose delirium can have significant ramifications in terms of delirium reversal, subsequent patient involvement in end-of-life decision making, and the recognition and treatment of other symptoms. METHOD: We report a case of a 63-year-old French-speaking woman admitted to our inpatient palliative care unit with colorectal cancer and a history of depression. This case report highlights the major challenges associated with making the diagnosis of delirium in a patient with a complex medical history, including depression. RESULTS: The patient presented with symptoms of depressed mood and fluctuation in psychomotor activity, but failed to respond to an increase in her fluoxetine treatment in addition to methylphenidate and treatment of her hypothyroidism. A psychiatric assessment in her own language detected features of inattention and confirmed a diagnosis of delirium that was multifactorial, secondary to a combination of posterior reversible encephalopathy syndrome (PRES), hypothyroidism, hepatic dysfunction, and medication. SIGNIFICANCE OF RESULTS: Subsyndromal delirium may present with mood lability, and as delirium and depression can coexist, clinicians should perform a delirium screen for all patients presenting with symptoms of depression, preferably in the patient's first language. Cognitive testing can be particularly helpful in distinguishing delirium, especially hypoactive delirium, from depression.
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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 | 0.009 |
| 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) | 0.001 | 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; both teacher heads agree on what is shown here.
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".