Clinical, Laboratory, and Neuroimaging Assessments Relevant for the Diagnostic Work-Up of Catatonia
Bibliographic record
Abstract
In addition to the international classification systems such as DSM-5 and ICD-11 discussed in earlier chapters of this book, we will now introduce three further diagnostic steps essential for diagnosing catatonia: (1) clinical rating scales, (2) the lorazepam challenge test, and (3) laboratory and neuroimaging work-up. This chapter will first present the widely used clinical rating scales for assessing catatonia, highlighting their advantages, limitations, and their role in scientific studies. While these scales are valuable tools, it is important to emphasize that clinical judgment remains crucial, as some catatonic symptoms may not be fully captured by these scales. Following this, we will explore the lorazepam challenge test, evaluating its diagnostic utility in light of current evidence. Lastly, the chapter will discuss the importance of laboratory and neuroimaging work-ups, including blood tests, lumbar puncture to examine cerebrospinal fluid, electroencephalogram, and magnetic resonance imaging, for both diagnosing catatonia and guiding therapeutic decisions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".