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Record W1993849455 · doi:10.1097/yct.0b013e3181fe28bd

Catatonia in Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition

2010· editorial· en· W1993849455 on OpenAlexafffund
Andrew Francis, Max Fink, Francisco Appiani, Aksel Bertelsen, Tom G. Bolwig, Peter Bräunig, Stanley N. Caroff, Brendan T. Carroll, Andrea E. Cavanna, David Cohen, Olivier Cottencin, Manuel J. Cuesta, Jessica Daniels, Dirk M. Dhossche, Gregory L. Fricchione, Gábor Gazdag, Neera Ghaziuddin, David Healy, Donald Klein, Stephanie Krüger, Joseph W. Y. Lee, Stephan C. Mann, Michael F. Mazurek, W. Vaughn McCall, William W. McDaniel, Georg Northoff, Víctor Peralta, Georgios Petrides, Patricia I. Rosebush, Teresa A. Rummans, Edward Shorter, Kazumasa Suzuki, Pierre Thomas, Guillaume Vaïva, Lee E. Wachtel

Bibliographic record

VenueJournal of Ect · 2010
Typeeditorial
Languageen
FieldMedicine
TopicElectroconvulsive Therapy Studies
Canadian institutionsMcMaster UniversityUniversity of TorontoUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsCatatoniaElectroconvulsive therapyPsychiatryPsychologyNeuroleptic malignant syndromeSchizophrenia (object-oriented programming)PediatricsMedicine

Abstract

fetched live from OpenAlex

As international scholars of catatonia, we are concerned that the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V) proposes to delete the codes 295.2 (schizophrenia, catatonic type) and 293.89 (catatonia secondary to a medical condition) and to substitute a noncoded "catatonia specifier" as the principal identifier. We believe that these changes will badly serve clinical practice and research. We advocate a unique and broadly defined code for catatonia in DSM-V. Catatonia is common among hospitalized psychiatric patients, including adults, adolescents, and occasionally children. In the 10 principal prospective studies from sites around the world, catatonia syndrome was identified in a mean (SEM) percentage of 9.8% (1.4%) of adult admissions (Table 1). These patients have multiple signs of catatonia (commonly >5); 68% (6%) are mute, and 62% (3%) are negativistic or withdrawn. Some are unable to eat, requiring parenteral nutrition and/or medication.TABLE 1: Prospective Studies of the Incidence of CatatoniaOnce catatonia is recognized, first-line treatment with benzodiazepines usually brings prompt relief, although high doses may be needed. If catatonia persists, electroconvulsive therapy is often rapidly beneficial. Every prospective study confirms that catatonia syndrome exists, occasionally becomes malignant, and requires prompt treatment. Under the proposed new guidelines for DSM-V, patients with catatonia syndrome will lack an informative diagnosis. Mutism, negativism, and withdrawal prevent assessment for mood, cognitive, and psychotic symptoms and impede proper delineation of episodes of prior illness. Without findings for a specific diagnosis, it is rational to use a provisional diagnosis of the catatonia syndrome to allow tests and treatments to proceed. Lacking recognition and treatment, catatonia may persist or worsen with adverse or life-threatening results. On the other hand, when patients with catatonia are identified and treated, they become verbal and interactive, allowing interviews and more definitive diagnoses, regardless of the primary pathological findings. When patients cannot provide information, clinicians may conflate or misdiagnose catatonia with schizophrenia (as in the DSM-IV schema), impute a psychotic process, foster the unproven use of neuroleptics, and risk adverse effects, such as conversion to malignant catatonia or the neuroleptic malignant syndrome. Similarly, assignment of catatonia to "psychosis not otherwise specified" (298.9, DSM-IV and DSM-V) would be erroneous because these patients often either lack hallucinations and delusions or cannot be assessed for them. The proposed elimination of DSM-IV "catatonia due to a general medical condition" (293.89) renders the coding for catatonia arising from general medical conditions problematic. At clinical presentation, the medical/toxic factors are rarely known, as time is often needed to identify these etiologies. We also note that noncoded specifiers are not useful for research on nosology, treatment, and outcome. To address all these issues, we urge inclusion in DSM-V of a specific diagnostic code for catatonia. One simple option is to retain the 293.89 code but revise its formulation to broadly encompass the catatonia syndrome without imputing a link to either primary psychiatric or general medical conditions. A unique and broadly defined code would foster recognition of the catatonia syndrome and permit research on nosology, treatment, and outcome. These goals are not met with the DSM-V plan for noncoded modifiers.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.014
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0200.008

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.

Opus teacher head0.004
GPT teacher head0.297
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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".

Quick stats

Citations85
Published2010
Admission routes2
Has abstractyes

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