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Record W3197773858 · doi:10.1186/s41983-021-00359-4

Case report on Cotard’s syndrome (CS) in a patient with schizophrenia: a rare case from Malaysia

2021· article· en· W3197773858 on OpenAlexaff
Natasha Subhas, Khin Ohnmar Naing, Chaw Su, Jiann Lin Loo, Aishah Farhana Shahbudin, Vevehkanandar Sivasubramaniam, Reenisha Thyagarajan

Bibliographic record

VenueThe Egyptian Journal of Neurology Psychiatry and Neurosurgery · 2021
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsYorkville University
Fundersnot available
KeywordsPresentation (obstetrics)Electroconvulsive therapySchizophrenia (object-oriented programming)Depression (economics)PsychiatryCase presentationDeliberationMedicineAntipsychoticPromotion (chess)PediatricsPsychologySurgery

Abstract

fetched live from OpenAlex

Abstract Background Cotard’s syndrome (CS) is a neuropsychiatric condition marked by nihilistic delusional(s). Due to its rarity, misdiagnosis of the syndrome often occurs. The current case study is of a Malaysian woman who was misdiagnosed for several years by professionals due to the presence of hypochondriac symptoms before receiving the correct diagnosis. Case presentation In this case presentation, we describe the case of L, a 42-year-old Malaysian lady who was first misdiagnosed with depression. The diagnosis of schizophrenia and CS was confirmed after thorough clinical examination, diagnostic investigations, and deliberation at a departmental forum. The patient improved after receiving electroconvulsive therapy (ECT) along with antipsychotic medications. Conclusions This case study highlights the importance of early recognition of CS by professionals as it can save time for both parties when setting up a treatment plan. Essentially, early recognition of CS in schizophrenia is paramount in the process of rapid stabilization through ECT and promotion of patient recovery.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.024
GPT teacher head0.241
Teacher spread0.217 · 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 designCase report
Domainnot available
GenreEmpirical

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

Citations2
Published2021
Admission routes1
Has abstractyes

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