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Record W4394688513 · doi:10.1016/j.psycr.2024.100224

Treatment of psychogenic polydipsia with electroconvulsive therapy (ECT)- A case report

2024· article· en· W4394688513 on OpenAlexaff
Arany Shanmugalingam, Sayani Paul, Ross M. Murray

Bibliographic record

VenuePsychiatry Research Case Reports · 2024
Typearticle
Languageen
FieldMedicine
TopicElectrolyte and hormonal disorders
Canadian institutionsOntario Shores Centre for Mental Health SciencesQueen's UniversityUniversity of Toronto
Fundersnot available
KeywordsElectroconvulsive therapyPsychogenic diseasePolydipsiaMedicinePsychologyPsychotherapistPsychiatryEndocrinologySchizophrenia (object-oriented programming)Diabetes mellitus

Abstract

fetched live from OpenAlex

Psychogenic polydipsia (PPD) is a condition characterized by excessive water intake that is not related to a physiological need. It is often seen in patients with schizophrenia and schizoaffective disorders and can lead to hyponatremia, a serious condition characterized by low sodium levels in the blood. This report summarizes the case of a 74-year-old male who had a longstanding history of schizoaffective disorder, bipolar type. At admission to the geriatric unit of a psychiatric hospital, the patient engaged in excessive drinking behavior and his serum sodium level was low (126 mmol/L). The patient required urgent treatment, however had a history of ineffective medication trials (including clozapine), and poor medication adherence. As such, the patient's family member who was the substitute decision maker consented to electroconvulsive therapy (ECT). Upon beginning ECT, there was noted improvement in PPD symptoms with regards to water seeking and eventually improved oral compliance for mediations. The patient completed 25 sessions of ECT and was discharged three months after admission. Significant improvements were also noted in symptoms of psychosis between admission and discharge. Overall, this case report offers ECT as a potential treatment modality for geriatric patients presenting with symptoms of PPD with psychosis.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.076
Threshold uncertainty score0.891

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.040
GPT teacher head0.398
Teacher spread0.358 · 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 teacher head, 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

Citations0
Published2024
Admission routes1
Has abstractyes

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