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Record W3013970657 · doi:10.1155/2020/7324185

Wanting to Forget: Intrusive and Delusional Memories from Critical Illness

2020· article· en· W3013970657 on OpenAlexaff
Lauren Doig, Kevin Solverson

Bibliographic record

VenueCase Reports in Critical Care · 2020
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDeliriumContext (archaeology)AnxietyMedicineIntensive care unitPsychiatryHarmCritical illnessIntensive care medicinePsychologyCritically ill

Abstract

fetched live from OpenAlex

Introduction. Delusional and fearful memories after critical illness are observed in up to 70% of patients post critical illness. However, they often go unrecognized after patients leave the intensive care unit (ICU). Case Presentation. A 40-year-old male was admitted to the ICU with community-acquired pneumonia and multiorgan failure requiring mechanical ventilation and renal replacement therapy. He developed protracted delirium and severe ICU-acquired weakness but was eventually discharged home. The patient returned to a follow-up clinic two months post-ICU discharge and revealed that he was suffering anxiety from memories in the ICU of different staff trying to harm and kill him, including being repeatedly suffocated. By providing context to the memories, the patient had significant relief in his anxiety. Conclusions. Intrusive memories contribute to psychological morbidity post critical illness, including posttraumatic stress disorder (PTSD) and reduced health-related quality of life. The majority of critical illness survivors do not share their intrusive or frightening memories, and therefore, most healthcare professionals are unaware of the problems they can pose. Assessment of patients’ memories from the ICU is essential and may create the opportunity to help patients place memories into context and improve psychological morbidities.

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)0.003
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.036
GPT teacher head0.363
Teacher spread0.327 · 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

Citations8
Published2020
Admission routes1
Has abstractyes

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