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Poor communication by health care professionals may lead to life-threatening complications: examples from two case reports

2019· preprint· en· W2914076523 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWellcome Open Research · 2019
Typepreprint
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsMemorial University of Newfoundland
FundersWellcome TrustWellcome
KeywordsMedicineTuberculosisPrednisoloneRheumatoid arthritisIntensive care unitIntensive care medicineHealth careVomitingPediatricsSurgeryInternal medicine

Abstract

fetched live from OpenAlex

We report two cases which highlight the fact how poor communication leads to dangerously poor health outcome. We present the case of a 50-year-old woman recently diagnosed with rheumatoid arthritis from Southern Nepal presented to Patan hospital with multiple episodes of vomiting and oral ulcers following the intake of methotrexate every day for 11 days, who was managed in the intensive care unit. Similarly, we present a 40-year-old man with ileo-caecal tuberculosis who was prescribed with anti-tubercular therapy (ATT) and prednisolone, who failed to take ATT due to poor communication and presented to Patan Hospital with features of disseminated tuberculosis following intake of 2 weeks of prednisolone alone. These were events that could have been easily prevented with proper communication skills. Improvement of communication between doctors and patients is paramount so that life-threatening events like these could be avoided.

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.

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)0.008
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesOpen science, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.705
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0080.000
Scholarly communication0.0000.000
Open science0.0060.032
Research integrity0.0010.010
Insufficient payload (model declined to judge)0.0010.003

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 head0.615
GPT teacher head0.593
Teacher spread0.023 · 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