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Record W2991197157 · doi:10.1016/j.dib.2019.104859

Data on patient-reported outcomes and the risk of readmission following a cardiac diagnosis

2019· article· en· W2991197157 on OpenAlexaboutno aff
Britt Borregaard, Anne Vinggaard Christensen, Ola Ekholm, Trine Bernholdt Rasmussen, Knud Juel, Astrid Lauberg, Marianne Vámosi, Lars Thrysoee, Selina Kikkenborg Berg

Bibliographic record

VenueData in Brief · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsnot available
FundersNovo Nordisk FondenAalborg UniversitetshospitalRigshospitaletOdense UniversitetshospitalAarhus UniversitetNovo NordiskGentofte HospitalAalborg UniversitetAarhus Universitetshospital
KeywordsMedicineHospital Anxiety and Depression ScaleDepression (economics)AnxietyCohortMedical diagnosisEmergency medicinePsychiatryInternal medicine

Abstract

fetched live from OpenAlex

The data presented in this paper describe a supplementary figure and supplementary tables to the research article; Patient-reported outcomes predict high readmission rates among patients with cardiac diagnoses - Findings from the DenHeart study [1]. The data reports on findings from the DenHeart study, investigating the association between patient-reported outcomes (PROs) and the risk of readmission after a cardiac diagnosis. Data from a national survey with register-based follow-up of a cohort of 34,564 patients were analysed. PROs included the following instruments; The Short Form-12 (SF-12), the Hospital Anxiety and Depression Scale (HADS), the EuroQol 5 Dimensions 5 Levels (EQ-5D 5L), the HeartQol and the Edmonton Symptom Assessment Scale (ESAS). The included tables show the association between PROs and the risk of readmission and the figure illustrates the cumulative incidence function of readmission.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.043
GPT teacher head0.361
Teacher spread0.318 · 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 designObservational
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

Citations3
Published2019
Admission routes1
Has abstractyes

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