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Record W2554153609

중환자실 퇴원환자의 집중치료 후 증후군과 삶의 질

2016· article· ko· W2554153609 on OpenAlexaboutno aff
김수경, 강지연

Bibliographic record

Venue중환자간호학회지 = Journal of Korean critical care nursing · 2016
Typearticle
Languageko
FieldMedicine
TopicMedical Research and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsDeliriumDepression (economics)AnxietyQuality of life (healthcare)HandwritingHospital Anxiety and Depression ScaleIntensive careCognitionMedicineActivities of daily livingPsychiatryPhysical therapyPsychologyNursing
DOInot available

Abstract

fetched live from OpenAlex

【Purpose: To investigate the post-intensive care syndrome (PICS) and to analyze the factors affecting the quality of life (QoL) of survivors of critical illness. Methods: Subjects were 114 outpatients who had been discharged from intensive care units of a university hospital in B city, Korea. From July 30 through September 30, 2015, PICS was assessed using the Korean Montreal Cognitive Assessment, Hospital Anxiety-Depression Scale, Korean Instrumental/Activities of Daily Living (K-I/ADL) index, and handwriting transformation, while physical and mental health-related QoL was measured using the SF-12. Results: Of the subjects, 39.5% were screened for mild cognitive disorder and 23.7% experienced handwriting transformation after discharge. Multiple regression analysis revealed that restraint application, current job, time of ${\geq}36$ months after discharge, depression, anxiety, and handwriting transformation accounted for 40.9% of the physical health-related QoL, and depression, anxiety and experience of delirium accounted for 62.4% of the mental health-related QoL. Conclusions: It is necessary to make efforts to reduce restraint application in intensive care units and prevent the occurrence of delirium, with the objective of reducing PICS and improving the QoL of critical illness survivors.】

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)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.949
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.048
GPT teacher head0.418
Teacher spread0.370 · 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.

Study designOther design
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
Published2016
Admission routes1
Has abstractyes

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Same venue중환자간호학회지 = Journal of Korean critical care nursingSame topicMedical Research and TreatmentsFrench-language works237,207