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Record W4384465833 · doi:10.5737/23688076333321

Medical nursing care of gastrointestinal tumour patients during chemotherapy

2023· article· en· W4384465833 on OpenAlexvenueno aff
Donghui Dai, Jie Chen

Bibliographic record

VenueCanadian Oncology Nursing Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicTraditional Chinese Medicine Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLung cancerNursingChemotherapyPsychological interventionNursing Interventions ClassificationNursing careQuality of life (healthcare)Intervention (counseling)Internal medicine

Abstract

fetched live from OpenAlex

Objectives: This research with gastrointestinal cancer patients analyzed the expected outcomes of nursing interventions on a) patient adherence to treatment; b) patient satisfaction with nursing care; and c) health of body conditions such as lung function. Methods: All patients (60 individuals) who underwent chemotherapy at The First Affiliated Hospital of Soochow University, Department of Traditional Chinese Medicine, were divided into two equal groups. Group 1 received planned care and Group 2 received evidence-based nursing interventions. Results: The results showed that treatment adherence was higher in Group 2 than in the control group (p = 0.01). In addition, there was a higher rating by patients for the quality of nursing care (p = 0.01), as well as a higher score obtained for lung function (p = 0.01). Treatment adherence resulted in a decrease in the secondary infection rate in Group 2 (p = 0.05). Conclusion: The results showed that quality nursing intervention is effective for lung function improvement, stress level reduction, treatment plans, and a reduction of secondary infections.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.326
Threshold uncertainty score0.937

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.319
Teacher spread0.303 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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