MétaCan
Menu
Back to cohort
Record W4388778809 · doi:10.5498/wjp.v13.i11.848

Clinical application of multidisciplinary team- and evidence-based practice project in gynecological patients with perioperative hypothermia

2023· article· en· W4388778809 on OpenAlexaboutno aff
Qing‐Yan Liu, Tongyang You, Daiying Zhang, Juan Wang

Bibliographic record

VenueWorld Journal of Psychiatry · 2023
Typearticle
Languageen
FieldMedicine
TopicThermal Regulation in Medicine
Canadian institutionsnot available
FundersSouthwest Medical University
KeywordsMedicinePerioperativeGynecological surgeryMultidisciplinary teamIncidence (geometry)Multidisciplinary approachIntervention (counseling)HypothermiaNursingIntensive care medicineEmergency medicinePhysical therapyAnesthesia

Abstract

fetched live from OpenAlex

BACKGROUND Perioperative hypothermia (PH) negatively affects the physical and mental health of patients to varying degrees. Currently, there is no effective multidisciplinary team (MDT) intervention for gynecological patients with PH. AIM To apply the best evidence on the prevention and management of PH in gynecological patients, improve the quality of perioperative evidence-based care based on treatment by an MDT for gynecological patients and analyze the effect of MDT- and evidence-based practice (EBP) projects on the psychological status and cognitive function of gynecological patients with PH. METHODS Under the guidance of knowledge translation and combined with the opinions of involved stakeholders and clinical experts, the best evidence for PH prevention and management in gynecological patients was selected and adjusted to suit the practice setting. Based on the evidence, the practice plan was developed, and the MDT intervention was carried out in the preoperative ward, the preoperative preparation room, the intraoperative operating room, the postanesthesia care unit, and the 24-hour postoperative gynecological ward through the EBP program. The incidence of hypothermia, the nurses’ awareness, the implementation rate of examination indicators, and the thermal comfort level, psychological status and cognitive function of patients were compared before and after the implementation of the program. RESULTS The incidence of PH in gynecological patients decreased from 43.33% to 13.33% after the implementation of the scheme. The implementation rate of examination indicators 6-10, 12, 14, 16-18, 21, and 22 reached 100%, and that of other indicators was above 90%, except for examination indicators 5 and 13, which was 66.67%; the indices were significantly improved compared with the baseline (before evidence application) (P < 0.05). The score of nurses' awareness of PH prevention and management in gynecological patients increased from 60.96 ± 9.70 to 88.08 ± 8.96, and the difference was statistically significant (P < 0.001). The total score of the perioperative thermal comfort level of patients undergoing gynecological surgery was 27.97 ± 2.04, which was significantly increased compared with the score of 21.27 ± 1.57 observed by researchers at baseline (P < 0.001). The perioperative Hamilton Depression Scale and Hamilton Anxiety Scale scores of patients undergoing gynecological surgery decreased from 15.03 ± 3.16 and 13.93 ± 2.64 to 4.30 ± 1.15 and 3.53 ± 0.78, respectively, with statistically significant differences (P < 0.001). The perioperative Montreal Cognitive Assessment Scale score of the gynecological surgery patients increased from 23.17 ± 1.68 to 26.93 ± 1.11, also with statistical significance (P < 0.001). CONCLUSION MDT-based EBP for PH prevention and management in gynecological patients during the perioperative period can standardize nursing operations, improve nurses' awareness and behavioral compliance with gynecological hypothermia management, and reduce the occurrence of PH in gynecological patients while playing a positive role in reducing patients’ negative emotions and enhancing their cognitive function.

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)0.001
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 score0.019
Threshold uncertainty score0.292

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.032
GPT teacher head0.383
Teacher spread0.351 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueWorld Journal of PsychiatrySame topicThermal Regulation in MedicineFrench-language works237,207