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Summary of the best evidence for preventing medical device-related pressure injury in prone surgical patients

2024· article· en· W4404540474 on OpenAlex
Xinyu Li, Qian Zhang, X T Wang

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueChinese Journal of Integrative Nursing · 2024
Typearticle
Languageen
FieldHealth Professions
TopicPressure Ulcer Prevention and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIntensive care medicine

Abstract

fetched live from OpenAlex

Objective To summarize the best evidence for the prevention of medical device-related pressure injury with prone surgical patients at home and abroad. It aims to provide practice standards for operating room to formulate relevant preventive measures. Methods We systematically searched from BMJ, Up To Date, Joanna Briggs Institute Library, Registered Nurses' Association of Ontario, Scottish Intercollegiate Guidelines Network, Cochrane Library, PubMed, Web of science, CNKI, VIP, Wanfang Data, Sinomed, EPIAP, Wound Ostomy and Continence Nurses Society from establishment of database to December 2023. It included guidelines, clinical decisions, consensus, systematic review and summaries of evidence. Two researchers independently evaluated the quality of the included literature, extracted evidence and determined the level of evidence. Results A total of 15 pieces of literature were included in this study, including 5 guidelines, 1 clinical decision, 3 consensus, 2 systematic reviews and 4 evidence summaries. Finally, summarized 39 pieces of evidence are in five areas: preoperative risk assessment, measures of protection, prone position placement, record keeping, education and training. Conclusion It is particularly important to perform a good preoperative risk assessment and intervene the modifiable risk factors according to the characteristics of prone position surgery. During clinical implementation, position placement is strictly in accordance with position placement standards, and preventive measures suitable for each medical institution were formulated according to the actual situation. (目的 总结俯卧位手术患者预防医疗器械压力性损伤的国内外最佳证据, 为手术室制定相关预防措施提供实践标准。方法 系统检索BMJ、Up To Date、JBI循证卫生保健中心、加拿大安大略注册护士协会、苏格兰学院间指南网、Cochrane Library、PubMed、Web of science、中国知网 (CNKI)、维普(VIP)、万方(Wanfang Data)、SinoMed、伤口造口失禁护理学会、EPIAP等数据库, 检索时限为建库至2023年12月, 包括实践指南、临床决策、共识、系统评价以及证据总结等。纳入文献的质量评价、证据提取和级别判定由2名研究者分别完成。结果 共纳入文献15篇, 涵盖5篇指南, 1篇临床决策, 3篇专家共识, 2篇系统评价以及4篇证据总结。从术前评估、防护措施、俯卧位摆放、记录、教育培训5个方面汇总39条证据。结论 做好术前风险评估, 并且结合俯卧位手术特点对可改变的风险因素进行干预尤为重要。在临床实施过程中, 严格按照体位摆放标准进行体位安置, 并按实际情况制定适合各医疗机构的预防措施。)

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)0.003
metaresearch head score (Gemma)0.003
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 score0.427
Threshold uncertainty score0.554

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
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 integrity0.0000.001
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 head0.047
GPT teacher head0.460
Teacher spread0.413 · 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