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Record W3157589256 · doi:10.3171/2020.10.jns203160

Enhanced Recovery After Surgery strategies for elective craniotomy: a systematic review

2021· review· en· W3157589256 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of neurosurgery · 2021
Typereview
Languageen
FieldMedicine
TopicEnhanced Recovery After Surgery
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicinePerioperativeNeurosurgeryPsychological interventionMEDLINEAnesthesiologyCochrane LibraryPostoperative nausea and vomitingNauseaAnesthesiaPatient satisfactionIntensive care medicineSurgeryRandomized controlled trialNursing

Abstract

fetched live from OpenAlex

OBJECTIVE: Enhanced Recovery After Surgery (ERAS) has led to a paradigm shift in perioperative care through multimodal interventions. Still, ERAS remains a relatively new concept in neurosurgery, and there is no summary of evidence on ERAS applications in cranial neurosurgery. METHODS: The authors systematically reviewed the literature using the PubMed/MEDLINE, Embase, Scopus, and Cochrane Library databases for ERAS protocols and elements. Studies had to assess at least one pre-, peri-, or postoperative ERAS element and evaluate at least one of the following outcomes: 1) length of hospital stay, 2) length of ICU stay, 3) postoperative pain, 4) direct and indirect healthcare cost, 5) complication rate, 6) readmission rate, or 7) patient satisfaction. RESULTS: A final 27 articles were included in the qualitative analysis, with mixed quality of evidence ranging from high in 3 cases to very low in 1 case. Seventeen studies reported a complete ERAS protocol. Preoperative ERAS elements include patient selection through multidisciplinary team discussion, patient counseling and education to adjust expectations of the postoperative period, and mental state assessment; antimicrobial, steroidal, and antiepileptic prophylaxes; nutritional assessment, as well as preoperative oral carbohydrate loading; and postoperative nausea and vomiting (PONV) prophylaxis. Anesthesiology interventions included local anesthesia for pin sites, regional field block or scalp block, avoidance or minimization of the duration of invasive monitoring, and limitation of intraoperative mannitol. Other intraoperative elements include absorbable skin sutures and avoidance of wound drains. Postoperatively, the authors identified early extubation, observation in a step-down unit instead of routine ICU admission, early mobilization, early fluid de-escalation, early intake of solid food and liquids, early removal of invasive monitoring, professional nutritional assessment, PONV management, nonopioid rescue analgesia, and early postoperative imaging. Other postoperative interventions included discharge criteria standardization and home visits or progress monitoring by a nurse. CONCLUSIONS: A wide range of evidence-based interventions are available to improve recovery after elective craniotomy, although there are few published ERAS protocols. Patient-centered optimization of neurosurgical care spanning the pre-, intra-, and postoperative periods is feasible and has already provided positive results in terms of improved outcomes such as postoperative pain, patient satisfaction, reduced length of stay, and cost reduction with an excellent safety profile. Although fast-track recovery protocols and ERAS studies are gaining momentum for elective craniotomy, prospective trials are needed to provide stronger evidence.

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)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMeta-epidemiology (broad)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.123
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0170.011
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.002
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 head0.044
GPT teacher head0.337
Teacher spread0.293 · 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