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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 OpenAlexaff
Vittorio Stumpo, Victor E. Staartjes, Ayesha Quddusi, Marco V. Corniola, Enrico Tessitore, Marc L. Schröder, Erich G. Anderer, Martin N. Stienen, Carlo Serra, Luca Regli

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.007
Bibliometrics0.0090.008
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations106
Published2021
Admission routes1
Has abstractyes

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