Evidence map›Paper›PMID 41049979›Full record

ReviewCureus2025

The Future of Enhanced Recovery After Surgery in General Surgery: Integrating Artificial Intelligence, Personalized Care, and Technological Advances.

Mohamed Abosheisha, Elmoatazbellah Nasr, Mohamed Abdellatif, Ahmed Swealem, Ahmed Ammar, Md Abdus Samad Hasan, Momen Abdelglil, Rezuana Tamanna, Mohamed Ismaiel

Abstract readReview
In one paragraph

Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Mohamed AbosheishaGeneral Surgery, Wirral University Teaching Hospital NHS Foundation Trust, Wirral, GBR.
Elmoatazbellah NasrGeneral Surgery, Calderdale and Huddersfield NHS Foundation Trust, Huddersfield, GBR.
Mohamed AbdellatifGeneral Surgery, University Hospitals of Leicester NHS Trust, Leicester, GBR.
Ahmed SwealemOrthopedics, North Bristol Foundation Trust, Bristol, GBR.
Ahmed AmmarGeneral Surgery, Sunderland Royal Hospital, Sunderland, GBR.
Md Abdus Samad HasanMedicine, Bangkok Hospital, Bangkok, THA.
Momen AbdelglilPediatric Surgery, Mansoura University Children Hospital, Mansoura, EGY.
Rezuana TamannaGeneral Surgery, Watford General Hospital, Watford, GBR.
Mohamed IsmaielSurgery, University Hospital Limerick, Limerick, IRL.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Enhanced Recovery After Surgery (ERAS) protocols have changed and improved surgical care and practice, transforming classic approaches toward more evidence-based practices. ERAS protocols demonstrate consistent benefits, including reduced hospital length of stay, decreased postoperative complications, and significant cost savings. Advances include the development and integration of AI and digital health technologies that promise to personalize and optimize recovery pathways. However, the global application of ERAS may face great challenges, starting with resource limitations, resistance to change, and variable compliance rates. This review discusses and highlights the application of ERAS, identifies barriers to implementation, and proposes evidence-based recommendations for optimizing ERAS adoption and sustainability in modern surgical practice.

Indexed as

artificial intelligenceenhanced recovery after surgeryerasgeneral surgeryimplementation scienceperioperative careprecision medicine

Identifiers

PMID41049979
PMCPMC12492726

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.