Evidence map›Paper›PMID 37663432›Full record

ArticleJSLS : Journal of the Society of Laparoendoscopic Surgeons

Technical Tips Following 850 Consecutive One Anastomosis Gastric Bypass (OAGB) Patients.

Mohit Bhatia, Sharmila Vijayan, Elia Azir, Shamsi El-Hasanii

Abstract read
In one paragraph

Article in JSLS : Journal of the Society of Laparoendoscopic Surgeons. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Mohit BhatiaDepartment of Upper GI & Bariatric Surgery, Princess Royal University Hospital Orpington, Kent, United Kingdom. (all authors).
Sharmila VijayanDepartment of Upper GI & Bariatric Surgery, Princess Royal University Hospital Orpington, Kent, United Kingdom. (all authors).
Elia AzirDepartment of Upper GI & Bariatric Surgery, Princess Royal University Hospital Orpington, Kent, United Kingdom. (all authors).
Shamsi El-HasaniiDepartment of Upper GI & Bariatric Surgery, Princess Royal University Hospital Orpington, Kent, United Kingdom. (all authors).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The surgical procedure One Anastomosis Gastric Bypass (OAGB) has become widely used worldwide. Since its inception, many modifications have been introduced to improve results. Objectives: The primary aim of this study was to share the modifications that we have introduced to our OAGB technique after reflecting on the problems and complications we have faced during the evolution of this procedure in our unit. Method: A total of 850 patients who underwent OAGB under the same surgical team at two different hospitals in the United Kingdom were displayed according to demography and comorbidities. All complications were reviewed and analysed to instigate the changes in our technique. Results: There were 756 (89%) primary and 94 (11%) revisional procedures. There were 596 females (70.11%) and 254 males (29.89%) in our study group. The body mass index range was 32-84 and the mean was 45. The pre-operative weight range was 89-274 kg and the mean was 126.4 kg. Conclusions: With experience and reflecting on our complications we have modified our surgical approach, and these alterations have helped us to adopt OAGB as the mainstream bariatric procedure. We want to share our experience with the bariatric community for the benefit of patient care.

Indexed as

Gastric BypassObesity, MorbidComorbidityFemaleHumansMaleRetrospective StudiesWeight LossBariatric surgeryGastric bypassMini-gastric bypassOne anastomosis gastric bypassWeight loss

Identifiers

PMID37663432
PMCPMC10473180

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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.