Evidence map›Paper›PMID 36824996›Full record

ArticleMethodsX2023

Design and evaluation of a new nurse-led case management intervention for bariatric surgery patients.

Cláudia Amaro Santos, Manuel Carvalho, João Gregório

Abstract read
In one paragraph

Article in MethodsX, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

3 authors.

Cláudia Amaro SantosHospital Espírito Santo de Évora, EPE, Évora, Portugal.
Manuel CarvalhoHospital Espírito Santo de Évora, EPE, Évora, Portugal.
João GregórioCBIOS - Universidade Lusófona's Research Center for Biosciences & Health Technologies Lisbon, Portugal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper provides a new management about the treatment of obesity, that have a growing incidence worldwide. A management centered on the patients' needs during the bariatric surgery is necessary. In this context, patient monitoring and follow-up by a case manager, who guides the provision of specialized care focused on patient's adaptation to the new reality, can prove to be essential to achieve better outcomes. This study, guided by the Design Science Research Methodology (DSRM), will have as main objective to design a new intervention (Case-managing program) aimed at patients undergoing bariatric surgery. As secondary objectives, we intend to analyze the influence of the new intervention in the perioperative period and impact on several clinical and humanistic endpoints. In the evaluation phase, an experimental, controlled, and randomized study (RCT) will be developed, with an intervention group (IG) and a control group (CG). The CG will receive the usual care and the IG, will receive the intervention for an expected period of one year. This project aims to be the first study to investigate the effect of a long-term specialized case-management intervention (face-to-face and e-health) in patients who are candidates for bariatric surgery during all the perioperative periods. This method presents: • The results will be reported the patients related outcomes measures for bariatric surgery • The results are expected to provide an overview of the most effective case management interventions for long-term better results on bariatric surgery • Allowing researchers to design and propose a new case management for bariatric surgery.

Indexed as

Bariatric surgeryCase managerDesign Science Research Methodologye-healthNurse case managementPerioperative care

Identifiers

PMID36824996
PMCPMC9941129

What OpenQuestion holds

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Registered trials

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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.