Evidence map›Paper›PMID 38864885›Full record

ArticleSurgical endoscopy2024

Learning curve of laparoscopic appendectomy in a low-resource setting: a cumulative sum analysis of operative length.

Abdourahmane Ndong, Adja C Diallo, Armaun D Rouhi, Mohamed L Diao, Sebastian Leon, Diago A Dia, Angelika N Alberstadt, Jacques N Tendeng, Noel N Williams, Mamadou Cissé and 2 more

Abstract read
PubMed Publisher
In one paragraph

Article in Surgical endoscopy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
–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, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  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

12 authors.

Abdourahmane NdongDepartment of Surgery, Saint-Louis Regional Hospital, Gaston Berger University, Road of Ngallelle, 234, Saint-Louis, Senegal. abdourahmane.ndong@ugb.edu.sn.ORCID 0000-0001-8103-1375
Adja C DialloDepartment of Surgery, Saint-Louis Regional Hospital, Gaston Berger University, Road of Ngallelle, 234, Saint-Louis, Senegal.
Armaun D RouhiDepartment of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Mohamed L DiaoDepartment of Surgery, Saint-Louis Regional Hospital, Gaston Berger University, Road of Ngallelle, 234, Saint-Louis, Senegal.
Sebastian LeonDepartment of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Diago A DiaDepartment of Surgery, Saint-Louis Regional Hospital, Gaston Berger University, Road of Ngallelle, 234, Saint-Louis, Senegal.
Angelika N AlberstadtDepartment of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Jacques N TendengDepartment of Surgery, Saint-Louis Regional Hospital, Gaston Berger University, Road of Ngallelle, 234, Saint-Louis, Senegal.
Noel N WilliamsDepartment of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Mamadou CisséDepartment of Surgery, Saint-Louis Regional Hospital, Gaston Berger University, Road of Ngallelle, 234, Saint-Louis, Senegal.
Kristoffel R DumonDepartment of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Ibrahima KonatéDepartment of Surgery, Saint-Louis Regional Hospital, Gaston Berger University, Road of Ngallelle, 234, Saint-Louis, Senegal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCumulative sum (CUSUM) analysis is a valuable tool for quantifying the learning curve of surgical teams by detecting significant changes in operative length. However, there is limited research evaluating the learning curve of laparoscopic techniques in low-resource settings. The objective of this study is to evaluate the learning curve for laparoscopic appendectomy within a single surgical team in Senegal.

methodsThis was a single-center prospective study conducted from May 1, 2018, to August 31, 2023 of patients who underwent laparoscopic appendectomy at a tertiary care institution in West Africa. The AAST classification was used to describe the severity of appendicitis. Parameters studied included age, sex, operative length, conversion rate, and postoperative outcomes. To quantify the learning curve, CUSUM analysis of operative length was performed.

resultsA total of 81 patients were included. The mean age was 26.7 years (range 11-70 years) with a sex ratio of 1.9. Pre-operative severity according to AAST was Grade I in 75.4% (n = 61), Grade III in 7.4% (n = 6), Grade IV in 6.1% (n = 5), and Grade V in 11.1% (n = 9). Conversion occurred in 5 cases (6.1%). The average operative length was 76.8 min (range 30-180 min) and the average length of hospitalization was 2.7 days (range 1-13 days). Morbidity was observed in 3.7% (n = 3) and there were no deaths. The CUSUM analysis showed that a steady operative length was achieved after 28 procedures, with decreasing operative lengths thereafter.

conclusionSurgeons in our setting overcame the learning curve for laparoscopic appendectomy after performing 28 procedures. Moreover, laparoscopic appendectomy is safe and feasible throughout the learning curve. CUSUM analysis should be applied to other laparoscopic procedures and individualized by surgical teams to improve surgical performance and patient outcomes in low-resource settings.

Indexed as

AppendectomyAppendicitisLaparoscopyLearning CurveOperative TimeAdolescentAdultAgedChildDeveloping CountriesFemaleHumansLength of StayMaleMiddle AgedPostoperative ComplicationsAppendectomyCumulative sum analysisGlobal surgeryLaparoscopyLearning curveSurgical training

Identifiers

What OpenQuestion holds

Textmetadata
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.