Evidence map›Paper›PMID 37679406›Full record

ArticleScientific reports2023

Classification and regression model to manage the hospitalization for laparoscopic cholecystectomy.

Arianna Scala, Teresa Angela Trunfio, Giovanni Improta

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
7.2field-weighted citation impact, top 2% of its field
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

2 citing papers in PubMed, 28 citations in OpenAlex.

  1. Management of Patients with Colorectal Cancer through Fast-Track Surgery.International journal of environmental research and public health · 2024
    Article
  2. 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 at 1 institution in 1 country.

Arianna ScalaDepartment of Public Health, University of Naples "Federico II", Naples, Italy.
Teresa Angela TrunfioDepartment of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy. teresa.trunfio@gmail.com.
Giovanni ImprotaDepartment of Public Health, University of Naples "Federico II", Naples, Italy.
University of Naples Federico II · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gallstone disease (GD) is one of the most common morbidities in the world. Laparoscopic Cholecystectomy (LC) is currently the gold standard, performed in about 96% of cases. The most affected groups are the elderly, who generally have higher pre- and post-operative morbidity and mortality rates and longer Length of Stay (LOS). For this reason, several indicators have been defined to improve quality and efficiency and contain costs. In this study, data from patients who underwent LC at the "San Giovanni di Dio e Ruggi d'Aragona" University Hospital of Salerno in the years 2010-2020 were processed using a Multiple Linear Regression (MLR) model and Classification algorithms in order to identify the variables that most influence LOS. The results of the 2352 patients analyzed showed that pre-operative LOS and Age were the independent variables that most affected LOS. In particular, MLR model had a R

Indexed as

Cholecystectomy, LaparoscopicAgedAlgorithmsHealth FacilitiesHospitalizationHumansLength of Stay

Identifiers

PMID37679406
PMCPMC10485042
OpenAlexW4386528828

What Socratic 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 Socratic graph.