Evidence map›Paper›PMID 39338109›Full record

ArticleInternational journal of environmental research and public health2024

Management of Patients with Colorectal Cancer through Fast-Track Surgery.

Arianna Scala, Antonio D'Amore, Maria Pia Mannelli, Mario Mensorio, Giovanni Improta

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2024. 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

5 authors.

Arianna ScalaDepartment of Public Health, University Hospital of Naples Federico II, 80131 Naples, Italy.ORCID 0000-0001-9735-5227
Antonio D'AmoreAORN "Antonio Cardarelli" Hospital, 80131 Naples, Italy.
Maria Pia MannelliAORN "Antonio Cardarelli" Hospital, 80131 Naples, Italy.
Mario MensorioAORN "Antonio Cardarelli" Hospital, 80131 Naples, Italy.
Giovanni ImprotaDepartment of Public Health, University Hospital of Naples Federico II, 80131 Naples, Italy.ORCID 0000-0002-9485-1687

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colorectal cancer (CRC) is the third most common cancer in men and the second most common in women globally. CRC is considered a priority public health issue due to its incidence and the high associated costs. Surgery is the predominant therapeutic approach for CRC. Given the involvement of the intestinal tract in the surgical process, there is a significant increase in postoperative morbidity rates, and the average length of hospital stay (LOS) tends to lengthen. In this research, we employed the Lean Six Sigma (LSS) methodology, specifically utilizing the DMAIC cycle, to identify and subsequently examine the effects of fast-track surgery on hospitalization times for interventions related to CRC at the AORN "Antonio Cardarelli" Hospital in Naples (Italy). The process analysis, guided by the DMAIC cycle, facilitated a reduction in the median LOS from 14 days to 12 days. The most notable improvement was observed in the 66-75 age group without comorbidities. The LSS approach provides methodological rigor, as previously recognized, enabling substantial enhancements to the process. This involves standardizing outcomes, minimizing variability, and achieving an overall reduction in the LOS from 14 to 12 days.

Indexed as

Colorectal NeoplasmsLength of StayAdultAgedAged, 80 and overFemaleHumansItalyMaleMiddle Agedcolorectal cancerhealth managementlean six sigmalean thinkinglength of stayvalue stream map

Identifiers

PMID39338109
PMCPMC11431235

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.