Evidence map›Paper›PMID 35768977›Full record

ArticleMedical science monitor : international medical journal of experimental and clinical research2022

Nomogram for Prediction of Postoperative Morbidity in Patients with Colon Cancer Requiring Emergency Therapy.

Raul Mihailov, Dorel Firescu, Georgiana Bianca Constantin, Cristina Șerban, Eugenia Panaitescu, Cristian Marica, Rodica Bîrlă, Traian Patrascu

Open access · hybridAbstract read
In one paragraph

Article in Medical science monitor : international medical journal of experimental and clinical research, 2022. 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
0.8field-weighted citation impact, top 27% 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, 5 citations in OpenAlex.

  1. Review
  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

8 authors at 3 institutions in 1 country.

Raul MihailovDepartment of Clinic Surgery, Dunarea de Jos University, Galati, Romania.
Dorel FirescuDepartment of Clinic Surgery, Dunarea de Jos University, Galati, Romania.
Georgiana Bianca ConstantinDepartment of Morphological and Functional Sciences, Dunarea de Jos University, Galati, Romania.
Cristina ȘerbanDepartment of Clinic Surgery, Dunarea de Jos University, Galati, Romania.
Eugenia PanaitescuDepartment of Medical Biostatistics, Carol Davila University, Bucharest, Romania.
Cristian MaricaDepartment of General Surgery, Titu Maiorescu University, Bucharest, Romania.ORCID 0000-0003-3380-4315
Rodica BîrlăDepartment of General Surgery, Carol Davila University, Bucharest, Romania.
Traian PatrascuDepartment of General Surgery, Carol Davila University, Bucharest, Romania.
"Dunarea de Jos" University of Galati · ROCarol Davila University of Medicine and Pharmacy · ROTitu Maiorescu University · RO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND Postoperative complications are the major cause of mortality and prolonged hospitalization after emergency surgery for colon cancer. This study aimed to propose an effective nomogram to predict postoperative complications in order to improve the outcomes. MATERIAL AND METHODS We retrospectively analyzed 449 patients who underwent emergency surgery for complicated colon cancer at the County Emergency Hospital Clinic "St. Apostle Andrei" in Galaţi, in the period from 2008 to 2017. Postoperative complications were intestinal obstruction, leakage, bleeding, peritonitis, wound infection, surgical wound dehiscence, respiratory failure, heart failure, acute renal failure, sepsis, and Clostridium difficile colitis, within a month after surgery. Logistic regression models were used to identify the independent prediction factors, and a nomogram was created, based on the best model. RESULTS A total of 106 patients (21%) presented postoperative complications after emergency surgery for colon cancer; 51 patients (11.36%) died during the postoperative period. After identifying the risk factors through univariate regression analysis, we identified the independent prediction factors in 2 multivariate regression models. The model with the highest accuracy included the following 7 independent prediction factors: Eastern Cooperative Oncology Group performance status, Charlson score, white blood cell count, electrolyte and coagulation disorders, surgery time, and cachexia (P<0.05 for all). This model showed good precision in predicting postoperative complications, with an area under curve of 0.83 and ideal accordance between the predicted and observed probabilities. CONCLUSIONS The nomogram developed in this study, which was based on a multivariate logistic regression model, had good individual prediction of postoperative complications.

Indexed as

Colonic NeoplasmsNomogramsEmergency TreatmentHumansMorbidityPostoperative ComplicationsPostoperative PeriodRetrospective StudiesRisk FactorsROC Curve

Identifiers

PMID35768977
PMCPMC9254725
OpenAlexW4282828228

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.