Evaluation of the Discrimination Ability of the Decision Rule Allowing to Predict the Probability of Death in Oncosurgical Patients with Comorbid Pathology.

Prognostic score prognosis of lethal outcome of oncosurgical patients validity of prognostic scores

Journal

Studies in health technology and informatics
ISSN: 1879-8365
Titre abrégé: Stud Health Technol Inform
Pays: Netherlands
ID NLM: 9214582

Informations de publication

Date de publication:
29 Jun 2022
Historique:
entrez: 1 7 2022
pubmed: 2 7 2022
medline: 6 7 2022
Statut: ppublish

Résumé

At the moment, there are many decision rules and mathematical models that reduce the risk of postoperative mortality and complications. A small part of such medical mathematical models (scales) is successfully used in practice, but there is also a part that eventually remains on the shelves and becomes morally obsolete. The purpose of this work is to evaluate the discrimination ability of the prognostic model underlying the decision rule that allows ranking patients into groups with favorable and unfavorable outcomes and into a group of patients subject to preoperative preparation to maintain the performance of the mathematical model Oncoprognosis 1.0. The discrimination ability carried out by constructing an area under the Receiver Operating Characteristic (ROC) curve. The investigation allowed conduct that any decision rule requires revision over time, its clarification and, if necessary, adjustments and updates.

Identifiants

pubmed: 35773930
pii: SHTI220784
doi: 10.3233/SHTI220784
doi:

Types de publication

Journal Article

Langues

eng

Pagination

538-541

Auteurs

Irina V Vasilyeva (IV)

State Research Center - Burnasyan Federal Medical Biophysical Center of Federal Medical Biological Agency, Moscow, Russia.
Pirogov Russian National Research Medical University, Moscow, Russia.

Yuri D Udalov (YD)

FSBI "Federal Scientific Clinical Centre for Medical Radiology and Oncology" of FMBA of Russia, Dimitrovgrad, Russia.

Angelina S Bachtina (AS)

State Research Center - Burnasyan Federal Medical Biophysical Center of Federal Medical Biological Agency, Moscow, Russia.

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Classifications MeSH