ZINNO, MARIA ANTONIETTA (2018) Virtual autopsy: possible applications in cases of presumed medical malpractice. [Tesi di dottorato]

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Item Type: Tesi di dottorato
Lingua: English
Title: Virtual autopsy: possible applications in cases of presumed medical malpractice.
Creators:
CreatorsEmail
ZINNO, MARIA ANTONIETTAmary.zinno@gmail.com
Date: 10 December 2018
Number of Pages: 75
Institution: Università degli Studi di Napoli Federico II
Department: Medicina Clinica e Chirurgia
Dottorato: Scienze biomorfologiche e chirurgiche
Ciclo di dottorato: 31
Coordinatore del Corso di dottorato:
nomeemail
Cuocolo, Albertoalberto.cuocolo@unina.it
Tutor:
nomeemail
BUCCELLI, CLAUDIOUNSPECIFIED
Date: 10 December 2018
Number of Pages: 75
Uncontrolled Keywords: virtual autopsy, malpractice, imaging.
Settori scientifico-disciplinari del MIUR: Area 06 - Scienze mediche > MED/43 - Medicina legale
Date Deposited: 21 Dec 2018 08:43
Last Modified: 26 Jun 2020 20:25
URI: http://www.fedoa.unina.it/id/eprint/12604

Abstract

An analysis of the international bibliography has shown the existence of several advantages associated with the use of the autoptic imaging techniques in cases of judicial interest. In this review, we examine whether the non-invasive or minimally invasive autopsy methods could replace conventional autopsy in cases of death related to suspected malpractice. We searched the main databases, including PubMed Central, Medline, Web of Science, Scopus and Cochrane. The search terms included the following elements: autopsy, imaging, malpractice. The last review of the research was carried out in September 2018. The use of autoptic imaging techniques such as PMCT and PMCTA, always followed by traditional autopsy, can significantly improve the diagnostic effectiveness in post-mortem investigations of presumed medical malpractice. However, their role in the analysis of mortality in the context of clinical risk management is still under investigation. Studies in the literature have been conducted on numbers that are too small to obtain scientifically relevant data for solid statistical analysis; therefore these results should be confirmed in the future on a larger sample, which could be obtained by conducting multi centric studies.

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