Search: onr:"swepub:oai:DiVA.org:umu-86006" > Comparison of physi...
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000 | 04758naa a2200589 4500 | |
001 | oai:DiVA.org:umu-86006 | |
003 | SwePub | |
008 | 140214s2014 | |||||||||||000 ||eng| | |
024 | 7 | a https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-860062 URI |
024 | 7 | a https://doi.org/10.1186/1741-7015-12-222 DOI |
040 | a (SwePub)umu | |
041 | a engb eng | |
042 | 9 SwePub | |
072 | 7 | a ref2 swepub-contenttype |
072 | 7 | a art2 swepub-publicationtype |
100 | 1 | a Leitao, Jordana4 aut |
245 | 1 0 | a Comparison of physician-certified verbal autopsy with computer-coded verbal autopsy for cause of death assignment in hospitalized patients in low- and middle-income countries :b systematic review |
264 | c 2014-02-04 | |
264 | 1 | b BioMed Central,c 2014 |
338 | a electronic2 rdacarrier | |
520 | a BACKGROUND: Computer-coded verbal autopsy (CCVA) methods to assign causes of death (CODs) for medically unattended deaths have been proposed as an alternative to physician-certified verbal autopsy (PCVA). We conducted a systematic review of 19 published comparison studies (from 684 evaluated), most of which used hospital-based deaths as the reference standard. We assessed the performance of PCVA and five CCVA methods: Random Forest, Tariff, InterVA, King-Lu, and Simplified Symptom Pattern.METHODS: The reviewed studies assessed methods' performance through various metrics: sensitivity, specificity, and chance-corrected concordance for coding individual deaths, and cause-specific mortality fraction (CSMF) error and CSMF accuracy at the population level. These results were summarized into means, medians, and ranges.RESULTS: The 19 studies ranged from 200 to 50,000 deaths per study (total over 116,000 deaths). Sensitivity of PCVA versus hospital-assigned COD varied widely by cause, but showed consistently high specificity. PCVA and CCVA methods had an overall chance-corrected concordance of about 50% or lower, across all ages and CODs. At the population level, the relative CSMF error between PCVA and hospital-based deaths indicated good performance for most CODs. Random Forest had the best CSMF accuracy performance, followed closely by PCVA and the other CCVA methods, but with lower values for InterVA-3.CONCLUSIONS: There is no single best-performing coding method for verbal autopsies across various studies and metrics. There is little current justification for CCVA to replace PCVA, particularly as physician diagnosis remains the worldwide standard for clinical diagnosis on live patients. Further assessments and large accessible datasets on which to train and test combinations of methods are required, particularly for rural deaths without medical attention. | |
650 | 7 | a MEDICIN OCH HÄLSOVETENSKAPx Hälsovetenskapx Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi0 (SwePub)303022 hsv//swe |
650 | 7 | a MEDICAL AND HEALTH SCIENCESx Health Sciencesx Public Health, Global Health, Social Medicine and Epidemiology0 (SwePub)303022 hsv//eng |
653 | a Causes of death | |
653 | a Computer-coded verbal autopsy | |
653 | a InterVA | |
653 | a King and Lu | |
653 | a Physician-certified verbal autopsy | |
653 | a Random forest | |
653 | a Simplified symptom pattern | |
653 | a Tariff | |
653 | a Validity | |
653 | a Verbal autopsy | |
700 | 1 | a Desai, Nikita4 aut |
700 | 1 | a Aleksandrowicz, Lukasz4 aut |
700 | 1 | a Byass, Peteru Umeå universitet,Epidemiologi och global hälsa,Umeå Centre for Global Health Research, Umeå University4 aut0 (Swepub:umu)peby0002 |
700 | 1 | a Miasnikof, Pierre4 aut |
700 | 1 | a Tollman, Stephenu Umeå universitet,Epidemiologi och global hälsa,Umeå Centre for Global Health Research, Umeå University, University of the Witwatersrand, Johannesburg, South Africa and International Network for the Demographic Evaluation of Populations and Their Health (INDEPTH) Network, Accra, Ghana4 aut0 (Swepub:umu)stto0004 |
700 | 1 | a Alam, Dewan4 aut |
700 | 1 | a Lu, Ying4 aut |
700 | 1 | a Rathi, Suresh Kumar4 aut |
700 | 1 | a Singh, Abhishek4 aut |
700 | 1 | a Suraweera, Wilson4 aut |
700 | 1 | a Ram, Faujdar4 aut |
700 | 1 | a Jha, Prabhat4 aut |
710 | 2 | a Umeå universitetb Epidemiologi och global hälsa4 org |
773 | 0 | t BMC Medicined : BioMed Centralg 12:1, s. 22-q 12:1<22-x 1741-7015 |
856 | 4 | u https://doi.org/10.1186/1741-7015-12-22y Fulltext |
856 | 4 | u https://umu.diva-portal.org/smash/get/diva2:696590/FULLTEXT01.pdfx primaryx Raw objecty fulltext:print |
856 | 4 | u https://bmcmedicine.biomedcentral.com/track/pdf/10.1186/1741-7015-12-22 |
856 | 4 8 | u https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-86006 |
856 | 4 8 | u https://doi.org/10.1186/1741-7015-12-22 |
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