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Agreement between cause of death assignment by computer-coded verbal autopsy methods and physician coding of verbal autopsy interviews in South Africa.
Groenewald, Pam; Thomas, Jason; Clark, Samuel J; Morof, Diane; Joubert, Jané D; Kabudula, Chodziwadziwa; Li, Zehang; Bradshaw, Debbie.
Afiliación
  • Groenewald P; Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa.
  • Thomas J; Department of Sociology, The Ohio State University, Columbus, Ohio, USA.
  • Clark SJ; Department of Sociology, The Ohio State University, Columbus, Ohio, USA.
  • Morof D; Division of Global HIV & TB, Centers for Disease Control and Prevention, Durban, South Africa.
  • Joubert JD; United States Public Health Service Commissioned Corps, Rockville, Maryland, USA.
  • Kabudula C; Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa.
  • Li Z; MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), University of Witwatersrand, Johannesburg, South Africa.
  • Bradshaw D; Department of Statistics, University of California Santa Cruz, Santa Cruz, California, USA.
Glob Health Action ; 16(1): 2285105, 2023 Dec 31.
Article en En | MEDLINE | ID: mdl-38038664
BACKGROUND: The South African national cause of death validation (NCODV 2017/18) project collected a national sample of verbal autopsies (VA) with cause of death (COD) assignment by physician-coded VA (PCVA) and computer-coded VA (CCVA). OBJECTIVE: The performance of three CCVA algorithms (InterVA-5, InSilicoVA and Tariff 2.0) in assigning a COD was compared with PCVA (reference standard). METHODS: Seven performance metrics assessed individual and population level agreement of COD assignment by age, sex and place of death subgroups. Positive predictive value (PPV), sensitivity, overall agreement, kappa, and chance corrected concordance (CCC) assessed individual level agreement. Cause-specific mortality fraction (CSMF) accuracy and Spearman's rank correlation assessed population level agreement. RESULTS: A total of 5386 VA records were analysed. PCVA and CCVAs all identified HIV/AIDS as the leading COD. CCVA PPV and sensitivity, based on confidence intervals, were comparable except for HIV/AIDS, TB, maternal, diabetes mellitus, other cancers, and some injuries. CCVAs performed well for identifying perinatal deaths, road traffic accidents, suicide and homicide but poorly for pneumonia, other infectious diseases and renal failure. Overall agreement between CCVAs and PCVA for the top single cause (48.2-51.6) indicated comparable weak agreement between methods. Overall agreement, for the top three causes showed moderate agreement for InterVA (70.9) and InSilicoVA (73.8). Agreement based on kappa (-0.05-0.49)and CCC (0.06-0.43) was weak to none for all algorithms and groups. CCVAs had moderate to strong agreement for CSMF accuracy, with InterVA-5 highest for neonates (0.90), Tariff 2.0 highest for adults (0.89) and males (0.84), and InSilicoVA highest for females (0.88), elders (0.83) and out-of-facility deaths (0.85). Rank correlation indicated moderate agreement for adults (0.75-0.79). CONCLUSIONS: Whilst CCVAs identified HIV/AIDS as the leading COD, consistent with PCVA, there is scope for improving the algorithms for use in South Africa.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Causas de Muerte / Síndrome de Inmunodeficiencia Adquirida Límite: Adult / Aged / Female / Humans / Male / Newborn País/Región como asunto: Africa Idioma: En Revista: Glob Health Action Año: 2023 Tipo del documento: Article País de afiliación: Sudáfrica

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Causas de Muerte / Síndrome de Inmunodeficiencia Adquirida Límite: Adult / Aged / Female / Humans / Male / Newborn País/Región como asunto: Africa Idioma: En Revista: Glob Health Action Año: 2023 Tipo del documento: Article País de afiliación: Sudáfrica