Validation of verbal autopsy: determination of cause of deaths in Malaysia 2013.
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ABSTRACT:
SUBMITTER: Ganapathy SS
PROVIDER: S-EPMC5553780 | biostudies-other | 2017 Aug
REPOSITORIES: biostudies-other
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Project description:BackgroundRegistration of the fact of death is almost complete in the city of Chennai and not so in the rural Villupuram district in Tamilnadu, India. The cause of death is often inadequately recorded on the death certificate in developing countries like India. A special verbal autopsy (VA) study of 48,000 adult (aged >or= 25 yrs) deaths in the city of Chennai (urban) during 1995-97 and 32,000 in rural Villupuram during 1997-98 was conducted to arrive at the probable underlying cause of death to estimate cause specific mortality.MethodsA ten day training on writing verbal autopsy (VA) report for adult deaths was given to non-medical graduates with at least 15 years of formal education. They interviewed surviving spouse/close associates of the deceased to write a verbal autopsy report in local language (Tamil) on the complaints, symptoms, signs, duration and treatment details of illness prior to death. Each report was reviewed centrally by two physicians independently. Random re-interviewing of 5% of the VA reports was done to check the reliability and reproducibility of the VA report. The validity of VA diagnosis was assessed only for cancer deaths.ResultsVerbal autopsy reduced the proportion of deaths attributed to unspecified and unknown causes from 54% to 23% (p < 0.0001) in urban and from 41% to 26% (p < 0.0001) in rural areas in Tamilnadu for adult deaths (>or= 25). The sensitivity of VA to identify cancer was 95% in the age group 25-69.ConclusionA ten day training programme to write verbal autopsy report with adequate feed back sessions and random sampling of 5% of the verbal autopsy reports for re-interview worked very well in Tamilnadu, to arrive at the probable underlying cause of death reliably for deaths in early adult life or middle age (25-69 years) and less reliably for older ages (70+). Thus VA is practicable for deaths in early adult life or middle age and is of more limited value in old age.
| S-EPMC535898 | biostudies-literature
Project description:BackgroundThe most common method for determining cause of death is certification by physicians based either on available medical records, or where such data are not available, through verbal autopsy (VA). The physician-certification approach is costly and inconvenient; however, recent work shows the potential of a computer-based probabilistic model (InterVA) to interpret verbal autopsy data in a more convenient, consistent, and rapid way. In this study we validate separately both physician-certified verbal autopsy (PCVA) and the InterVA probabilistic model against hospital cause of death (HCOD) in adults dying in a district hospital on the coast of Kenya.MethodsBetween March 2007 and June 2010, VA interviews were conducted for 145 adult deaths that occurred at Kilifi District Hospital. The VA data were reviewed by a physician and the cause of death established. A range of indicators (including age, gender, physical signs and symptoms, pregnancy status, medical history, and the circumstances of death) from the VA forms were included in the InterVA for interpretation. Cause-specific mortality fractions (CSMF), Cohen's kappa (κ) statistic, receiver operating characteristic (ROC) curves, sensitivity, specificity, and positive predictive values were applied to compare agreement between PCVA, InterVA, and HCOD.ResultsHCOD, InterVA, and PCVA yielded the same top five underlying causes of adult deaths. The InterVA overestimated tuberculosis as a cause of death compared to the HCOD. On the other hand, PCVA overestimated diabetes. Overall, CSMF for the five major cause groups by the InterVA, PCVA, and HCOD were 70%, 65%, and 60%, respectively. PCVA versus HCOD yielded a higher kappa value (κ = 0.52, 95% confidence interval [CI]: 0.48, 0.54) than the InterVA versus HCOD which yielded a kappa (κ) value of 0.32 (95% CI: 0.30, 0.38). Overall, (κ) agreement across the three methods was 0.41 (95% CI: 0.37, 0.48). The areas under the ROC curves were 0.82 for InterVA and 0.88 for PCVA. The observed sensitivities and specificities across the five major causes of death varied from 43% to 100% and 87% to 99%, respectively, for the InterVA/PCVA against the HCOD.ConclusionBoth the InterVA and PCVA compared well with the HCOD at a population level and determined the top five underlying causes of death in the rural community of Kilifi. We hope that our study, albeit small, provides new and useful data that will stimulate further definitive work on methods of interpreting VA data.
| S-EPMC3160942 | biostudies-literature
Project description:BackgroundA verbal autopsy (VA) is a post-hoc written interview report of the symptoms preceding a person's death in cases where no official cause of death (CoD) was determined by a physician. Current leading automated VA coding methods primarily use structured data from VAs to assign a CoD category. We present a method to automatically determine CoD categories from VA free-text narratives alone.MethodsAfter preprocessing and spelling correction, our method extracts word frequency counts from the narratives and uses them as input to four different machine learning classifiers: naïve Bayes, random forest, support vector machines, and a neural network.ResultsFor individual CoD classification, our best classifier achieves a sensitivity of.770 for adult deaths for 15 CoD categories (as compared to the current best reported sensitivity of.57), and.662 with 48 WHO categories. When predicting the CoD distribution at the population level, our best classifier achieves.962 cause-specific mortality fraction accuracy for 15 categories and.908 for 48 categories, which is on par with leading CoD distribution estimation methods.ConclusionsOur narrative-based machine learning classifier performs as well as classifiers based on structured data at the individual level. Moreover, our method demonstrates that VA narratives provide important information that can be used by a machine learning system for automated CoD classification. Unlike the structured questionnaire-based methods, this method can be applied to any verbal autopsy dataset, regardless of the collection process or country of origin.
| S-EPMC6617656 | biostudies-literature
Project description:BackgroundVerbal autopsy (VA) has emerged as an increasingly popular technique to assign cause of death in parts of the world where the majority of deaths occur without proper medical certification. The purpose of this study was to examine the key characteristics of studies that have attempted to validate VA cause of death against an established cause of death.MethodsA systematic review was conducted by searching the MEDLINE, EMBASE, Cochrane-library, and Scopus electronic databases. Included studies contained 1) a VA component, 2) a validation component, and 3) original analysis or re-analysis. Characteristics of VA studies were extracted. A total of 527 studies were assessed, and 481 studies screened to give 66 studies selected for data extraction.ResultsSixty-six studies were included from multiple countries. Ten studies used an existing database. Sixteen studies used the World Health Organization VA questionnaire and 5 studies used the Population Health Metrics Research Consortium VA questionnaire. Physician certification was used in 36 studies and computer coded methods were used in 14 studies. Thirty-seven studies used high level comparator data with detailed laboratory investigations.ConclusionMost studies found VA to be an effective cause of death assignment method and compared VA cause of death to a high-quality established cause of death. Nonetheless, there were inconsistencies in the methodologies of the validation studies, and many used poor quality comparison cause of death data. Future VA validation studies should adhere to consistent methodological criteria so that policymakers can easily interpret the findings to select the most appropriate VA method.Prospero registrationCRD42020186886.
| S-EPMC9706899 | biostudies-literature
Project description:Despite global health efforts to reduce maternal mortality, rates continue to be unacceptably high in large parts of the world. Feasible, acceptable, and accurate postmortem sampling methods could provide the necessary evidence to improve the understanding of the real causes of maternal mortality, guiding the design of interventions to reduce this burden.The validity of a minimally invasive autopsy (MIA) method in determining the cause of death was assessed in an observational study in 57 maternal deaths by comparing the results of the MIA with those of the gold standard (complete diagnostic autopsy [CDA], which includes any available clinical information). Concordance between the MIA and the gold standard diagnostic categories was assessed by the kappa statistic, and the sensitivity, specificity, positive and negative predictive values and their 95% confidence intervals (95% CI) to identify the categories of diagnoses were estimated. The main limitation of the study is that both the MIA and the CDA include some degree of subjective interpretation in the attribution of cause of death. A cause of death was identified in the CDA in 98% (56/57) of cases, with indirect obstetric conditions accounting for 32 (56%) deaths and direct obstetric complications for 24 (42%) deaths. Nonobstetric infectious diseases (22/32, 69%) and obstetric hemorrhage (13/24, 54%) were the most common causes of death among indirect and direct obstetric conditions, respectively. Thirty-six (63%) women were HIV positive, and HIV-related conditions accounted for 16 (28%) of all deaths. Cerebral malaria caused 4 (7%) deaths. The MIA identified a cause of death in 86% of women. The overall concordance of the MIA with the CDA was moderate (kappa = 0.48, 95% CI: 0.31-0.66). Both methods agreed in 68% of the diagnostic categories and the agreement was higher for indirect (91%) than for direct obstetric causes (38%). All HIV infections and cerebral malaria cases were identified in the MIA. The main limitation of the technique is its relatively low performance for identifying obstetric causes of death in the absence of clinical information.The MIA procedure could be a valuable tool to determine the causes of maternal death, especially for indirect obstetric conditions, most of which are infectious diseases. The information provided by the MIA could help to prioritize interventions to reduce maternal mortality and to monitor progress towards achieving global health targets.
| S-EPMC5695595 | biostudies-literature
Project description:BackgroundThe 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).ObjectiveThe performance of three CCVA algorithms (InterVA-5, InSilicoVA and Tariff 2.0) in assigning a COD was compared with PCVA (reference standard).MethodsSeven 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.ResultsA 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).ConclusionsWhilst CCVAs identified HIV/AIDS as the leading COD, consistent with PCVA, there is scope for improving the algorithms for use in South Africa.
| S-EPMC10795603 | biostudies-literature
Project description:BackgroundIn recent decades, the world has witnessed unprecedented progress in child survival. However, our knowledge of what is killing nearly 6 million children annually in low- and middle-income countries remains poor, partly because of the inadequacy and reduced precision of the methods currently utilized in these settings to investigate causes of death (CoDs). The study objective was to validate the use of a minimally invasive autopsy (MIA) approach as an adequate and more acceptable substitute for the complete diagnostic autopsy (CDA) for pediatric CoD investigation in a poor setting.Methods and findingsIn this observational study, the validity of the MIA approach in determining the CoD was assessed in 54 post-neonatal pediatric deaths (age range: ≥1 mo to 15 y) in a referral hospital of Mozambique by comparing the results of the MIA with those of the CDA. Concordance in the category of disease obtained by the two methods was evaluated by the Kappa statistic, and the sensitivity, specificity, and positive and negative predictive values of the MIA diagnoses were calculated. A CoD was identified in all cases in the CDA and in 52/54 (96%) of the cases in the MIA, with infections and malignant tumors accounting for the majority of diagnoses. The MIA categorization of disease showed a substantial concordance with the CDA categorization (Kappa = 0.70, 95% CI 0.49-0.92), and sensitivity, specificity, and overall accuracy were high. The ICD-10 diagnoses were coincident in up to 75% (36/48) of the cases. The MIA allowed the identification of the specific pathogen deemed responsible for the death in two-thirds (21/32; 66%) of all deaths of infectious origin. Discrepancies between the MIA and the CDA in individual diagnoses could be minimized with the addition of some basic clinical information such as those ascertainable through a verbal autopsy or clinical record. The main limitation of the analysis is that both the MIA and the CDA include some degree of expert subjective interpretation.ConclusionsThe MIA showed substantial concordance with CDA for CoD identification in this series of pediatric deaths in Mozambique. This minimally invasive approach, simpler and more readily acceptable than the more invasive CDA, could provide robust data for CoD surveillance, especially in resource-limited settings, which could be helpful for guiding child survival strategies in the future.
| S-EPMC5478091 | biostudies-literature
Project description:IntroductionEach year, more than 10 million children younger than five years of age die. The large majority of these deaths occur in the developing world. The verbal autopsy (VA) is a tool designed to ascertain cause of death in such settings. While VA has been validated against hospital diagnosed cause of death, there has been no research conducted to better understand the factors that may influence individual physicians in determining cause of death from VA.Methodology/principal findingsThis study uses data from over 27,000 neonatal and childhood deaths from The Million Death Study in which 6.3 million people in India were monitored for vital status between 1998 and 2003. The main outcome variable was physician agreement or disagreement of category of death and the variables were assessed for association using the kappa statistic, univariate and multivariate logistic regression using a conceptual hierarchical model, and a sensitivity and specificity analysis using the final VA category of mortality as the gold standard. The main variables found to be significantly associated with increased physician agreement included older ages and male gender of the deceased. When taking into account confounding factors in the multivariate analysis, we did not find consistent significant differences in physician agreement based on the death being in a rural or urban area, at home or in a health care facility, registered or not, or the respondent's gender, religion, relationship to the deceased, or whether or not the respondent lived with the deceased.Conclusions/significanceFactors influencing physician agreement/disagreement to the greatest degree are the gender and age of the deceased; specifically, physicians tend to be less likely to agree on a common category of death in female children and in younger ages, particularly neonates. Additional training of physician reviewers and continued adaptation of the VA itself, with a focus on gender and age of the deceased, may be useful in increasing rates of physician agreement in these groups.
| S-EPMC2833201 | biostudies-literature
Project description:ObjectivesThis study was conducted to evaluate the performance of World Health Organisation (WHO) verbal autopsy tool in determining major causes of neonatal deaths.MethodsFrom a tertiary care hospital and a government multispecialty hospital, the attending paediatricians ascertained a clinical cause of death for 371 neonatal deaths. Trained field workers conducted verbal autopsy (VA) interviews. Two independent paediatricians, who had no access to the clinical information, assigned cause of death as per verbal autopsy. Analysis was based on 313 cases in which both clinical diagnosis and VA diagnosis was obtained.FindingsAs per the clinical diagnosis, four most common causes of neonatal deaths were sepsis (29.1%), preterm birth (27.8%), birth asphyxia (27.2%), and congenital anomalies (11.5%). Cause specific mortality fractions by VA diagnosis were statistically similar to those obtained by clinical diagnosis except for birth asphyxia (16.3%). Diagnostic accuracy of verbal autopsy diagnosis against clinical diagnosis ranged from 78% to 92% in ascertaining different underlying causes of death. Area under the Receiver-Operator Characteristics curve (95% confidence interval) was 0.75 (0.69-0.80) for sepsis, 0.74 (0.68-0.80) for preterm birth, 0.73 (0.65-0.82) for congenital anomaly and 0.70 (0.64-0.75) for birth asphyxia. Kappa for all four causes was moderate (0.46-0.55).InterpretationThe WHO verbal autopsy tools can provide reasonably good estimates of predominant causes of neonatal deaths in countries where neonatal mortality is high. Caution is required to interpret cause specific mortality fraction (CSMF) for birth asphyxia by VA because it is likely to be an underestimate.
| S-EPMC3555991 | biostudies-literature
Project description:BackgroundCause-specific mortality statistics remain scarce for the majority of low-income countries, where the highest disease burdens are experienced. Neither facility-based information systems nor vital registration provide adequate or representative data. The expansion of sample vital registration with verbal autopsy procedures represents the most promising interim solution for this problem. The development and validation of core verbal autopsy forms and suitable coding and tabulation procedures are an essential first step to extending the benefits of this method.Methods and findingsCore forms for peri- and neonatal, child, and adult deaths were developed and revised over 12 y through a project of the Tanzanian Ministry of Health and were applied to over 50,000 deaths. The contents of the core forms draw upon and are generally comparable with previously proposed verbal autopsy procedures. The core forms and coding procedures based on the International Statistical Classification of Diseases (ICD) were further adapted for use in China. These forms, the ICD tabulation list, the summary validation protocol, and the summary validation results from Tanzania and China are presented here.ConclusionsThe procedures are capable of providing reasonable mortality estimates as adjudged against stated performance criteria for several common causes of death in two countries with radically different cause structures of mortality. However, the specific causes for which the procedures perform well varied between the two settings because of differences in the underlying prevalence of the main causes of death. These differences serve to emphasize the need to undertake validation studies of verbal autopsy procedures when they are applied in new epidemiological settings.
| S-EPMC1502154 | biostudies-literature