Validation of physician certified verbal autopsy using conventional autopsy: a large study of adult non-external causes of death in a metropolitan area in Brazil.

BACKGROUND: Reliable mortality data are essential for the development of public health policies. In Brazil, although there is a well-consolidated universal system for mortality data, the quality of information on causes of death (CoD) is not even among Brazilian regions, with a high proportion of ill-defined CoD. Verbal autopsy (VA) is an alternative to improve mortality data. This study aimed to evaluate the performance of an adapted and reduced version of VA in identifying the underlying causes of non-forensic deaths, in São Paulo, Brazil. This is the first time that a version of the questionnaire has been validated considering the autopsy as the gold standard. METHODS: The performance of a physician-certified verbal autopsy (PCVA) was evaluated considering conventional autopsy (macroscopy plus microscopy) as gold standard, based on a sample of 2060 decedents that were sent to the Post-Mortem Verification Service (SVOC-USP). All CoD, from the underlying to the immediate, were listed by both parties, and ICD-10 attributed by a senior coder. For each cause, sensitivity and chance corrected concordance (CCC) were computed considering first the underlying causes attributed by the pathologist and PCVA, and then any CoD listed in the death certificate given by PCVA. Cause specific mortality fraction accuracy (CSMF-accuracy) and chance corrected CSMF-accuracy were computed to evaluate the PCVA performance at the populational level. RESULTS: There was substantial variability of the sensitivities and CCC across the causes. Well-known chronic diseases with accurate diagnoses that had been informed by physicians to family members, such as various cancers, had sensitivities above 40% or 50%. However, PCVA was not effective in attributing Pneumonia, Cardiomyopathy and Leukemia/Lymphoma as underlying CoD. At populational level, the PCVA estimated cause specific mortality fractions (CSMF) may be considered close to the fractions pointed by the gold standard. The CSMF-accuracy was 0.81 and the chance corrected CSMF-accuracy was 0.49. CONCLUSIONS: The PCVA was efficient in attributing some causes individually and proved effective in estimating the CSMF, which indicates that the method is useful to establish public health priorities.

Resolution of sickle cell disease-associated inflammation and tissue damage with 17R-resolvin D1.

Resolvins (Rvs), endogenous lipid mediators, play a key role in the resolution of inflammation. Sickle cell disease (SCD), a genetic disorder of hemoglobin, is characterized by inflammatory and vaso-occlusive pathologies. We document altered proresolving events following hypoxia/reperfusion in humanized SCD mice. We demonstrate novel protective actions of 17R-resolvin D1 (17R-RvD1; 7S, 8R, 17R-trihydroxy-4Z, 9E, 11E, 13Z, 15E, 19Z-docosahexaenoic acid) in reducing ex vivo human SCD blood leukocyte recruitment by microvascular endothelial cells and in vivo neutrophil adhesion and transmigration. In SCD mice exposed to hypoxia/reoxygenation, oral administration of 17R -RvD1 reduces systemic/local inflammation and vascular dysfunction in lung and kidney. The mechanism of action of 17R-RvD1 involves (1) enhancement of SCD erythrocytes and polymorphonuclear leukocyte efferocytosis, (2) blunting of NF-κB activation, and (3) a reduction in inflammatory cytokines, vascular activation markers, and E-selectin expression. Thus, 17R-RvD1 might represent a new therapeutic strategy for the inflammatory vasculopathy of SCD.

Routine mortality surveillance to identify the cause of death pattern for out-of-hospital adult (aged 12+ years) deaths in Bangladesh: introduction of automated verbal autopsy.

BACKGROUND: In Bangladesh, a poorly functioning national system of registering deaths and determining their causes leaves the country without important information on which to inform health programming, particularly for the 85% of deaths that occur in the community. In 2017, an improved death registration system and automated verbal autopsy (VA) were introduced to 13 upazilas to assess the utility of VA as a routine source of policy-relevant information and to identify leading causes of deaths (COD) in rural Bangladesh. METHODS: Data from 22,535 VAs, collected in 12 upazilas between October 2017 and August 2019, were assigned a COD using the SmartVA Analyze 2.0 computer algorithm. The plausibility of the VA results was assessed using a series of demographic and epidemiological checks in the Verbal Autopsy Interpretation, Performance and Evaluation Resource (VIPER) software tool. RESULTS: Completeness of community death reporting was 65%. The vast majority (85%) of adult deaths were due to non-communicable diseases, with ischemic heart disease, stroke and chronic respiratory disease comprising about 60% alone. Leading COD were broadly consistent with Global Burden of Disease study estimates. CONCLUSIONS: Routine VA collection using automated methods is feasible, can produce plausible results and provides critical information on community COD in Bangladesh. Routine VA and VIPER have potential application to countries with weak death registration systems.

Born to fail: flaws in replication design produce intended results.

We recently published in BMC Medicine an evaluation of the comparative diagnostic performance of InSilicoVA, a software to map the underlying causes of death from verbal autopsy interviews. The developers of this software claim to have failed to replicate our results and appear to have also failed to locate our replication archive for this work. In this Correspondence, we provide feedback on how this might have been done more usefully and offer some suggestions to improve future attempts at reproducible research. We also offer an alternative interpretation of the results presented by Li et al., namely that, out of 100 verbal autopsy interviews, InSilicoVA will, at best, correctly identify the underlying cause of death in 40 cases and incorrectly in 60 - a markedly inferior performance to alternative existing approaches.

Improving medical certification of cause of death: effective strategies and approaches based on experiences from the Data for Health Initiative.

BACKGROUND: Accurate and timely cause of death (COD) data are essential for informed public health policymaking. Medical certification of COD generally provides the majority of COD data in a population and is an essential component of civil registration and vital statistics (CRVS) systems. Accurate completion of the medical certificate of cause of death (MCCOD) should be a relatively straightforward procedure for physicians, but mistakes are common. Here, we present three training strategies implemented in five countries supported by the Bloomberg Philanthropies Data for Health (D4H) Initiative at the University of Melbourne (UoM) and evaluate the impact on the quality of certification. METHODS: The three training strategies evaluated were (1) training of trainers (TOT) in the Philippines, Myanmar, and Sri Lanka; (2) direct training of physicians by the UoM D4H in Papua New Guinea (PNG); and (3) the implementation of an online and basic training strategy in Peru. The evaluation involved an assessment of MCCODs before and after training using an assessment tool developed by the University of Melbourne. RESULTS: The TOT strategy led to reductions in incorrectly completed certificates of between 28% in Sri Lanka and 40% in the Philippines. Following direct training of physicians in PNG, the reduction in incorrectly completed certificates was 30%. In Peru, the reduction in incorrect certificates was 30% after implementation and training on an online system only and 43% after training on both the online system and basic medical certification principles. CONCLUSIONS: The results of this study indicate that a variety of training strategies can produce benefits in the quality of certification, but further improvements are possible. The experiences of D4H suggest several aspects of the strategies that should be further developed to improve outcomes, particularly key stakeholder engagement from early in the intervention and local committees to oversee activities and support an improved culture in hospitals to support better diagnostic skills and practices.

Specialized pro-resolving lipid mediators are differentially altered in peripheral blood of patients with multiple sclerosis and attenuate monocyte and blood-brain barrier dysfunction.

Chronic inflammation is a key pathological hallmark of multiple sclerosis (MS) and suggests that resolution of inflammation, orchestrated by specialized pro-resolving lipid mediators (LM), is impaired. Here, through targeted-metabololipidomics in peripheral blood of patients with MS, we revealed that each disease form was associated with distinct LM profiles that significantly correlated with disease severity. In particular, relapsing and progressive MS patients were associated with high eicosanoids levels, whereas the majority of pro-resolving LM were significantly reduced or below limits of detection and correlated with disease progression. Furthermore, we found impaired expression of several pro-resolving LM biosynthetic enzymes and receptors in blood-derived leukocytes of MS patients. Mechanistically, differentially expressed mediators like LXA4, LXB4, RvD1 and PD1 reduced MS-derived monocyte activation and cytokine production, and inhibited inflammation-induced blood-brain barrier dysfunction and monocyte transendothelial migration. Altogether, these findings reveal peripheral defects in the resolution pathway in MS, suggesting pro-resolving LM as novel diagnostic biomarkers and potentially safe therapeutics.

Monitoring progress in reducing maternal mortality using verbal autopsy methods in vital registration systems: what can we conclude about specific causes of maternal death?

Reducing maternal mortality is a key focus of development strategies and one of the indicators used to measure progress towards achieving the Sustainable Development Goals. In the absence of medical certification of the cause of deaths that occur in the community, verbal autopsy (VA) methods are the only available means to assess levels and trends of maternal deaths that occur outside health facilities. The 2016 World Health Organization VA Instrument facilitates the identification of eight specific causes of maternal death, yet maternal deaths are often unsupervised, leading to sparse and generally poor symptom reporting to inform a reliable diagnosis using VAs. There is little research evidence to support the reliable identification of specific causes of maternal death in the context of routine VAs. We recommend that routine VAs are only used to capture the event of a maternal death and that more detailed follow-up interviews are used to identify the specific causes.

On the estimation of population cause-specific mortality fractions from in-hospital deaths.

BACKGROUND: Almost all countries without complete vital registration systems have data on deaths collected by hospitals. However, these data have not been widely used to estimate cause of death (COD) patterns in populations because only a non-representative fraction of people in these countries die in health facilities. Methods that can exploit hospital mortality statistics to reliably estimate community COD patterns are required to strengthen the evidence base for disease and injury control programs. We propose a method that weights hospital-certified causes by the probability of death to estimate population cause-specific mortality fractions (CSMFs). METHODS: We used an established verbal autopsy instrument (VAI) to collect data from hospital catchment areas in Chandpur and Comilla Districts, Bangladesh, and Bohol province, the Philippines, between 2011 and 2014, along with demographic covariates for each death. Hospital medical certificates of cause of death (death certificates) were collected and mapped to the corresponding cause categories of the VAI. Tariff 2.0 was used to assign a COD for community deaths. Logistic regression models were created for broad causes in each country to calculate the probability of in-hospital death, given a set of covariate values. The reweighted CSMFs for deaths in the hospital catchment population, represented by each hospital death, were calculated from the corresponding regression models. RESULTS: We collected data on 4228 adult deaths in the Philippines and 3725 deaths in Bangladesh. Short time to hospital and education were consistently associated with in-hospital death in the Philippines and absence of a disability was consistently associated with in-hospital death in Bangladesh. Non-communicable diseases (excluding stroke) and stroke were the leading causes of death in both the Philippines (33.9%, 19.1%) and Bangladesh (46.1%, 21.1%) according to the reweighted method. The reweighted method generally estimated CSMFs that fell between those derived from hospitals and those diagnosed by Tariff 2.0. CONCLUSIONS: Statistical methods can be used to derive estimates of cause-specific probability of death in-hospital for Bangladesh and the Philippines to generate population CSMFs. In regions where hospital death certification is of reasonable quality and routine verbal autopsy is not applied, these estimates could be applied to generate cost-effective and robust CSMFs for the population.

Improving coverage of civil registration and vital statistics, Bangladesh.

PROBLEM: Bangladesh has no national system for registering deaths and determining their causes. As a result, policy-makers lack reliable and complete data to inform public health decisions. APPROACH: In 2016, the government of Bangladesh introduced a pilot project to strengthen the civil registration and vital statistics system and generate cause of death data in Kaliganj Upazila. Community-based health workers were trained to notify births and deaths to the civil registrar, and to conduct verbal autopsy interviews with family members of a deceased person. International experts in cause-of-death certification and coding trained master trainers on how to complete the international medical certificate of cause of death. These trainers then trained physicians and coders. LOCAL SETTING: Kaliganj Upazila has an estimated population of 304 600, and 5600 births and 1550 deaths annually. Health assistants and family welfare assistants make regular visits to households to track certain health outcomes. RELEVANT CHANGES: Following the start of the project in 2016, the number of births registered within 45 days rose from 873 to 4630 in 2018. The number of deaths registered within 45 days increased from 458 to 1404. During this period, health assistants conducted 7837 verbal autopsy interviews. Between January 2017 and December 2018, 105 master trainers and more than 7000 physicians were trained to complete the international medical certificate of cause of death and they completed more than 12 000 certificates. LESSONS LEARNT: Training community-based health workers, physicians and coders were successful approaches to improve death registration completeness and availability of cause-of-death data.

New maresin conjugates in tissue regeneration pathway counters leukotriene D4-stimulated vascular responses.

Resolution of acute inflammation is governed, in part, by lipid mediator class switching from proinflammatory eicosanoids to specialized proresolving mediators, including a recently identified new pathway of mediators, termed maresin conjugates in tissue regeneration (MCTR), which includes MCTR1, MCTR2, and MCTR3. Here, we addressed whether each MCTR can impact the known vascular actions of cysteinyl leukotrienes. Leukotriene D4 (LTD4; 1.5 nmol/mouse) initiated vascular leakage in mouse cremaster vessels, which was reduced (>75%) by MCTR1 and MCTR2 (0.15 nmol each). With isolated Ciona intestinalis (sea squirt) primordial hearts, LTD4 (1-100 nM) induced negative inotropic action and lowered heartbeats 20-30%. Each MCTR (1-100 nM) prevented LTD4-reduced heart rates. With human cysteinyl leukotriene receptor-1 (CysLT1) expressed in CHO cells, each MCTR (10-100 nM) significantly reduced LTD4-initiated signaling. To assess the contribution of CysLT1 in the proresolving actions of MCTR, we carried out human macrophage (MΦ) phagocytosis. Each MCTR (0.1-10 nM) stimulated human MΦ phagocytosis of live Escherichia coli, whereas LTD4 did not stimulate phagocytosis. MCTR-activated phagocytosis was significantly blocked by a pharmacologic receptor antagonist (MK571). With both CHO-CysLT1 and human MΦs, each MCTR competed for specific [3H]-LTD4 binding with apparent lower affinity than LTD4. Thus, each MCTR functionally interacts with human CysLT1 to pharmacologically counter-regulate vascular responses and stimulate physiologic phagocytosis with MΦs.-Chiang, N., Riley, I. R., Dalli, J., Rodriguez, A. R., Spur, B. W., Serhan, C. N. New maresin conjugates in tissue regeneration pathway counters leukotriene D4-stimulated vascular responses.

Robustness of the Tariff method for diagnosing verbal autopsies: impact of additional site data on the relationship between symptom and cause.

BACKGROUND: Verbal autopsy (VA) is increasingly being considered as a cost-effective method to improve cause of death information in countries with low quality vital registration. VA algorithms that use empirical data have an advantage over expert derived algorithms in that they use responses to the VA instrument as a reference instead of physician opinion. It is unclear how stable these data driven algorithms, such as the Tariff 2.0 method, are to cultural and epidemiological variations in populations where they might be employed. METHODS: VAs were conducted in three sites as part of the Improving Methods to Measure Comparable Mortality by Cause (IMMCMC) study: Bohol, Philippines; Chandpur and Comila Districts, Bangladesh; and Central and Eastern Highlands Provinces, Papua New Guinea. Similar diagnostic criteria and cause lists as the Population Health Metrics Research Consortium (PHMRC) study were used to identify gold standard (GS) deaths. We assessed changes in Tariffs by examining the proportion of Tariffs that changed significantly after the addition of the IMMCMC dataset to the PHMRC dataset. RESULTS: The IMMCMC study added 3512 deaths to the GS VA database (2491 adults, 320 children, and 701 neonates). Chance-corrected cause specific mortality fractions for Tariff improved with the addition of the IMMCMC dataset for adults (+ 5.0%), children (+ 5.8%), and neonates (+ 1.5%). 97.2% of Tariffs did not change significantly after the addition of the IMMCMC dataset. CONCLUSIONS: Tariffs generally remained consistent after adding the IMMCMC dataset. Population level performance of the Tariff method for diagnosing VAs improved marginally for all age groups in the combined dataset. These findings suggest that cause-symptom relationships of Tariff 2.0 might well be robust across different population settings in developing countries. Increasing the total number of GS deaths improves the validity of Tariff and provides a foundation for the validation of other empirical algorithms.

Estimating the pattern of causes of death in Papua New Guinea.

BACKGROUND: Papua New Guinea (PNG) is a diverse country with high mortality and evidence of increased prevalence of non-communicable diseases (NCDs), but there is no reliable cause of death (COD) data because civil registration is insufficient and routine health data comprise only a small proportion of deaths. This study aims to estimate cause-specific mortality fractions (CSMFs) for five broad groups of causes (endemic infections, emerging infections, endemic NCDs, emerging NCDs and injuries), by sex for each of PNG's provinces. METHODS: CSMFs are calculated as the average of estimates obtained from: (1) Empirical cause method: Utilising available Verbal Autopsy (VA) data and Discharge Health Information System (DHIS) data, and applying statistical models of community versus facility CODs; and (2) Expected cause patterns method: Utilising existing estimates of mortality levels in each province and statistical models of the relationship between all-cause and cause-specific mortality using Global Burden of Disease (GBD) data. RESULTS: An estimated 41% of male and 49% of female deaths in PNG are due to infectious, maternal (female only), neonatal and nutritional causes. Furthermore, 45% of male and 42% of female deaths arise from NCDs. Infectious diseases, maternal, neonatal and nutritional conditions account for more than half the deaths in a number of provinces, including lower socioeconomic status provinces of Gulf and Sandaun, while provinces with higher CSMFs from emerging NCDs (e.g. ischemic heart disease, stroke) tend to be those where socioeconomic status is comparatively high (e.g. National Capital District, Western Highlands Province, Manus Province, New Ireland Province and East New Britain Province). Provinces with the highest estimated proportion of deaths from emerging infectious diseases are readily accessible by road and have the highest rates of sexually transmitted infections (STIs), while provinces with the highest CSMFs from endemic infectious, maternal, neonatal and nutritional causes are geographically isolated, have high malaria and high all-cause mortality. CONCLUSIONS: Infectious, maternal, neonatal and nutritional causes continue to be an important COD in PNG, and are likely to be higher than what is estimated by the GBD. Nonetheless, there is evidence of the emergence of NCDs in provinces with higher socioeconomic status. The introduction of routine VA for non-facility deaths should improve COD data quality to support health policy and planning to control both infectious and NCDs.

Maresin conjugates in tissue regeneration biosynthesis enzymes in human macrophages.

Macrophages are central in coordinating immune responses, tissue repair, and regeneration, with different subtypes being associated with inflammation-initiating and proresolving actions. We recently identified a family of macrophage-derived proresolving and tissue regenerative molecules coined maresin conjugates in tissue regeneration (MCTR). Herein, using lipid mediator profiling we identified MCTR in human serum, lymph nodes, and plasma and investigated MCTR biosynthetic pathways in human macrophages. With human recombinant enzymes, primary cells, and enantiomerically pure compounds we found that the synthetic maresin epoxide intermediate 13S,14S-eMaR (13S,14S-epoxy- 4Z,7Z,9E,11E,16Z,19Z-docosahexaenoic acid) was converted to MCTR1 (13R-glutathionyl, 14S-hydroxy-4Z,7Z,9E,11E,13R,14S,16Z,19Z-docosahexaenoic acid) by LTC4S and GSTM4. Incubation of human macrophages with LTC4S inhibitors blocked LTC4 and increased resolvins and lipoxins. The conversion of MCTR1 to MCTR2 (13R-cysteinylglycinyl, 14S-hydroxy-4Z,7Z,9E,11E,13R,14S,16Z,19Z-docosahexaenoic acid) was catalyzed by γ-glutamyl transferase (GGT) in human macrophages. Biosynthesis of MCTR3 was mediated by dipeptidases that cleaved the cysteinyl-glycinyl bond of MCTR2 to give 13R-cysteinyl, 14S-hydroxy-4Z,7Z,9E,11E,13R,14S,16Z,19Z-docosahexaenoic acid. Of note, both GSTM4 and GGT enzymes displayed higher affinity to 13S,14S-eMaR and MCTR1 compared with their classic substrates in the cysteinyl leukotriene metabolome. Together these results establish the MCTR biosynthetic pathway and provide mechanisms in tissue repair and regeneration.

The WHO 2016 verbal autopsy instrument: An international standard suitable for automated analysis by InterVA, InSilicoVA, and Tariff 2.0.

BACKGROUND: Verbal autopsy (VA) is a practical method for determining probable causes of death at the population level in places where systems for medical certification of cause of death are weak. VA methods suitable for use in routine settings, such as civil registration and vital statistics (CRVS) systems, have developed rapidly in the last decade. These developments have been part of a growing global momentum to strengthen CRVS systems in low-income countries. With this momentum have come pressure for continued research and development of VA methods and the need for a single standard VA instrument on which multiple automated diagnostic methods can be developed. METHODS AND FINDINGS: In 2016, partners harmonized a WHO VA standard instrument that fully incorporates the indicators necessary to run currently available automated diagnostic algorithms. The WHO 2016 VA instrument, together with validated approaches to analyzing VA data, offers countries solutions to improving information about patterns of cause-specific mortality. This VA instrument offers the opportunity to harmonize the automated diagnostic algorithms in the future. CONCLUSIONS: Despite all improvements in design and technology, VA is only recommended where medical certification of cause of death is not possible. The method can nevertheless provide sufficient information to guide public health priorities in communities in which physician certification of deaths is largely unavailable. The WHO 2016 VA instrument, together with validated approaches to analyzing VA data, offers countries solutions to improving information about patterns of cause-specific mortality.

Performance of InSilicoVA for assigning causes of death to verbal autopsies: multisite validation study using clinical diagnostic gold standards.

BACKGROUND: Recently, a new algorithm for automatic computer certification of verbal autopsy data named InSilicoVA was published. The authors presented their algorithm as a statistical method and assessed its performance using a single set of model predictors and one age group. METHODS: We perform a standard procedure for analyzing the predictive accuracy of verbal autopsy classification methods using the same data and the publicly available implementation of the algorithm released by the authors. We extend the original analysis to include children and neonates, instead of only adults, and test accuracy using different sets of predictors, including the set used in the original paper and a set that matches the released software. RESULTS: The population-level performance (i.e., predictive accuracy) of the algorithm varied from 2.1 to 37.6% when trained on data preprocessed similarly as in the original study. When trained on data that matched the software default format, the performance ranged from -11.5 to 17.5%. When using the default training data provided, the performance ranged from -59.4 to -38.5%. Overall, the InSilicoVA predictive accuracy was found to be 11.6-8.2 percentage points lower than that of an alternative algorithm. Additionally, the sensitivity for InSilicoVA was consistently lower than that for an alternative diagnostic algorithm (Tariff 2.0), although the specificity was comparable. CONCLUSIONS: The default format and training data provided by the software lead to results that are at best suboptimal, with poor cause-of-death predictive performance. This method is likely to generate erroneous cause of death predictions and, even if properly configured, is not as accurate as alternative automated diagnostic methods.

Assessing the quality of medical death certification: a case study of concordance between national statistics and results from a medical record review in a regional hospital in the Philippines.

BACKGROUND: Medical certificates of cause of death (MCCOD) issued by hospital physicians are a key input to vital registration systems. Deaths certified by hospital physicians have been implicitly considered to be of high quality, but recent evidence suggests otherwise. We conducted a medical record review (MRR) of hospital MCCOD in the Philippines and compared the cause of death concordance with certificates coded by the Philippines Statistics Authority (PSA). METHODS: MCCOD for adult deaths in Bohol Regional Hospital (BRH) in 2007-2008 and 2011 were collected and reviewed by a team of study physicians. Corresponding MCCOD coded by the PSA were linked by a hospital identifier. The study physicians wrote a new MCCOD using the patient medical record, noted the quality of the medical record to produce a cause of death, and indicated whether it was necessary to change the underlying cause of death (UCOD). Chance-corrected concordance, cause-specific mortality fraction (CSMF) accuracy, and chance-corrected CSMF were used to examine the concordance between the MRR and PSA. RESULTS: A total of 1052 adult deaths were linked between the MRR and PSA. Median chance-corrected concordance was 0.73, CSMF accuracy was 0.85, and chance-corrected CSMF accuracy was 0.58. 74.8% of medical records were deemed to be of high enough quality to assign a cause of death, yet study physicians indicated that it was necessary to change the UCOD in 41% of deaths, 82% of which required addition of a new UCOD. CONCLUSIONS: Medical records were generally of sufficient quality to assign a cause of death and concordance between the PSA and MRR was reasonably high, suggesting that routine mortality statistics data are reasonably accurate for describing population level causes of death in Bohol. While overall agreement between the PSA and MRR in major cause groups was sufficient for public health purposes, improvements in death certification practices are recommended to help physicians differentiate between treatable (immediate) COD and COD that are important for public health surveillance.

Comparing tariff and medical assistant assigned causes of death from verbal autopsy interviews in Matlab, Bangladesh: implications for a health and demographic surveillance system.

BACKGROUND: Deaths in developing countries often occur outside health facilities, making it extremely difficult to gather reliable cause of death (COD) information. Automated COD assignment using a verbal autopsy instrument (VAI) has been proposed as a reliable and cost-effective alternative to traditional physician-certified verbal autopsy, but its performance is still being evaluated. The purpose of this study was to compare the similarity of diagnosis by Medical Assistants (MA) in the Matlab Health and Demographic Surveillance System (HDSS) with the SmartVA Analyze 1.2 (Tariff 2.0) diagnosis. METHODS: This study took place between January 2011 and April 2014 in Matlab, Bangladesh. MA with 3 years of medical training assigned COD to Matlab residents by reviewing the information collected using the Population Health Metrics Research Consortium (PHMRC) long-form VAI. Smart VA Analyze 1.2 automatically assigned COD using the same questionnaire. COD agreement and cause-specific mortality fractions (CSMFs) were compared for MA and Tariff. RESULTS: Of the 4969 verbal autopsy cases reviewed, 4328 were adults, 296 were children, and 345 were neonates. Cohen's kappa was 0.38 (0.36, 0.40) for adults, 0.43 (0.38, 0.49) for children, and 0.27 (0.22, 0.33) for neonates. For adults, the top two COD for MA were stroke (29.6%) and ischemic heart diseases (IHD) (14.2%) and for Tariff these were stroke (32.0%) and IHD (14.0%). For children, the top two COD for MA were drowning (33.5%) and pneumonia (13.2%) and for Tariff these were also drowning (36.8%) and pneumonia (12.4%). For neonates, the top two COD for MA were birth asphyxia (41.2%) and meningitis/sepsis (22.3%) and for Tariff these were birth asphyxia (37.0%) and preterm delivery (30.9%). CONCLUSION: The CSMFs for Tariff and MA showed very close agreement across all age categories but some differences were observed for neonate preterm delivery and meningitis/sepsis. Given the known advantages of automated methods over physician certified verbal autopsy, the SmartVA software, incorporating the shortened VAI questionnaire and Tariff 2.0, could serve as a cost-effective alternative to Matlab MA to routinely collect and analyze verbal autopsy data in a HDSS to generate essential population level COD data for planning.

Collecting verbal autopsies: improving and streamlining data collection processes using electronic tablets.

BACKGROUND: There is increasing interest in using verbal autopsy to produce nationally representative population-level estimates of causes of death. However, the burden of processing a large quantity of surveys collected with paper and pencil has been a barrier to scaling up verbal autopsy surveillance. Direct electronic data capture has been used in other large-scale surveys and can be used in verbal autopsy as well, to reduce time and cost of going from collected data to actionable information. METHODS: We collected verbal autopsy interviews using paper and pencil and using electronic tablets at two sites, and measured the cost and time required to process the surveys for analysis. From these cost and time data, we extrapolated costs associated with conducting large-scale surveillance with verbal autopsy. RESULTS: We found that the median time between data collection and data entry for surveys collected on paper and pencil was approximately 3 months. For surveys collected on electronic tablets, this was less than 2 days. For small-scale surveys, we found that the upfront costs of purchasing electronic tablets was the primary cost and resulted in a higher total cost. For large-scale surveys, the costs associated with data entry exceeded the cost of the tablets, so electronic data capture provides both a quicker and cheaper method of data collection. CONCLUSIONS: As countries increase verbal autopsy surveillance, it is important to consider the best way to design sustainable systems for data collection. Electronic data capture has the potential to greatly reduce the time and costs associated with data collection. For long-term, large-scale surveillance required by national vital statistical systems, electronic data capture reduces costs and allows data to be available sooner.

Identification and Actions of the Maresin 1 Metabolome in Infectious Inflammation.

Maresin 1 (MaR1) is an immunoresolvent that governs resolution of acute inflammation, and its local metabolism in the context of infectious inflammation is of interest. In this study, we investigated the MaR1 metabolome in infectious exudates and its bioactions in regulating leukocyte responses in the context of bacterial infection. In Escherichia coli infectious exudates, MaR1 was temporally regulated with maximal levels at 4 h (2.2 ± 0.4 pg/lavage). In these exudates we also identified two novel products, and their structure elucidation gave 22-hydroxy-MaR1 and 14-oxo-MaR1. Using human primary leukocytes, we found that neutrophils primarily produced 22-OH-MaR1, whereas the main macrophage product was 14-oxo-MaR1. Both 22-OH-MaR1 and 14-oxo-MaR1 incubated with human primary macrophages gave dose-dependent increases in macrophage phagocytosis of ∼75% at 1 pM 22-OH-MaR1 and ∼25% at 1 pM 14-oxo-MaR1, whereas 14-oxo-MaR1 was less active than MaR1 at higher concentrations. Together these findings establish the temporal regulation of MaR1 during infectious inflammation, and elucidate the structures and actions of two novel MaR1 further metabolites that carry bioactivities.

Electrochemical Genetic Profiling of Single Cancer Cells.

Recent understandings in the development and spread of cancer have led to the realization of novel single cell analysis platforms focused on circulating tumor cells (CTCs). A simple, rapid, and inexpensive analytical platform capable of providing genetic information on these rare cells is highly desirable to support clinicians and researchers alike to either support the selection or adjustment of therapy or provide fundamental insights into cell function and cancer progression mechanisms. We report on the genetic profiling of single cancer cells, exploiting a combination of multiplex ligation-dependent probe amplification (MLPA) and electrochemical detection. Cells were isolated using laser capture and lysed, and the mRNA was extracted and transcribed into DNA. Seven markers were amplified by MLPA, which allows for the simultaneous amplification of multiple targets with a single primer pair, using MLPA probes containing unique barcode sequences. Capture probes complementary to each of these barcode sequences were immobilized on a printed circuit board (PCB) manufactured electrode array and exposed to single-stranded MLPA products and subsequently to a single stranded DNA reporter probe bearing a HRP molecule, followed by substrate addition and fast electrochemical pulse amperometric detection. We present a simple, rapid, flexible, and inexpensive approach for the simultaneous quantification of multiple breast cancer related mRNA markers, with single tumor cell sensitivity.