There has been a shift from the group category of “perinatal causes” based on the Perinatal chapter of ICD2, to programmatic categories for causes of neonatal deaths (Chapter 4). Six selected categories, with a residual group of ‘neonatal other’ were outlined in Table 4.1 and have been used for the multi-cause modelling. While a few are single causes, such as neonatal tetanus, most are causal categories and some such as congenital include hundreds of specific diagnoses. Where the health information system capacity allows this, analysing more detail within these causal categories may be useful for programmatic planning and tracking. Table 8.3 proposes relevant sub groups possible through facility data, and VR data which can map onto the basic 7 categories which are possible in VA data. This layered approach allows comparison across different countries and levels of data capacity, but still enables high income, high data capacity settings to have more complex and detailed information.
Table ⑲8.3 Case definitions for neonatal cause-of-death showing mapping of seven programmatic categories which are possible in Verbal Autopsy onto more detailed categories possible where complex data collection is at high coverage
Cause-of-death Congenital abnormalities Chromosomal abnormalities
Cardiac defects Neural tube defects
Other major structural abnormalities (e.g.
abdominal wall, gastro-intestinal, genitor
Neonatal tetanus Neonatal death due to tetanus - Preterm birth Surfactant deficiency (Respiratory distress
syndrome),
Pneumonia/ acute respiratory tract infection Other neonatal infection
Specific organisms Specific
complications
Diarrhoea Neonatal death due to diarrhoea Specific organisms
Other Neonatal jaundice
Haemorrhagic disease of the newborn Term baby dying due to in-utero growth restriction
Sudden Infant Death Syndrome Injury (deliberate and accidental)
Multiple codes possible in ICD
Case definitions do have an effect on proportionate outcome, particularly for “birth asphyxia”
(Chapter 4), but the major effect on proportionate mortality comes from varying the hierarchy.130 For example the WHO and London School of Hygiene and Tropical Medicine child survival VA tool which categorised all deaths in the first 3 days of life as “early perinatal”.52 In addition, since diarrhoea was the first category in the hierarchy and congenital was far down the hierarchy, a baby with a neural tube defect and incontinence would be coded as dying from diarrhoea. The next generation of VA tools in the late 1990s followed two different approaches in attributed cause-of-death amongst preterm babies. One extreme is to assume that for all preterm babies who die, preterm is assigned as the cause. This does not follow ICD rules, and also results in the vast majority of deaths in one large category (60 to 95%) which reduces the value for public health prioritisation. At the other extreme, preterm birth is the last on the hierarchy and so it is only considered a cause if the baby did not die of anything else. It also classifies all babies not breathing at birth as being due to “birth asphyxia”, which is an over-estimate for intrapartum neonatal deaths in term babies and an underestimate for preterm birth complications.208 Adapting from NICE,65 the CHERG expert group developed a hierarchy (Figure 8.2) which has since been used by several large VA studies, including in India56 and Ghana.99;141
Figure １７ 8.2 Hierarchical classification system for causes of neonatal death used by the Child health Epidemiology Reference Group
Unexplained cause of death in the neonatal period Other specific cause in the neonatal period
(eg, jaundice, haemorhagic disease of the newborn, injuries)
Diarrhoea
Neonatal infections
(sepsis, pneumonia, meningitis)
Intrapartum‐related
Preterm direct complications or gestational age <34 weeks (approx equivalent of < 2000 gms birthweight)
Neonatal Tetanus Congenital abnormality
Neonatal deaths
Note: the hierarchy is consistent with table 4.1. If congenital abnormality and neonatal tetanus are both present then expert opinion may be required to determine the primary underlying cause. Congenital abnormalities are markedly underestimated in verbal autopsy data as only obvious external abnormalities will be detected and congenital heart disease is commonly misclassified as infection.
How to collect the data?
As with counting pregnancy outcomes, the potential data mechanisms for cause-of-death will vary by country. For high income countries, VR data are high coverage but not always high quality. There are multiple codes used for causes of death in the neonatal period – in this analysis we identified around 12 000 codes across the 83 countries. WHO have proposed a marker of quality for VR based on the proportion of cause-of-death codes that are considered to be “garbage” codes.133
For low and middle income countries, while increasing coverage and quality of VR is important, in the short to medium term other larger scale data collection mechanisms are urgently required, not just for neonatal cause-of-death but also for child and potentially stillbirths and maternal deaths. The main options were outlined in Chapter 5 and include Sample Registration sites, networks of DSS such as the INDEPTH network (see page 16 for more detail), follow-up studies after national DHS and special research studies. Follow-up studies after nationally representative DHS are especially promising, for example in Bangladesh,209 Egypt168 and a recent one in Pakistan which is the first to include stillbirths and maternal, neonatal and child deaths (Prof ZA Bhutta, personal communication). If investing in these or other special studies for cause-of-death or morbidity data, it would be crucial to consider quality criteria in designing sample size, seasonality issues and use of standard tools so that the data will be comparable and useful for policy and programmes.
One recently suggested option is that of using data collected at health facilities and correcting for known biases with modelling. Facility data may differ systematically from population based data in a predictable manner - the case mix, for example, might show a higher proportion of intrapartum-related neonatal deaths in high-risk and referred infants. Such modelling could provide a useful, and inexpensive, tracking method.
Advancing the tools and key research gaps
Recently the Health Metrics Network have facilitated a process to develop standard VA data collection forms for neonatal deaths, child deaths aged 1 month to 5 years and all deaths from 5 years to old age.131 The neonatal VA form is only 8 pages long and takes around 30 minutes to administer.27 The variables provide enough information to categorise a stillbirth into intrapartum or antenatal as well as attribute a neonatal death to any of the 6 specific categories and also to jaundice and haemorrhagic disease of the newborn. This allows comparable cause-of-death with high income countries, mapping with ICD codes.
A standard VA questionnaire is an important step, but will not necessarily prevent questionable variation in cause-proportionate mortality patterns if subsequent steps remain unstandardised.
However there is as yet no specific algorithm or guide for attributing causes of death. More research is required to compare expert opinion as used in most VA studies, with expert option using an algorithm (as per the recent Ghana Kintampo VA study),99 with computer algorithms.
The Bill & Melinda Gates Foundation Grand Challenges VA research group based at Johns Hopkins are attempting to develop computer algorithms (Baqui, personal communication).
Another important area of research for VA is to detail the implications of varying algorithms.
Recent analysis by Lee and colleagues130 using a dataset from Nepal has examined various hierarchies for birth asphyxia and shows major differences in the proportionate mortality attributed to birth asphyxia depending if it is put above or below preterm birth in the hierarchy.
Through another Gates Grand Challenges grant Murray and colleagues are using probabilistic approaches to allocate cause-of-death.30 All of these hold potential to make verbal autopsy both more standardised and also less reliant on time-intensive expert input which may extend the use of the tools beyond research teams.
8.3.3 Neonatal morbidity and risk factors