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Abstract

  1. Top of page
  2. Abstract
  3. Method
  4. Results
  5. Discussion
  6. Conclusion
  7. Acknowledgements
  8. References

Aim

The aim of this study was to describe the distribution of magnetic resonance imaging (MRI) patterns in a large population sample of children with cerebral palsy (CP) and to examine associations between MRI patterns, and antenatal and perinatal variables.

Method

Data were retrieved from the Victorian CP Register for 884 children (527 males, 357 females) born between 1999 and 2006. Postneonatal MRI was classified for 594 children. For 563 children (329 males, 234 females) for whom classification was to a single MRI pattern, the frequency of each variable was compared between patterns and with the population frequency.

Results

White matter injury was the most common MRI pattern (45%), followed by grey matter injury (14%), normal imaging (13%), malformations (10%), focal vascular insults (9%), and miscellaneous patterns (7%). Parity, birth gestation, level of neonatal care, Apgar score, and time to established respiration varied between MRI patterns (p<0.01). Nulliparity was most strongly associated with focal vascular insults, whereas multiparity was associated only with malformations. Grey matter injury was not associated with birth in a tertiary unit, but was strongly associated with severe perinatal compromise. The frequency of neonatal seizures and of nursery admissions was lowest among children with malformations.

Interpretation

As known risk factors for CP are differentially associated with specific MRI patterns, future exploration of causal pathways might be facilitated when performed in pathogenically defined groups.

Abbreviations
GMI

Grey matter injury

LGA

Large for gestational age

NICU

Neonatal intensive care unit

SCN

Special care nursery

SGA

Small for gestational age

WMI

White matter injury

Cerebral palsy (CP) is a disorder of movement and posture that results from a non-progressive disturbance to the developing brain.[1] The condition encompasses a variety of aetiological pathways, pathogenic mechanisms, and clinical manifestations. Magnetic resonance imaging (MRI) provides an in vivo view of brain structure and plays a pivotal role in identification of the most likely pathogenic mechanism. Particular patterns of abnormality on neuroimaging can provide clues as to the nature, timing, and severity of the cerebral injury. Consequently, investigation of potentially preventable antecedent factors is likely to be most informative when performed in subgroups based on neuroimaging patterns. Clinically defined subgroups are less useful for this purpose as different types of adverse event may result in the same clinical pattern of CP and a similar aetiology may produce variable outcomes.[2]

Three systematic reviews have amalgamated imaging data and determined the proportion of abnormal scans in children with CP; however, few of the included studies used population samples or included all CP subtypes.[2-4] More recently, CP registries have adopted comparable classification systems for imaging findings in CP. This has enabled comparison of imaging findings between contemporary population cohorts and has resulted in a small number of papers reporting associations between imaging patterns, birth gestation, and clinical variables.[5-8]

In this study, we aimed to describe the distribution of MRI patterns in a large population-based sample of children with CP and to examine associations between neuroimaging patterns, and antenatal and perinatal factors typically recorded by CP registries. The strength of evidence for causality was also considered, particularly with respect to strength of association, consistency of findings between studies, and biological plausibility. We built on previous work by using a larger, geographically defined cohort, including a range of antenatal and perinatal variables, in addition to birth gestation, and through the use of population comparison data. Our intention was that this work would set the scene for ongoing research, in which MRI characteristics, relationships with clinical outcomes, and causal pathways could be explored in greater depth.

Method

  1. Top of page
  2. Abstract
  3. Method
  4. Results
  5. Discussion
  6. Conclusion
  7. Acknowledgements
  8. References

This study was undertaken at the Murdoch Childrens Research Institute at the Royal Children's Hospital in Melbourne, Australia, and the University of Melbourne. Ethical approval was obtained from the human research ethics committee of the Royal Children's Hospital.

Data collection

Demographic, birth, and clinical data were retrieved from the Victorian Cerebral Palsy Register for children with CP who were born in the Australian state of Victoria between 1999 and 2006. Antenatal and perinatal factors previously reported to be associated with CP were extracted from the register. Small for gestational age (SGA) status was defined as birthweight at or below the 10th Australian national centile, and large for gestational age (LGA) as birthweight at or above the 90th Australian national centile.[9] Comparison data for the Victorian population were obtained from reports of statutory birth notifications in Victoria between 1999 and 2006,[10] except for the frequency of neonatal seizures. This was estimated from summed control data from a case–control study performed in Victoria and published in 2004,[11] and control data collected as part of the Western Australian case–control study of CP and perinatal death (Blair E, personal communication 2013).

Clinical MR images were assessed by one of two paediatric radiologists (CD, MD) who have between them 25 years of radiological experience at large tertiary paediatric institutions. Assessment was performed blind to clinical information and previously generated imaging reports. All available imaging and sequences were reviewed. The majority of scans were performed on 1.5-tesla magnets, all included T1- and T2-weighted axial sequences, and nearly all included sagittal sequences. Fluid-attenuated inversion recovery and diffusion-weighted imaging sequences were available in 76% and 54% of cases respectively. The most recent scan was classified to reduce the potential confounding effect of unmyelinated white matter. Scans were not classified if the quality was inadequate to distinguish between patterns, including normal from abnormal findings. Children were excluded if their most recent MRI was performed in the first 28 days of life. The classification system was adapted from one developed for a pilot study that included a cohort of children born between 2000 and 2001,[12] but also took into account classifications used for the European Cerebral Palsy Study and the broad groups used for previous systematic reviews.[2, 3, 5] Difficulties with classification were discussed and resolved between the two radiologists. Each MRI pattern is described in Table 1.

Table 1. Definitions for magnetic resonance imaging patterns used by the Victorian Cerebral Palsy Register
ClassificationDescription
NormalNo detectable abnormality
White matter injurySignal abnormality and⁄or volume loss in the periventricular and⁄or deep white matter. Ventricular dilatation, scalloping of the ventricles, and cysts may also be present
Grey matter injurySignal abnormality and⁄or volume loss predominantly involving the cortical-subcortical grey matter, deep grey matter, or both. White matter may also be involved
Focal vascular insultSignal abnormality, volume loss, or porencephaly in an established vascular territory. Includes venous sinus thrombosis and isolated haemorrhagic lesions
MalformationAbnormal formation of the brain, including cortical dysplasia, polymicrogyria, lissencephaly, pachygyria, heterotopia, schizencephaly, cerebellar hypoplasia or dysgenesis, holoprosencephaly, hydranencephaly, hydrocephalus, and agenesis of the corpus callosum. This category also includes the sequelae of intrauterine infection which may manifest as dystrophic, predominantly periventricular, calcification with or without focal white matter destruction, microcephaly, and cerebellar hypoplasia
MiscellaneousAbnormalities unable to be classified into one of the above patterns

Statistical analysis

To assess the generalizability of the MRI findings for included individuals to the entire birth year cohort, characteristics of children with and without assessed imaging were compared using a χ2 test. For children with assessed scans and a single MRI pattern, the frequency distribution of each variable within each MRI pattern was compared across MRI patterns and with the Victorian population or comparison frequency, as previously described, using χ2 tests. The resulting p-values were used as a descriptive aid to assess the strength of associations versus their respective null hypotheses. All analysis was performed using stata 12.1 software (StataCorp 2011, College Station, TX, USA).

Results

  1. Top of page
  2. Abstract
  3. Method
  4. Results
  5. Discussion
  6. Conclusion
  7. Acknowledgements
  8. References

On 1 February 2012, the Victorian Cerebral Palsy Register held records for 884 eligible children with CP. Of these, MRI findings were classified in 593 (67%). Scans for 60 (7%) children were unavailable, 230 (26%) children were not known to have undergone postneonatal MRI, and one child was excluded for quality reasons. MRI findings were less likely to be available for children born in earlier birth cohorts, born earlier than 32 weeks' gestation, or functioning at GMFCS level I or II (Table 2). The mean age at imaging was 2 years 9 months (range 1mo–11y 5mo); 163 (27%) children were under 1 year of age. The majority of assessed scans (519 [82.5%]) showed a single pattern of abnormality; 74 (12.5%) scans showed no observable abnormality and 30 (5%) scans showed dual abnormalities. The most common combinations of abnormalities were white matter injuries (WMI) and focal vascular insults (12 out of 30 scans), and WMI and malformations (5 out of 30 scans). Children whose scans showed dual abnormalities (n=30) were excluded from the final cohort (n=563).

Table 2. Characteristics of 884 children with and without MRI classification
CharacteristicNo MRIMRI classifiedp-value for difference
n % n %
  1. MRI, magnetic resonance imaging.

Year of birth
1999–200217761.028848.5<0.001
2003–200611339.030651.5
Maternal age (y)
<2052.0234.40.136
20–3922892.747892.1
40+135.3183.5
Missing4475
Previous births
011044.425647.50.670
1–312952.026749.5
4+93.6163.0
Missing4255
Sex
Male17660.735159.10.649
Female11439.324340.9
Plurality
Singleton22981.852891.0<0.001
Multiple5118.2529.0
Missing1014
Gestational age (wks)
<275218.4539.0<0.001
28–315519.57112.1
32–364014.28915.2
37+13547.937463.7
Missing87
Small for gestational age
No20478.546382.10.217
Yes5621.510117.9
Missing3030
Apgar at 5min
0–3218.6346.60.314
4–63414.05911.4
7–1018877.442482.0
Missing4777
Time to established respiration (min)
1 or less11348.328458.90.008
2–96326.912024.9
10 or intubated5824.87816.2
Missing56112
Neonatal seizures
No12169.131068.10.807
Yes5430.914531.9
Missing115139
Motor type
Spastic26493.049985.20.007
Ataxic93.2264.4
Dyskinetic62.1366.1
Hypotonic51.8254.3
Missing68
Topographical pattern
Hemiplegia10437.819635.00.024
Diplegia10337.517531.2
Quadriplegia6824.718933.8
Missing1534
Gross Motor Function Classification System level
I–II19167.734459.20.016
III–V9132.323740.8
Missing813
Epilepsy
No22079.741070.70.005
Yes5620.317029.3
Missing1414
Vision
No impairment16060.628451.80.114
Strabismus only4316.311921.7
Some impairment5119.312021.9
Functionally blind103.8254.6
Missing2646
Hearing
No impairment23487.348286.40.282
Some impairment2710.1498.8
Bilateral deafness72.6274.8
Missing2236
Intellect
No impairment12951.825348.80.442
Some impairment12048.226551.2
Missing4176
Speech
No impairment12950.420036.60.001
Some impairment7228.118934.5
Non verbal5521.515828.9
Missing3447

Distribution of MRI patterns

The distribution of MRI patterns in the 563 included children (329 males, 234 females) is shown in Figure. 1. WMI was the most common MRI pattern, evident in 45% of assessed scans from children with all CP subtypes, followed by grey matter injury (GMI [14%]), normal imaging (13%), malformations (10%), focal vascular insults (9%), and miscellaneous patterns (7%). The most common miscellaneous abnormalities were isolated ventricular dilatation, isolated volume loss in the corpus callosum, cerebellar haemorrhage, cerebellar atrophy, and Chiari malformations.

image

Figure 1. Distribution of magnetic resonance imaging patterns based on the most recent postneonatal scan and a single classification. Norm, normal; WMI, white matter injury; GMI, grey matter injury; FVI, focal vascular insult; Malf, malformation; Misc, miscellaneous.

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Antenatal and perinatal factors

There was good evidence to suggest a difference in the distribution of imaging patterns between groups for nulliparity (p=0.004), three or more previous births (p=0.002), multiple pregnancy (p=0.002), and birth gestation (p<0.001; Table 3). The distribution of MRI patterns for term versus preterm birth is shown in Figure. 2. Delivery at a tertiary hospital (p=0.002), low 5-minute Apgar scores, delayed spontaneous respiratory efforts, neonatal seizures, and neonatal care admission were also strongly associated with MRI pattern (all p<0.001).

Table 3. Factors associated with each abnormal MRI pattern for a 1999–2006 birth cohort of 563 children with CP and available MRI, including comparison frequencies from the Victorian population
FactorPopulationaWhite matter injury (nb=255)Grey matter injury (nb=81)Focal vascular insults (nb=53)Malformations (nb=58) p c
%n/total% p c n/total% p c n/total% p c n/total% p d
  1. aWhole population data from the Australian state of Victoria, except for neonatal seizures where data were obtained from previous studies. bDenominators vary because of missing data. cp-value from χ2 test for difference from the population proportion. dp-value from χ2 test for difference between magnetic resonance imaging (MRI) patterns. pc, percentile; TER, time to established respiration.

Antenatal factors
Rural residence25.444/22519.50.04221/7926.60.80611/5022.00.58112/5223.10.7030.607
Maternal birth ex-Australasia21.237/24415.20.02211/7814.10.12511/5121.60.94412/5721.10.9850.485
Maternal age <20y3.06/2172.80.8635/766.60.0662/484.20.6264/537.50.0550.314
Maternal age 40+y3.35/2172.30.4100/760.00.1074/488.30.0533/535.70.3280.036
Nulliparity42.2108/23146.80.16043/7755.80.01629/4860.40.01116/5628.60.0390.004
Parity 3+7.922/2319.50.3670/770.00.0106/4812.50.23711/5619.60.0010.002
Multiple birth3.533/25113.2<0.0013/803.80.8841/521.90.5301/561.80.4890.002
Male sex51.3151/25559.20.01251/8163.00.03531/5358.50.29431/5853.40.7490.735
SGA (<10pc)10.041/24216.9<0.00112/8114.80.15013/5125.5<0.0019/5616.10.1280.424
LGA (>90pc)10.021/2428.70.5007/818.60.6751/512.00.0574/567.20.4850.420
Birth gestation (wks)
20–270.734/25513.3<0.0010/810.00.4500/520.00.5451/571.80.319<0.001
28–310.758/25522.8<0.0011/811.20.5892/523.80.0071/571.80.319
32–365.649/25519.2<0.0019/819.90.0928/5215.40.00211/5719.3<0.001
37+93.0114/25544.7<0.00171/8188.90.14842/5280.8<0.00144/5777.2<0.001
Perinatal factors
Born at a tertiary hospital21.4107/23645.3<0.00117/7921.50.98317/5034.00.03021/5141.2<0.0010.002
Apgar at 5min <71.334/21316.0<0.00147/8058.8<0.0013/506.00.0030/490.00.422<0.001
Apgar at 5min <40.39/2134.2<0.00123/8028.8<0.0010/500.00.6980/490.00.701<0.001
TER >1min12.387/19943.7<0.00152/7371.2<0.00112/4427.30.0029/4719.10.156<0.001
TER 10+min or intubation0.532/19916.1<0.00135/7147.9<0.0011/442.30.0910/470.00.627<0.001
Neonatal intensive care unit or special care nursery admission14.7175/23474.8<0.00174/8092.5<0.00130/4862.5<0.00117/4934.7<0.001<0.001
Neonatal seizures0.746/18325.1<0.00160/7085.7<0.00116/4535.6<0.0012/484.20.004<0.001
image

Figure 2. Comparison of the distribution of term and preterm birth between magnetic resonance imaging patterns. Norm, normal; WMI, white matter injury; GMI, grey matter injury; FVI, focal vascular insult; Malf, malformation; Misc, miscellaneous.

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Factors associated with each abnormal MRI pattern

White matter injury

Compared with the total Victorian population, birth before 32 completed weeks was strongly associated with WMI (Table 3). Multiple birth, SGA status, and, to a lesser extent, male sex were all more common in children with WMI. Nearly half the group with WMI were delivered at a tertiary obstetric hospital with a neonatal intensive care unit (NICU). Signs of early neonatal compromise were common; 16% of infants were intubated after delivery or regular respiration took 10 minutes or more to be established, 75% were admitted to a NICU or special care nursery (SCN), and 25% experienced neonatal seizures.

Grey matter injury

Nearly 90% of children with GMI were born at term. Perinatal variables had the strongest associations with GMI. There was very strong evidence that children with GMI were more likely than those in the general population to have Apgar scores below 4, require intubation or more than 10 minutes' duration to establish respiration, and to experience neonatal seizures. Although 93% of children with GMI were admitted to the NICU or SCN and 86% had a history of neonatal seizures, the proportion of children with GMI born in a hospital with an NICU did not differ substantially from the proportion in the general population.

Focal vascular insults

SGA was strongly associated with focal vascular insults. Evidence was weaker for associations with young and advanced maternal age, nulliparity, multiparity, and male sex. Although 81% of children with focal vascular insults were born at term, this pattern of injury was seen relatively more often in children born between 28 weeks and 36 weeks' gestation. Focal vascular insults were also associated with lower Apgar scores and longer time for respiration to be established, but all children had a 5-minute Apgar score over 3. Approximately one-third of children had a history of neonatal seizures and two-thirds were admitted to a nursery.

Brain malformations

The strongest antenatal risk factor for cerebral malformations in children with CP was multiparity. Compared with the general Victorian population, children with brain malformations were more likely to have been delivered at 32 to 36 weeks' gestation. Even so, the majority of children (77%) were born at term. An increased probability of birth in a tertiary hospital with NICU facilities suggested that prenatal diagnosis or premature labour may have influenced the level of care., All children had Apgar scores of at least 7, one-third were admitted to an NICU or SCN, and only 2 out of 48 children had neonatal seizures.

Discussion

  1. Top of page
  2. Abstract
  3. Method
  4. Results
  5. Discussion
  6. Conclusion
  7. Acknowledgements
  8. References

These Australian data pertain to the largest known population cohort of children with CP and classified neuroimaging. Brain MRI findings in 593 children born between 1999 and 2006 were classified as normal or as exhibiting one of five patterns of abnormality that broadly reflect the pathogenesis of the cerebral abnormality. The use of a population cohort allowed assessment of sampling bias, and the decision to assess each child's imaging records without access to information on past history and clinical characteristics reduced the opportunity for the radiologists to be influenced by known associations between MRI findings and clinical information. The size of the cohort enabled exploration of associations between each MRI pattern and multiple antenatal and perinatal variables, whereas previous studies have reported associations only with clinical and birth gestation variables.

The diagnosis of CP is established clinically through the identification of signs and symptoms indicating motor impairment of cerebral origin. Brain imaging may be performed to rule out the possibility of alternative conditions that do not fall under the CP umbrella, and to provide information about the most likely pathogenic mechanism. Stratification of MRI patterns is, therefore, an ideal starting point for the exploration of causal pathways. An important finding of this study was that risk factors for CP that were already identified, including parity, plurality, birth gestation, place of birth, and condition at birth, had differentially stronger associations with particular MRI patterns. Although only a relatively small number of variables were included, there is a strong possibility that future research may identify groups of variables that share common causal pathways.

Children born earlier than 32 to 34 weeks' gestation are at a high risk of perinatally acquired intraventricular haemorrhage/periventricular haemorrhagic venous infarction and periventricular leukomalacia.[13] Consequently, it was not surprising that WMI was found to be strongly associated with preterm delivery, very low birthweight, and multiple birth. Nor was it surprising that WMI was associated with low Apgar scores and the need for intubation, particularly in the least mature neonates. The strong association with birth at a tertiary hospital suggests that the increased risk of WMI was known before delivery in at least some cases. Interestingly, although WMI was observed in 71% of children born preterm, this pattern was also seen in 32% of children born at term. Our figure of 32% was the same as that reported from a population study of term-born singletons with CP,[14] but higher than that reported by other groups.[5, 6, 8] At this stage, little is known about WMI in term-born children, apart from the fact that clinical outcomes appear to differ from the outcomes of children with WMI who were born preterm.[15, 16]

GMI was seen on MRI in 14% of all included children. Compared with all births in Victoria over the same time period,[10] children with GMI were more likely to have signs suggestive of severe perinatal compromise, including low Apgar scores, need for resuscitation, and neonatal seizures. More children with GMI than with any other MRI pattern had 5-minute Apgar scores below 7 or below 4, experienced delay in establishing spontaneous breathing, experienced neonatal seizures, or were admitted to the intensive care or special needs nursery. Most children with GMI were born at term, had a birthweight over 2500g, and were a normal weight for gestational age. They were no more likely than children without CP to be born in a tertiary hospital, suggesting that the risk of brain injury was not recognized early enough to allow in utero transfer. Taken together, these associations suggest a perinatal timing for the brain injury, although additional perinatal data would assist in confirming a diagnosis of acute encephalopathy. Researchers from Utrecht and Hammersmith previously reported that more than 90% of infants with encephalopathy had evidence of perinatally acquired lesions on MRI and a very low rate of established antenatal brain injury or other confounding diagnoses.[17] Notwithstanding the fact that antenatal factors may increase susceptibility to, or intolerance of, stress in labour, current evidence supports the view that antenatally established cerebral damage in infants with an acute encephalopathy is not common.[17]

Nine per cent of the Victorian cohort had MRI evidence of a focal vascular insult. This MRI pattern was seen relatively more frequently in male children. An explanation for the poorer outcomes in males has been suggested by animal studies performed in the context of experimental stroke, in which females demonstrated reduced sensitivity to the effects of induced ischaemia compared with males.[18]

Children with focal vascular insults were the most likely to be born to primiparous mothers. The finding of an association between primiparity and focal vascular insults supports the results of earlier studies of children with perinatal arterial ischaemic stroke.[19] It has been suggested, however, that risk factors such as prolonged second stage of labour[19] and pregnancy-induced hypertension/pre-eclampsia[20] may be confounders in the association between perinatal stroke and primiparity. A 2005 case–control study from California identified chorioamnionitis, infertility, pre-eclampsia, and prolonged second stage of labour as independent risk factors for perinatal stroke, whereas the effect of primiparity lost statistical significance on multivariable analysis.[19]

The focal vascular group accounted for the highest proportion of children who were SGA. A 2004 study from the Californian group found that intrauterine growth restriction was an independent risk factor for perinatal arterial stroke in neonatal infants who developed long-term motor impairment,[21] but their rate of SGA of 13% was substantially lower than the 25% in our study. In terms of the condition after delivery of children with focal vascular insults, our findings are consistent with the observation made by Rutherford et al. that delivery of infants following perinatal stroke can sometimes be difficult and some resuscitation may be required, but the infant usually recovers sufficiently that nursery admission is not required, even though many of these infants present with isolated seizures.[22] In our study, 36% of infants had neonatal seizures, a figure comparable to the 39% reported from the Californian cohort that included only children with motor impairment.[21]

Ten per cent of children in this Victorian cohort had a brain malformation on MRI. Malformations were the only MRI pattern that was not relatively more common in males. Furthermore, multiparity (three or more previous births) was a strong risk factor for malformations, whereas there was no strong evidence for associations between multiparity and the other MRI patterns. Term birth and a low frequency of perinatal difficulties were characteristics consistent with other reports.[2] In this study, children with malformations were those least likely to have had neonatal seizures and to require admission to the NICU or SCN.

The study has some limitations. First, we believe that our estimate of the proportion of WMI in CP, although higher than most other estimates from developed countries,[5, 8] is likely to be an underestimate. In keeping with the findings of an earlier pilot study from Victoria[12] and a study from Quebec,[8] preterm birth was associated with a reduced likelihood that MRI was available, most likely because in many children born preterm the diagnosis of WMI was established through serial cranial ultrasonography during the neonatal period. Furthermore, a proportion of those with ‘normal’ imaging may have had diffuse WMI that was undetectable using current imaging methods and qualitative assessment.[23] Second, only a small number of variables were studied; in future studies we hope to increase the number of variables studied as potential risk factors for CP.

Conclusion

  1. Top of page
  2. Abstract
  3. Method
  4. Results
  5. Discussion
  6. Conclusion
  7. Acknowledgements
  8. References

Many of the associations seen in this large, population-based study were specific to particular neuropathological groups in CP, thus demonstrating the potential benefits of stratification on neuroimaging patterns in the exploration of causal pathways and in the search for preventative strategies. Information from this preliminary study sets the scene for future research involving more detailed descriptions of each MRI pattern, associations between neuroimaging and clinical characteristics, and more exhaustive exploration of causal pathways.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Method
  4. Results
  5. Discussion
  6. Conclusion
  7. Acknowledgements
  8. References

The Lorenzo and Pamela Galli Charitable Trust funded this study. Assessment of the MRI was funded by the William Henry and Vera Ellen Houston Memorial Trust Fund and the CP Alliance. The Victorian Medical Insurance Agency Ltd and the Victorian Department of Health provided funding for the Victorian Cerebral Palsy Register. Infrastructure support was provided by the Victorian government's Operational Infrastructure Support programme and the first author's doctoral research was supported by a scholarship (2009–2012) from the Australian National Health and Medical Research Council. The Consultative Council on Obstetric and Paediatric Mortality and Morbidity provided population data for the project from the Victorian Perinatal Data Collection. The authors have stated that they had no interests which might be perceived as posing a conflict or bias.

References

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  2. Abstract
  3. Method
  4. Results
  5. Discussion
  6. Conclusion
  7. Acknowledgements
  8. References
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