Success based on periapical health associated with roots following 1°RCTx (83%) or 2°RCTx (80%) was similar, with 10 factors having a common effect on both, whilst the 11th factor 'EDTA as an additional irrigant' had different effects on the two treatments.

The estimated weighted pooled success rates of treatments completed at least 1 year prior to review, ranged between 68% and 85% when strict criteria were used. The reported success rates had not improved over the last four (or five) decades. The quality of evidence for treatment factors affecting primary root canal treatment outcome is sub-optimal; there was substantial variation in the study-designs. It would be desirable to standardize aspects of study-design, data recording and presentation format of outcome data in the much needed future outcome studies.

The 4-year tooth survival following primary or secondary root canal treatment was 95%, with thirteen prognostic factors common to both.

Four conditions (pre-operative absence of periapical radiolucency, root filling with no voids, root filling extending to 2 mm within the radiographic apex and satisfactory coronal restoration) were found to improve the outcome of primary root canal treatment significantly. Root canal treatment should therefore aim at achieving and maintaining access to apical anatomy during chemo-mechanical debridement, obturating the canal with densely compacted material to the apical terminus without extrusion into the apical tissues and preventing re-infection with a good quality coronal restoration.

There is growing recognition that the risk of many diseases in later life, such as type 2 diabetes or breast cancer, is affected by adult as well as early-life variables, including those operating prior to conception and during the prenatal period. Most of these risk factors are correlated because of common biologic and/or social pathways, while some are intrinsically ordered over time. The study of how they jointly influence later ("distal") disease outcomes is referred to as life course epidemiology. This area of research raises several issues relevant to the current debate on causal inference in epidemiology. The authors give a brief overview of the main analytical and practical problems and consider a range of modeling approaches, their differences determined by the degree with which associations present (or presumed) among the correlated explanatory variables are explicitly acknowledged. Standard multiple regression (i.e., conditional) models are compared with joint models where more than one outcome is specified. Issues arising from measurement error and missing data are addressed. Examples from two cohorts in the United Kingdom are used to illustrate alternative modeling strategies. The authors conclude that more than one analytical approach should be adopted to gain more insight into the underlying mechanisms.

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BackgroundThe aim of the STRIPES trial was to assess the effectiveness of providing supplementary, remedial teaching and learning materials (and an additional ‘kit’ of materials for girls) on a composite of language and mathematics test scores for children in classes two, three and four in public primary schools in villages in the Nagarkurnool division of Andhra Pradesh, India.MethodsSTRIPES was a cluster randomised trial in which 214 villages were allocated either to the supplementary teaching intervention (n = 107) or to serve as controls (n = 107). 54 of the intervention villages were further randomly allocated to receive additional kit for girls. The study was not blinded. Analysis was conducted on the intention to treat principle, allowing for clustering.ResultsComposite test scores were significantly higher in the intervention group (107 villages; 2364 children) than in the control group (106 villages; 2014 children) at the end of the trial (mean difference on a percentage scale 15.8; 95% CI 13.1 to 18.6; p<0.001; 0.75 Standard Deviation (SD) difference). Composite test scores were not significantly different in the 54 villages (614 girls) with the additional kits for girls compared to the 53 villages (636 girls) without these kits at the end of the trial (mean difference on a percentage scale 0.5; 95% CI -4.34 to 5.4; p = 0.84). The cost per 0.1 SD increase in composite test score for intervention without kits is Rs. 382.97 (£4.45, $7.13), and Rs.480.59 (£5.58, $8.94) for the intervention with kits.ConclusionsA 18 month programme of supplementary remedial teaching and learning materials had a substantial impact on language and mathematics scores of primary school students in rural Andhra Pradesh, yet providing a ‘kit’ of materials to girls in these villages did not lead to any measured additional benefit.Trial RegistrationControlled-Trials.com ISRCTN69951502

Background-Little is known about the contribution of maternal and paternal factors to the inverse association between birth weight and later blood pressure in human offspring. A study of within-and between-family associations of birth weight with blood pressure, which collected data on both parents, would address this gap in our knowledge. Methods and Results-The study examined families composed of mother, father, and 2 full sibs delivered between 38 and 41 weeks' gestation within 36 months of each other. A total of 1967 families meeting our inclusion criteria were contacted and 602 were examined (children 5 to 14 years old, 1998 to 2000). Birth weight and gestational age were available from obstetric records. Systolic blood pressure in childhood was inversely associated with birth weight within families (Ϫ2.3 mm Hg/kg, 95% CI Ϫ4.4 to Ϫ0.3) after adjustment for gestational age, sex, height, and weight at examination. The between-family effect (Ϫ1.5 mm Hg/kg, Ϫ3.1 to 0.0) was strengthened on adjustment for maternal and paternal height and weight, whereas adjustment for paternal and maternal systolic blood pressure at examination independently attenuated the effect. Conclusions-The existence of an inverse association of birth weight with systolic blood pressure within families (adjusted for height and weight at examination) demonstrates that factors that vary between pregnancies in the same woman (including fetal genotype) can influence the later blood pressure of offspring. We conclude that this apparent fetal programming effect on blood pressure will not be eliminated solely by interventions aimed at modifying growth and cumulative nutritional status from conception through childhood or other fixed characteristics of future mothers.