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Peter J Fleming

Publications and source records attributed to Peter J Fleming.

9 recordsLinked to original sources
PubMed2006

Major epidemiological changes in sudden infant death syndrome: a 20-year population-based study in the UK.

BACKGROUND: Results of case-control studies in the past 5 years suggest that the epidemiology of sudden infant death syndrome (SIDS) has changed since the 1991 UK Back to Sleep campaign. The campaign's advice that parents put babies on their back to sleep led to a fall in death rates. We used a longitudinal dataset to assess these potential changes. METHODS: Population-based data from home visits have been collected for 369 consecutive unexpected infant deaths (300 SIDS and 69 explained deaths) in Avon over 20 years (1984-2003). Data obtained between 1993 and 1996 from 1300 controls with a chosen "reference" sleep before interview have been used for comparison. FINDINGS: Over the past 20 years, the proportion of children who died from SIDS while co-sleeping with their parents, has risen from 12% to 50% (p<0.0001), but the actual number of SIDS deaths in the parental bed has halved (p=0.01). The proportion seems to have increased partly because the Back to Sleep campaign led to fewer deaths in infants sleeping alone-rather than because of a rise in deaths of infants who bed-shared, and partly because of an increase in the number of deaths in infants sleeping with their parents on a sofa. The proportion of deaths in families from deprived socioeconomic backgrounds has risen from 47% to 74% (p=0.003), the prevalence of maternal smoking during pregnancy from 57% to 86% (p=0.0004), and the proportion of pre-term infants from 12% to 34% (p=0.0001). Although many SIDS infants come from large families, first-born infants are now the largest group. The age of infants who bed-share is significantly smaller than that before the campaign, and fewer are breastfed. INTERPRETATION: Factors that contribute to SIDS have changed in their importance over the past 20 years. Although the reasons for the rise in deaths when a parent sleeps with their infant on a sofa are still unclear, we strongly recommend that parents avoid this sleeping environment. Most SIDS deaths now occur in deprived families. To better understand contributory factors and plan preventive measures we need control data from similarly deprived families, and particularly, infant sleep environments.

Case-Control Studies↗
PubMed2003

Sudden unexpected deaths after discharge from the neonatal intensive care unit.

The published evidence on the risk of sudden unexpected death in infants after discharge from the neonatal intensive care unit (NICU) is reviewed, together with the relevance of the various identified potentially modifiable post-natal risk factors, particularly sleeping position. Infants of low birthweight, short gestation, and those with adverse perinatal histories are at substantially increased risk of sudden infant death syndrome (SIDS), but the potential benefits from following the measures designed to reduce the risk of SIDS are proportionally greater than for term infants. The use of home apnoea monitors has not been shown to be of value in preventing SIDS, but the importance of maintaining adequate oxygenation in infants with bronchopulmonary dysplasia is emphasised. Evidence based recommendations for care of infants after discharge from the NICU with a view to reducing the risk of SIDS are presented, and do not differ significantly from those for low-risk infants.

Female↗
PubMed2003

Sudden infant death syndrome and social deprivation: assessing epidemiological factors after post-matching for deprivation.

As part of the confidential enquiry into stillbirths and deaths in infancy (CESDI), a 3-year population-based case-control study was specifically designed to look at risk factors associated with sudden infant death syndrome (SIDS) after the dramatic fall in incidence. The study was conducted between 1993 and 1996 in five English Health Regions (population 17 million) with parental interviews for each death and four age-matched controls. The aim of this analysis was to investigate the extent to which epidemiological characteristics associated with SIDS were particular to the syndrome or more general markers for socio-economic deprivation. One control was reassigned to each case post-matched for infant age, time of sleep and socio-economic status using components of the Townsend Deprivation Score. The post-matched analysis involved 323 SIDS infants and 323 controls with a similar socio-economic profile. Notable factors significant in the original univariable analysis that became non-significant after post-matching included young maternal age (median: 23 years 4 months SIDS vs. 23 years 11 months post-matched controls), being an unsupported mother (13.6% SIDS vs. 11.1% post-matched controls) and being bottle-fed (56.7% SIDS vs. 55.4% post-matched controls). Other factors, although clearly related to deprivation, such as parental smoking, remained significant in both the univariable and multivariable post-matched analyses.

Adult↗
PubMed2002

Multiobjective optimization in quantitative structure-activity relationships: deriving accurate and interpretable QSARs.

Deriving quantitative structure-activity relationship (QSAR) models that are accurate, reliable, and easily interpretable is a difficult task. In this study, two new methods have been developed that aim to find useful QSAR models that represent an appropriate balance between model accuracy and complexity. Both methods are based on genetic programming (GP). The first method, referred to as genetic QSAR (or GPQSAR), uses a penalty function to control model complexity. GPQSAR is designed to derive a single linear model that represents an appropriate balance between the variance and the number of descriptors selected for the model. The second method, referred to as multiobjective genetic QSAR (MoQSAR), is based on multiobjective GP and represents a new way of thinking of QSAR. Specifically, QSAR is considered as a multiobjective optimization problem that comprises a number of competitive objectives. Typical objectives include model fitting, the total number of terms, and the occurrence of nonlinear terms. MoQSAR results in a family of equivalent QSAR models where each QSAR represents a different tradeoff in the objectives. A practical consideration often overlooked in QSAR studies is the need for the model to promote an understanding of the biochemical response under investigation. To accomplish this, chemically intuitive descriptors are needed but do not always give rise to statistically robust models. This problem is addressed by the addition of a further objective, called chemical desirability, that aims to reward models that consist of descriptors that are easily interpretable by chemists. GPQSAR and MoQSAR have been tested on various data sets including the Selwood data set and two different solubility data sets. The study demonstrates that the MoQSAR method is able to find models that are at least as good as models derived using standard statistical approaches and also yields models that allow a medicinal chemist to trade statistical robustness for chemical interpretability.

Algorithms↗
PubMed2002

Designing focused libraries using MoSELECT.

When designing a combinatorial library it is usually desirable to optimise multiple properties of the library simultaneously and often the properties are in competition with one another. For example, a library that is designed to be focused around a given target molecule should ideally have minimum cost and also contain molecules that are bioavailable. In this paper, we describe the program MoSELECT for multiobjective library design that is based on a multiobjective genetic algorithm (MOGA). MoSELECT searches the product-space of a virtual combinatorial library to generate a family of equivalent solutions where each solution represents a combinatorial subset of the virtual library optimised over multiple objectives. The family of solutions allows the relationships between the objectives to be explored and thus enables the library designer to make an informed choice on an appropriate compromise solution. Experiments are reported where MoSELECT has been applied to the design of various focused libraries.

Algorithms↗
PubMedDate not supplied

Combinatorial library design using a multiobjective genetic algorithm.

Early results from screening combinatorial libraries have been disappointing with libraries either failing to deliver the improved hit rates that were expected or resulting in hits with characteristics that make them undesirable as lead compounds. Consequently, the focus in library design has shifted toward designing libraries that are optimized on multiple properties simultaneously, for example, diversity and "druglike" physicochemical properties. Here we describe the program MoSELECT that is based on a multiobjective genetic algorithm and which is able to suggest a family of solutions to multiobjective library design where all the solutions are equally valid and each represents a different compromise between the objectives. MoSELECT also allows the relationships between the different objectives to be explored with competing objectives easily identified. The library designer can then make an informed choice on which solution(s) to explore. Various performance characteristics of MoSELECT are reported based on a number of different combinatorial libraries.

Algorithms↗