Effect of the interval between pregnancies on perinatal outcomes.

BACKGROUND: A short interval between pregnancies has been associated with adverse perinatal outcomes. Whether that association is due to confounding by other risk factors, such as maternal age, socioeconomic status, and reproductive history, is unknown. METHODS: We evaluated the interpregnancy interval in relation to low birth weight, preterm birth, and small size for gestational age by analyzing data from the birth certificates of 173,205 singleton infants born alive to multiparous mothers in Utah from 1989 to 1996. RESULTS: Infants conceived 18 to 23 months after a previous live birth had the lowest risks of adverse perinatal outcomes; shorter and longer interpregnancy intervals were associated with higher risks. These associations persisted when the data were stratified according to and controlled for 16 biologic, sociodemographic, and behavioral risk factors. As compared with infants conceived 18 to 23 months after a live birth, infants conceived less than 6 months after a live birth had odds ratios of 1.4 (95 percent confidence interval, 1.3 to 1.6) for low birth weight, 1.4 (95 percent confidence interval, 1.3 to 1.5) for preterm birth, and 1.3 (95 percent confidence interval, 1.2 to 1.4) for small size for gestational age; infants conceived 120 months or more after a live birth had odds ratios of 2.0 (95 percent confidence interval, 1.7 to 2.4);1.5 (95 percent confidence interval, 1.3 to 1.7), and 1.8 (95 percent confidence interval, 1.6 to 2.0) for these three adverse outcomes, respectively, when we controlled for all 16 risk factors with logistic regression. CONCLUSIONS: The optimal interpregnancy interval for preventing adverse perinatal outcomes is 18 to 23 months.

Effective retrieval in Hospital Information Systems: the use of context in answering queries to Patient Discharge Summaries.

The move towards the electronic storage of medical records in Hospital Information Systems (HISs) presents significant challenges for AI retrieval techniques. In this paper, we argue that adequate information retrieval in such systems will have to rely on the exploitation of the conceptual knowledge in those records rather than superficial string searches. However, this course of action is dependent on the developments of natural language processing techniques and on retrieval systems that can exploit semantic/conceptual knowledge. We present a retrieval system, which attempts to realise the second of these developments. This system, called CONIR [developed in the context of the European Community project MENELAS (AIM 2023)] operates in the domain of Patient Discharge Summaries on coronary illness. CONIR uses flexible retrieval techniques, that exploit conceptual context information, over a database of elaborated semantic records. In the course of the paper we outline the sorts of knowledge structures that are required to do this type of retrieval and indicate how they are constructed.