Vaginal progesterone for prevention of preterm birth in asymptomatic high-risk women with a normal cervical length: a systematic review and meta-analysis.

Objective: To determine whether vaginal progesterone reduces spontaneous preterm birth (sPTB) before 37 weeks in asymptomatic high-risk women with a singleton pregnancy and normal mid-gestation cervical length.Study design: Databases were searched (from inception to December 2020) with the search terms "progesterone" and "premature birth" or "preterm birth". Studies were screened and included if they assessed vaginal progesterone compared to placebo in women with normal cervical length. Data were pooled and synthesized in a meta-analysis using a random effects model.Data sources: MEDLINE and Embase databases.Study synthesis: Following PRISMA screening guidelines, data from 1127 women across three studies were available for synthesis. All studies had low risk of bias and were of high quality. The primary outcome was sPTB <37 weeks, with secondary outcomes of sPTB <34 weeks. Vaginal progesterone did not significantly reduce sPTB before 37 weeks, or before 34 weeks with a relative risk (RR) of 0.76 (95% CI 0.37-1.55, p = .45) and 0.51 (95% CI 0.12-2.13, p = .35), respectively.Conclusions: Vaginal progesterone does not decrease the risk of sPTB in high-risk singleton pregnancies with a normal mid-gestation cervical length.

Fast generic selection of features for neural network classifiers.

The authors describe experiments using a genetic algorithm for feature selection in the context of neural network classifiers, specifically, counterpropagation networks. They present the novel techniques used in the application of genetic algorithms. First, the genetic algorithm is configured to use an approximate evaluation in order to reduce significantly the computation required. In particular, though the desired classifiers are counterpropagation networks, they use a nearest-neighbor classifier to evaluate features sets and show that the features selected by this method are effective in the context of counterpropagation networks. Second, a method called the training set sampling in which only a portion of the training set is used on any given evaluation, is proposed. Computational savings can be made using this method, i.e., evaluations can be made over an order of magnitude faster. This method selects feature sets that are as good as and occasionally better for counterpropagation than those chosen by an evaluation that uses the entire training set.

A sampling study of bedside nursing activity in a cardiac surgical intensive care unit. Part 1: Analysis of the elements of activity in the nursing workload, and its variation with patient age group and pathology.

For a selected group of 17 patients following cardiac surgery, 33 discrete elements of nursing workload have been defined. It was possible to identify 3 broad types of activity undertaken by the bedside nurse; technical nursing care (Type 1), intermittent nursing care (Type 2), and learning activities (Type 3). The latter is the balance of the nurses time which is largely concerned with observation and liaison with other staff. The 17 patients comprised 4 groups of pathologies, 2 each representative of the adult and paediatric workload. The primary bedside nurse performs virtually all of the Type 1 activities, recruiting the assistance of a secondary nurse principally to change the patients' posture (a Type 2 activity). The only practically significant period of time spent by the secondary nurse is in clinical discussion with the bedside nurse, largely at change of shift. Statistically significant differences in bedside nursing activities between age groups can be explained by the relative physical size of the patients and equipment. However the nurse maintains a higher level of awareness with shorter periods of inattention when nursing children. A greater number of significant differences between pathologies were found within the paediatric group of patients; this may indicate that a broader spectrum of such differences is to be found in this age group. An estimate was made of the impact of computer technology on the nurse's bedside workload.

Volumetric descriptions of objects from multiple views.

Occluding contours from an image sequence with view-point specifications determine a bounding volume approximating the object generating the contours. The initial creation and continual refinement of the approximation requires a volumetric representation that facilitates modification yet is descriptive of surface detail. The ``volume segment'' representation presented in this paper is one such representation.