PREVALENCE RATE DIFFERENCES BASED ON HERDMATE COMPARISONS

A non-random survey of ovine progressive pneumonia (OPP) seropositive prevalence rates among 16,827 sheep in 29 states in the United states revealed large breed differences, a higher prevalence rate among older sheep and an unexplainable female rate that was more that three times the male rate. The herdmate comparison procedure, successfully used in evaluating dairy bulls, was adapted to compare the prevalence of a breed to the rate of its herdmates within herds. Likewise, sex and age differences in OPP prevalence were compared within herds that contained animals of both sexes and several ages. Using herdmate comparisons, breed and age differences in OPP prevalence remained but the sex difference disappeared

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Calibrating and Validating Deterministic Traffic Models: Application to the HCM Control Delay at Signalized Intersections”, presented at the 84 th Annual Meeting of TRB

Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF)

Regression Models For Air Pollution And Daily Mortality: Analysis Of Data From Birmingham, Alabama

In recent years, a very large literature has built up on the human health effects of air pollution. Many studies have been based on time series analyses in which daily mortality counts, or some other measure such as hospital admissions, have been decomposed through regression analysis into contributions based on long-term trend and seasonality, meteorological effects, and air pollution. There has been a particular focus on particulate air pollution represented by PM 10 (particulate matter of aerodynamic diameter 10 m or less), though in recent years more attention has been given to very small particles of diameter 2.5m or less. Most of the existing data studies, however, are based on PM 10 because of the wide availability of monitoring data for this variable. The persistence of the resulting effects across many different studies is widely cited as evidence that this is not mere statistical association but indeed establishes a causal relationship. These studies have been cited by the Un..

Assessing uncertainties in traffic simulation: a key component in model calibration and validation

Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF)