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1.
Epidemiol Infect ; 151: e6, 2022 12 11.
Article in English | MEDLINE | ID: mdl-36502811

ABSTRACT

In June 2019 the Health Protection Team in Yorkshire and Humber, England, was notified of cases of hepatitis A virus (HAV) infection in staff at a secondary school. Investigation revealed that an earlier case worked as a food handler in the school kitchen. Indirect transmission through food from the canteen was considered the most likely route of transmission. Cases were described according to setting of exposure. Oral fluid was obtained from students for serological testing. Environmental investigations were undertaken at settings where food handling was considered a potential transmission risk. Thirty-three confirmed cases were linked to the outbreak. All of those tested (n = 31) shared the same sequence with a HAV IB genotype. The first three cases were a household cluster and included the index case for the school. A further 19 cases (16 students, 3 staff) were associated with the school and consistent with indirect exposure to the food handler. One late onset case could not be ruled out as a secondary case within the school and resulted in vaccination of the school population. Five cases were linked to a bakery where a case from the initial household cluster worked as a food server. No concerns about hygiene standards were noted at either the school or the bakery. Oral fluid samples taken at the time of vaccination from asymptomatic students (n = 219, 11-16 years-old) showed no evidence of recent or current infection. This outbreak included household and foodborne transmission but limited (and possibly zero) person-to-person transmission among secondary school students. Where adequate hygiene exists, secondary transmission within older students may not occur.


Subject(s)
Hepatitis A virus , Hepatitis A , Humans , Child , Adolescent , Hepatitis A virus/genetics , Disease Outbreaks/prevention & control , Schools , England/epidemiology , Students
2.
Ultrasound Obstet Gynecol ; 47(1): 104-9, 2016 Jan.
Article in English | MEDLINE | ID: mdl-25846437

ABSTRACT

OBJECTIVE: To develop a predictive tool for spontaneous preterm birth (sPTB) in asymptomatic high-risk women that includes quantification of fetal fibronectin (fFN) along with cervical length (CL) measurement and other clinical factors. METHODS: Data were analyzed that had been collected prospectively from 1249 women at high risk for sPTB attending preterm surveillance clinics. Clinicians were blinded to quantitative measurements of fFN (qfFN), although they were aware of qualitative fFN results. Parametric survival models for sPTB, with time-updated covariates, were developed and the best was selected using the Akaike and Bayesian information criteria. The model was developed on the first 624 consecutive women and validated on the subsequent 625. Fractional polynomials were used to accommodate possible non-linear effects of qfFN and CL. The estimated probability of delivery before 30, 34 or 37 weeks' gestation and within 2 or 4 weeks of testing was calculated for each patient and analyzed as a predictive test for the actual occurrence of each event. Predictive statistics were calculated to compare training and validation sets. RESULTS: The final model that was selected used a log-normal survival curve with CL, √qfFN and previous sPTB/preterm prelabor rupture of membranes as predictors. Predictive statistics were similar for training and validation sets. Areas under the receiver-operating characteristics curves ranged from 0.77 to 0.99, indicating accurate prediction across all five delivery outcomes. CONCLUSIONS: sPTB in high-risk asymptomatic women can be predicted accurately using a model combining qfFN and CL, which supersedes the single-threshold fFN test, demographic information and obstetric history. This algorithm has been incorporated into an App (QUiPP) for widespread use.


Subject(s)
Cervical Length Measurement , Cervix Uteri/diagnostic imaging , Decision Support Techniques , Fibronectins/analysis , Premature Birth/epidemiology , Adult , Area Under Curve , Asymptomatic Diseases , Bayes Theorem , Female , Humans , Pregnancy , Pregnancy, High-Risk , Prospective Studies , ROC Curve , Risk Assessment
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