IntroductionThe discharge of patients from the intensive care unit (ICU) to a hospital ward is a common transition of care that is associated with error and adverse events. Risk stratification tools may help identify high-risk patients for targeted interventions, but it is unclear if proper tools have been developed.MethodsWe searched Ovid EMBASE, Ovid MEDLINE, CINAHL, PUBMED and Cochrane Central Register of Controlled Trials from the earliest available date through March 2013, plus reference lists and citations of all studies included in the systematic review. Cohort studies were selected that described the derivation, validation or clinical impact of tools for predicting medical emergency team activation, ICU readmission or mortality following patient discharge from the ICU. Data were extracted on the study design, setting, population, sample size, tool (components, measurement properties) and outcomes.ResultsThe literature search identified 9,926 citations, of which eight studies describing eight tools met the inclusion criteria. Reported outcomes included ICU readmission (n = 4 studies), hospital mortality (n = 3 studies) and both ICU readmission and hospital mortality (n = 1 studies). Seven of the tools were comprised of distinct measurable component variables, while one tool used subjective scoring of patient risk by intensive care physicians. The areas under receiver operator curves were reported for all studies and ranged from 0.66 to 0.92. A single study provided a direct comparative analysis between two tools. We did not find any studies evaluating the impact of risk prediction on processes and outcomes of care.ConclusionsEight risk stratification tools for predicting severe adverse events following patient discharge from ICU have been developed, but have undergone limited comparative evaluation. Although risk stratification tools may help clinician decision-making, further evaluation of the existing tools' effects on care is required prior to clinical implementation.

OBJECTIVES: Recent studies have connected increased fluoride exposure with increased risk of neurodevelopmental-related outcomes, such as ADHD (attention deficit hyperactivity disorder) and lower IQ in children. Our primary objective was to examine the association between fluoride exposure and reported diagnosis of a learning disability among a population-based sample of Canadian children aged 3-12 years. METHODS:We analyzed data from Cycles 2 and 3 of the Canadian Health Measures Survey. Four measures of fluoride exposure were available: 1) urinary fluoride (μmol/L), 2) creatinine-adjusted urinary fluoride (μmol/mmol), 3) specific gravity-adjusted urinary fluoride (μmol/L), and 4) fluoride concentration of tap water (mg/L) (Cycle 3 only). Diagnosis of a learning disability (yes/no) was based on parental-or self-report. Associations were examined using logistic regression (where possible), unadjusted and adjusted for covariates. RESULTS:When Cycles 2 and 3 were examined separately, reported learning disability diagnosis was not significantly associated with any measure of fluoride exposure in unadjusted or adjusted models. When Cycles 2 and 3 were combined, a small but statistically significant effect was observed such that children with higher urinary fluoride had higher odds of having a reported learning disability in the adjusted model (p = 0.03). However, the association was not observed in models that used creatinine-adjusted urinary fluoride and specific gravity-adjusted urinary fluoride, which are believed to be more accurate measures due to their correction for urinary dilution. CONCLUSION:Overall, there did not appear to be a robust association between fluoride exposure and parental-or self-reported diagnosis of a learning disability among Canadian children.KEY WORDS: Population; fluoridation; cognition; learning disorders; surveys and questionnaires La traduction du résumé se trouve à la fin de l'article.

IntroductionWe sought to derive literature-based summary estimates of readmission to the ICU and hospital mortality among patients discharged alive from the ICU.MethodsWe searched MEDLINE, Embase, CINAHL and the Cochrane Central Register of Controlled Trials from inception to March 2013, as well as the reference lists in the publications of the included studies. We selected cohort studies of ICU discharge prognostic factors that in which readmission to the ICU or hospital mortality among patients discharged alive from the ICU was reported. Two reviewers independently abstracted the number of patients readmitted to the ICU and hospital deaths among patients discharged alive from the ICU. Fixed effects and random effects models were used to estimate the pooled cumulative incidence of ICU readmission and the pooled cumulative incidence of hospital mortality.ResultsThe analysis included 58 studies (n = 2,073,170 patients). The majority of studies followed patients until hospital discharge (n = 46 studies) and reported readmission to the ICU (n = 46 studies) or hospital mortality (n = 49 studies). The cumulative incidence of ICU readmission was 4.0 readmissions (95% confidence interval (CI), 3.9 to 4.0) per 100 patient discharges using fixed effects pooling and 6.3 readmissions (95% CI, 5.6 to 6.9) per 100 patient discharges using random effects pooling. The cumulative incidence of hospital mortality was 3.3 deaths (95% CI, 3.3 to 3.3) per 100 patient discharges using fixed effects pooling and 6.8 deaths (95% CI, 6.1 to 7.6) per 100 patient discharges using random effects pooling. There was significant heterogeneity for the pooled estimates, which was partially explained by patient, institution and study methodological characteristics.ConclusionsUsing current literature estimates, for every 100 patients discharged alive from the ICU, between 4 and 6 patients on average will be readmitted to the ICU and between 3 and 7 patients on average will die prior to hospital discharge. These estimates can inform the selection of benchmarks for quality metrics of transitions of patient care between the ICU and the hospital ward.

BackgroundThere are concerns that altered thyroid functioning could be the result of ingesting too much fluoride. Community water fluoridation (CWF) is an important source of fluoride exposure. Our objectives were to examine the association between fluoride exposure and (1) diagnosis of a thyroid condition and (2) indicators of thyroid functioning among a national population-based sample of Canadians.MethodsWe analysed data from Cycles 2 and 3 of the Canadian Health Measures Survey (CHMS). Logistic regression was used to assess associations between fluoride from urine and tap water samples and the diagnosis of a thyroid condition. Multinomial logistic regression was used to examine the relationship between fluoride exposure and thyroid-stimulating hormone (TSH) level (low/normal/high). Other available variables permitted additional exploratory analyses among the subset of participants for whom we could discern some fluoride exposure from drinking water and/or dental products.ResultsThere was no evidence of a relationship between fluoride exposure (from urine and tap water) and the diagnosis of a thyroid condition. There was no statistically significant association between fluoride exposure and abnormal (low or high) TSH levels relative to normal TSH levels. Rerunning the models with the sample constrained to the subset of participants for whom we could discern some source(s) of fluoride exposure from drinking water and/or dental products revealed no significant associations.ConclusionThese analyses suggest that, at the population level, fluoride exposure is not associated with impaired thyroid functioning in a time and place where multiple sources of fluoride exposure, including CWF, exist.

HPV 16 and HPV 18 were the primary HPV genotypes associated with cases of invasive squamous cell carcinoma in the current Trinidad study. This strong association leads us to conclude that the HPV vaccines targeting HPV 16 and HPV 18 may contribute to reducing the cervical cancer burden in Trinidad.