191 research outputs found
Thyroid antibody status, subclinical hypothyroidism, and the risk of coronary heart disease: an individual participant data analysis.
CONTEXT: Subclinical hypothyroidism has been associated with increased risk of coronary heart disease (CHD), particularly with thyrotropin levels of 10.0 mIU/L or greater. The measurement of thyroid antibodies helps predict the progression to overt hypothyroidism, but it is unclear whether thyroid autoimmunity independently affects CHD risk.
OBJECTIVE: The objective of the study was to compare the CHD risk of subclinical hypothyroidism with and without thyroid peroxidase antibodies (TPOAbs).
DATA SOURCES AND STUDY SELECTION: A MEDLINE and EMBASE search from 1950 to 2011 was conducted for prospective cohorts, reporting baseline thyroid function, antibodies, and CHD outcomes.
DATA EXTRACTION: Individual data of 38 274 participants from six cohorts for CHD mortality followed up for 460 333 person-years and 33 394 participants from four cohorts for CHD events.
DATA SYNTHESIS: Among 38 274 adults (median age 55 y, 63% women), 1691 (4.4%) had subclinical hypothyroidism, of whom 775 (45.8%) had positive TPOAbs. During follow-up, 1436 participants died of CHD and 3285 had CHD events. Compared with euthyroid individuals, age- and gender-adjusted risks of CHD mortality in subclinical hypothyroidism were similar among individuals with and without TPOAbs [hazard ratio (HR) 1.15, 95% confidence interval (CI) 0.87-1.53 vs HR 1.26, CI 1.01-1.58, P for interaction = .62], as were risks of CHD events (HR 1.16, CI 0.87-1.56 vs HR 1.26, CI 1.02-1.56, P for interaction = .65). Risks of CHD mortality and events increased with higher thyrotropin, but within each stratum, risks did not differ by TPOAb status.
CONCLUSIONS: CHD risk associated with subclinical hypothyroidism did not differ by TPOAb status, suggesting that biomarkers of thyroid autoimmunity do not add independent prognostic information for CHD outcomes
Incorporating Baseline Outcome Data in Individual Participant Data Meta-Analysis of Non-randomized Studies
Background: In non-randomized studies (NRSs) where a continuous outcome variable (e.g., depressive symptoms) is assessed at baseline and follow-up, it is common to observe imbalance of the baseline values between the treatment/exposure group and control group. This may bias the study and consequently a meta-analysis (MA) estimate. These estimates may differ across statistical methods used to deal with this issue. Analysis of individual participant data (IPD) allows standardization of methods across studies. We aimed to identify methods used in published IPD-MAs of NRSs for continuous outcomes, and to compare different methods to account for baseline values of outcome variables in IPD-MA of NRSs using two empirical examples from the Thyroid Studies Collaboration (TSC). Methods: For the first aim we systematically searched in MEDLINE, EMBASE, and Cochrane from inception to February 2021 to identify published IPD-MAs of NRSs that adjusted for baseline outcome measures in the analysis of continuous outcomes. For the second aim, we applied analysis of covariance (ANCOVA), change score, propensity score and the naïve approach (ignores the baseline outcome data) in IPD-MA from NRSs on the association between subclinical hyperthyroidism and depressive symptoms and renal function. We estimated the study and meta-analytic mean difference (MD) and relative standard error (SE). We used both fixed- and random-effects MA. Results: Ten of 18 (56%) of the included studies used the change score method, seven (39%) studies used ANCOVA and one the propensity score (5%). The study estimates were similar across the methods in studies in which groups were balanced at baseline with regard to outcome variables but differed in studies with baseline imbalance. In our empirical examples, ANCOVA and change score showed study results on the same direction, not the propensity score. In our applications, ANCOVA provided more precise estimates, both at study and meta-analytical level, in comparison to other methods. Heterogeneity was higher when change score was used as outcome, moderate for ANCOVA and null with the propensity score. Conclusion: ANCOVA provided the most precise estimates at both study and meta-analytic level and thus seems preferable in the meta-analysis of IPD from non-randomized studies. For the studies that were well-balanced between groups, change score, and ANCOVA performed similarly
Subclinical Hypothyroidism and the Risk of Stroke Events and Fatal Stroke: An Individual Participant Data Analysis.
OBJECTIVE: The objective was to determine the risk of stroke associated with subclinical hypothyroidism.
DATA SOURCES AND STUDY SELECTION: Published prospective cohort studies were identified through a systematic search through November 2013 without restrictions in several databases. Unpublished studies were identified through the Thyroid Studies Collaboration. We collected individual participant data on thyroid function and stroke outcome. Euthyroidism was defined as TSH levels of 0.45-4.49 mIU/L, and subclinical hypothyroidism was defined as TSH levels of 4.5-19.9 mIU/L with normal T4 levels.
DATA EXTRACTION AND SYNTHESIS: We collected individual participant data on 47 573 adults (3451 subclinical hypothyroidism) from 17 cohorts and followed up from 1972-2014 (489 192 person-years). Age- and sex-adjusted pooled hazard ratios (HRs) for participants with subclinical hypothyroidism compared to euthyroidism were 1.05 (95% confidence interval [CI], 0.91-1.21) for stroke events (combined fatal and nonfatal stroke) and 1.07 (95% CI, 0.80-1.42) for fatal stroke. Stratified by age, the HR for stroke events was 3.32 (95% CI, 1.25-8.80) for individuals aged 18-49 years. There was an increased risk of fatal stroke in the age groups 18-49 and 50-64 years, with a HR of 4.22 (95% CI, 1.08-16.55) and 2.86 (95% CI, 1.31-6.26), respectively (p trend 0.04). We found no increased risk for those 65-79 years old (HR, 1.00; 95% CI, 0.86-1.18) or ≥ 80 years old (HR, 1.31; 95% CI, 0.79-2.18). There was a pattern of increased risk of fatal stroke with higher TSH concentrations.
CONCLUSIONS: Although no overall effect of subclinical hypothyroidism on stroke could be demonstrated, an increased risk in subjects younger than 65 years and those with higher TSH concentrations was observed
Thyroid Function Within the Reference Range and the Risk of Stroke: An Individual Participant Data Analysis.
The currently applied reference ranges for thyroid function are under debate. Despite evidence that thyroid function within the reference range is related with several cardiovascular disorders, its association with the risk of stroke has not been evaluated previously.
We identified studies through a systematic literature search and the Thyroid Studies Collaboration, a collaboration of prospective cohort studies. Studies measuring baseline TSH, free T4, and stroke outcomes were included, and we collected individual participant data from each study, including thyroid function measurements and incident all stroke (combined fatal and nonfatal) and fatal stroke. The applied reference range for TSH levels was between 0.45 and 4.49 mIU/L.
We collected individual participant data on 43 598 adults with TSH within the reference range from 17 cohorts, with a median follow-up of 11.6 years (interquartile range 5.1-13.9), including 449 908 person-years. Age- and sex-adjusted pooled hazard ratio for TSH was 0.78 (95% confidence interval [CI] 0.65-0.95 across the reference range of TSH) for all stroke and 0.83 (95% CI 0.62-1.09) for fatal stroke. For the free T4 analyses, the hazard ratio was 1.08 (95% CI 0.99-1.15 per SD increase) for all stroke and 1.10 (95% CI 1.04-1.19) for fatal stroke. This was independent of cardiovascular risk factors including systolic blood pressure, total cholesterol, smoking, and prevalent diabetes.
Higher levels of TSH within the reference range may decrease the risk of stroke, highlighting the need for further research focusing on the clinical consequences associated with differences within the reference range of thyroid function
Incorporating Baseline Outcome Data in Individual Participant Data Meta-Analysis of Non-randomized Studies.
Background
In non-randomized studies (NRSs) where a continuous outcome variable (e.g., depressive symptoms) is assessed at baseline and follow-up, it is common to observe imbalance of the baseline values between the treatment/exposure group and control group. This may bias the study and consequently a meta-analysis (MA) estimate. These estimates may differ across statistical methods used to deal with this issue. Analysis of individual participant data (IPD) allows standardization of methods across studies. We aimed to identify methods used in published IPD-MAs of NRSs for continuous outcomes, and to compare different methods to account for baseline values of outcome variables in IPD-MA of NRSs using two empirical examples from the Thyroid Studies Collaboration (TSC).
Methods
For the first aim we systematically searched in MEDLINE, EMBASE, and Cochrane from inception to February 2021 to identify published IPD-MAs of NRSs that adjusted for baseline outcome measures in the analysis of continuous outcomes. For the second aim, we applied analysis of covariance (ANCOVA), change score, propensity score and the naïve approach (ignores the baseline outcome data) in IPD-MA from NRSs on the association between subclinical hyperthyroidism and depressive symptoms and renal function. We estimated the study and meta-analytic mean difference (MD) and relative standard error (SE). We used both fixed- and random-effects MA.
Results
Ten of 18 (56%) of the included studies used the change score method, seven (39%) studies used ANCOVA and one the propensity score (5%). The study estimates were similar across the methods in studies in which groups were balanced at baseline with regard to outcome variables but differed in studies with baseline imbalance. In our empirical examples, ANCOVA and change score showed study results on the same direction, not the propensity score. In our applications, ANCOVA provided more precise estimates, both at study and meta-analytical level, in comparison to other methods. Heterogeneity was higher when change score was used as outcome, moderate for ANCOVA and null with the propensity score.
Conclusion
ANCOVA provided the most precise estimates at both study and meta-analytic level and thus seems preferable in the meta-analysis of IPD from non-randomized studies. For the studies that were well-balanced between groups, change score, and ANCOVA performed similarly
Fertirrigação na produção de mudas de Eucalyptus grandis nos períodos de inverno e verão
Improved functionalization of oleic acid-coated iron oxide nanoparticles for biomedical applications
Superparamagnetic iron oxide nanoparticles
can providemultiple benefits for biomedical applications
in aqueous environments such asmagnetic separation or
magnetic resonance imaging. To increase the colloidal
stability and allow subsequent reactions, the introduction
of hydrophilic functional groups onto the particles’
surface is essential. During this process, the original
coating is exchanged by preferably covalently bonded
ligands such as trialkoxysilanes. The duration of the
silane exchange reaction, which commonly takes more
than 24 h, is an important drawback for this approach. In
this paper, we present a novel method, which introduces
ultrasonication as an energy source to dramatically
accelerate this process, resulting in high-quality waterdispersible nanoparticles around 10 nmin size. To prove
the generic character, different functional groups were
introduced on the surface including polyethylene glycol
chains, carboxylic acid, amine, and thiol groups. Their
colloidal stability in various aqueous buffer solutions as
well as human plasma and serum was investigated to
allow implementation in biomedical and sensing
applications.status: publishe
- …