SUMMARY Background

Aim: Research shows that subclinical hypothyroidism (SCH) is related to an increased carotid intima –media thickness (CIMT), a surrogate marker of subclinical cardiovascular disease (CVD). It is controversial whether or not SCH should be treated to reduce CVD morbidity and mortality. This meta-analysis aimed to determine whether SCH is associated with an increase in CIMT as compared to Euthyroidism (EU) and whether thyroxin (T4) treatment in SCH can reverse the change in CIMT.Methods: Two independent reviewers conducted an extensive database research up to December 2016. A total of 12 clinical trials discussed the effect of Thyroxin on CIMT values at pre- and post-treatment in subjects with SCH.Results: CIMT was significantly higher among SCH (n = 280) as compared to EU controls (n = 263) at baseline; the pooled weighted mean difference (WMD) of CIMT was 0.44 mm [95% confidence interval (CI) 0.14, 0.74], p = 0.004; I2 = 65%. After treatment with thyroxin in subjects with SCH (n = 314), there was a statistically significant decrease in CIMT from pre- to post-treatment; the pooled WMD of CIMT decrease was [WMD −0.32; 95% CI (−0.47, −0.16), p = < 0.0001; I2 = 2%], and it was no longer different from EU controls [WMD 0.13 mm; 95% CI (−0.04, 0.30); p = 0.14; I2 = 27%]. The total cholesterol (TC), triglycerides (TG), and low-density lipoprotein (LDL) were higher in SCH as compared to EU controls and decreased significantly after treatment with thyroxin.Conclusion: This meta-analysis shows that thyroxin therapy in subjects with SCH significantly decreases CIMT and improves lipid profile, modifiable CVD risk factors. Thyroid hormone replacement in subjects with SCH may play a role in slowing down or preventing the progression of atherosclerosis.

Butt et al. This is an open access article distributed under the terms of the Creative Commons Attribution License CC-BY 4.0., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Reference: Fung C, Wiseman-Hakes C, Stergiou-Kita M, Nguyen M, Colantonio A (2013) Time to wake up: bridging the gap between theory and practice for sleep in occupational therapy.

Background With the growing adoption of the electronic health record (EHR) worldwide over the last decade, new opportunities exist for leveraging EHR data for detection of rare diseases. Rare diseases are often not diagnosed or delayed in diagnosis by clinicians who encounter them infrequently. One such rare disease that may be amenable to EHR-based detection is acute hepatic porphyria (AHP). AHP consists of a family of rare, metabolic diseases characterized by potentially life-threatening acute attacks and chronic debilitating symptoms. The goal of this study was to apply machine learning and knowledge engineering to a large extract of EHR data to determine whether they could be effective in identifying patients not previously tested for AHP who should receive a proper diagnostic workup for AHP.