Tables 1 and 2 Caross results

Processed data. Participants' characteristics and risk evaluation. Excel shee

Patient characteristics: Random sample of 1002 adults aged 50–80 years in four Swiss university primary care settings.

a<p>Defined as a coronary heart disease (CHD) event in male first-degree relatives <55 years or in female first-degree relatives <65 years.</p>b<p>A former smoker had stopped smoking ≥6 months before baseline and a current smoker was smoking at baseline or had stopped<6 months before baseline.</p>c<p>If the patient has a record of ever having the listed condition or risk factor.</p>d<p>History of transient ischemic attack, cerebral vascular accident, coronary artery disease, angina, myocardial infarction, congestive heart failure or peripheral vascular disease.</p>e<p>Depression, bipolar disorder, psychosis, schizophrenia, pervasive development disorder.</p>f<p>Chronic obstructive pulmonary disease (COPD), asthma, sleep apnea syndrome, sarcoidosis, pulmonary hypertension, bronchiectases, interstitial pulmonary disease or global respiratory insufficiency.</p>g<p>Solid metastatic, solid non-metastatic cancer, lymphoma, leukemia.</p

Number of comorbidities, Charlson index and quality of preventive care and cardiovascular preventive care, analyzed also for specific subgroups.

a<p>Data adjusted for these patients characteristics: age, sex, civil status, legal status, occupation and center. In a 2nd model we adjusted also for the number of outpatient visits by performing a Sensitivity analyses, which showed similar results.</p>b<p>Based on previous studies<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096142#pone.0096142-Collet1" target="_blank">[16]</a> and the Charlson index <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096142#pone.0096142-Charlson1" target="_blank">[20]</a>.</p>c<p>p for trend.</p>d<p>If the patient has a record of ever having the listed condition or risk factor.</p>e<p>History of transient ischemic attack, cerebral vascular accident, coronary artery disease, angina, myocardial infarction, congestive heart failure or peripheral vascular disease.</p>f<p>p-value comparing adjusted data for each subgroup to patients with 0 comorbidities.</p>g<p>Chronic obstructive pulmonary disease (COPD), asthma, sleep apnea syndrome, sarcoidosis, pulmonary hypertension, bronchiectases, interstitial pulmonary disease or global respiratory insufficiency.</p>h<p>Depression, bipolar disorder, psychosis, schizophrenia, pervasive development disorder.</p>i<p>Not further adjusted for legal status because of low number of patients with data on legal status (n = 10 of 19 patients with schizophrenia).</p>j<p>Solid metastatic, solid non-metastatic cancer, lymphoma, leukemia.</p>k<p>Lower care when metastatic cancer only (data not shown, due to small number of 16 patients).</p

Measures of multimorbidity and association with quality of preventive care.

<p>Left part: Number of comorbidities and percent of provided care for preventive care (blue line) and cardiovascular preventive care (red line), bars showing 95% confidence intervals. Right part: Respective analysis with the Charlson index. Data adjusted for age, sex, civil status, legal status, occupation and treatment center. In a second model we adjusted for number outpatient visits and found similar results.</p

Thyroid dysfunction and the risk of dementia and cognitive decline: Systematic review, meta-analysis and clinical implications

Context: While both overt hyper- and hypothyroidism are known to lead to cognitive impairment, data on the association between subclinical thyroid dysfunction and cognitive function are conflicting. Objective: To determine the risk of dementia and cognitive decline associated with subclinical thyroid dysfunction among prospective cohort studies. Data Sources: Search in MEDLINE and EMBASE (inception until November 2014) and reference lists of key articles without language restrictions. Study Selection: Two physicians identified prospective cohorts that assessed thyroid function at baseline and cognitive outcomes (dementia; Mini-Mental State Examination, MMSE). Data Extraction: Data were extracted by one reviewer following standardized protocols and verified by a second reviewer. Both reviewers independently assessed study quality. The primary outcomes were dementia and decline in cognitive function measured by MMSE. We calculated risk ratios and 95% confidence intervals using random-effects models. Data Synthesis: Eleven prospective cohorts followed 16,805 participants during a median follow-up of 44.4 months. Five studies analyzed the risk of dementia in subclinical hyperthyroidism (n=6410), six in subclinical hypothyroidism (n=7401). Five studies analyzed MMSE decline in subclinical hyperthyroidism (n=7895), seven in subclinical hypothyroidism (n=8960). In random-effects models, the pooled adjusted RR for dementia in subclinical hyperthyroidism was 1.67 (95% confidence interval [CI] 1.04-2.69) and 1.14 (95%CI 0.84-1.55) in subclinical hypothyroidism versus euthyroidism, both without evidence of significant heterogeneity (I2=0.0%). Sensitivity analyses pooling only studies with formal outcome adjudication or population-based studies yielded similar results. The pooled mean MMSE decline from baseline to follow-up (mean 32 months) did not significantly differ between subclinical hyper- or hypothyroidism versus euthyroidism. Conclusions: Subclinical hyperthyroidism might be associated with an elevated risk for dementia, while subclinical hypothyroidism is not, and both conditions are not associated with faster decline in MMSE over time. Available data are limited, and additional large, high-quality studies are needed

Participant characteristics.

<p>Participant characteristics.</p

Ft4 measures when TSH falls within the normal range.

<p>FT4 measures when TSH falls within the normal range (0.45–4.5 mU/L); 85% of abnormal fT4 measures are within 2 pmol/l (dashed lines) of the reference range (11.2 to 20.8 pmol/L, solid lines). Abbreviations: Free Thyroxine (fT4) Thyroid-Stimulating Hormone (TSH).</p

Number of individuals with low, normal, and high TSH and FT4.

<p>Number of individuals with low, normal, and high TSH and FT4.</p

Prevalence of potentially inappropriate prescribing in a subpopulation of older European clinical trial participants: a cross-sectional study

Objectives To estimate and compare the prevalence and type of potentially inappropriate prescribing (PIP) and potential prescribing omissions (PPOs) among communitydwelling older adults (≥65 years) enrolled to a clinical trial in three European countries. Design A secondary analysis of the Thyroid Hormone Replacement for Subclinical Hypothyroidism Trial dataset. Participants A subset of 48/80 PIP and 22/34 PPOs indicators from the Screening Tool of Older Persons Prescriptions/Screening Tool to Alert doctors to Right Treatment (STOPP/START) V2 criteria were applied to prescribed medication data for 532/737 trial participants in Ireland, Switzerland and the Netherlands. Results The overall prevalence of PIP was lower in the Irish participants (8.7%) compared with the Swiss (16.7%) and Dutch (12.5%) participants (P=0.15) and was not statistically significant. The overall prevalence of PPOs was approximately one-quarter in the Swiss (25.3%) and Dutch (24%) participants and lower in the Irish (14%) participants (P=0.04) and the difference was statistically significant. The hypnotic Z-drugs were the most frequent PIP in Irish participants, (3.5%, n=4), while it was non-steroidal anti-inflammatory drug and oral anticoagulant combination, sulfonylureas with a long duration of action, and benzodiazepines (all 4.3%, n=7) in Swiss, and benzodiazepines (7.1%, n=18) in Dutch participants. The most frequent PPOs in Irish participants were vitamin D and calcium in osteoporosis (3.5%, n=4). In the Swiss and Dutch participants, they were bone antiresorptive/anabolic therapy in osteoporosis (9.9%, n=16, 8.6%, n=22) respectively. The odds of any PIP after adjusting for age, sex, multimorbidity and polypharmacy were (adjusted OR (aOR)) 3.04 (95% CI 1.33 to 6.95, P<0.01) for Swiss participants and aOR 1.74 (95% CI 0.79 to 3.85, P=0.17) for Dutch participants compared with Irish participants. The odds of any PPOs were aOR 2.48 (95% CI 1.27 to 4.85, P<0.01) for Swiss participants and aOR 2.10 (95% CI 1.11 to 3.96, P=0.02) for Dutch participants compared with Irish participants. Conclusions This study has estimated and compared the prevalence and type of PIP and PPOs among this cohort of community-dwelling older people. It demonstrated a significant difference in the prevalence of PPOs between the three populations. Further research is urgently needed into the impact of system level factors as this has important implications for patient safety, healthcare provision and economic costs