The optimal healthy ranges of thyroid function defined by the risk of cardiovascular disease and mortality: systematic review and individual participant data meta-analysis.

BACKGROUND: Reference intervals of thyroid-stimulating hormone (TSH) and free thyroxine (FT4) are statistically defined by the 2·5-97·5th percentiles, without accounting for potential risk of clinical outcomes. We aimed to define the optimal healthy ranges of TSH and FT4 based on the risk of cardiovascular disease and mortality. METHODS: This systematic review and individual participant data (IPD) meta-analysis identified eligible prospective cohorts through the Thyroid Studies Collaboration, supplemented with a systematic search via Embase, MEDLINE (Ovid), Web of science, the Cochrane Central Register of Controlled Trials, and Google Scholar from Jan 1, 2011, to Feb 12, 2017 with an updated search to Oct 13, 2022 (cohorts found in the second search were not included in the IPD). We included cohorts that collected TSH or FT4, and cardiovascular outcomes or mortality for adults (aged ≥18 years). We excluded cohorts that included solely pregnant women, individuals with overt thyroid diseases, and individuals with cardiovascular disease. We contacted the study investigators of eligible cohorts to provide IPD on demographics, TSH, FT4, thyroid peroxidase antibodies, history of cardiovascular disease and risk factors, medication use, cardiovascular disease events, cardiovascular disease mortality, and all-cause mortality. The primary outcome was a composite outcome including cardiovascular disease events (coronary heart disease, stroke, and heart failure) and all-cause mortality. Secondary outcomes were the separate assessment of cardiovascular disease events, all-cause mortality, and cardiovascular disease mortality. We performed one-step (cohort-stratified Cox models) and two-step (random-effects models) meta-analyses adjusting for age, sex, smoking, systolic blood pressure, diabetes, and total cholesterol. The study was registered with PROSPERO, CRD42017057576. FINDINGS: We identified 3935 studies, of which 53 cohorts fulfilled the inclusion criteria and 26 cohorts agreed to participate. We included IPD on 134 346 participants with a median age of 59 years (range 18-106) at baseline. There was a J-shaped association of FT4 with the composite outcome and secondary outcomes, with the 20th (median 13·5 pmol/L [IQR 11·2-13·9]) to 40th percentiles (median 14·8 pmol/L [12·3-15·0]) conveying the lowest risk. Compared with the 20-40th percentiles, the age-adjusted and sex-adjusted hazard ratio (HR) for FT4 in the 80-100th percentiles was 1·20 (95% CI 1·11-1·31) for the composite outcome, 1·34 (1·20-1·49) for all-cause mortality, 1·57 (1·31-1·89) for cardiovascular disease mortality, and 1·22 (1·11-1·33) for cardiovascular disease events. In individuals aged 70 years and older, the 10-year absolute risk of composite outcome increased over 5% for women with FT4 greater than the 85th percentile (median 17·6 pmol/L [IQR 15·0-18·3]), and men with FT4 greater than the 75th percentile (16·7 pmol/L [14·0-17·4]). Non-linear associations were identified for TSH, with the 60th (median 1·90 mIU/L [IQR 1·68-2·25]) to 80th percentiles (2·90 mIU/L [2·41-3·32]) associated with the lowest risk of cardiovascular disease and mortality. Compared with the 60-80th percentiles, the age-adjusted and sex-adjusted HR of TSH in the 0-20th percentiles was 1·07 (95% CI 1·02-1·12) for the composite outcome, 1·09 (1·05-1·14) for all-cause mortality, and 1·07 (0·99-1·16) for cardiovascular disease mortality. INTERPRETATION: There was a J-shaped association of FT4 with cardiovascular disease and mortality. Low concentrations of TSH were associated with a higher risk of all-cause mortality and cardiovascular disease mortality. The 20-40th percentiles of FT4 and the 60-80th percentiles of TSH could represent the optimal healthy ranges of thyroid function based on the risk of cardiovascular disease and mortality, with more than 5% increase of 10-year composite risk identified for FT4 greater than the 85th percentile in women and men older than 70 years. We propose a feasible approach to establish the optimal healthy ranges of thyroid function, allowing for better identification of individuals with a higher risk of thyroid-related outcomes. FUNDING: None.

Association of statin use and lipid levels with cerebral microbleeds and intracranial hemorrhage in patients with atrial fibrillation: A prospective cohort study.

BACKGROUND: An increased risk of intracranial hemorrhage (ICH) associated with statins has been reported, but data on the relationship between statin use and cerebral microbleeds (CMBs) in patients with atrial fibrillation (AF), a population at high bleeding and cardiovascular risk, are lacking. AIMS: To explore the association between statin use and blood lipid levels with the prevalence and progression of CMBs in patients with AF with a particular focus on anticoagulated patients. METHODS: Data of Swiss-AF, a prospective cohort of patients with established AF, were analyzed. Statin use was assessed during baseline and throughout follow-up. Lipid values were measured at baseline. CMBs were assessed using magnetic resonance imagining (MRI) at baseline and at 2 years follow-up. Imaging data were centrally assessed by blinded investigators. Associations of statin use and low-density lipoprotein (LDL) levels with CMB prevalence at baseline or CMB progression (at least one additional or new CMB on follow-up MRI at 2 years compared with baseline) were assessed using logistic regression models; the association with ICH was assessed using flexible parametric survival models. Models were adjusted for hypertension, smoking, body mass index, diabetes, stroke/transient ischemic attack, coronary heart disease, antiplatelet use, anticoagulant use, and education. RESULTS: Of the 1693 patients with CMB data at baseline MRI (mean ± SD age 72.5 ± 8.4 years, 27.6% women, 90.1% on oral anticoagulants), 802 patients (47.4%) were statin users. The multivariable adjusted odds ratio (adjOR) for CMBs prevalence at baseline for statin users was 1.10 (95% CI = 0.83-1.45). AdjOR for 1 unit increase in LDL levels was 0.95 (95% CI = 0.82-1.10). At 2 years, 1188 patients had follow-up MRI. CMBs progression was observed in 44 (8.0%) statin users and 47 (7.4%) non-statin users. Of these patients, 64 (70.3%) developed a single new CMB, 14 (15.4%) developed 2 CMBs, and 13 developed more than 3 CMBs. The multivariable adjOR for statin users was 1.09 (95% CI = 0.66-1.80). There was no association between LDL levels and CMB progression (adjOR 1.02, 95% CI = 0.79-1.32). At follow-up 14 (1.2%) statin users had ICH versus 16 (1.3%) non-users. The age and sex adjusted hazard ratio (adjHR) was 0.75 (95% CI = 0.36-1.55). The results remained robust in sensitivity analyses excluding participants without anticoagulants. CONCLUSIONS: In this prospective cohort of patients with AF, a population at increased hemorrhagic risk due to anticoagulation, the use of statins was not associated with an increased risk of CMBs.

Major malformations risk following early pregnancy exposure to metformin: a systematic review and meta-analysis.

Metformin is considered as first-line treatment for type 2 diabetes and an effective treatment for polycystic ovary syndrome (PCOS). However, evidence regarding its safety in pregnancy is limited. We conducted a systematic review and meta-analysis of major congenital malformations (MCMs) risk after first-trimester exposure to metformin in women with PCOS and pregestational diabetes mellitus (PGDM). Randomized controlled trials (RCTs) and observational cohort studies with a control group investigating risk of MCM after first-trimester pregnancy exposure to metformin were searched until December 2021. ORs and 95% CIs were calculated separately according to indications and study type using Mantel-Haenszel method; outcome data were combined using random-effects model. Eleven studies (two RCTs; nine observational cohorts) met the inclusion criteria: four included pregnant women with PCOS, four included those with PGDM and three evaluated both indications separately and were considered in both indication groups. In PCOS group, there were two RCTs (57 exposed, 52 control infants) and five observational studies (472 exposed, 1892 control infants); point estimates for MCM rates in RCTs and observational studies were OR 0.93 (95% CI 0.09 to 9.21) (I2=0%; Q test=0.31; p value=0.58) and OR 1.35 (95% CI 0.37 to 4.90) (I2=65%; Q test=9.43; p value=0.05), respectively. In PGDM group, all seven studies were observational (1122 exposed, 1851 control infants); the point estimate for MCM rates was OR 1.05 (95% CI 0.50 to 2.18) (I2=59%; Q test=16.34; p value=0.01). Metformin use in first-trimester pregnancy in women with PCOS or PGDM do not meaningfully increase the MCM risk overall. However, further studies are needed to characterize residual safety concerns.

Polypill eligibility and equivalent intake in a Swiss population-based study.

The polypill has been advocated for cardiovascular disease (CVD) management. The fraction of the population who could benefit from the polypill in Switzerland is unknown. Assess (1) the prevalence of subjects (a) eligible for the polypill and (b) already taking a polypill equivalent; and (2) the determinants of polypill intake in the first (2009-2012) and second follow-ups (2014-2017) of a population-based prospective study conducted in Lausanne, Switzerland. The first and the second follow-ups included 5038 and 4596 participants aged 40-80 years, respectively. Polypill eligibility was defined as having a high CVD risk as assessed by an absolute CVD risk ≥ 5% with the SCORE equation for Switzerland and/or presenting with CVD. Four polypill equivalents were defined: statin + any antihypertensive with (A) or without (B) aspirin; statin + calcium channel blocker (CCB) (C); and statin + CCB + angiotensin-converting enzyme inhibitor (D). The prevalence of polypill eligibility was 20.6% (95% CI 19.5-21.8) and 27.7% (26.5-29.1) in the first and second follow-up, respectively. However, only around one-third of the eligible 29.5% (95% CI 26.7-32.3) and 30.4% (27.9-33.0) respectively, already took the polypill equivalents. All polypill equivalents were more prevalent among men, elderly and in presence of CVD. After multivariable adjustment, in both periods, male gender was associated with taking polypill equivalent A (OR: 1.93; 95% CI 1.45-2.55 and OR: 1.67; 95% CI 1.27-2.19, respectively) and polypill equivalent B (OR: 1.52; 95% CI 1.17-1.96 and OR: 1.41; 95% CI 1.07-1.85, respectively). Similarly, in both periods, age over 70 years, compared to middle-age, was associated with taking polypill equivalent A (OR: 11.71; CI 6.74-20.33 and OR: 9.56; CI 4.13-22.13, respectively) and equivalent B (OR: 13.22; CI 7.27-24.07 and OR: 20.63; CI 6.51-56.36, respectively). Former or current smoking was also associated with a higher likelihood of taking polypill equivalent A in both periods. A large fraction of the population is eligible for the polypill, but only one-third of them actually benefits from an equivalent, and this proportion did not change over time.

Trends and Determinants of Polypharmacy and Potential Drug-Drug Interactions at Discharge From Hospital Between 2009-2015.

BACKGROUND: Polypharmacy (PP) and excessive polypharmacy (EPP) are increasingly common and associated with risk of drug-drug interactions (DDIs). We aimed to measure the trends and determinants of PP and DDIs among patients discharged from the Department of Internal Medicine of the Lausanne University Hospital. METHODS: The retrospective study included 17,742 adult patients discharged between 2009 and 2015. Polypharmacy and EPP were defined as the concomitant prescription of five or more and ten or more drugs, respectively. Drug-drug interactions were defined as any combination of a drug metabolized by a cytochrome P450 or P-glycoprotein, and a drug considered as strong inductor or inhibitor of the corresponding enzyme was defined as a potential interaction. RESULTS: Three most commonly classes of drugs prescribed were "alimentary tract and metabolism (including insulins)," "nervous system," and "blood and blood forming organs." Polypharmacy decreased from 45% in 2009 to 41% in 2015, whereas EPP increased from 40% to 46%. In 2015, 13% of patients received 15 or more drugs. Age, coming from other health care settings, higher Charlson Index, number of comorbidities, and quartiles of length of stay were significantly and independently associated with PP and EPP. The risk of having at least one DDI decreased from 67.0% (95% confidence interval = 64.8-69.0) in 2009 to 59.3% (57.6-62.0) in 2015 (P < 0.001). Multivariate analysis showed number of drugs (odds ratio and 95% confidence interval = 3.68 [3.3-4.1], 9.39 [8.3-10.6], and 20.5 [17.3-28.4] for [5-9], [10-14], and 15+ drugs, respectively), gastrointestinal disease (3.13 [2.73-3.58]), and cancer (1.37 [1.18-1.58]) to be positively associated, and lung (0.82 [0.74-0.90]) and endocrinological (0.62 [0.52-0.74]) diseases to be negatively associated with risk of DDI. CONCLUSIONS: The pattern of drug prescription has changed and most prescribed groups increased during the study period. Excessive polypharmacy is increasing among hospital patients. The decrease in the overall risk of DDI could be due to an improved management of multidrug therapy.

Ten-Year Trend in Polypharmacy in the Lausanne Population.

BACKGROUND: Aging and associated morbidities place individuals at higher risk of polypharmacy and drug-drug interactions (DDIs). How polypharmacy and DDIs change with aging is important for public health management. OBJECTIVES: The aim of the study was to assess the 10-year trends in prevalence of polypharmacy and potential DDIs in a population-based sample. METHODS: Baseline (2003-2006) and follow-up (2014-2016) data were obtained from a sample of 4512 participants (baseline age range = 35-75 y, 55.1% women) from the population of Lausanne, Switzerland. Polypharmacy and polyactive drug use were defined by the regular use of five or more medications and five or more pharmacologically active substances, respectively. Drug-drug interactions were defined according to the criteria of the Geneva University Hospital. RESULTS: The percentage of participants taking at least one drug increased from 56.1% to 79.5% (P < 0.001). Among participants taking drugs, number of medications increased from 2.6 ± 1.9 (mean ± standard deviation) to 3.8 ± 2.9 after 10.9-year follow-up (P < 0.001); the corresponding values for active substances were 2.7 ± 2.0 and 4.0 ± 3.0 (P < 0.001). The prevalence of polypharmacy and polyactive substance use increased from 7.7% to 25.0% and from 8.8% to 27.1%, respectively (P < 0.001). The presence of at least one potential DDI increased from less than 1% to almost one sixth of all participants. CONCLUSIONS: In a community-dwelling sample, the prevalence of polypharmacy and polyactive substance use tripled during a 10.9-year follow-up, with an even greater increase in the prevalence of potential DDIs. Increasing rates of polypharmacy and DDIS warns the importance of preventing potential DDIs throughout healthcare system through various interventions.

Polypharmacy, defined as taking five or more drugs, is inadequate in the cardiovascular setting.

BACKGROUND: By how much polypharmacy (defined by number of drugs) differs from polyactive ingredient use (defined by the number of pharmacologically active ingredients) has not been assessed. OBJECTIVES: To compare the extent of polypharmacy vs. polyactive ingredients among patients taking cardiovascular (CV) medicines. METHODS: Prospective, 10-year follow-up study conducted among 880 participants of the CoLaus study taking CV drugs at baseline. Polypharmacy was defined as the use of five or more CV medicines; polyactive ingredient use was defined as the use of five or more pharmacologically active CV ingredients. RESULTS: The prevalence of polypharmacy increased from 1.4% (0.7-2.4) (prevalence rate [95% confidence interval]) at baseline to 11.9% (9.9-14.3) at follow-up, and the prevalence of polyactive ingredients increased from 2.4% (1.5-3.6) at baseline to almost 17.6% (15.2-20.3) at follow-up. The prevalence of combination drugs increased from 15.7% (13.3-18.3) at baseline to 25.9% (23-28.9) at follow-up, and the prevalence of three-component combination use increased from 0.1% (0.0-0.6) at baseline to 2.3% (1.4-3.5) at follow-up. At baseline, nine of 21 participants on polyactive ingredients were not considered as being on polypharmacy; at follow-up, the rate was 50 of 155 participants. CONCLUSION: Among individuals taking CV drugs, polypharmacy as defined by the number of drugs underestimates the prevalence of individuals taking five or more pharmacologically active drugs. Polypharmacy should no longer be based on the number of drugs but on the number of pharmacologically active drugs.

Prevalence and determinants of polypharmacy in Switzerland: data from the CoLaus study.

BACKGROUND: Polypharmacy is a frequent condition, but its prevalence and determinants in the Swiss mid-aged population are unknown. We aimed to evaluate the prevalence and determinants of polypharmacy in a large Swiss mid-aged population-based sample. METHODS: Data from 4938 participants of the CoLaus study (53% women, age range 40-81 years) were collected between 2009 and 2012. Polypharmacy was defined by the regular use of five or more drugs. RESULTS: Polypharmacy was reported by 580 participants [11.8%, 95% confidence interval (10.9; 12.6)]. Participants on polypharmacy were significantly older (mean ± standard deviation: 66.0 ± 9.1 vs. 56.6 ± 10.1 years), more frequently obese (35.9% vs. 14.7%), of lower education (66.6% vs. 50.7%) and former smokers (46.7% vs. 36.4%) than participants not on polypharmacy. These findings were confirmed by multivariate analysis: odds ratio and (95% confidence interval) for age groups 50-64 and 65-81 relative to 40-49 years: 2.90 (2.04; 4.12) and 10.3 (7.26; 14.5), respectively, p for trend < 0.001; for low relative to high education: 1.56 (1.17; 2.07); for overweight and obese relative to normal weight participants: 2.09 (1.65; 2.66) and 4.38 (3.39; 5.66), respectively, p for trend < 0.001; for former and current relative to never smokers: 1.42 (1.14, 1.75) and 1.63 (1.25, 2.12), respectively, p for trend < 0.001. CONCLUSION: One out of nine participants of our sample is on polypharmacy. Increasing age, body mass index, smoking and lower education independently increase the likelihood of being on polypharmacy.

Determinants of change in polypharmacy status in Switzerland: the population-based CoLaus study.

OBJECTIVES: This study aimed to assess the prevalence, the change, and the determinants of change in polypharmacy in a population-based sample. METHODS: Baseline (2003-2006) and follow-up (2009-2012) data are from 4679 participants aged between 35 and 75 years (53.5% women, mean age 52.6 ± 10.6 years) from the population of Lausanne, Switzerland. Polypharmacy was defined by the regular use of ≥5 drugs. Four categories of change were defined: never (no polypharmacy at baseline and follow-up), initiating (no polypharmacy at baseline but at follow-up), maintaining, or quitting. RESULTS: Polypharmacy increased from 7.7% at baseline to 15.3% at follow-up. Cardiovascular drugs were the most prescribed medicines at baseline and follow-up. Gender, age, obesity, smoking, previously diagnosed hypertension, or diabetes or dyslipidemia were significantly and independently associated with initiating and maintaining polypharmacy. CONCLUSION: In a population-based sample, prevalence of polypharmacy doubled over a 5.6-year period. The main determinants of initiating polypharmacy were age, overweight and obesity, smoking status, and previously diagnosed cardiovascular risk factors.