Dataset Information

Impact of low-dose quetiapine-use on glycosylated hemoglobin, triglyceride and cholesterol levels.

ABSTRACT:

Objective

Quetiapine use at standard doses has been associated with hyperglycemia and dyslipidemia. However, whether even frequently prescribed low-dose quetiapine results in significant metabolic disturbances remains unclear. Thus, this study aimed to investigate the association between off-label, low-dose quetiapine and changes in glycosylated hemoglobin (HbA1c) levels/lipid parameters.

Methods

We identified new users of low-dose quetiapine (≤50 mg tablets) in Denmark 2008-2018 with measurements of HbA1c, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), or fasting triglycerides (fTG) within 365 days before and after quetiapine initiation. Mixed-effects linear regression models were used to estimate coefficients (β) with 95% confidence intervals (95%CIs) for change in cardiometabolic parameters after quetiapine initiation. Inverse probability weighting was used to mitigate selection bias. Higher doses of quetiapine (>50 mg) were included in sensitivity analyses.

Results

Among 106,711 eligible new low-dose quetiapine users (median age = 45 years, females = 55%), low-dose quetiapine initiation was associated with increased fTG (β = 1.049[95%CI:1.027-1.072]) and decreased HDL-C (β = 0.982[0.978-0.986]). Although HbA1c did not change significantly and TC and LDL-C even decreased considering all subjects, all three metabolic parameters increased significantly among individuals with normal pre-quetiapine initiation levels. The adverse metabolic effect of quetiapine on HbA1c, TC, LDL-C, and HDL-C was dose-dependent, which was not the case for fTG.

Conclusions

Low-dose quetiapine was associated with a significant increase in fTG and decreases in HDL-C in all subjects, as well as with significant increases in HbA1c, TC, and LDL-C among those with normal baseline values. The risk of metabolic worsening with quetiapine was dose-dependent, except for fTG.

SUBMITTER: Hojlund M

PROVIDER: S-EPMC10099591 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Publications

Impact of low-dose quetiapine-use on glycosylated hemoglobin, triglyceride and cholesterol levels.

Højlund Mikkel M Støvring Henrik H Andersen Kjeld K Correll Christoph U CU Hallas Jesper J

Acta psychiatrica Scandinavica 20221104 1

<h4>Objective</h4>Quetiapine use at standard doses has been associated with hyperglycemia and dyslipidemia. However, whether even frequently prescribed low-dose quetiapine results in significant metabolic disturbances remains unclear. Thus, this study aimed to investigate the association between off-label, low-dose quetiapine and changes in glycosylated hemoglobin (HbA1c) levels/lipid parameters.<h4>Methods</h4>We identified new users of low-dose quetiapine (≤50 mg tablets) in Denmark 2008-2018 ...[more]

PMID: 36281759

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Project description:ImportanceQuetiapine has been associated with increased risk of type 2 diabetes when used in medium or high doses for the treatment of severe mental disorders. It is not known whether low doses, commonly used off-label for sedative-hypnotic purposes, are also associated with increased risk of type 2 diabetes.ObjectiveTo investigate whether there is an association between prescription of low-dose quetiapine and the risk of type 2 diabetes.Design, setting, and participantsThis cohort study examined nationwide Danish health registers for data regarding new users of quetiapine (n = 185 938) or selective serotonin reuptake inhibitors (SSRIs) (n = 1 031 920) who were aged 18 years or older between January 1, 1998, and December 31, 2018. Individuals with schizophrenia or bipolar disorder were excluded. Quetiapine-initiators were matched 1:1 with initiators of SSRIs, using a high-dimensional propensity score (hdPS). Maximum follow-up was 5 years. Association with cumulative dose was investigated, using a case-control approach nested among quetiapine users. Data analysis was performed from May to September 2020.ExposuresDispensing of quetiapine or SSRIs. Quetiapine prescriptions were limited to tablet strengths of 25 mg and 50 mg to focus on low-dose use.Main outcomes and measuresIncident type 2 diabetes was defined as first filling of an antidiabetic medication, first register diagnosis of type 2 diabetes or first hemoglobin A1C measurement greater than or equal to 6.4% (≥48 mmol/mol). Incidence rates (IRs), incidence rate ratios (IRRs), and number-needed-to-harm (NNH) were calculated for full and matched cohorts using as-treated and intention-to-treat approaches. Odds ratios (ORs) were calculated for the association with cumulative quetiapine dose.ResultsAltogether, 896 285 patients were included in the full cohort; 538 164 (60%) were female and the median (interquartile range) age was 47 (33-67) years. There were 57 701 low-dose quetiapine initiators and 838 584 SSRI initiators. The matched cohort consisted of 54 616 pairs. In as-treated analyses, the incidence of type 2 diabetes during treatment with low-dose quetiapine (425 cases) was 9.59 cases/1000 person-years (PY) (95% CI, 8.72-10.5/1000 PY), which was slightly higher than for SSRI users (8462 cases; IR, 8.13/1000 PY; 95% CI, 7.96-8.30/1000 PY), resulting in a significant IRR of 1.18 (95% CI, 1.07-1.30) and NNH of 684 (95% CI, 418-1873). However, the between-group difference was nonsignificant in the hdPS-matched cohort (IR, 9.49 vs IR, 9.58; IRR, 0.99; 95% CI, 0.87-1.13). The case-control analysis found no dose-response association of low-dose quetiapine with diabetes (OR for doubling of the cumulative dose: 1.02; 95% CI, 0.95-1.09; P = .54), but in sensitivity analyses higher daily doses were associated with diabetes (all tablet strengths: OR, 1.08; 95% CI, 1.03-1.13).Conclusions and relevanceIn this cohort study, use of low-dose quetiapine was not associated with excess risk of type 2 diabetes in comparison with SSRIs.

Project description:ImportanceLow-density lipoprotein cholesterol (LDL-C) is typically estimated with the Friedewald or Martin/Hopkins equation; however, if triglyceride levels are 400 mg/dL or greater, laboratories reflexively perform direct LDL-C (dLDL-C) measurement. The use of direct chemical LDL-C assays and estimation of LDL-C via the National Institutes of Health Sampson equation are not well validated, and data on the accuracy of LDL-C estimation at higher triglyceride levels are limited.ObjectiveTo compare an extended Martin/Hopkins equation for triglyceride values of 400 to 799 mg/dL with the Friedewald and Sampson equations.Design, setting, and participantsThis cross-sectional study evaluated consecutive patients at clinical sites across the US with patient lipid distributions representative of the US population in the Very Large Database of Lipids from January 1, 2006, to December 31, 2015, with triglyceride levels of 400 to 799 mg/dL. Data analysis was performed from November 9, 2020, to March 23, 2021.Main outcomes and measuresAccuracy in LDL-C classification according to guideline-based categories and absolute errors between estimated LDL-C and dLDL-C levels. Patients were randomly assigned 2:1 to derivation and validation data sets. Levels of dLDL-C were measured by vertical spin-density gradient ultracentrifugation. The LDL-C levels were estimated using the Friedewald method, with a fixed ratio of triglycerides to very low-density lipoprotein cholesterol (VLDL-C ratio of 5:1), extended Martin/Hopkins equation with a flexible ratio, and Sampson equation with VLDL-C estimation by multiple least-squares regression.ResultsA total of 111 939 patients (mean [SD] age, 52 [13] years; 65.0% male) with triglyceride levels of 400 to 799 mg/dL were included, representing 2.2% of 5 081 680 patients in the database. Across all individual guideline LDL-C classes (<40, 40-69, 70-99, 100-129, 130-159, 160-189, and ≥190), estimation of LDL-C by the extended Martin/Hopkins equation was most accurate (62.1%) compared with the Friedewald (19.3%) and Sampson (40.4%) equations. In classifying LDL-C levels less than 70 mg/dL across all triglyceride strata, the extended Martin/Hopkins equation was most accurate (67.3%) compared with Friedewald (5.1%) and Sampson (26.4%) equations. In addition, for classifying LDL-C levels less than 40 mg/dL across all triglyceride strata, the extended Martin/Hopkins equation was most accurate (57.2%) compared with the Friedewald (4.3%) and Sampson (14.4%) equations. However, considerable underclassification of LDL-C occurred. The magnitude of error between the Martin/Hopkins equation estimation and dLDL-C was also smaller: at LDL-C levels less than 40 mg/dL, 2.7% of patients had 30 mg/dL or greater differences between dLDL-C and estimated LDL-C using the Martin/Hopkins equation compared with the Friedewald (92.5%) and Sampson (38.7%) equations.Conclusions and relevanceIn this cross-sectional study, the extended Martin/Hopkins equation offered greater LDL-C accuracy compared with the Friedewald and Sampson equations in patients with triglyceride levels of 400 to 799 mg/dL. However, regardless of method used, caution is advised with LDL-C estimation in this triglyceride range.

Project description:ImportancePopulation mean levels of total cholesterol and fasting triglycerides have decreased substantially in the US in recent decades, but improvements in cardiometabolic health may have slowed among younger cohorts. Conversely, prevalence of diabetes (types 1 and 2) and obesity has increased, especially among adults younger than 65 years. It is unclear how trends in cholesterol, triglyceride, and glucose levels have changed across different birth cohorts and whether adverse trends in obesity are associated with these patterns.ObjectiveTo quantify national trends in total cholesterol, fasting triglyceride, and fasting glucose levels among cohorts born between 1920 and 1999 and examine the potential association of these patterns with body mass index (BMI).Design, setting, and participantsThis serial cross-sectional study used National Health and Nutrition Examination Survey (NHANES) data from the 1999-2000 to 2017-2020 cycles. Data were analyzed between November 1, 2023, and July 31, 2024. Participants included nonpregnant and noninstitutionalized US adults 18 years or older, born between 1920 and 1999, who had data collected from 1999 to 2020.ExposureEight 10-year birth cohorts (from 1920 to 1999).Main outcomes and measuresTotal cholesterol, fasting triglyceride, and fasting glucose levels and BMI. Quantile regression models reported average marginal effects to quantify mean change in cardiometabolic outcome measures per decade of birth years. Parametric regression models estimated the association of birth cohort with outcomes, assessing BMI as the mediator.ResultsOf 52 006 participants weighted to represent 264 664 915 US adults, weighted median age was 46 (IQR, 33-60) years and 50.6% were women. For the 50th percentile of measures, mean difference per 1-decade younger birth cohort was -7.1 (95% CI, -8.2 to -6.1) mg/dL for total cholesterol level, -13.1 (95% CI, -15.1 to -11.1) mg/dL for fasting triglyceride level, and 2.7 (95% CI, 2.3-3.1) mg/dL for fasting glucose level. BMI appeared to attenuate the associations between birth cohort and lipid levels and enhanced the associations between birth cohort and fasting glucose levels. However, up to 80% of the associations between birth cohorts and cardiometabolic outcomes were not mediated through BMI.Conclusions and relevanceIn this cross-sectional study of 52 006 participants representing 264 664 915 US adults, population-level improvements in total cholesterol and triglyceride levels decelerated and adverse trends in glucose levels accelerated in more recent birth cohorts, which was partially mediated by concurrent increases in BMI. Public health initiatives that target antecedent health behaviors are needed to improve cardiometabolic health across generations.

Dataset Information

Impact of low-dose quetiapine-use on glycosylated hemoglobin, triglyceride and cholesterol levels.

Objective

Methods

Results

Conclusions

Publications

Impact of low-dose quetiapine-use on glycosylated hemoglobin, triglyceride and cholesterol levels.

Similar Datasets

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