The association between antidepressant use and hypoglycaemia in diabetic patients: a nested case-control study

Antidepressant prescribing inequalities in people with comorbid depression and type 2 diabetes: A UK primary care electronic health record study

AIMS

To compare the likelihood of being prescribed an antidepressant in depressed individuals with and without type 2 diabetes.

METHODS

We performed a matched cohort study using primary care record data from the UK Clinical Practice Research Datalink. We used multivariable logistic regression to compare antidepressant prescribing during the first five years of starting oral antidiabetic medication to a comparison group without type 2 diabetes, matched based on GP practice, age and sex. We performed subgroup analyses stratified by sex, age and ethnicity.

RESULTS

People with type 2 diabetes and depression were 75% less likely to be prescribed an antidepressant compared to people with depression alone (odds ratio (OR) 0.25, 95% confidence interval (CI) 0.25 to 0.26). This difference was greater in males (OR 0.23, 95% CI, 0.22 to 0.24), people older than 56 years (OR 0.23, 95% CI, 0.22 to 0.24), or from a minoritised ethnic background (Asian OR 0.14, 95% CI 0.12-0.14; Black OR 0.12, 95% CI 0.09-0.14).

CONCLUSIONS

There may be inequalities in access to antidepressant treatment for people with type 2 diabetes, particularly those who are male, older or from minoritised ethnic backgrounds.

The association between antidepressant treatment and rates of insulin initiation in comorbid depression and type 2 diabetes: A UK electronic health record nested case-control study

AIMS

To investigate the association between antidepressant prescribing and the rate of insulin initiation in type 2 diabetes.

METHODS

Using UK primary care records we completed a nested-case control study in a individuals with comorbid depression and type 2 diabetes. Cases were defined as individuals initiating insulin, controls were individuals remaining on oral antidiabetic medication. We used conditional logistic regression to estimate incident rate ratios (IRR) and the 95% confidence intervals (CI) for the association between antidepressant prescribing and initiating insulin. We adjusted for demographic characteristics, comorbidities, health service and previous medication use.

RESULTS

We included 11,862 cases who initiated insulin, and 43,452 controls. Increased rates of insulin initiation were associated with any antidepressant prescription (IRR 3.78, 95% CI 3.53-4.04), longer (24+ months) durations of antidepressant treatment (IRR 5.61, 95% CI 5.23-6.03), and higher numbers (3+) of different antidepressant agents prescribed (IRR 5.72, 95% CI 5.25-6.24). There was no difference between recent and non-recent antidepressant prescriptions, or between different antidepressant agents.

CONCLUSIONS

Antidepressant prescribing was highly associated with the initiation of insulin therapy. However, this may not indicate a direct causal effect of the antidepressant medication itself, and may be a marker of more severe depression influencing diabetic control.

Amisulpride as the antipsychotic of choice in severe psychotic disorder with comorbid impaired glucose tolerance

Antipsychotics are the mainstay treatment for the majority of severe mental illnesses. Such patients are also more prone to develop medical comorbidities, which complicate the treatment decisions. It is estimated that up to 40% of individuals with schizophrenia have impaired glucose tolerance (IGT) or diabetes, which can be attributed to a combination of genetic, lifestyle, and medication-related factors. Some widely used antipsychotic medications like olanzapine, risperidone, and clozapine have been associated with an increased risk of weight gain, insulin resistance, and other metabolic abnormalities, which can worsen IGT and increase the risk of developing diabetes. Among second-generation antipsychotics (SGAs), amisulpride, aripirazole, and ziprasidone have a fairly low potency to cause obesity and hyperglycemia. In this context, clinicians must balance the benefits and risks of different antipsychotic medications and consider the individual's specific needs and preferences. Here, we shall discuss three cases, to ascertain how the use of amisulpride helped in glycemic control, and also reflect on probable etiologies leading to deranged glucose levels.

Previously unrecognized risk factors for severe hypoglycaemia requiring emergency medical care in insulin-treated type 2 diabetes: Results from a real-world nested case-control study

AIM

Several risk factors for severe hypoglycaemia (SH) are associated with insulin-treated diabetes. This study explored potential risk factors in adults with insulin-treated type 2 diabetes mellitus (T2DM).

MATERIALS AND METHODS

In this case-control study, adults with T2DM initiating insulin were identified in the IQVIA PharMetrics® Plus database. The index date was the date of the first SH event (cases). Using incidence-density sampling, controls were selected from those who had been exposed 'at risk' of SH for the same amount of time as each case. After exact-matching on the well-established factors, previously unreported risk factors were evaluated through conditional logistic regression.

RESULTS

In 3153 case-control pairs, pregnancy [odds ratios (OR) = 3.20, p = .0003], alcohol abuse (OR = 2.43, p < .0001), short-/rapid-acting insulin (OR = 2.22/1.47, p < .0001), cancer (OR = 1.87, p < .0001), dementia/Alzheimer's disease (OR = 1.73, p = .0175), peripheral vascular disease (OR = 1.59, p < .0001), antipsychotics (OR = 1.59; p = .0059), anxiolytics (OR = 1.51, p = .0012), paralysis/hemiplegia/paraplegia (OR = 1.51, p = .0416), hepatitis (OR = 1.50, p = .0303), congestive heart failure (OR = 1.47, p = .0002), adrenergic-corticosteroid combinations (OR = 1.45, p = .0165), β-adrenoceptor agonists (OR = 1.40, p = .0225), opioids (OR = 1.38, p < .0001), corticosteroids (OR = 1.35, p = .0159), cardiac arrhythmia (OR = 1.29. p = .0065), smoking (OR = 1.28, p = .005), Charlson Comorbidity Index score 2 (OR = 1.28, p = .0026), 3 (OR = 1.41, p = .0016) or ≥4 (OR = 1.57, p = .0002), liver/gallbladder/pancreatic disease (OR = 1.26, p = .0182) and hypertension (OR = 1.19, p = .0164) were independently associated with SH.

CONCLUSIONS

Although all people with insulin-treated diabetes are at risk of SH, these results have identified some previously unrecognized risk factors and sub-groups of insulin-treated adults with T2DM at greater risk. Scrutiny of current therapies and comorbidities are advised as well as additional glucose monitoring and education, when identifying and managing SH in vulnerable populations.

Targeting the Pancreatic α-Cell to Prevent Hypoglycemia in Type 1 Diabetes

Life-threatening hypoglycemia is a limiting factor in the management of type 1 diabetes. People with diabetes are prone to develop hypoglycemia because they lose physiological mechanisms that prevent plasma glucose levels from falling. Among these so-called counterregulatory responses, secretion of glucagon from pancreatic α-cells is preeminent. Glucagon, a hormone secreted in response to a lowering in glucose concentration, counteracts a further drop in glycemia by promoting gluconeogenesis and glycogenolysis in target tissues. In diabetes, however, α-cells do not respond appropriately to changes in glycemia and, thus, cannot mount a counterregulatory response. If the α-cell could be targeted therapeutically to restore its ability to prevent hypoglycemia, type 1 diabetes could be managed more efficiently and safely. Unfortunately, the mechanisms that allow the α-cell to respond to hypoglycemia have not been fully elucidated. We know even less about the pathophysiological mechanisms that cause α-cell dysfunction in diabetes. Based on published findings and unpublished observations, and taking into account its electrophysiological properties, we propose here a model of α-cell function that could explain its impairment in diabetes. Within this frame, we emphasize those elements that could be targeted pharmacologically with repurposed U.S. Food and Drug Administration-approved drugs to rescue α-cell function and restore glucose counterregulation in people with diabetes.

Population-Based Signals of Antidepressant Drug Interactions Associated With Unintentional Traumatic Injury

Antidepressants are very widely used and associated with traumatic injury, yet little is known about their potential for harmful drug interactions. We aimed to identify potential drug interaction signals by assessing concomitant medications (precipitant drugs) taken with individual antidepressants (object drugs) that were associated with unintentional traumatic injury. We conducted pharmacoepidemiologic screening of 2000-2015 Optum Clinformatics data, identifying drug interaction signals by performing self-controlled case series studies for antidepressant + precipitant pairs and injury. We included persons aged 16-90 years codispensed an antidepressant and ≥ 1 precipitant drug(s), with an injury during antidepressant therapy. We classified antidepressant person-days as either precipitant-exposed or precipitant-unexposed. The outcome was an emergency department or inpatient discharge diagnosis for unintentional traumatic injury. We used conditional Poisson regression to calculate confounder adjusted rate ratios (RRs) and accounted for multiple estimation via semi-Bayes shrinkage. We identified 330,884 new users of antidepressants who experienced an injury. Among such persons, we studied concomitant use of 7,953 antidepressant + precipitant pairs. Two hundred fifty-six (3.2%) pairs were positively associated with injury and deemed potential drug interaction signals; 22 of these signals had adjusted RRs > 2.00. Adjusted RRs ranged from 1.06 (95% confidence interval: 1.00-1.12, P = 0.04) for citalopram + gabapentin to 3.06 (1.42-6.60) for nefazodone + levonorgestrel. Sixty-five (25.4%) signals are currently reported in a seminal drug interaction knowledgebase. We identified numerous new population-based signals of antidepressant drug interactions associated with unintentional traumatic injury. Future studies, intended to test hypotheses, should confirm or refute these potential interactions.

Management of drug-disease interactions: a best practice from the Netherlands

Background Drug-disease interactions are situations where pharmacotherapy may have a negative effect on patients' comorbidities. In these cases, it can be necessary to avoid that drug, adjust its dose or monitor therapy. In the Netherlands, pharmacists have developed a best practice how to systematically evaluate drug-disease interactions based on pharmacological considerations and implement recommendations for specific drug-disease interactions. Aim To describe the development of recommendations for drug-disease interactions and the implementation in prescribing and dispensing practice in the Netherlands. Setting Pharmacies and physicians' practices in primary care and hospitals in the Netherlands. Development A multi-disciplinary expert panel assessed if diseases had clinically relevant drug-disease interactions and evaluated drug-disease interactions by literature review and expert opinion, and subsequently developed practice recommendations. Implementation The recommendations were implemented in all clinical decision support systems in primary care and hospitals throughout the Netherlands. Evaluation Recommendations were developed for 57 diseases and conditions. Cardiovascular diseases have the most drug-disease interactions (n = 12, e.g. long QT-syndrome, heart failure), followed by conditions related to the reproductive system (n = 7, e.g. pregnancy). The number of drugs with recommendations differed between 6 for endometriosis and tympanostomy tubes, and up to 1171 in the case of porphyria or even all drugs for pregnancy. Conclusion Practice recommendations for drug-disease interactions were developed, and implemented in prescribing and dispensing practice. These recommendations support both pharmacists and physicians by signalling clinically relevant drug-disease interactions at point of care, thereby improving medication safety. This practice may be adopted and contribute to safer medication use in other countries as well.

Doxepin Exacerbates Renal Damage, Glucose Intolerance, Nonalcoholic Fatty Liver Disease, and Urinary Chromium Loss in Obese Mice

Doxepin is commonly prescribed for depression and anxiety treatment. Doxepin-related disruptions to metabolism and renal/hepatic adverse effects remain unclear; thus, the underlying mechanism of action warrants further research. Here, we investigated how doxepin affects lipid change, glucose homeostasis, chromium (Cr) distribution, renal impairment, liver damage, and fatty liver scores in C57BL6/J mice subjected to a high-fat diet and 5 mg/kg/day doxepin treatment for eight weeks. We noted that the treated mice had higher body, kidney, liver, retroperitoneal, and epididymal white adipose tissue weights; serum and liver triglyceride, alanine aminotransferase, aspartate aminotransferase, blood urea nitrogen, and creatinine levels; daily food efficiency; and liver lipid regulation marker expression. They also demonstrated exacerbated insulin resistance and glucose intolerance with lower Akt phosphorylation, GLUT4 expression, and renal damage as well as higher reactive oxygen species and interleukin 1 and lower catalase, superoxide dismutase, and glutathione peroxidase levels. The treated mice had a net-negative Cr balance due to increased urinary excretion, leading to Cr mobilization, delaying hyperglycemia recovery. Furthermore, they had considerably increased fatty liver scores, paralleling increases in adiponectin, FASN, PNPLA3, FABP4 mRNA, and SREBP1 mRNA levels. In conclusion, doxepin administration potentially worsens renal injury, nonalcoholic fatty liver disease, and diabetes.

Drug Interactions of Psychiatric and COVID-19 Medications

INTRODUCTION

Coronavirus disease 2019 (COVID-19) has become a pandemic with 1771514 cases identified in the world and 70029 cases in Iran until April 12, 2020. The co-prescription of psychotropics with COVID-19 medication is not uncommon. Healthcare providers should be familiar with many Potential Drug-Drug Interactions (DDIs) between COVID-19 therapeutic agents and psychotropic drugs based on cytochrome P450 metabolism. This review comprehensively summarizes the current literature on DDIs between antiretroviral drugs and chloroquine/hydroxychloroquine, and psychotropics, including antidepressants, antipsychotics, mood stabilizers, and anxiolytics.

METHODS

Medical databases, including Google Scholar, PubMed, Web of Science, and Scopus were searched to identify studies in English with keywords related to psychiatric disorders, medications used in the treatment of psychiatric disorders and COVID-19 medications.

RESULTS

There is a great potential for DDIs between psychiatric and COVID-19 medications ranging from interactions that are not clinically apparent (minor) to those that produce life-threatening adverse drug reactions, or loss of treatment efficacy. The majority of interactions are pharmacokinetic interactions via the cytochrome P450 enzyme system.

CONCLUSION

DDIs are a major concern in the comorbidity of psychiatric disorders and COVID-19 infection resulting in the alteration of expected therapeutic outcomes. The risk of toxicity or lack of efficacy may occur due to a higher or lower plasma concentration of medications. However, psychiatric medication can be safely used in combination with COVID-19 pharmacotherapy with either a wise selection of medication with the least possibility of interaction or careful patient monitoring and management.

The Impact of Antidepressant Therapy on Glycemic Control in Canadian Primary Care Patients With Diabetes Mellitus

Context: Depression is common in people with diabetes and is associated with poor glycemic control. Evidence suggests that certain antidepressants (AD) increase the risk of poor control. Few population-based studies have examined the impact of individual ADs on glycemic control. This study's objective is to measure the impact of Citalopram, Amitriptyline, Venlafaxine, Trazodone and Escitalopram on glycated hemoglobin (HbA1c) in Canadian primary care patients with diabetes.

Methods: A retrospective study of electronic medical records (EMR) from 115 primary care practices across Canada was undertaken. Data were obtained from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN). The sample population comprised 1,084 diabetic patients with 1,127 prescriptions of one of the five selected ADs and with baseline and post-exposure HbA1c measurements. Generalized linear mixed models were computed to estimate the effect of the ADs on HbA1c.

Results: Mean HbA1c ratios for Amitriptyline, Venlafaxine, Trazodone and Escitalopram were all numerically lower than Citalopram. The confidence intervals included the minimum detectable effect, however the differences were not statistically significant. The lowest clinically relevant HbA1c ratios, relative to Citalopram, were found in patients prescribed Trazodone and Escitalopram. Accounting for the prescription of Trazodone for indications other than depression, this research suggests that Escitalopram may be safer than Citalopram for people with diabetes and depression, in terms of its effect on blood glucose.

Conclusion: This study can inform future research examining the relationship between ADs and blood glucose and provides insight into the limitations pertaining to the use of health data in health research. Future research should seek to control for, across multiple time points: depression symptoms, depression severity, depression duration, weight, diabetes medication, tobacco and alcohol consumption and other medications with a known impact on blood glucose.

The Bidirectional Association Between Depression and Severe Hypoglycemic and Hyperglycemic Events in Type 1 Diabetes

OBJECTIVE

Severe hyperglycemia and hypoglycemia ("severe dysglycemia") are serious complications of type 1 diabetes (T1D). Depression has been associated with severe dysglycemia in type 2 diabetes but has not been thoroughly examined specifically in T1D. We evaluated bidirectional associations between depression and severe dysglycemia among older people with T1D.

RESEARCH DESIGN AND METHODS

We abstracted depression and severe dysglycemia requiring emergency room visit or hospitalization from medical health records in 3,742 patients with T1D during the study period (1996-2015). Cox proportional hazards models estimated the associations between depression and severe dysglycemia in both directions, adjusting for demographics, micro- and macrovascular complications, and HbA_1c.

RESULTS

During the study period, 41% had depression and 376 (11%) and 641 (20%) had hyperglycemia and hypoglycemia, respectively. Depression was strongly associated with a 2.5-fold increased risk of severe hyperglycemic events (hazard ratio [HR] 2.47 [95% CI 2.00, 3.05]) and 89% increased risk of severe hypoglycemic events (HR 1.89 [95% CI 1.61, 2.22]). The association was strongest within the first 6 months (HR_{hyperglycemia} 7.14 [95% CI 5.29, 9.63]; HR_hypoglycemia 5.58 [95% CI 4.46, 6.99]) to 1 year (HR_{hyperglycemia} 5.16 [95% CI 3.88, 6.88]; HR_hypoglycemia 4.05 [95% CI 3.26, 5.04]) after depression diagnosis. In models specifying severe dysglycemia as the exposure, hyperglycemic and hypoglycemic events were associated with 143% (HR 2.43 [95% CI 2.03, 2.91]) and 74% (HR 1.75 [95% CI 1.49, 2.05]) increased risk of depression, respectively.

CONCLUSIONS

Depression and severe dysglycemia are associated bidirectionally among patients with T1D. Depression greatly increases the risk of severe hypoglycemic and hyperglycemic events, particularly in the first 6 months to 1 year after diagnosis, and depression risk increases after severe dysglycemia episodes.

Drug-drug interactions involving antidepressants: focus on desvenlafaxine

Psychiatric and physical conditions often coexist, and there is robust evidence that associates the frequency of depression with single and multiple physical conditions. More than half of patients with depression may have at least one chronic physical condition. Therefore, antidepressants are often used in cotherapy with other medications for the management of both psychiatric and chronic physical illnesses. The risk of drug-drug interactions (DDIs) is augmented by complex polypharmacy regimens and extended periods of treatment required, of which possible outcomes range from tolerability issues to lack of efficacy and serious adverse events. Optimal patient outcomes may be achieved through drug selection with minimal potential for DDIs. Desvenlafaxine is a serotonin-norepinephrine reuptake inhibitor approved for the treatment of adults with major depressive disorder. Pharmacokinetic studies of desvenlafaxine have shown a simple metabolic profile unique among antidepressants. This review examines the DDI profiles of antidepressants, particularly desvenlafaxine, in relation to drugs of different therapeutic areas. The summary and comparison of information available is meant to help clinicians in making informed decisions when using desvenlafaxine in patients with depression and comorbid chronic conditions.

Psychiatric aspects of diabetes mellitus

Diabetes is an increasingly common health problem, especially in the West, where there is an emerging epidemic of type 2 diabetes, closely related to the epidemic of obesity. Many people with diabetes struggle to optimise their diabetes control, often because they also have mental illnesses or psychological and social problems. Poor diabetes control has significant consequences for the individual, and if not addressed will result in complications that include blindness, kidney failure and even amputations. There are also consequences for health services resulting from increased admissions and emergency department presentations with diabetes-related difficulties. In the long-term, the costs associated with complications such as renal failure and amputation are high. Addressing the psychiatric and psychological barriers to good glucose control can help reduce the burden of diabetes and its complications on both the individual and the health service.

Risk Factors for Severe Hypoglycemia in Black and White Adults With Diabetes: The Atherosclerosis Risk in Communities (ARIC) Study

OBJECTIVE

Severe hypoglycemia is a rare but important complication of type 2 diabetes. Few studies have examined the epidemiology of hypoglycemia in a community-based population.

RESEARCH DESIGN AND METHODS

We included 1,206 Atherosclerosis Risk in Communities (ARIC) Study participants with diagnosed diabetes (baseline: 1996-1998). Severe hypoglycemic events were identified through 2013 by ICD-9 codes from claims for hospitalizations, emergency department visits, and ambulance use. We used Cox regression to evaluate risk factors for severe hypoglycemia.

RESULTS

The mean age of participants was 64 years, 32% were black, and 54% were female. During a median follow-up period of 15.2 years, there were 185 severe hypoglycemic events. Important risk factors after multivariable adjustment were as follows: age (per 5 years: hazard ratio [HR] 1.24; 95% CI 1.07-1.43), black race (HR 1.39; 95% CI 1.02-1.88), diabetes medications (any insulin use vs. no medications: HR 3.00; 95% CI 1.71-5.28; oral medications only vs. no medications: HR 2.20; 95% CI 1.28-3.76), glycemic control (moderate vs. good: HR 1.78; 95% CI 1.11-2.83; poor vs. good: HR 2.62; 95% CI 1.67-4.10), macroalbuminuria (HR 1.95; 95% CI 1.23-3.07), and poor cognitive function (Digit Symbol Substitution Test z score: HR 1.57; 95% CI 1.33-1.84). In an analysis of nontraditional risk factors, low 1,5-anhydroglucitol, difficulty with activities of daily living, Medicaid insurance, and antidepressant use were positively associated with severe hypoglycemia after multivariate adjustment.

CONCLUSIONS

Poor glycemic control, glycemic variability as captured by 1,5-anhydroglucitol, kidney damage, and measures of cognitive and functional impairments were strongly associated with increased risk of severe hypoglycemia. These factors should be considered in hypoglycemia risk assessments when individualizing diabetes care for older adults.

Use of antidepressants in patients with depression and comorbid diabetes mellitus: a systematic review

OBJECTIVE

Depression may be difficult to treat and with comorbid diabetes mellitus (DM) it is an even bigger challenge. This article aims to evaluate antidepressants most suitable for patients with depression and comorbid DM. Design and methods Initially we searched for randomised, controlled double-blind trials of treatment with antidepressants in depressed with DM but there were only a few studies and many of them were small trials. Thus, we decided to include studies that were not only randomised-controlled trials. In total, we ended up with 18 articles for our purposes.

RESULTS

The combination of depression and DM may be harmful as depression has a strong impact on psychosocial and medical outcomes in patients with DM. Almost all of the trials in this review showed a reduction in depressive symptoms after treatment with an antidepressant in the acute as well as during maintenance phase. It showed that depression improvement had a favourable effect on glycaemic control that was weight independent. Some studies included only subjects with minor depression or with suboptimal-controlled diabetes making it difficult to show an effect.

CONCLUSION

From these data, we will recommend choosing an selective serotonin reuptake inhibitor (SSRI) if possible to treat a depression among patients with diabetes. If treatment with a tricyclic antidepressant is needed, closer glycaemic monitoring is recommended. Bear in mind that there is a possible risk of hypoglycemia when using SSRIs. Agomelatine and bupropion have shown promising results, but need to be investigated in more trials.

Human Beta Cells Produce and Release Serotonin to Inhibit Glucagon Secretion from Alpha Cells

In the pancreatic islet, serotonin is an autocrine signal increasing beta cell mass during metabolic challenges such as those associated with pregnancy or high-fat diet. It is still unclear whether serotonin is relevant for regular islet physiology and hormone secretion. Here, we show that human beta cells produce and secrete serotonin when stimulated with increases in glucose concentration. Serotonin secretion from beta cells decreases cyclic AMP (cAMP) levels in neighboring alpha cells via 5-HT1F receptors and inhibits glucagon secretion. Without serotonergic input, alpha cells lose their ability to regulate glucagon secretion in response to changes in glucose concentration, suggesting that diminished serotonergic control of alpha cells can cause glucose blindness and the uncontrolled glucagon secretion associated with diabetes. Supporting this model, pharmacological activation of 5-HT1F receptors reduces glucagon secretion and has hypoglycemic effects in diabetic mice. Thus, modulation of serotonin signaling in the islet represents a drug intervention opportunity.

Effects of antidepressants on glucose metabolism and diabetes mellitus type 2 in adults

PURPOSE OF REVIEW

Depression and diabetes mellitus type 2 (DM2) are frequently comorbid conditions. It is of considerable clinical significance to avoid metabolic risks in nondiabetic depressed patients and to consider effects on glucose regulation in depressed DM2 patients. This review is an overview on antidepressant treatment and its potential metabolic risks.

RECENT FINDINGS

It is increasingly recognized that effective treatment with antidepressants improves glucose homeostasis in nondiabetic depressed patients in the short run, whereas long-term effects are a matter of debate. Cognitive behavioral and selective serotonin reuptake inhibitor (SSRI) treatment may improve glycemic control in depressed DM2 patients, whereas noradrenergic antidepressants and tricyclic antidepressants (TCAs) may cause the metabolic situation to deteriorate.

SUMMARY

SSRIs are preferable in nondiabetic depressed patients since they improve glucose regulation in the short run and may have little untoward effects in the long run. In depressed DM2 patients, SSRIs are the only class of antidepressants with confirmed favorable effects on glycemic control.

[Severe hypoglycemia induced by tramadol: two new cases of an unlisted side effect]

INTRODUCTION

Tramadol is a weak opioid analgesic used as a step two analgesic, approved in France for the treatment of moderate to severe pain in adult patients. The most common side effects are gastrointestinal and neurologic. Hypoglycaemia is an almost unknown side effect.

CASE REPORTS

We report two patients who presented with severe hypoglycaemia related to oral administration of tramadol in non diabetic patients. The underlying mechanisms of hypoglycaemia induced by tramadol are unclear. The only weak opioid analgesic drug reported to cause hypoglycaemia is propoxyphene, which has been widely used in France. The recent withdrawal of dextropropoxyphene in France might increase the prescriptions of tramadol and healthcare professionals should be aware of the risk of hypoglycaemia.

CONCLUSION

The risk of hypoglycaemia should be added to the summary of product characteristics of tramadol.

Glucose dysregulation associated with antidepressant agents: an analysis of 17 published case reports

AIM OF THE REVIEW

Although there are several case reports in literature linking use of antidepressants and disturbances in glucose control, it is difficult to identify risk factors for serious adverse drug events from individual case reports. The aim of this review is to provide a descriptive analysis of the demographic and clinical characteristics of published glucose dysregulation case reports following initiation of antidepressant agents.

METHODS

Published case reports of glucose dysregulation associated with antidepressants were accessed through PubMed (Medline), PsycINFO, and Web of Science (WOS) between January 1, 1970 and April 30, 2010. The following key words were used: antidepressant agents, glucose dysregulation, hypoglycemia, hyperglycemia, diabetes mellitus, and diabetic ketoacidosis. Case reports were excluded if glucose dysregulation occurred after a drug overdose/improper dosing or after the patient was prescribed drugs known to cause glucose disturbances in addition to antidepressant agents.

RESULTS

Out of the 17 cases reports reviewed, nine (53%) were of hyperglycemia while eight (47%) were of hypoglycemia. Hyperglycemia was reported following treatment with clomipramine, fluvoxamine, imipramine, mianserin, mirtazapine, paroxetine, and sertraline. Hypoglycemia was reported following treatment with doxepine, fluoxetine, imipramine, nefazodone, nortriptyline, maprotiline, and sertraline. Fourteen out of the seventeen patients were female (82%) while ten had a history of diabetes mellitus (59%). The average age of the patients was 53.9 (SD = 17.5) years (range: 24-84 years). The time to onset of glucose dysregulation ranged from 4 days to 5 months after initiation of antidepressant therapy. More than two-thirds (68%) of the cases (n = 11) reported glucose control disturbances within 1 month of therapy.

CONCLUSIONS

It is not clear from published case reports whether changes in glucose regulation, following antidepressant therapy initiation are due to antidepressants or changes in mood and lifestyle. Nonetheless, healthcare providers should be aware of the potential changes in glucose regulation especially in the first month of antidepressant therapy, and use appropriate clinical and laboratory monitoring to prevent serious adverse events in patients at risk.

Duloxetine treatment and glycemic controls in patients with diagnoses other than diabetic peripheral neuropathic pain: a meta-analysis

OBJECTIVE

Mood disorders are often associated with poor glycemic control, and antidepressant treatments for mood and pain disorders can alter plasma glucose levels in patients with diabetes. A previous meta-analysis from three studies showed that duloxetine modestly increased fasting plasma glucose (FPG) and HbA(1c) levels in patients with diabetic peripheral neuropathic pain (DPNP). This meta-analysis examined whether there were any short- and long-term effects of duloxetine (20-120 mg/day) on glycemic control in patients with diagnoses other than DPNP.

RESEARCH DESIGN AND METHODS

Short-term data (9-27 weeks): seven studies of duloxetine in general anxiety disorder, fibromyalgia, and chronic lower back pain (CLBP). Long-term data: 41-week, uncontrolled extension of the short-term CLBP study and 52-week study in patients with recurrence of major depressive disorder.

MAIN OUTCOME MEASURES

Baseline-to-endpoint changes in FPG and HbA(1c) levels.

RESULTS

In short-term studies, patients were randomly assigned to placebo (n = 1098) or duloxetine (n = 1563). Mean baseline-to-endpoint changes in FPG and HbA(1c) did not significantly differ in duloxetine-treated patients compared with placebo-treated patients. In the 41-week study (n = 181), duloxetine-treated patients experienced a small but significant within-group baseline-to-endpoint increase in HbA(1c) (mean change = 0.1%; p < 0.001). This result was in contrast to absence of effect on mean baseline-to-endpoint within-group changes in FPG (p = 0.326) in that study, and to absence of between-treatment changes in FPG (p = 0.744) and HbA(1c) (p = 0.180) in the 52-week placebo-controlled study.

CONCLUSION

Duloxetine treatment did not significantly alter FPG and HbA(1c) levels compared with placebo treatment in the short-term studies. A small but statistically significant within-group increase in HbA(1c) was found in the 41-week study, but not in between-treatment group differences in the 52-week study. Neither of the long-term studies showed significant changes in the FPG levels. The small, non-reproducible HbA(1c) increase in one study of patients without DPNP may have resulted from patients with unrecognized diabetes in these trials.