The effect of metformin therapy on serum thyrotropin and free thyroxine concentrations in patients with type 2 diabetes: a meta-analysis.

Type 2 diabetes and thyroid function disorders are two common chronic endocrine disorders with the high prevalence in various populations. Metformin is well established as the first-line drug therapy for managing diabetes mellitus. In this meta-analysis, we aimed to determine the effect of metformin on serum TSH and FT4 concentrations in patients with type 2 diabetes. We searched PubMed, Scopus, web of science, Cochrane library, and google scholar to collect information on the effect of metformin on serum TSH and FT4 levels. Demographic and clinical information and serum TSH and FT4 concentrations before and after metformin treatment were extracted. Studies on patients over 18 years of age were included. A total of 11 studies including 1147 patients were selected for the final analysis. In hypothyroid patients, the TSH level decreased significantly after treatment with metformin (Hedges's g:1.55, 95%CI 0.93-2.16, p-value < 0.001); FT4 level increased slightly after taking metformin, but the increase was not significant (Heddges's g: - 0.30, 95%CI - 0.90,0.31, p-value = 0.34). In euthyroid subjects, the slight decrease found in TSH and FT4 concentrations was not statistically significant. Metformin reduces TSH levels in hypothyroid patients; however, it has no effect on TSH levels in euthyroid patients. Metformin does not affect serum FT4 levels in euthyroid and hypothyroid patients.

The value of machine learning for prognosis prediction of diphenhydramine exposure: National analysis of 50,000 patients in the United States.

Background: Diphenhydramine (DPH) is an antihistamine medication that in overdose can result in anticholinergic symptoms and serious complications, including arrhythmia and coma. We aimed to compare the value of various machine learning (ML) models, including light gradient boosting machine (LGBM), logistic regression (LR), and random forest (RF), in the outcome prediction of DPH poisoning. Materials and Methods: We used the National Poison Data System database and included all of the human exposures of DPH from January 01, 2017 to December 31, 2017, and excluded those cases with missing information, duplicated cases, and those who reported co-ingestion. Data were split into training and test datasets, and three ML models were compared. We developed confusion matrices for each, and standard performance metrics were calculated. Results: Our study population included 53,761 patients with DPH exposure. The most common reasons for exposure, outcome, chronicity of exposure, and formulation were captured. Our results showed that the average precision-recall area under the curve (AUC) of 0.84. LGBM and RF had the highest performance (average AUC of 0.91), followed by LR (average AUC of 0.90). The specificity of the models was 87.0% in the testing groups. The precision of models was 75.0%. Recall (sensitivity) of models ranged between 73% and 75% with an F1 score of 75.0%. The overall accuracy of LGBM, LR, and RF models in the test dataset was 74.8%, 74.0%, and 75.1%, respectively. In total, just 1.1% of patients (mostly those with major outcomes) received physostigmine. Conclusion: Our study demonstrates the application of ML in the prediction of DPH poisoning.

Toward Integration of Pharmacogenomic Tests into Daily Clinical Practice: A General Survey for Polish Healthcare Workers.

BACKGROUND Pharmacogenomics (PGx) has a direct influence on personalized drug therapy for various types of disorders and has been proven to have an important role in the future of medicine. The present study evaluated the awareness of PGx testing of clinicians and healthcare workers in the Republic of Poland. To the best of our knowledge, this is the first direct assessment of Polish healthcare professionals' attitudes toward introducing PGx tests into daily clinical practice. MATERIAL AND METHODS We used a comprehensive anonymous questionnaire with queries on level of education, background knowledge of PGx tests, advantages and barriers for implementation of such tests, and clinicians' desire to order the test that was distributed online to doctors, healthcare workers, related students/Ph.D. students, and administrative staff managing healthcare units. RESULTS We gathered 315 responses. According to the answers, two-thirds of participants had heard about PGx before (64.4%). An overwhelming majority of respondents appreciated the benefits of PGx (93.3%). Indeed, prior knowledge and level of education showed significant associations with positive attitudes toward PGx clinical testing (P≤0.05). However, all participants agreed there are major challenges for including such tests as part of routine clinical practice. CONCLUSIONS While the awareness and interest in PGx clinical testing in Polish healthcare providers are rising, some main barriers for implementation of these tests still need to be addressed in Poland.

Comparison of decision tree with common machine learning models for prediction of biguanide and sulfonylurea poisoning in the United States: an analysis of the National Poison Data System.

BACKGROUND: Biguanides and sulfonylurea are two classes of anti-diabetic medications that have commonly been prescribed all around the world. Diagnosis of biguanide and sulfonylurea exposures is based on history taking and physical examination; thus, physicians might misdiagnose these two different clinical settings. We aimed to conduct a study to develop a model based on decision tree analysis to help physicians better diagnose these poisoning cases. METHODS: The National Poison Data System was used for this six-year retrospective cohort study.The decision tree model, common machine learning models multi layers perceptron, stochastic gradient descent (SGD), Adaboosting classiefier, linear support vector machine and ensembling methods including bagging, voting and stacking methods were used. The confusion matrix, precision, recall, specificity, f1-score, and accuracy were reported to evaluate the model's performance. RESULTS: Of 6183 participants, 3336 patients (54.0%) were identified as biguanides exposures, and the remaining were those with sulfonylureas exposures. The decision tree model showed that the most important clinical findings defining biguanide and sulfonylurea exposures were hypoglycemia, abdominal pain, acidosis, diaphoresis, tremor, vomiting, diarrhea, age, and reasons for exposure. The specificity, precision, recall, f1-score, and accuracy of all models were greater than 86%, 89%, 88%, and 88%, respectively. The lowest values belong to SGD model. The decision tree model has a sensitivity (recall) of 93.3%, specificity of 92.8%, precision of 93.4%, f1_score of 93.3%, and accuracy of 93.3%. CONCLUSION: Our results indicated that machine learning methods including decision tree and ensembling methods provide a precise prediction model to diagnose biguanides and sulfonylureas exposure.

The effects of Berberis vulgaris L. and Berberis aristata L. in metabolic syndrome patients: a systematic and meta-analysis study.

INTRODUCTION: This meta-analysis study assessed the effects of Berberis vulgaris L. and Berberis aristata L. in patients with metabolic syndrome. METHODS: Data were analysed through "random-effects meta-regression" performance. RESULTS: The findings indicated that LDL was 0.68 and 2.92 lower in the B. vulgaris L. and B. aristata L.-treated groups versus the controls. The HDL was 0.71-fold higher in the B. aristata L.-treated group versus the controls. The total-cholesterol levels were 1.02 and 2.25 folds lower in the B. vulgaris L. and B. aristata L.-treated groups versus the matched control groups. The triglyceride levels were 1.35 and 1.16-fold lower in the B. vulgaris L. and B. aristata L.-treated groups versus the controls. Glucose was 0.96 and 0.54 folds lower in the B. vulgaris L. and B. aristata L.-treated groups versus the control groups, respectively. CONCLUSION: B. vulgaris L. and B. aristata L. have beneficial effects in patients with metabolic syndrome.

Association Between Biological Lead Concentrations and Autism Spectrum Disorder (ASD) in Children: a Systematic Review and Meta-Analysis.

Studies have been conducted in different countries of the world to illustrate a link between autism spectrum disorder (ASD) and lead (Pb) in different specimens such as hair, blood, and urine. Therefore, we carried out a systematic review and meta-analysis to determine the association between Pb concentration in biological samples (blood, urine, and hair) and ASD in children through case-control and cross-sectional studies. In this systematic review, PubMed, Web of Sciences, Scopus, and Google Scholar were searched for relevant studies from January 2000 to February 2022. A random-effects model was used to pool the results. The effect sizes were standardized mean differences (proxied by Hedges' g) followed by a 95% confidence interval. Pooling data under the random effect model from blood and hair studies showed a significant difference between the children in the ASD group and the control group in blood lead level (Hedges' g: 1.21, 95% CI: 0.33-2.09, P = 0.01) and hair level (Hedges' g: 2.20, 95% CI: 0.56-3.85, P = 0.01). For urine studies, pooling data under the random effect model from eight studies indicated no significant difference between the children in the ASD group and control group in urinary lead level (Hedges' g: - 0.34, 95% CI: - 1.14,0.45, P = 0.40). Moreover, the funnel plot and the results of the Egger test for the blood and urine samples showed no publication bias, while, for the hair samples, the funnel plot illustrated the existence of publication bias.

Withdrawal Notice: The Performance of Interferon-gamma Release Assays and Tuberculin Skin Tests in the Diagnosis of Latent Tuberculosis Infection among Immune-mediated Inflammatory Diseases: A Meta-analysis Study

Since the authors are not responding to the editor's requests to fulfill the editorial requirement, therefore, the article has been withdrawn.Bentham Science apologizes to the readers of the journal for any inconvenience this may cause.The Bentham Editorial Policy on Article Withdrawal can be found at https://benthamscience.com/editorial-policies-main.php. Bentham Science Disclaimer: It is a condition of publication that manuscripts submitted to this journal have not been published and will not be simultaneously submitted or published elsewhere. Furthermore, any data, illustration, structure or table that has been published elsewhere must be reported, and copyright permission for reproduction must be obtained. Plagiarism is strictly forbidden, and by submitting the article for publication the authors agree that the publishers have the legal right to take appropriate action against the authors, if plagiarism or fabricated information is discovered. By submitting a manuscript, the authors agree that the copyright of their article is transferred to the publishers if and when the article is accepted for publication.

Curcumin and blood lipid levels: an updated systematic review and meta-analysis of randomised clinical trials.

The present study was designed to indicate the protective effects of curcumin on dyslipidemia. Main databases were searched to recognise randomised clinical trials evaluating the effect of curcumin on blood lipid profiles. The pooled odds ratio with a 95% confidence interval (CI) was used to evaluate the effect of curcumin on blood lipid parameters. HDL-C levels in the curcumin group were 0.04-fold lower than placebo (95% CI:-0.36-0.29; Z = 0.23; p = .82). LDL-C levels in the curcumin group reduced by 0.17 versus the placebo group (95% CI: -0.43-0.09; Z = 1.27; p = .2). TC levels in the curcumin group were 0.21 lower versus the placebo group (95% CI: -0.55-0.13; Z = 1.22; p = .22). TG level in the curcumin group were 0.05 lower versus the placebo (95% CI: -0.20-0.11; Z = 0.58; p = .56). This study suggests that curcumin may reduce blood lipid levels and can be used as a hypolipidemic agent.

Association of environmental tobacco smoke (ETS) with lead and cadmium concentrations in biological samples of children and women: systematic review and meta-analysis.

OBJECTIVES: Previous literature has shown that heavy metals (HMs) in cigarette smoke have been overestimated, and second-hand smoke (SHS) has recently raised public concern. This study aimed to review the effects of passive tobacco exposure on lead (Pb) and cadmium (Cd) concentrations of children and women in different biological samples. CONTENT: In this systematic review, two independent researchers assessed different databases/search engines including PubMed, Web of Science, Scopus, and Google Scholar using Mesh terms and Text Words. Studies between January 2000 and May 2022 were included. After quality assessment, studies with sufficient data were included in the meta-analysis. A fixed or random model was used to pool the results in a meta-analysis. Heterogeneity between the studies was assessed by using I-square and Q tests. Forest plots demonstrating the point and pooled estimates were provided. SUMMARY: A total of 976 studies were obtained from different databases and finally 17 studies meet our criteria and were included in our systematic review. Out of 17 studies, six studies had sufficient data for analysis and were included in the meta-analysis. The results of the meta-analysis showed a significant difference in blood lead concentrations (BLC) between the children with SHS exposure and the control group (Hedges' g: 2.44, 95% CI: 1.01-3.86, p<0.05). Also, there were significant differences in hair levels of Cd (Hedges' g: 0.66, 95% CI: 0.04, 1.28, p<0.05) and Pb (Hedges' g: 0.94, 95% CI: 0.05, 1.83, p<0.05) between children with SHS exposure compared to the control group. OUTLOOK: The results of the present meta-analysis showed that passive smokers had higher Pb and Cd concentrations than those who were not exposed to cigarette smoke.

Which model is superior in predicting ICU survival: artificial intelligence versus conventional approaches.

BACKGROUND: A disease severity classification system is widely used to predict the survival of patients admitted to the intensive care unit with different diagnoses. In the present study, conventional severity classification systems were compared with artificial intelligence predictive models (Artificial Neural Network and Decision Tree) in terms of the prediction of the survival rate of the patients admitted to the intensive care unit. METHODS: This retrospective cohort study was performed on the data of the patients admitted to the ICU of Ghaemshahr's Razi Teaching Care Center from March 20th, 2017, to September 22nd, 2019. The required data for calculating conventional severity classification models (SOFA, SAPS II, APACHE II, and APACHE IV) were collected from the patients' medical records. Subsequently, the score of each model was calculated. Artificial intelligence predictive models (Artificial Neural Network and Decision Tree) were developed in the next step. Lastly, the performance of each model in predicting the survival of the patients admitted to the intensive care unit was evaluated using the criteria of sensitivity, specificity, accuracy, F-measure, and area under the ROC curve. Also, each model was validated externally. The R program, version 4.1, was used to create the artificial intelligence models, and SPSS Statistics Software, version 21, was utilized to perform statistical analysis. RESULTS: The area under the ROC curve of SOFA, SAPS II, APACHE II, APACHE IV, multilayer perceptron artificial neural network, and CART decision tree were 76.0, 77.1, 80.3, 78.5, 84.1, and 80.0, respectively. CONCLUSION: The results showed that although the APACHE II model had better results than other conventional models in predicting the survival rate of the patients admitted to the intensive care unit, the other conventional models provided acceptable results too. Moreover, the findings showed that the artificial neural network model had the best performance among all the studied models, indicating the discrimination power of this model in predicting patient survival compared to the other models.

Risk assessment of elevated blood lead concentrations in the adult population using a decision tree approach.

Lead is a common toxin which has detrimental effects on human health. Since lead poisoning is not associated with specific symptoms, diagnosing elevated blood lead concentration (EBLC) should be taken seriously. The purpose of this study was to propose a prediction model for EBLC based on demographic and clinical variables through a decision-tree model.In this cross-sectional study, 630 subjects (above 40 years old) living in South Khorasan Province, Iran in 2017 were selected via cluster random sampling method. From among the 630 participants who met the inclusion criteria, 70% (N = 456) were chosen randomly to achieve a set for developing the decision tree and multiple logistic regression (MLR). The other 30% (N = 174) were placed in a holdout sample to examine the function of the decision tree and MLR models. The predictive performance for various models was studied using the Receiver Operating Characteristic (ROC) curve.In the decision tree model, the parameters of hematocrit (HCT), White Blood Cell (WBC), Red Blood Cell (RBC), Mean corpuscular volume (MCV), creatinine concentration, abdominal pain, gender, route of administration, and history of cigarette smoking were the most critical factors in identifying people at risk of EBLC. The HCT concentration was the most critical variable, which was chosen as the root node of the tree. Based on the ROC curve, the decision tree model had better predictive accuracy than the logistic regression model.Our results indicated that the decision tree model offers far greater predictive precision than the logistic regression model. Doctors should pay more attention to some factors including the hematological parameters such as MCV, RBC, HCT, leukocytosis, creatinine levels, male sex, history of cigarette, and opium consumption for the screening of EBLCs.

Trends of acute drug and chemical toxicities in adults and adolescents in Tehran, Iran between 2012 and 2018: a retrospective chart review.

Poisoning is among the top three common causes of suicidal deaths in Iran. We aimed to evaluate the epidemiologic trend of poisoning and its mortality rate in the largest tertiary toxicology referral center in Iran between 2012 and 2018. A total of 84,242 patients were hospitalized or died due to poisoning in this center during the study period, of whom 2114 (2.5%) died. The most frequent poisonings were those with antiepileptics, sedativehypnotics, and antiparkinson medications (T42) followed by narcotics and psychodysleptics (T40). Psychodysleptics had the highest mortality rate (684; 32.4% of the deaths). Among drugs of abuse, methadone was the most common cause of admission reported in 10,398 cases (12.3%). In conclusion, suicidal or recreational methadone poisoning is becoming the most common cause of admission to poisoning referral wards in Iran. Rigorous supervision of daily dosing at opioid maintenance clinics as well as efforts to control the black-market offering methadone are needed to prevent further methadone-related acute poisonings and deaths.

Metabolic impact of saffron and crocin: an updated systematic and meta-analysis of randomised clinical trials.

The present systematic and meta-analysis study was designed to show the protective impact of saffron and crocin supplementation on hyperlipidaemia and hyperglycaemia in randomised and clinical trials (RCTs). A pooled analysis using a model for random-effects showed that HDL-C levels were 0.21 fold higher in the saffron and 0.01 fold higher in the crocin group than placebo. LDL-C levels in the saffron group reduced by 0.51 and 0.04 fold in the crocin group versus the placebo. Moreover, TC levels in the saffron group were 0.19 lower and 0.11 fold lower in crocin group than in the placebo group. TG level in saffron group was 0.04 lower and 0.02 fold lower in crocin than the control group. The blood glucose levels did not significantly differ from the control group. This study suggests that saffron and crocin may modulate the serum lipid profile in patient with metabolic disorders.

Blood lead concentrations in children with iron deficiency anemia: a systematic review and meta-analysis.

Iron deficiency is the most common nutritional disorder detrimental to the behavior, cognitive performance, immune system, and physical growth of infants and preschool- and school-age children. Iron deficiency anemia (IDA) increases children's susceptibility to some metals, including the highly toxic lead (Pb), but the character of this relationship is still disputed. Thus, this study aimed to review and meta-analyze the association between the IDA and blood lead levels (BLL) among children, based on papers indexed by international scientific databases and published up to September 2021. A search was performed of the literature in several databases including the ISI Web of Science, PubMed, and Scopus. The final papers were assessed concerning their quality based on the Newcastle-Ottawa Scale (NOS) for cross-sectional studies. Moreover, analyses were performed using R statistical software with the "meta" package. Of the 1528 articles found, only 12 studies met the inclusion criteria and were considered in the meta-analysis. Significantly higher BLL in IDA children (SMD = 2.40; CI 95%, 0.93-3.87 µg/L; p = 0.0014) was seen when compared to non-IDA children. Moreover, the pooled OR is equal to 2.75 (CI 95%, 1.10-6.85 µg/L; p = 0.0303) suggesting a higher risk of IDA development among children with BLL > 10 µg/dL. Thus, we recommend systematic monitoring of Fe and Pb levels among children, especially in countries with limited sources of nutritious food. Since only a few studies were available for this meta-analysis, further studies are necessary to examine the association between IDA and BLL in detail.

A Systematic and Meta-Analysis Study on the Prevalence of Tuberculosis and Relative Risk Factors for Prisoners in Iran.

INTRODUCTION: Tuberculosis (TB) is a serious infectious disease that affects human health globally. The incidence of TB in prisons is usually much higher than the general population in different countries. The aim of this study was to evaluate the incidence of TB among prisoners in Iran, estimating the relative risk factors by performing a systematic and meta-analysis study on the related articles. METHODOLOGY: Our systematic and meta-analysis study was performed according to the PRISMA guidelines. Two authors systematically searched Scopus, Iran doc, Cochrane, Pubmed, Medline, Embase, Iran medex, Magiran, SID, Google Scholar, and EBSCO. The quality assessment of articles was performed by using the Newcastle-Ottawa Scale. After article quality assessment, a fixed or random model, as appropriate, was used to pool the results in a meta-analysis. Heterogeneity between the studies was assessed using I-square and Q-test. Forest plots demonstrating the point and pooled estimates were drawn. RESULTS: Overall, data from 19562 prisoners indicated 63 cases of TB. The prevalence of TB in prisoners was reported to range from 0.025% to 52% in eight studies. The highest prevalence of tuberculosis was related to the study of Rasht, 517 in 100,000, and the lowest rate was related to the study of Sought Khorasan, 25 in 100,000. The ES of the random effect model is 0.003 (95% CI, 0.001-0.005) and p-value <0.0001. The Higgins' I2 of all studies is 86.55%, and the p-value of the Cochrane Q statistics is <0.001, indicating that there is heterogeneity. Based on the Egger regression plot (t=2.18, p = 0.08, CI 95%: -0.001, 0.005), no publication bias existed. CONCLUSION: According to the analysis findings, the frequency of tuberculosis among the prison in Iran was low. The highest prevalence obtained in our systematic study was 517 in 100,000 in Rasht, which was near the world statistics in the systematic review of world studies. Due to significant limitations in this study, it is not possible to indicate the exact prevalence of TB in prisons in Iran and compare this with the general population. However, more studies are needed to assess the related risk factors for designing health intervention plans to decrease the incidence rate of TB among prisoners.

Prevalence and factors connected with chronic diseases in the elderly residents of Birjand: a community - based study in Birjand, South Khorasan Province, Iran.

OBJECTIVES: The rapid rise of non-communicable diseases (NCDs) across the elderly has attracted much attention in Iran due to the high rate of population aging in the country. The current survey intended to evaluate the prevalence of and factors associated with five NCDs in the elderly residents of Birjand, a metropolis of South Khorasan, Iran. METHODS: Following an observational design, 1820 elderly dwellers of Birjand aged ≥ 60 years residing in urban or rural areas were explored. Data on the target NCDS and socio-demographic features, health behavioral factors, and objective assessment of height and weight were collected using interviews. RESULTS: The prevalence of hypertension, diabetes mellitus, chronic obstructive pulmonary disease (COPD), stroke, and cancer was 55.2% (1004/1819), 25.5% (463/1819), 1.0% (18/1807), 4.4% (80/1810), and 1.8% (33/1816), respectively. There was no gender difference concerning the prevalence of COPD, whereas the prevalence of hypertension, diabetes mellitus, and cancer was higher in women than men. Stroke was conversely higher in males than females. The common correlations of the five main NCDs were locality of residence and low body mass index (BMI). Rural residents had higher odds of diabetes mellitus and hypertension and lower odds of stroke. Diabetes mellitus, hypertension, and stroke were associated with a low BMI. Gender, age, and occupation were found to be associated with some of the NCDs. Retired and housewives had more chance to have hypertension and diabetes mellitus than the unemployed elderly. CONCLUSION: The findings demonstrated that hypertension, diabetes mellitus, and stroke are the three prevalent NCDs among elders in the area and warrant a specific focus on reducing the burden of diseases and aligning healthcare services to prepare the whole needs of this population.

COVID-19 pandemic and methanol poisoning outbreak in Iranian children and adolescents: A data linkage study.

BACKGROUND: During the first wave of COVID-19, many Iranians were poisoned by ingesting hand sanitizers and/or alcoholic beverages to avoid viral infection. To assess whether the COVID-19 pandemic resulted in an increased prevalence of accidental hand sanitizer/alcoholic beverage exposure in children and adolescents, we compared pediatric hospitalization rates during COVID-19 and the previous year. For poisoning admissions during COVID-19, we also evaluated the cause by age and clinical outcomes. METHODS: This retrospective data linkage study evaluated data from the Legal Medicine Organization (reporting mortalities) and hospitalization data from nine toxicology referral centers for alcohol-poisoned patients (age 0 to 18 years) for the study period (February 23 to June 22, 2020) and the pre-COVID-19 reference period (same dates in 2019). RESULTS: Hospitalization rates due to ethanol and methanol exposure were significantly higher in 2020 (n = 375) than 2019 (n = 202; OR [95% CI] 1.9 [1.6, 2.2], p < 0.001). During COVID-19, in patients ≤15 years, the odds of intoxication from hand sanitizers were significantly higher than from alcoholic beverages, while in 15- to 18-year-olds, alcoholic beverage exposure was 6.7 times more common (95% CI 2.8, 16.1, p < 0.001). Of 375 children/adolescents hospitalized for alcoholic beverage and hand sanitizer exposure in 2020, six did not survive. The odds of fatal outcome were seven times higher in 15- to 18-year-olds (OR (95% CI) 7.0 (2.4, 20.1); p < 0.001). CONCLUSION: The Iranian methanol poisoning outbreak during the first wave of COVID-19 was associated with significantly increased hospitalization rates among children and adolescents-including at least six pediatric in-hospital deaths from poisoning. Public awareness needs to be raised of the risks associated with ingesting alcoholic hand sanitizers.

Effects of naloxone and diazepam on blood glucose levels in tramadol overdose using generalized estimating equation (GEE) model; (an experimental study).

BACKGROUND: Tramadol is a synthetic opioid and poisoning is increasing around the world day by day. Various treatments are applied for tramadol poisoning. Due to the unknown effects of tramadol poisoning and some of its treatments on blood glucose levels, this study was conducted to investigate the overdose of tramadol and its common treatments (naloxone, diazepam), and their combination on blood glucose levels in male rats. METHODS: This study was conducted in 45 male Wistar rats. The animals were randomly divided into five groups of 9. They received a 75 mg/kg dose of tramadol alone with naloxone, diazepam, and a combination of both of these two drugs. On the last day, animals' tail vein blood glucose levels (BGL) were measured using a glucometer at different times, including before the tramadol injection (baseline) and 1 hour, 3 hours, and 6 hours after wards. The rats were anesthetized and sacrificed 24 h after the last injection. Blood samples were then taken, and the serum obtained was used to verify the fasting glucose concentration. Data were analyzed using SPSS software at a significance level of 0.05 using a one-way analysis of variance (ANOVA) and a generalized estimating equation (GEE). RESULTS: According to the GEE model results, the diazepam-tramadol and naloxone-diazepam-tramadol groups showed blood glucose levels five units higher than the tramadol group (p < 0.05). The diazepam-tramadol group had significantly higher blood glucose levels than the naloxone-tramadol group (p < 0.05). The mean blood glucose levels before the intervention, 3 hours and 6 hours after the injection of tramadol did not differ between the groups, but the blood glucose levels 1 hour after the injection of tramadol in the group of naloxone-tramadol were significantly lower than in the control group (p < 0.05). Blood glucose levels did not differ between the groups 24 h after injection of tramadol. CONCLUSION: The results of the present study showed tramadol overdose does not affect blood glucose levels. The diazepam-tramadol combination and the diazepam-naloxone-tramadol combination caused an increase in blood glucose levels.

The effects of naloxone, diazepam, and quercetin on seizure and sedation in acute on chronic tramadol administration: an experimental study.

BACKGROUND: Tramadol is a widely used synthetic opioid. Substantial research has previously focused on the neurological effects of this drug, while the efficacy of various treatments to reduce the associated side effects has not been well studied. This study aimed to evaluate the protective effects of naloxone, diazepam, and quercetin on tramadol overdose-induced seizure and sedation level in male rats. METHODS: The project was performed with 72 male Wistar rats with an average weight of 200-250 g. The rats were randomly assigned to eight groups. Tramadol was administered intraperitoneally at an initial dose of 25 mg/kg/day. On the 14th day, tramadol was injected at 75 mg/kg, either alone or together with naloxone, diazepam, and quercetin (acute and chronic) individually or in combination. The rats were monitored for 6 h on the last day, and the number, the duration, and the severity of seizures (using the criteria of Racine) were measured over a 6-h observation period. The sedation level was also assessed based on a 4-point criterion, ranging from 0 to 3. Data were analyzed in SPSS software using Kruskal-Wallis, Chi-square, regression analysis, and generalized estimating equation (GEE) tests. The significance level was set at P < 0.05. RESULTS: The naloxone-diazepam combination reduced the number, severity, and cumulative duration of seizures compared to tramadol use alone and reduced the number of higher-intensity seizures (level 3, 4) to a greater extent than other treatments. Naloxone alone reduced the number and duration of seizures but increased the number of mild seizures (level 2). Diazepam decreased the severity and duration of seizures. However, it increased the number of mild seizures (level 2). In comparison with the tramadol alone group, the acute quercetin group exhibited higher numbers of mild (level 2) and moderate (level 3) seizures. Chronic quercetin administration significantly increased the number of mild seizures. In the GEE model, all groups had higher sedation levels than the saline only group (P < 0.001). None of the protocols had a significant effect on sedation levels compared to the tramadol group. CONCLUSION: The combined administration of naloxone and diazepam in acute-on-chronic tramadol poisoning can effectively reduce most seizure variables compared to tramadol use alone. However, none of the treatments improved sedation levels.