Prediction the prognosis of the poisoned patients undergoing hemodialysis using machine learning algorithms.

BACKGROUND: Hemodialysis is a life-saving treatment used to eliminate toxins and metabolites from the body during poisoning. Despite its effectiveness, there needs to be more research on this method precisely, with most studies focusing on specific poisoning. This study aims to bridge the existing knowledge gap by developing a machine-learning prediction model for forecasting the prognosis of the poisoned patient undergoing hemodialysis. METHODS: Using a registry database from 2016 to 2022, this study conducted a retrospective cohort study at Loghman Hakim Hospital. First, the relief feature selection algorithm was used to identify the most important variables influencing the prognosis of poisoned patients undergoing hemodialysis. Second, four machine learning algorithms, including extreme gradient boosting (XGBoost), histgradient boosting (HGB), k-nearest neighbors (KNN), and adaptive boosting (AdaBoost), were trained to construct predictive models for predicting the prognosis of poisoned patients undergoing hemodialysis. Finally, the performance of paired feature selection and machine learning (ML) algorithm were evaluated to select the best models using five evaluation metrics including accuracy, sensitivity, specificity the area under the curve (AUC), and f1-score. RESULT: The study comprised 980 patients in total. The experimental results showed that ten variables had a significant influence on prognosis outcomes including age, intubation, acidity (PH), previous medical history, bicarbonate (HCO3), Glasgow coma scale (GCS), intensive care unit (ICU) admission, acute kidney injury, and potassium. Out of the four models evaluated, the HGB classifier stood out with superior results on the test dataset. It achieved an impressive mean classification accuracy of 94.8%, a mean specificity of 93.5 a mean sensitivity of 94%, a mean F-score of 89.2%, and a mean receiver operating characteristic (ROC) of 92%. CONCLUSION: ML-based predictive models can predict the prognosis of poisoned patients undergoing hemodialysis with high performance. The developed ML models demonstrate valuable potential for providing frontline clinicians with data-driven, evidence-based tools to guide time-sensitive prognosis evaluations and care decisions for poisoned patients in need of hemodialysis. Further large-scale multi-center studies are warranted to validate the efficacy of these models across diverse populations.

Assessment of renal function indexes in methamphetamine or tramadol intoxication adults to the emergency departments: a systematic review and meta-analysis.

BACKGROUND: Renal dysfunction is one of the adverse effects observed in methamphetamine (MET) or tramadol abusers. In this study, we aimed to review articles involving intoxication with MET or tramadol to assess the occurrence of renal dysfunction. METHODS: Two researchers systematically searched PubMed, Scopus, Web of Sciences, and Google Scholar databases from 2000 to 2022. All articles that assessed renal function indexes including creatine, Blood Urea Nitrogen (BUN), and Creatine phosphokinase (CPK) in MET and tramadol intoxication at the time of admission in hospitals were included. We applied random effect model with Knapp-Hartung adjustment for meta-analysis using STATA.16 software and reported outcomes with pooled Weighted Mean (WM). RESULTS: Pooled WM for BUN was 29.85 (95% CI, 21.25-38.46) in tramadol intoxication and 31.64(95% CI, 12.71-50.57) in MET intoxication. Pooled WM for creatinine in tramadol and MET intoxication was respectively 1.04 (95% CI, 0.84-1.25) and 1.35 (95% CI, 1.13-1.56). Also, pooled WM for CPK was 397.68(376.42-418.94) in tramadol and 909.87(549.98-1269.76) in MET intoxication. No significance was observed in publication bias and heterogeneity tests. CONCLUSION: Our findings showed that tramadol or MET intoxication is associated with a considerably increased risk of renal dysfunction that may result in organ failure.

The outbreak of methanol intoxication during COVID-19 pandemic: prevalence of brain lesions and its predisposing factors.

During the COVID-19 pandemic, methanol-containing beverages' consumption has risen because people mistakenly believed that alcohol might protect them against the virus. This study aimed to evaluate the prevalence and predisposing factors of brain lesions in patients with methanol toxicity and its outcome. A total of 516 patients with confirmed methanol poisoning were enrolled in this retrospective study, of which 40 patients underwent spiral brain computed tomography (CT) scan. The presence of unilateral or bilateral brain necrosis was significantly higher in the non-survival group (p = 0.001). Also, intracerebral hemorrhage (ICH) and brain edema were prevalent among patients that subsequently died (p = 0.004 and p = 0.002, respectively). Lower Glasgow Coma Scale (GCS) was related to a higher mortality rate (p = 0.001). The mortality rate in chronic alcohol consumption was lower than the patients who drank alcohol for the first time (p = 0.014). In conclusion, increasing the number of methanol poisoning and its associated mortality and morbidity should be considered a threat during the COVID-19 pandemic.

Nasal Air Puff Promotes Default Mode Network Activity in Mechanically Ventilated Comatose Patients: A Noninvasive Brain Stimulation Approach.

OBJECTIVES: Coma state and loss of consciousness are associated with impaired brain activity, particularly gamma oscillations, that integrate functional connectivity in neural networks, including the default mode network (DMN). Mechanical ventilation (MV) in comatose patients can aggravate brain activity, which has decreased in coma, presumably because of diminished nasal airflow. Nasal airflow, known to drive functional neural oscillations, synchronizing distant brain networks activity, is eliminated by tracheal intubation and MV. Hence, we proposed that rhythmic nasal air puffing in mechanically ventilated comatose patients may promote brain activity and improve network connectivity. MATERIALS AND METHODS: We recorded electroencephalography (EEG) from 15 comatose patients (seven women) admitted to the intensive care unit because of opium poisoning and assessed the activity, complexity, and connectivity of the DMN before and during the nasal air-puff stimulation. Nasal cavity air puffing was done through a nasal cannula controlled by an electrical valve (open duration of 630 ms) with a frequency of 0.2 Hz (ie, 12 puff/min). RESULTS: Our analyses demonstrated that nasal air puffing enhanced the power of gamma oscillations (30-100 Hz) in the DMN. In addition, we found that the coherence and synchrony between DMN regions were increased during nasal air puffing. Recurrence quantification and fractal dimension analyses revealed that EEG global complexity and irregularity, typically seen in wakefulness and conscious state, increased during rhythmic nasal air puffing. CONCLUSIONS: Rhythmic nasal air puffing, as a noninvasive brain stimulation method, opens a new window to modifying the brain connectivity integration in comatose patients. This approach may potentially influence comatose patients' outcomes by increasing brain reactivity and network connectivity.

Hearing status in patients with overdose of illicit drugs.

Background: The overdose of illicit drugs is not always fatal but can lead to various complications. One of the unusual medical complications is a sensorineural hearing loss (SNHL). There are multiple case reports about this subject. Considering the importance of hearing loss on quality of life, we investigated hearing status in patients with overdose of illicit drugs. Methods: This cross-sectional study was performed in Loghman Hakim hospital in Shahid Beheshti University of Medical Sciences, Tehran, Iran, in 2016-2017. The hearing status of 95 patients with illicit drugs overdose and 44 healthy individuals were assessed using standard pure tone audiometry and distortion product otoacoustic emissions. The patient group was categorized based on hearing status and compared based on some variables. We applied 2 independent t tests, Mann-Whitney, Chi-square, and binary logistic regression tests. All analyses were conducted in Stata 12 (STATA Corp, USA) and significance level was set at less than 0.05. Results: We found higher percentage frequency of SNHL in the patient group than the control group (15.8% vs 2.3%; p=0.021). The frequency of hearing loss was 21.7% in opioid users, 5.3% in stimulant users, and 6.3% in concomitant use of both. There was a significant relationship between SNHL and overdose of illicit drugs (aOR = 14.48, 95% CI = 1.53-136.44; p=0.019) with adjusting age, sex, and smoking. Conclusion: Illicit drugs overdose can potentially affect the hearing system. Opioid drugs, especially methadone and tramadol, have been found to affect the hearing system. Therefore, it is important to conduct longitudinal studies to demonstrate the role of opioid drugs on the hearing system.

Potential prognostic roles of serum lactate and Creatine kinase levels in poisoned patients.

BACKGROUND: Examination of serum lactate level and its changes, as an indicator of tissue oxygenation, as well as level of creatine kinase (CK) inhibitors, as a factor of mortality which partially expresses heart, brain, and muscle damage, may be considered as tools to determine prognosis in critically ill patients. We aimed to evaluate these two factors as potential prognostic factors in critically poisoned patients admitted to our toxicology ICU. METHOD: This is a cross-sectional descriptive-analytic study that was performed on poisoned patients referred to emergency department of Loghman Hakim Hospital. One-hundred critically poisoned patients who had been admitted to ICU were conveniently chosen using a random number table and included into the study after obtaining consent forms from their next of kin. Their serum lactate and CK levels were checked on admission. These levels were compared subsequently between survivors and non-survivors to seek for their potential prognostic role. RESULTS: In a total of 100 patients enrolled, 61 were male. Serum level of lactate (with a cut off of 26 mg/dL) and serum CK with a cutoff point of 169 U/L could have prognosticated death with sensitivity and specificity of 78 and 77% (for lactate) and 74 and 62% (for serum CK), respectively. CONCLUSIONS: In poisoned patients, serum lactate and CK can be used as possible prognostic factors because they rapidly increase in the serum and are easily detectable.

Inhibition of glucose-6-phosphate dehydrogenase protects hepatocytes from aluminum phosphide-induced toxicity.

Aluminum phosphide (AlP) poisoning is a severe toxicity with 30-70% mortality rate. However, several case reports presented AlP-poisoned patients with glucose-6-phosphate dehydrogenase (G6PD) deficiency and extensive hemolysis who survived the toxicity. This brought to our mind that maybe G6PD deficiency could protect the patients from severe fatal poisoning by this pesticide. In this research, we investigated the protective effect of 6-aminonicotinamide (6-AN)- as a well-established inhibitor of the NADP+- dependent enzyme 6-phosphogluconate dehydrogenase- on isolated rat hepatocytes in AlP poisoning. Hepatocytes were isolated by collagenase perfusion method and incubated into three different flasks: control, AlP, and 6-AN+ALP. Cellar parameters such as cell viability, reactive oxygen species (ROS) formation, mitochondria membrane potential collapse (MMP), lysosomal integrity, content of reduced (GSH) and oxidized glutathione (GSSG) and lipid peroxidation were assayed at intervals. All analyzed cellular parameters significantly decreased in the third group (6-AN+AlP) compared to the second group (AlP), showing the fact that G6PD deficiency induced by 6-AN had a significant protective effect on the hepatocytes. It was concluded that G6PD deficiency significantly reduced the hepatotoxicity of AlP. Future drugs with the power to induce such deficiency may be promising in treatment of AlP poisoning.

Clinical and biochemical analysis of acute paint thinner intoxication in adults: a retrospective descriptive study.

CONTEXT: Paint thinner contains a mixture of various aromatic hydrocarbons. A few studies have reported biochemical abnormalities and clinical symptoms of paint thinner intoxication among adult patients. OBJECTIVE: We aimed to design a retrospective descriptive study to evaluate clinical and laboratory biochemistry abnormalities due to paint thinner intoxication among adult patients. METHODS: Data were obtained by using questionnaires from paint thinner-intoxicated patients recruited at the Loghman-Hakim General Teaching Hospital Poison Center. RESULTS: Clinical and paraclinical data from a total of 37 patients, 24 males (64.86%) and 13 females (35.14%) with the mean age of 34.35 ± 14.15 years and mode of 22 years, was obtained and analyzed. Patients' ages ranged between 15 and 70 years. The estimated mean consumed dose was 246.70 ± 390.72 ml with a mode of 60 ml (range of 1-1500 ml). Nausea, vomiting, asthma, sore throat, stomach ache, drowsiness, dizziness, agitation, cough and diarrhea were the most frequent clinical features, respectively. Reported tissue damage biomarkers were alkaline phosphatase (ALP, 233.84 ± 122.06) and lactate dehydrogenase enzymes (LDH, 749.33 ± 471.03 IU/l). They reflected development of liver and pulmonary toxicities. Arterial blood gas (ABG) showed acidosis without hypoxia in adult paint thinner-intoxicated patients. DISCUSSION AND CONCLUSION: Focusing on biochemical abnormalities and clinical toxicity symptoms is essential for screening organs in paint thinner toxicity. In addition, they provide good information for physicians/clinical toxicologists to perform appropriate conservative treatments in adult paint thinner-intoxicated patients.

Favorable results after conservative management of 316 valproate intoxicated patients.

BACKGROUND: Valproic acid (VPA) is an effective antiepileptic drug widely used worldwide. Despite several studies indicating the usefulness of intravenous L-carnitine in the treatment of VPA poisoning, this drug is not readily available in Iran. The aim of this study was to determine whether supportive care without antidote would result in acceptable outcomes in VPA poisoned patients. MATERIALS AND METHODS: In an observational, retrospective, single-center case series, all patients >12-year-old with VPA overdose who had referred to a tertiary center between 2009 and 2013 were consecutively enrolled. Patients' demographic and presenting features, physical examinations, clinical management, laboratory data, and outcomes were recorded. RESULTS: A total of 316 patients were enrolled with pure VPA toxicity. The most common presenting signs/symptoms were drowsiness, nausea and vomiting, vertigo, and headache. In the course of the disease, 14 patients (4.4%) were intubated and three (0.9%) required hemodialysis with mean dialysis sessions of two. Fourteen patients were admitted to Intensive Care Unit, and seizures occurred in five. The initial level of consciousness was lower in patients with poor outcome. The median ingested dose of VPA in patients who required dialysis was significantly higher (20 vs. 6 g; P = 0.006). Multivariate analyses revealed that coma on presentation was associated with a worse outcome (P = 0.001; odds ratio = 61.5, 95% CI = 5.8-646.7). CONCLUSION: Prognosis of VPA poisoned patients appears to be good even with supportive care. According to our study, older age, ingestion of higher amounts of VPA and lower PCO2, HCO3, base excess, and CPK levels prone the patients to more severe toxicities in univariate analysis, but the main poor prognostic factor is coma on presentation in multivariate analysis.

Acute tramadol poisoning and its clinical and laboratory findings.

BACKGROUND: Tramadol is a centrally acting analgesic with opioid and nonopioid properties, which extensively used in the relief of mild to moderate pain. Tramadol poisoning is a common cause of acute pharmaceutical poisoning in Iran. There are a few studies about clinical and laboratory findings related to acute tramadol poisoning. Therefore, the aim of this study was to demonstrate the clinical and laboratory findings in tramadol acute poisoning cases. MATERIALS AND METHODS: This was a retrospective descriptive study of patients with acute tramadol poisoning who referred to Loghman Hakim Hospital Poison Center during January to April 2012. Data such as patient's age, sex, time of ingestion, ingested dose, cause of poisoning, mean duration of hospitalization, patient's clinical presentations, laboratory findings, therapeutic measures, and patient's outcome have collected in a predesigned checklist. RESULTS: A total of 144 patients including 111 men (77%) and 33 women (23%) with acute tramadol poisoning was included in this study. The mean ingested dose was 1971.2 mg (100-20000 mg). Seizure (47.91%) was the most frequent clinical symptom. Blood gas on admission showed pH (7.3 ± 0.1), PCO2 (49.7 ± 8.6 mmHg) and HCO3 (-) (24.1 ± 3.8 mEq/L), indicating pure acute respiratory acidosis may be occurred in tramadol-intoxicated patients. There were significant differences between tramadol-intoxicated cases with and without a seizure with regard to the time interval between ingestion and admission on hospital, ingested dose and PCO2. CONCLUSION: Seizure and rise of PCO2 were the most findings in this study.

Age- and gender-specific acute poisoning with drugs and medications affecting nervous system.

BACKGROUND: We investigated acute poisonings resulting from medications affecting the nervous system and illicit substances at Loghman Hakim Hospital in Tehran. METHODS: We retrospectively reviewed patient records at Iran's largest tertiary toxicology referral center between January 2010 and December 2015. We analyzed the prevalence, trend, age and gender distribution of acute poisoning caused by nervous system agents. RESULTS: The present study included 16,657 (57.27%) males and 12,426 (42.73%) females, resulting in 29,083 patients. The median age of men and women was 29 and 26 years, respectively (p < 0.0001). There were 12,071 (72.47%) men and 10,326 (83.10%) women under the age of 40 (p < 0.001). Most cases were intentional (69.38% in men and 79.00% in women, p < 0.001) and 44.10% had a history of poisoning. The proportions of men and women varied significantly between different age groups and nervous system agents. For women, the most common agent was alprazolam, whereas for men, methadone. The overall trend of acute poisoning with drug used in addictive disorders, opioids and alcohol was increasing but decreasing with benzodiazepines and antidepressants. Acute poisoning by nervous system agents led to more deaths in men (1.95% vs. 0.56%; p < 0.001). CONCLUSIONS: Methadone intoxication was common especially among young men and most of these intoxications were intentional. Women and men aged 20-29 most frequently suffer poisoning from alprazolam and clonazepam, respectively. Women over 60 and men over 30 used opium. Illicit drugs caused more than half of the deaths, and opium dominated. This study may create awareness and develop educational and preventive gender and age-specific local programs.

Prediction of naloxone dose in opioids toxicity based on machine learning techniques (artificial intelligence).

BACKGROUND: Treatment management for opioid poisoning is critical and, at the same time, requires specialized knowledge and skills. This study was designed to develop and evaluate machine learning algorithms for predicting the maintenance dose and duration of hospital stay in opioid poisoning, in order to facilitate appropriate clinical decision-making. METHOD AND RESULTS: This study used artificial intelligence technology to predict the maintenance dose and duration of administration by selecting clinical and paraclinical features that were selected by Pearson correlation (filter method) (Stage 1) and then the (wrapper method) Recursive Feature Elimination Cross-Validated (RFECV) (Stage2). The duration of administration was divided into two categories: A (which includes a duration of less than or equal to 24 h of infusion) and B (more than 24 h of naloxone infusion). XGBoost algorithm model with an accuracy rate of 91.04%, a prediction rate of 91.34%, and a sensitivity rate of 91.04% and area under the Curve (AUC) 0.97 was best model for classification patients. Also, the best maintenance dose of naloxone was obtained with XGBoost algorithm with R2 = 0.678. Based on the selected algorithm, the most important features for classifying patients for the duration of treatment were bicarbonate, respiration rate, physical sign, The partial pressure of carbon dioxide (PCO2), diastolic blood pressure, pulse rate, naloxone bolus dose, Blood Creatinine(Cr), Body temperature (T). The most important characteristics for determining the maintenance dose of naloxone were physical signs, bolus dose of 4.5 mg/kg, Glasgow Coma Scale (GCS), Creatine Phosphokinase (CPK) and intensive care unit (ICU) add. CONCLUSION: A predictive model can significantly enhance the decision-making and clinical care provided by emergency physicians in hospitals and medical settings. XGBoost was found to be the superior model.

Explainable artificial intelligence (XAI) for predicting the need for intubation in methanol-poisoned patients: a study comparing deep and machine learning models.

The need for intubation in methanol-poisoned patients, if not predicted in time, can lead to irreparable complications and even death. Artificial intelligence (AI) techniques like machine learning (ML) and deep learning (DL) greatly aid in accurately predicting intubation needs for methanol-poisoned patients. So, our study aims to assess Explainable Artificial Intelligence (XAI) for predicting intubation necessity in methanol-poisoned patients, comparing deep learning and machine learning models. This study analyzed a dataset of 897 patient records from Loghman Hakim Hospital in Tehran, Iran, encompassing cases of methanol poisoning, including those requiring intubation (202 cases) and those not requiring it (695 cases). Eight established ML (SVM, XGB, DT, RF) and DL (DNN, FNN, LSTM, CNN) models were used. Techniques such as tenfold cross-validation and hyperparameter tuning were applied to prevent overfitting. The study also focused on interpretability through SHAP and LIME methods. Model performance was evaluated based on accuracy, specificity, sensitivity, F1-score, and ROC curve metrics. Among DL models, LSTM showed superior performance in accuracy (94.0%), sensitivity (99.0%), specificity (94.0%), and F1-score (97.0%). CNN led in ROC with 78.0%. For ML models, RF excelled in accuracy (97.0%) and specificity (100%), followed by XGB with sensitivity (99.37%), F1-score (98.27%), and ROC (96.08%). Overall, RF and XGB outperformed other models, with accuracy (97.0%) and specificity (100%) for RF, and sensitivity (99.37%), F1-score (98.27%), and ROC (96.08%) for XGB. ML models surpassed DL models across all metrics, with accuracies from 93.0% to 97.0% for DL and 93.0% to 99.0% for ML. Sensitivities ranged from 98.0% to 99.37% for DL and 93.0% to 99.0% for ML. DL models achieved specificities from 78.0% to 94.0%, while ML models ranged from 93.0% to 100%. F1-scores for DL were between 93.0% and 97.0%, and for ML between 96.0% and 98.27%. DL models scored ROC between 68.0% and 78.0%, while ML models ranged from 84.0% to 96.08%. Key features for predicting intubation necessity include GCS at admission, ICU admission, age, longer folic acid therapy duration, elevated BUN and AST levels, VBG_HCO3 at initial record, and hemodialysis presence. This study as the showcases XAI's effectiveness in predicting intubation necessity in methanol-poisoned patients. ML models, particularly RF and XGB, outperform DL counterparts, underscoring their potential for clinical decision-making.

Prediction of acute methanol poisoning prognosis using machine learning techniques.

Methanol poisoning is a global public health concern, especially prevalent in developing nations. This study focuses on predicting the severity of methanol intoxication using machine learning techniques, aiming to improve early identification and prognosis assessment. The study, conducted at Loghman Hakim Hospital in Tehran, Iran. The data pertaining to individuals afflicted with methanol poisoning was retrieved retrospectively and divided into training and test groups at a ratio of 70:30. The selected features were then inputted into various machine learning methods. The models were implemented using the Scikit-learn library in the Python programming language. Ultimately, the efficacy of the developed models was assessed through ten-fold cross-validation techniques and specific evaluation criteria, with a confidence level of 95%. A total number of 897 patients were included and divided in three groups including without sequel (n = 573), with sequel (n = 234), and patients who died (n = 90). The two-step feature selection was yielded 43 features in first step and 23 features in second step. In best model (Gradient Boosting Classifier) test dataset metric by 32 features younger age, higher methanol ingestion, respiratory symptoms, lower GCS scores, type of visual symptom, duration of therapeutic intervention, ICU admission, and elevated CPK levels were among the most important features predicting the prognosis of methanol poisoning. The Gradient Boosting Classifier demonstrated the highest predictive capability, achieving AUC values of 0.947 and 0.943 in the test dataset with 43 and 23 features, respectively. This research introduces a machine learning-driven prognostic model for methanol poisoning, demonstrating superior predictive capabilities compared to traditional statistical methods. The identified features provide valuable insights for early intervention and personalized treatment strategies.

Role of clinical and paraclinical manifestations of methanol poisoning in outcome prediction.

BACKGROUND: Methanol poisoning is one of the most important poisoning due to drinking of illegal and non-standard alcoholic beverage in some countries. Relatively limited studies have been carried out to identify the prognostic factors in methanol poisoning. MATERIALS AND METHODS: We performed a retrospective study on acute methanol-intoxicated patients, which were admitted on the Loghman Hakim Hospital Poison Center (Tehran, Iran) over a 24-month period. The demographic data, clinical manifestations and paraclinical findings, therapeutic interventions and outcome (survivors with or without complications and non-survivors) were extracted. RESULTS: We evaluated 30 patients with methanol poisoning during 2 years. All of the patients were male; with the median age of 25.5 years. Visual disturbances, respiratory manifestations, and loss of consciousness were the most common clinical manifestations on admission time. The results of paraclinical manifestations on admission time were as following: The median of blood methanol level was 20 mg/dL. The median of pH, PaCO2 and HCO3 was 7.15, 22.35 mmHg and 7.2 mEq/L, respectively. Hyperglycemia was observed in 70% of the patients and the median of blood glucose was 184.5 mg/dL. In fourteen of the patients hemodialysis was performed. Median duration of hospitalization was 48 h. Nine of the patients died. There was a significant difference between survivors and non-survivors with regard to coma, blood methanol level, and PaCO2 and blood glucose. Furthermore, we did not observe a significant difference between these two groups regarding to pH, HCO3 level, and time interval between alcohol ingestion to hospital admission and beginning of hemodialysis. CONCLUSION: Regarding the results of this study, it can be suggested that coma, PaCO2 and hyperglycemia on admission time could be used as strong predictors of poor outcome.

Association between intoxication with psychoactive substances and adverse effects occurrence in consumers.

Background: The prevalence of psychoactive substance use is increasing worldwide and identifying adverse effects of these types of drugs is necessary in intoxicated patients. Objective: We aimed to investigate the association of psychoactive substance intoxication with their adverse effects on the functioning of the bodily organs. Methods: This was a single-center study between March 2019 and April 2022 on intoxicated patients with psychoactive substances. Inclusion criteria were intoxication with alcohol, opioids, and stimulants, and having available results of laboratory biomarkers. Demographic and clinical data of patients at the time of admission as well as during hospitalization were reviewed, retrospectively. Data were analyzed using a generalized linear mixed model in R software and the Adjusted Odds Ratio (AOR) was estimated. Results: A total of 800 hospitalized patients in the ICU (n = 400) and general ward (n = 400) were divided into two groups of intoxicated with alcohol (n = 200) and opioids or stimulants (n = 200). Liver (AOR = 0.15, p = 0.033; AOR = 0.13, p = 0.007) and kidney (AOR = 0.46, p = 0.004; AOR = 0.24, p = 0.021) dysfunction occurred less in the ICU and general ward, respectively, in opioids or stimulants intoxication compared to alcohol. Cardiovascular dysfunctions occurred more in opioids or stimulants intoxication compared to alcohol in both ICU (AOR = 10.32, p < 0.0001) and general ward (AOR = 4.74, p < 0.0001). Conclusion: Kidney dysfunctions had a greater effect on mortality compared to other dysfunctions. During the follow-up, the incidence of dysfunctions increased in those intoxicated with opioids or stimulants. Men experienced more liver and kidney dysfunctions as well as mortality, but psychoactive substance experience was a protective factor in cardiovascular dysfunctions and mortality.

A rare case report of lead encephalopathy due to high blood lead level.

Here we report a case of lead poisoning having a serum lead level of 412 mcg dL-1 who presented with decreasing level of consciousness and recurrent seizures. He responded well to treatment with chelation therapy.

Montelukast Is Effective in Treating Rhabdomyolysis Due to Intoxication: A Randomized Clinical Trial.

INTRODUCTION: Rhabdomyolysis is a clinical syndrome accompanied with biochemical changes that is diagnosed in some patients with acute chemical or drug poisoning. In this regard, the present study aimed to evaluate the effects of Montelukast in the treatment of intoxication-induced rhabdomyolysis. METHODS: This single-blind randomized clinical trial study was conducted in Loghman Hakim Hospital from March 2021 to March 2022. The study participants were 60 individuals evenly distributed into experimental and control groups. The experimental group received Montelukast plus routine treatment and the control group Creatine phosphokinase (CPK), urea, creatinine, aspartate aminotransferase (AST) and alanine transaminase (ALT) levels were monitored daily in both groups for seven days. The variables of age, gender and history of diabetes mellitus and kidney diseases were recorded. RESULTS: The mean age was 39.9 ± 16.87 and 38.2 ± 16.3 years in the control and intervention groups, respectively. Montelukast significantly (P < .05) reduced CPK levels on days five and seven, urea on days three, four, five and seven, and creatinine on days two to seven. The AST and ALT levels, unlike the control group which has a decreasing trend, increased first in the Montelukast group and then decreased on the sixth and seventh days. CONCLUSION: The results showed that Montelukast effectively reduced CPK, urea and creatinine levels, as well as the recovery time in patients with poison-induced rhabdomyolysis. In other words, Montelukast is effective in the treatment of rhabdomyolysis.  DOI: 10.52547/ijkd.7222.

Visual impairment following aluminum phosphide poisoning: A rare case.

Key Clinical Message: Aluminum phosphide poisoning may cause rare visual impairment. In a case, a 31-year-old female, visual loss was linked to shock-induced hypoperfusion, causing oxygen lack and cerebral atrophy, emphasizing the need for identifying atypical symptoms. Abstract: This case report describes the multidisciplinary evaluation of a 31-year-old female patient who suffered from visual impairment as a result of aluminum phosphide (AlP) poisoning. Phosphine, which is formed in the body when AlP reacts with water, cannot cross the blood-brain barrier; therefore, visual impairment seems unlikely to be the direct result of phosphine. To our knowledge, it is the first documented report of such impairment due to AlP.

Incidence of rhabdomyolysis occurrence in psychoactive substances intoxication: a systematic review and meta-analysis.

Rhabdomyolysis is a potentially life-threatening condition induced by diverse mechanisms including drugs and toxins. We aimed to investigate the incidence of rhabdomyolysis occurrence in intoxicated patients with psychoactive substances. In this review, three databases (PubMed, Scopus, Web of Science) and search engine (Google Scholar) were searched by various keywords. After the screening of retrieved documents, related data of included studies were extracted and analyzed with weighted mean difference (WMD) in random effect model. The highest incidence of rhabdomyolysis was observed in intoxication with heroin (57.2 [95% CI 22.6-91.8]), amphetamines (30.5 [95% CI 22.6-38.5]), and cocaine (26.6 [95% CI 11.1-42.1]). The pooled effect size for blood urea nitrogen (WMD = 8.78, p = 0.002), creatinine (WMD = 0.44, p < 0.001), and creatinine phosphokinase (WMD = 2590.9, p < 0.001) was high in patients with rhabdomyolysis compared to patients without rhabdomyolysis. Our results showed a high incidence of rhabdomyolysis induced by psychoactive substance intoxication in ICU patients when compared to total wards. Also, the incidence of rhabdomyolysis occurrence was high in ICU patients with heroin and amphetamine intoxication. Therefore, clinicians should anticipate this complication, monitor for rhabdomyolysis, and institute appropriate treatment protocols early in the patient's clinical course.