Predictors of poor outcomes among patients of acute methanol intoxication with particular reference to Sequential Organ Failure Assessment (SOFA) score

Assessment of co-ingestion effects on poisoning patterns, drug-drug interactions, and adverse outcomes in acute toxic exposure

Multiple toxic exposures are increasing nowadays. In cases of acute poisoning involving multiple agents, there is a potential for additional toxicity that goes beyond the effects and toxicity of each drug. Very scarce studies have investigated the problem of multiple toxic exposures where the information on drug-drug interactions (DDIs) originates from clinical experience, which is inconclusive and cannot be generalized to patients. Therefore, the current study aimed to explore the influence of co-ingestion on the clinical presentation of exposed patients and to identify the common associated DDIs and their effect on poisoning outcomes, including the need for mechanical ventilation (MV), intensive care unit (ICU) utilization, and prolonged hospital stay. The current study is a retrospective cross-sectional study that was conducted using medical records of 169 adult patients admitted to a poison control center and diagnosed with acute drug poisoning. Of them, 40.8 % were exposed to multiple drugs. The total number of drugs reported in the current study was 320 preparations, with an average of 1.9 drugs per patient. There were about 726 potential DDIs; more than half of these interactions were significant (n = 486). Antidepressants and psychotropics showed the highest total number of DDIs. Patients with multiple ingestion were significantly older and this pattern of exposure was more frequent among suicidal attempters, substance abusers, cardiac patients, and patients diagnosed with neurological and psychological problems. Moreover, patients with multiple ingestions showed severe presentations indicated by higher grades of Poison Severity Score and lower Glasgow Coma Scale. Multiple ingestion was associated with higher liability for MV, ICU admission, and prolonged length of hospital stay (p < 0.001). There was a significant moderate direct correlation between the number of drugs consumed and the number of resulting DDIs (r = 0.542, p < 0.001). There was a significant direct correlation between the occurrence of significant chronic/chronic drug interactions from one side and the history of substance abuse (r = 0.596, p = 0.041) and psychological illness (r = 0.662, p = 0.019) from the other side. Moreover, significant acute/acute drug interactions were correlated with being male (r = 0.969, p < 0.001) of older age (r = 0.672, p = 0.024). Similarly, significant acute/chronic drug interactions were moderately correlated with being a male (r = 0.692, p = 0.013). The presence of epilepsy and psychological problems were the main significant predictors of multiple acute toxic exposures. Among the patients exposed acutely to more than one agent who were on long-term treatment, exposure to three drugs or more could significantly predict the need for MV with excellent area under the curve (AUC) of 0.896 and 77.0 % accuracy. Moreover, and it was a fair predictor of ICU admission (AUC = 0.625), with an 88.9 % ability to exclude patients unlikely to need ICU admission. Particular attention should be paid to the patients at risk of potential DDIs. When prescribing drugs, the minimum number of drugs with the lowest effective doses, and minimal potential DDIs should be prioritized.

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.

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.

Evaluation of various scoring systems as predictors of the need for intensive care unit admission and other adverse outcomes among patients with acute clozapine poisoning

Acute clozapine poisoning (ACP) is frequently reported worldwide. We evaluated the efficacy of the Poison Severity Score (PSS), Acute Physiology and Chronic Health Evaluation II (APACHE II) score, Rapid Emergency Medicine Score (REMS), and Modified Early Warning Score (MEWS) as predictors for intensive care unit (ICU) admission, mechanical ventilation (MV), mortality, and length of hospital stay in patients with ACP. A retrospective cohort study was conducted using records of patients diagnosed with ACP from January 2017 to June 2022 and admitted to an Egyptian poison control center. Analyzing 156 records showed that all assessed scores were significant predictors of the studied outcomes. The PSS and APACHE II score showed the highest area under the curve (AUC) as ICU admission predictors with insignificant variations. The APACHE II score showed the best discriminatory power in predicting MV and mortality. Nevertheless, MEWS exhibited the highest odds ratio (OR) as an ICU predictor (OR = 2.39, and 95% confidence interval = 1.86-3.27) and as a mortality predictor (OR = 1.98, and 95% confidence interval = 1.16-4.41). REMS and MEWS were better predictors of length of hospital stay compared with the APACHE II score. The simpler, lab-independent nature and the comparable discrimination but higher odds ratio of MEWS compared with APACHE II score justify MEWS' superior utility as an outcome predictor in ACP. We recommend using either the APACHE II score or MEWS, depending on the availability of laboratory investigations, resources, and the case's urgency. Otherwise, the MEWS is a substantially feasible, economical, and bedside alternative outcome predictor in ACP.

Could the serum glucose/potassium ratio offer an early reliable predictor of life-threatening events in acute methylxanthine intoxication?

Methylxanthines are widely used to manage pulmonary disorders, particularly in developing countries. Methylxanthines are unsafe due to their narrow therapeutic index and associated morbidity and mortality. The current study aimed to investigate the role of glucose/potassium ratio as a substantially useful early predictor of life-threatening events (LTEs) in the form of cardiovascular and neurological complications among methylxanthine users. A retrospective cohort study was conducted using medical records of patients diagnosed with acute methylxanthine intoxications and presented to an Egyptian Poison Control Center for 2 years. A total of 366 patients were enrolled. Of them, 59 patients (16.1%) were complicated with LTEs. The most frequent serious arrhythmia was T wave inversion (45.6% of patients with LTEs). Laboratory investigations that could significantly predict LTEs were the random blood glucose and potassium levels, glucose/potassium ratio, pH, liver transaminases, HCO3 level, hemoglobin, and platelet count (P < 0.05). The glucose/potassium ratio was the best predictor of LTEs (odds ratio = 2.92, and 95% confidence interval = 2.02-4.23). With an excellent area under the curve (0.906) and at a cutoff of 2.44, that ratio could correctly classify the patients based on their risk of LTEs with an overall accuracy of 73% (sensitivity of 88% and specificity of 70%). The current study endorsed an important, feasible, and easily obtainable ratio that could predictor stratify the patients according to severity and risk of LTEs, which guides the decision-making and prioritizes the treatment lines in methylxanthine intoxicated patients.

Accuracy of Rapid Emergency Medicine Score and Sequential Organ Failure Assessment Score in predicting acute paraphenylenediamine poisoning adverse outcomes

Paraphenylenediamine (PPD) is a commonly used xenobiotic in hair dying, causing deleterious outcomes in acute poisoning. Although many epidemiological studies and case reports explained their clinical presentations and fatal consequences, no studies have evaluated the early determinants of adverse outcomes. Therefore, the present study aimed to assess the initial predictors of acute PPD poisoning adverse outcomes, focusing on the discriminatory accuracy of the Rapid Emergency Medicine Score (REMS) and Sequential Organ Failure Assessment (SOFA) score. A retrospective cohort study included all acute PPD-poisoned patients admitted to three Egyptian emergency hospitals from January 2020 to January 2022. Data was gathered on admission, including demographics, toxicological, clinical, scoring systems, and laboratory investigations. Patients were categorized according to their outcomes (mortality and complications). Ninety-seven patients with acute PPD poisoning were included, with a median age of 23 years, female predominance (60.8%), and suicidal intention (95.9%). Out of all patients, 25.77% died, and 43.29% had complicated outcomes. Respiratory failure was the primary cause of fatalities (10.30%), while acute renal failure (38.14%) was a chief cause of complications. The delay time till hospitalization, abnormal electrocardiogram, initial creatine phosphokinase, bicarbonate level, REMS, and SOFA scores were the significant determinants for adverse outcomes. The REMS exhibited the highest odds ratio (OR = 1.91 [95% confidence interval (CI): 1.41-2.60], p < 0.001) and had the best discriminatory power with the area under the curve (AUC) = 0.918 and overall accuracy of 91.8% in predicting mortality. However, the SOFA score had the highest odds ratio (OR = 4.97 [95% CI: 1.16-21.21], p = 0.001) and only yielded a significant prediction for complicated sequels with AUC = 0.913 and overall accuracy of 84.7%. The REMS is a simple clinical score that accurately predicts mortality, whereas the SOFA score is more practicable for anticipating complications in acute PPD-poisoned patients.

Comparing the effectiveness of L-carnitine and paraffin oil in acute aluminum phosphide poisoning using predictive biomarkers and scores: A randomized controlled clinical trial

Aluminum phosphide (AlP) poisoning is a serious medical emergency with a high mortality rate. The absence of an exact antidote for AlP poisoning necessitates the quest for alternative treatment options. The study sought to assess the efficacy of adding L-carnitine or medicated paraffin oil to the conventional approach of treatment employed in cases of acute AlP poisoning. We conducted a 1 year, randomized, controlled, parallel-group, single-blind clinical study. 96 individuals with acute AlP poisoning were randomly assigned to one of three groups. The standard AlP therapy was administered to all groups according to the Poison Control Center guidelines at the Ain-Shams University hospitals. All patients underwent a medical history review, clinical examination, and laboratory tests. The outcomes were assessed. The participants in the study groups had mean ages ranging from 25.6 to 26.3 years. The cases analyzed were evenly distributed between genders, with the majority originating from rural areas. The average delay time varied from 2.9 to 4.2 h. All patients in the study reported ingesting AlP during suicide attempts. 12 hours after admission, many clinical and biochemical data improved in both intervention groups including cytochrome c oxidase, caspase-3, caspase-9, catalase, and superoxide dismutase. The intervention groups required significantly less mechanical ventilation and had a lower mortality rate than the control group. Decontamination with paraffin oil could be advantageous for reducing the severity of AlP poisoning, improving prognosis, and lowering the mortality rate.

Development and validation of a risk prediction nomogram for disposition of acute clozapine intoxicated patients to intensive care unit

BACKGROUND

Clozapine is an atypical antipsychotic drug used for the treatment of refractory schizophrenia. It is reported as the most toxic in its class. Using serum clozapine level as a severity indicator is doubtful and unfeasible, particularly in low resourced countries.

METHODS

This is an extended two-phase retrospective study that utilized medical records of patients diagnosed with acute clozapine intoxication and admitted to Tanta University Poison Control Center, Egypt during the past 6 years. Two hundred and eight medical records were used to establish and validate a nomogram for predicting the need for intensive care unit (ICU) admission in acute clozapine intoxicated patients.

RESULTS

A reliable simple bedside nomogram was developed and proved its significant ability to predict the need for ICU admission, with an area under the curve (AUC) of 83.9% and 80.8% accuracy. It encompassed the age of admitted patients (AUC = 64.8%, p = .003), respiratory rate (AUC = 74.7%, p < .001), O₂ saturation (AUC = 71.7%, p < .001), and random blood glucose level upon admission (AUC = 70.5%, p < .001). External validation of the proposed nomogram showed a high AUC (99.2%) with an overall accuracy of 96.2%.

CONCLUSION

There is a need to develop a reliable objective tool predicting the severity and need for ICU admission in acute clozapine intoxication. The proposed nomogram is a substantially valuable tool to estimate ICU admission probabilities among patients with acute clozapine intoxication and will help clinical toxicologists make rapid decisions for ICU admission, especially in countries with low resources.

Prognostic factors in acute poisoning with central nervous system xenobiotics: development of a nomogram predicting risk of intensive care unit admission

Background

Acute intoxication with central nervous system (CNS) xenobiotics is an increasing global problem. Predicting the prognosis of acute toxic exposure among patients can significantly alter the morbidity and mortality. The present study outlined the early risk predictors among patients diagnosed with acute exposure to CNS xenobiotics and endorsed bedside nomograms for identifying patients requiring intensive care unit (ICU) admission and those at risk of poor prognosis or death.

Methods

This study is a 6-year retrospective cohort study conducted among patients presented with acute exposure to CNS xenobiotics.

Results

A total of 143 patients' records were included, where (36.4%) were admitted to the ICU, and a significant proportion of which was due to exposure to alcohols, sedative hypnotics, psychotropic, and antidepressants (P = 0.021). ICU admission was associated with significantly lower blood pressure, pH, and HCO₃ levels and higher random blood glucose (RBG), serum urea, and creatinine levels (P < 0.05). The study findings indicate that the decision of ICU admission could be determined using a nomogram combining the initial HCO₃ level, blood pH, modified PSS, and GCS. HCO₃ level < 17.1 mEq/L, pH < 7.2, moderate-to-severe PSS, and GCS < 11 significantly predicted ICU admission. Moreover, high PSS and low HCO₃ levels significantly predicted poor prognosis and mortality. Hyperglycemia was another significant predictor of mortality. Combining initial GCS, RBG level, and HCO₃ is substantially helpful in predicting the need for ICU admission in acute alcohol intoxication.

Conclusion

The proposed nomograms yielded significant straightforward and reliable prognostic outcomes predictors in acute exposure to CNS xenobiotics.

Examination of patients admitted to a university hospital with methanol intoxication

Objective: The aim of this study is to evaluate the demographic data, clinical features and laboratory findings of patients followed up with methanol poisoning in our internal medicine clinic. In addition, to examine the data of the patients followed in our intensive care unit and to contribute to the literature in this direction. Material and Method: In this study, 21 patients diagnosed with methanol intoxication who were hospitalized in the internal medicine clinic of our hospital between 01.01.2019 and 01.04.2022 were included. Demographic information of the patients, initial complaints, accompanying symptoms, laboratory results, blood gas values, intensive care unit requirements, mechanical ventilation needs, length of hospital stay and whether they received hemodialysis treatment were recorded from the hospital automation system. Results: 21 patients were included in the study. The mean time for patients to apply to the hospital after drinking alcohol was calculated as 31.42±4.27 hours. The mean hospital stay was 3.0±1.02 days. While 12 patients were followed up in the intensive care unit, it was found that 6 patients needed mechanical ventilation and 9 patients needed hemodialysis. Glucose, creatinine, acetyl aminotransferase (AST), partial carbon dioxide pressure (PaCO2), lactate, anion gap and base gap were found to be statistically significantly higher in the group treated in the intensive care unit (p