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

Schiller EY, Goyal A, Mechanic OJ. Opioid overdose. Europe PMC. 2017.

Clarke SF, Dargan PI, Jones AL. Naloxone in opioid poisoning: walking the tightrope. Emerg Med J. 2005;22(9):612–6.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Rzasa Lynn R, Galinkin J. Naloxone dosage for opioid reversal: current evidence and clinical implications. Ther Adv Drug safe. 2018;9(1):63–88.

Article  CAS  Google Scholar 

Wermeling DP. A response to the opioid overdose epidemic: naloxone nasal spray. Drug Deliv Transl Res. 2013;3:63–74.

Article  PubMed  CAS  Google Scholar 

Borras M, et al. fMRI measurement of CNS responses to naloxone infusion and subsequent mild noxious thermal stimuli in healthy volunteers. J Neurophysiol. 2004;91(6):2723–33.

Article  PubMed  CAS  Google Scholar 

Sadove MS, et al. Study of a narcotic antagonist—N-allyl-noroxymorphone. JAMA. 1963;183(8):666–8.

Article  PubMed  CAS  Google Scholar 

Mowry JB, et al. 2014 annual report of the american association of poison control centers’ national poison data system (NPDS): 32nd annual report. Clin Toxicol. 2015;53(10):962–1147.

Article  CAS  Google Scholar 

Evans J, et al. Degree and duration of reversal by naloxone of effects of morphine in conscious subjects. Br Med J. 1974;2(5919):589–91.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Ngai S, et al. Pharmacokinetics of naloxone in rats and in man: basis for its potency and short duration of action. Anesthesiology. 1976;44(5):398–401.

Article  PubMed  CAS  Google Scholar 

Rawal N, et al. Influence of naloxone infusion on analgesia and respiratory depression following epidural morphine. Anesthesiology. 1986;64(2):194–201.

Article  PubMed  CAS  Google Scholar 

Sinha M, Sachan DK, Parthasarathi R. Artificial intelligence in clinical toxicology. In: Artificial Intelligence in Medicine. Springer; 2021. p. 1–15.

Google Scholar 

Shin S, et al. Machine learning vs. conventional statistical models for predicting heart failure readmission and mortality. ESC heart failure. 2021;8(1):106–15.

Article  PubMed  Google Scholar 

Ley C, et al. Machine learning and conventional statistics: making sense of the differences. Knee Surg Sports Traumatol Arthrosc. 2022;30(3):753–7.

Article  PubMed  Google Scholar 

Badger J, et al. Machine learning for phenotyping opioid overdose events. J Biomed Inform. 2019;94:103185.

Article  PubMed  PubMed Central  Google Scholar 

Lo-Ciganic W-H, et al. Evaluation of machine-learning algorithms for predicting opioid overdose risk among medicare beneficiaries with opioid prescriptions. JAMA Netw Open. 2019;2(3):e190968–e190968.

Article  PubMed  PubMed Central  Google Scholar 

Mehrpour O, et al. The value of machine learning for prognosis prediction of diphenhydramine exposure: National analysis of 50,000 patients in the United States. J Res Med Sci. 2023;28(1):49.

PubMed  PubMed Central  CAS  Google Scholar 

Mehrpour O, et al. 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. BMC Med Inform Decis Mak. 2023;23(1):1–11.

Article  Google Scholar 

Mehrpour O, et al. Utility of support vector machine and decision tree to identify the prognosis of metformin poisoning in the United States: analysis of National Poisoning Data System. BMC Pharmacol Toxicol. 2022;23(1):49.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Mehrpour O, et al. The role of decision tree and machine learning models for outcome prediction of bupropion exposure: A nationwide analysis of more than 14 000 patients in the United States. Basic Clin Pharmacol Toxicol. 2023;133(1):98–110.

Article  PubMed  CAS  Google Scholar 

Tang J, et al. Application of machine-learning models to predict tacrolimus stable dose in renal transplant recipients. Sci Rep. 2017;7(1):42192.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Ma Z, et al. Ensemble of machine learning algorithms using the stacked generalization approach to estimate the warfarin dose. PLoS ONE. 2018;13(10):e0205872.

Article  PubMed  PubMed Central  Google Scholar 

Chen SS, et al. Optimizing levothyroxine dose adjustment after thyroidectomy with a decision tree. J Surg Res. 2019;244:102–6.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Zhu X, et al. A machine learning approach to personalized dose adjustment of lamotrigine using noninvasive clinical parameters. Sci Rep. 2021;11(1):5568.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Zarei MJ, et al. Comparing two naloxone tapering methods in management of methadone intoxication; a quasi-experimental study. Arch Acad Emerg Med. 2023;11(1).

Aziz R, et al. The optimal initial dose and route of naloxone administration for successful opioid reversal: a systematic literature review. Cureus. 2024;16(1).

Trescot AM, et al. Opioid pharmacology. Pain physician. 2008;11(2S):S133.

Article  PubMed  Google Scholar 

Kirubakaran JJ, Dhanaraju M. “Toxidrome” A review. Saudi Journal of Medical and Pharmaceutical Sciences. 2019;5(3):206–12.

Powers DM. Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation. arXiv:2010.16061 [Peprint]. 2020. Available from: https://www.arxiv.org/abs/2010.16061. Accessed 28 Oct 2020.

Li Y, et al. Literature review on the applications of machine learning and blockchain technology in smart healthcare industry: a bibliometric analysis. J Healthc Eng. 2021;2021.

Brnabic A, Hess LM. Systematic literature review of machine learning methods used in the analysis of real-world data for patient-provider decision making. BMC Med Inform Decis Mak. 2021;21(1):1–19.

Article  Google Scholar 

Goldfrank L, et al. A dosing nomogram for continuous infusion intravenous naloxone. Ann Emerg Med. 1986;15(5):566–70.

Article  PubMed  CAS  Google Scholar 

Clemency BM, et al. Hospital Observation Upon Reversal (HOUR) with naloxone: a prospective clinical prediction rule validation study. Acad Emerg Med. 2019;26(1):7–15.

Article  PubMed  Google Scholar 

Seidler D, et al. After antagonization of acute opiate overdose: a survey at hospitals in Vienna. Addiction. 1996;91(10):1479–87.

Article  PubMed  CAS  Google Scholar 

Christenson J, et al. Early discharge of patients with presumed opioid overdose: development of a clinical prediction rule. Acad Emerg Med. 2000;7(10):1110–8.

Article  PubMed  CAS  Google Scholar 

Vilke GM, et al. Assessment for deaths in out-of-hospital heroin overdose patients treated with naloxone who refuse transport. Acad Emerg Med. 2003;10(8):893–6.

PubMed  Google Scholar 

Buajordet I, et al. Adverse events after naloxone treatment of episodes of suspected acute opioid overdose. Eur J Emerg Med. 2004;11(1):19–23.

Article  PubMed  Google Scholar 

Boyd J, et al. Recurrent opioid toxicity after pre-hospital care of presumed heroin overdose patients. Acta Anaesthesiol Scand. 2006;50(10):1266–70.

Article  PubMed  CAS  Google Scholar 

Rudolph S, et al. Prehospital treatment of opioid overdose in Copenhagen—is it safe to discharge on-scene? Resuscitation. 2011;82(11):1414–8.

Article  PubMed  CAS  Google Scholar 

Wampler DA, et al. No deaths associated with patient refusal of transport after naloxone-reversed opioid overdose. Prehosp Emerg Care. 2011;15(3):320–4.

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