What Do We Know about Opioids and the Kidney?

Mallappallil, Mary; Sabu, Jacob; Friedman, Eli A.; Salifu, Moro O.

doi:10.3390/ijms18010223

Cited by 80 publications

(70 citation statements)

References 86 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…She left the hospital with advanced CKD. While acute heroin overdose can result in AKI, it is the chronic abuse that is more commonly associated with kidney injury [8]. This is due to the fact that with chronic abuse the drug and its metabolites are distributed and accumulated in multiple body compartments [8].…”

Section: Discussionmentioning

confidence: 99%

“…Dehydration and hypotension act in concert to induce renal hypoperfusion and hence intra-renal vasoconstriction. Opioids also activate the so-called renal opioid peptide receptors and directly cause intra-renal vasoconstriction [8]. The intense intra-renal vasoconstriction can cause AKI.…”

Section: Discussionmentioning

confidence: 99%

“…Both of our patients were chronic abusers of heroin for more than 2 years and hence more susceptible to renal damage. In their elegant paper, Mallappallil et al have recently elucidated multiple mechanisms by virtue of which heroin can cause AKI [8] (Fig. 2).…”

Section: Discussionmentioning

confidence: 99%

“…Opioids can lead to a decrease in fluid intake resulting in dehydration. Opioids also increase vagal activity as well as parasympathetic stimulation resulting in decreased cardiac ionotropy, bradycardia and hypotension [8][9][10][11]. Dehydration and hypotension act in concert to induce renal hypoperfusion and hence intra-renal vasoconstriction.…”

Section: Discussionmentioning

confidence: 99%

“…Cardiopulmonary demise is a major cause of death in heroin overdose; however, acute kidney injury (AKI) is emerging as a major contributor [5,6,[8][9][10][11]. It has been documented that the development of AKI is associated with a fourfold increase in death and that its timely diagnosis and treatment improves mortality [12].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Heroin Epidemic and Acute Kidney Injury: An Under-Recognized but Important Consequence of Opioid Overdose

et al. 2017

View full text Add to dashboard Cite

Heroin abuse and overdose are increasing at an alarming rate in the United States. Due to its relatively low cost and ease of availability, over a million people are abusing this agent. What is most disturbing is the fact that heroin-associated deaths have tripled over the past 5 years. While heroin has a major negative impact on the cardiopulmonary system, acute kidney injury (AKI) following heroin overdose is emerging as a major problem. AKI increases mortality and is a major cause of the development of chronic kidney disease and its antecedent long-term mortality. Timely diagnosis of AKI and its treatment reduces mortality. In this article, we present two cases (a 25-year-old man and a 22-year-old woman) of heroin-induced AKI. Both presented with altered mental status, respiratory depression and low blood pressure. AKI was diagnosed by the treating internist in a timely fashion and optimally treated in the 25-year-old man. In the 22-year-old woman who presented to the emergency department, AKI could not be recognized. She was discharged home after the management of overdose with resolution of pulmonary and neurological issues. Six days later, she returned to the emergency department with shortness of breath, volume overload, and severe acute tubular necrosis, required hemodialysis and left the hospital with serum creatinine of 2.5 mg/ dL (estimated glomerular filtration rate (eGFR) = 46 mL/min). At a 7-month follow-up, this patient continues to have eGFR of 45 mL/min (stage III chronic kidney disease). This article presents the mechanism of heroin-induced AKI as well as its management strategy and calls for heightened awareness for early diagnosis and prompt treatment.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Heroin Epidemic and Acute Kidney Injury: An Under-Recognized but Important Consequence of Opioid Overdose

et al. 2017

View full text Add to dashboard Cite

show abstract

Toxicology of Specific Substances

Jones¹,

Mußhoff²,

Krämer³

et al. 2022

Handbook of Forensic Medicine

View full text Add to dashboard Cite

Using machine learning to predict adverse events in acute coronary syndrome: A retrospective study

Song,

Li,

Nie

et al. 2023

Clinical Cardiology

View full text Add to dashboard Cite

BackgroundUp to 30% of patients with acute coronary syndrome (ACS) die from adverse events, mainly renal failure and myocardial infarction (MI). Accurate prediction of adverse events is therefore essential to improve patient prognosis.HypothesisMachine learning (ML) methods can accurately identify risk factors and predict adverse events.MethodsA total of 5240 patients diagnosed with ACS who underwent PCI were enrolled and followed for 1 year. Support vector machine, extreme gradient boosting, adaptive boosting, K‐nearest neighbors, random forest, decision tree, categorical boosting, and linear discriminant analysis (LDA) were developed with 10‐fold cross‐validation to predict acute kidney injury (AKI), MI during hospitalization, and all‐cause mortality within 1 year. Features with mean Shapley Additive exPlanations score >0.1 were screened by XGBoost method as input for model construction. Accuracy, F1 score, area under curve (AUC), and precision/recall curve were used to evaluate the performance of the models.ResultsOverall, 2.6% of patients died within 1 year, 4.2% had AKI, and 4.7% had MI during hospitalization. The LDA model was superior to the other seven ML models, with an AUC of 0.83, F1 score of 0.90, accuracy of 0.85, recall of 0.85, specificity of 0.68, and precision of 0.99 in predicting all‐cause mortality. For AKI and MI, the LDA model also showed good discriminating capacity with an AUC of 0.74.ConclusionThe LDA model, using easily accessible variables from in‐hospital patients, showed the potential to effectively predict the risk of adverse events and mortality within 1 year in ACS patients after PCI.

show abstract

What Do We Know about Opioids and the Kidney?

Cited by 80 publications

References 86 publications

Heroin Epidemic and Acute Kidney Injury: An Under-Recognized but Important Consequence of Opioid Overdose

Heroin Epidemic and Acute Kidney Injury: An Under-Recognized but Important Consequence of Opioid Overdose

Toxicology of Specific Substances

Using machine learning to predict adverse events in acute coronary syndrome: A retrospective study

Contact Info

Product

Resources

About