Azithromycin and the Risk of Cardiovascular Death

Albert, Richard K.; Connett, John; Woodruff, Prescott G.

doi:10.1056/nejmc1207269

Cited by 11 publications

(3 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, cefotaxime (a third-generation cephalosporin) was more commonly used in newborns under 3 months of age, but azithromycin was rarely administered in that age group. This observation might reflect the results of some published studies which reported an increased risk of cardiovascular death associated with the use of azithromycin, specifically, in infants [25,26].…”

Section: Resultssupporting

confidence: 70%

Medication Use for Childhood Pneumonia at a Children’s Hospital in Shanghai, China: Analysis of Pattern Mining Algorithms

et al. 2019

View full text Add to dashboard Cite

Background Pattern mining utilizes multiple algorithms to explore objective and sometimes unexpected patterns in real-world data. This technique could be applied to electronic medical record data mining; however, it first requires a careful clinical assessment and validation. Objective The aim of this study was to examine the use of pattern mining techniques on a large clinical dataset to detect treatment and medication use patterns for childhood pneumonia. Methods We applied 3 pattern mining algorithms to 680,138 medication administration records from 30,512 childhood inpatients with diagnosis of pneumonia during a 6-year period at a children’s hospital in China. Patients’ ages ranged from 0 to 17 years, where 37.53% (11,453/30,512) were 0 to 3 months old, 86.55% (26,408/30,512) were under 5 years, 60.37% (18,419/30,512) were male, and 60.10% (18,338/30,512) had a hospital stay of 9 to 15 days. We used the FP-Growth, PrefixSpan, and USpan pattern mining algorithms. The first 2 are more traditional methods of pattern mining and mine a complete set of frequent medication use patterns. PrefixSpan also incorporates an administration sequence. The newer USpan method considers medication utility , defined by the dose, frequency, and timing of use of the 652 individual medications in the dataset. Together, these 3 methods identified the top 10 patterns from 6 age groups, forming a total of 180 distinct medication combinations. These medications encompassed the top 40 (73.66%, 500,982/680,138) most frequently used medications. These patterns were then evaluated by subject matter experts to summarize 5 medication use and 2 treatment patterns. Results We identified 5 medication use patterns: (1) antiasthmatics and expectorants and corticosteroids, (2) antibiotics and (antiasthmatics or expectorants or corticosteroids), (3) third-generation cephalosporin antibiotics with (or followed by) traditional antibiotics, (4) antibiotics and (medications for enteritis or skin diseases), and (5) (antiasthmatics or expectorants or corticosteroids) and (medications for enteritis or skin diseases). We also identified 2 frequent treatment patterns: (1) 42.89% (291,701/680,138) of specific medication administration records were of intravenous therapy with antibiotics, diluents, and nutritional supplements and (2) 11.53% (78,390/680,138) were of various combinations of inhalation of antiasthmatics, expectorants, or corticosteroids. Fleiss kappa for the subject experts’ evaluation was 0.693, indicating moderate agreement. Conclusions Utilizing a pattern mining approach, we summarized 5 medication use patterns and 2 treatment patterns. These warrant further investigation.

show abstract

Section: Resultssupporting

confidence: 70%

Medication Use for Childhood Pneumonia at a Children’s Hospital in Shanghai, China: Analysis of Pattern Mining Algorithms

et al. 2019

View full text Add to dashboard Cite

show abstract

“…10, 11 While Ray et al used appropriate analytic methodologies to attempt to correct for any confounding bias intrinsic to the observational, nonrandomized nature of the study design, due to a higher prevalence of comorbid/co-existing conditions and increased mortality rates associated with Medicaid beneficiaries in the United States, legitimate questions were raised about whether the results of the study could be generalized to populations with substantially lower baseline CV disease risk and if differences in the baseline characteristics of the treatment groups were adequately controlled. 12, 13 …”

mentioning

confidence: 99%

Azithromycin and risk of sudden cardiac death: Guilty as charged or falsely accused?

Giudicessi

Ackerman

2013

CCJM

View full text Add to dashboard Cite

“…In the COVID-19 era, azithromycin is used daily for its anti-inflammatory and bacterial preventive properties, but the exact benefit is not fully understood [ 92 , 93 ]. The use of azithromycin in COVID-19 patients is not well established and is still debated, while adverse effects such as prolongation of the QT interval could potentially increase the risk of sudden cardiac death in non-monitored patients [ 94 ] ( Table 2 , Figure 2 ).…”

Section: Anti-inflammatory Agents and Treatment Optionsmentioning

confidence: 99%

Genetic Predisposition and Inflammatory Inhibitors in COVID-19: Where Do We Stand?

et al. 2022

View full text Add to dashboard Cite

Severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2) and the resulting coronavirus disease-19 (COVID-19) have led to a global pandemic associated with high fatality rates. COVID-19 primarily manifests in the respiratory system as an acute respiratory distress syndrome following viral entry through the angiotensin-converting enzyme-2 (ACE2) that is present in pulmonary epithelial cells. Central in COVID-19 is the burst of cytokines, known as a “cytokine storm”, and the subsequent widespread endothelial activation, leading to cardiovascular complications such as myocarditis, arrhythmias, and adverse vascular events, among others. Genetic alterations may play an additive, detrimental role in the clinical course of patients with COVID-19, since gene alterations concerning ACE2, major histocompatibility complex class I, and toll-like receptors may predispose patients to a worse clinical outcome. Since the role of inflammation is quintessential in COVID-19, pharmacologic inhibition of various signaling pathways such as the interleukin-1 and -6, tumor necrosis factor-alpha, interferon gamma, Janus kinase-signal transducer and activator of transcription, and granulocyte–macrophage colony-stimulating factor may ameliorate the prognosis following timely administration. Finally, frequently used, non-specific anti-inflammatory agents such as corticosteroids, statins, colchicine, and macrolides represent additional therapeutic considerations.

show abstract

Azithromycin and the Risk of Cardiovascular Death

Cited by 11 publications

References 33 publications

Medication Use for Childhood Pneumonia at a Children’s Hospital in Shanghai, China: Analysis of Pattern Mining Algorithms

Medication Use for Childhood Pneumonia at a Children’s Hospital in Shanghai, China: Analysis of Pattern Mining Algorithms

Azithromycin and risk of sudden cardiac death: Guilty as charged or falsely accused?

Genetic Predisposition and Inflammatory Inhibitors in COVID-19: Where Do We Stand?

Contact Info

Product

Resources

About