RESUMEN
OBJECTIVE: This study investigated the prevalence and correlates of fibromyalgia and insomnia in a sample of Women with Multiple Sclerosis (WMS). METHODS: The study was cross-sectional in design and recruited a sample of 163 women with Relapsing-Remitting Multiple Sclerosis (RRMS). Fibromyalgia was assessed using the Patient Self-Report Survey (PSRS), following criteria outlined by the American College of Rheumatology. Insomnia was measured using the Arabic version of the Insomnia Severity Index (ISI-A). RESULTS: The prevalence of fibromyalgia and insomnia was 28.2% (n = 46) and 46.3% (n = 76), respectively. Multivariate analyses were used to determine significant independent correlates. Fibromyalgia was associated with age above 40 years (OR = 2.29, 95% CI = 1.01-5.18, P = .04), high school education (OR = 3.69, 95% CI = 1.62-8.37, P = .002), and non-use of analgesics (OR = .02, 95% CI = .004-.21, P = .001). Insomnia symptoms were significantly associated only with age above 40 years (OR = 2.16, 95% CI = 1.16-4.04, P = .01). CONCLUSION: These findings highlight the need for increased attention by primary care physicians towards diagnosing and treating fibromyalgia and insomnia among women with RRMS in Jordan, particularly among older women.
RESUMEN
OBJECTIVE: Clinicians have noted that the ongoing war on Gaza has had a psychological impact on people with multiple sclerosis (PwMS) whose mental health is particularly vulnerable during times such as these. The present study sought to examine the prevalence and correlates of posttraumatic stress disorder (PTSD) symptoms among PwMS in Jordan during the Gaza war outbreak. METHODS: This was a cross-sectional study involving 171 patients (PwMS) out of 372 patients approached (46% response rate) who were being seen in the MS unit at Al Bashir Hospital, Ammann, Jordan. Inclusion criteria required that participants had been following daily news updates of the October 7 war in Gaza for the past 4 months. RESULTS: Of participants, 125 (73.1%) were female, 98 (57.3%) were on therapy for less than five years, and 30 (17.5%) reported having a relapse during the past 6 months. Significant PTSD symptoms were identified in 58.5% (100 of 171 participants). Those at higher risk were the unemployed (OR = 2.14, 95% CI = 1.13-4.07, P = 0.02), whereas patients receiving dimethyl fumarate (19.9%) were at lower risk (OR = 0.43, 95% CI = 0.19-0.94, P = 0.02). CONCLUSION: The high rate of significant PTSD symptoms among people with MS in this study underscores the need for attention by primary care providers and implementation of a comprehensive multidisciplinary approach to optimize the mental well-being of this fragile population.
RESUMEN
BACKGROUND: This study aimed to evaluate the implementation of the prevention of mother-to-child transmission (PMTCT) of the HIV-PMTCT program in Kermanshah, west of Iran, from 2014 to 2021. METHODS: The data of all HIV-infected mothers and their infants who were monitored by the Kermanshah behavioral diseases counseling center was extracted and recorded in a checklist. RESULTS: Out of 95 included infant, 45 (47.4%) were girls and 50 (52.6%) were boys. The mothers were mostly infected with HIV via their infected spouse. The pregnancies of 77 cases (82.1%) were in accordance with the national guideline. The average length of treatment for this group was 185 days. Of the 18 mothers who did not receive treatment, nine were diagnosed during childbirth and nine had no available information. All infants born from infected mothers underwent after-birth-antiretroviral prophylaxis, and all remained healthy. There was no statistically significant relationship between the birth weight and height of neonates with maternal age, maternal last viral load, disease stage, education, and maternal CD4 levels. Only a statistically significant relationship was observed between the duration of treatment and the infants' weight. CONCLUSION: The results suggest the feasibility and effectiveness of the PMTCT program for HIV-positive mothers in Kermanshah. It seems that if pregnant HIV-positive women are diagnosed early and covered by a good prevention program on time, the risk of HIV to their babies will be reduced, significantly.
Asunto(s)
Infecciones por VIH , Complicaciones Infecciosas del Embarazo , Lactante , Embarazo , Recién Nacido , Masculino , Femenino , Humanos , Infecciones por VIH/tratamiento farmacológico , Complicaciones Infecciosas del Embarazo/tratamiento farmacológico , Transmisión Vertical de Enfermedad Infecciosa/prevención & control , Irán/epidemiología , MadresRESUMEN
Background: Mental health in people with epilepsy (PWE) is often overlooked, especially in developing countries.Purpose: Consequently, the current work had two objectives: (1) to estimate the burden of depression, anxiety, insomnia, and stress, and (2) to examine the association of these psychiatric/psychological symptoms with levetiracetam and other relevant clinical factors in a cohort of Jordanian PWE.Research Design: This is a cross-sectional study. The demographic and clinical data were recorded. Depression was measured by the Patient Health Questionnaire-9 (PHQ-9, Arabic-validated version) and anxiety by the General Anxiety Disorder-7 (GAD-7, Arabic-validated version). The insomnia severity index (ISI-A, Arabic version) was used to assess sleep quality, and the Perceived Stress Scale (PSS-A, Arabic version) was used to measure perceived stress.Study Sample: Data were analyzed from 280 patients, of which 178 (63.6%) received levetiracetam as monotherapy or as adjuvant.Results: Depression was reported in 150 (53.6%), anxiety in 110 (39.3%), insomnia in 131 (46.8%), and clinically significant stress in 211 (75.4%). At univariate analysis, levetiracetam was not associated with psychiatric symptoms. Multivariate logistic regression revealed that severe depressive symptoms were associated with family history (OR = 2.47, 95% CI = 1.42-4.33, P = .001) and seizure type (OR = 1.69, 95% CI = 1.01-2.80, P = .04), severe anxiety symptoms were associated with family history (OR = 1.90, 95% CI = 1.12-3.23, P = .01), severe insomnia was associated with seizure type (OR = 2.16, 95% CI = 1.33-3.5, P = .002) and severe stress was associated with marital status (OR = 2.37, 95% CI = 1.31-4.29, P = .004).Conclusions: The high psychological burden of PWE is a challenging issue that requires attention and prompt action to control its risk factors.
RESUMEN
Vitamin D deficiency is being recognized as a global issue and has been implicated in many health issues. Hence, there is an increased interest in developing sensitive, reproducible, and non-invasive assays to measure Vitamin D levels. This study aimed to apply a sensitive liquid chromatography-mass spectrometric assay to hair samples to develop and validate a clinical assay to provide a quarterly average level of vitamin D in one test. Hair samples were collected from 70 male university students/young adults and pulverized/sonicated in methanol/water for 2 h to extract Vitamin D metabolites. A sensitive liquid chromatographic-mass spectrometric assay was employed to quantitate vitamin D and metabolites. Of the eight Vitamin D and metabolites screened, only the primary, clinically significant form of vitamin D (25OHD3) was detected and quantified in hair samples in the range of 17-1541 pg/mg. One-third of the hair samples (21 out of 70) had Vitamin D levels below the LLOD of the assay (10 pg/mg). The mean and standard deviation values for hair (25OHD3) were 276.7 ± 329.9, respectively. This pilot study reveals the potential of the vitamin D hair test in clinical assays as a complementary test to a vitamin D blood test, which would provide a quarterly average.
Asunto(s)
Técnicas de Química Analítica , Colecalciferol/análisis , Cabello , Adolescente , Adulto , Calibración , Cromatografía Liquida , Progresión de la Enfermedad , Humanos , Límite de Detección , Masculino , Proyectos Piloto , Reproducibilidad de los Resultados , Sonicación , Espectrometría de Masas en Tándem , Vitamina D/análisis , Adulto JovenRESUMEN
BACKGROUND: Despite the misconceptions regarding E-cigarettes (ECs), only a few studies have been conducted in the Middle East that focused on this topic. This study assesses the knowledge of and attitudes towards ECs in Lebanon, determines how these two measures are associated, and identifies the variables that explain each of these measures. METHODS: A cross sectional study was conducted on a convenience sample of Lebanese pedestrians aged between 18 and 64 inclusive. A structured self-administered questionnaire comprising of knowledge and attitude scales, and questions on demographical, health and smoking characteristics was used. RESULTS: Scores for attitudes and knowledge of ECs were summed and dichotomized using a 75% cutoff, above which the participant was considered to have a positive attitude and good knowledge. Among the 352 participants (56.6% males, 43.3% females, mean age 30.3, 46.2% smokers), 63.3% exhibited a lower level of EC knowledge. More than 50% erroneously thought that ECs are not associated with lung and bladder cancer or impair lung and heart function. 65% falsely thought that it is harmless and not addictive. As for attitude, 43.3, 53.9, and 44.3% thought that it is socially acceptable, helps in smoking cessation, and is a good replacement for cigarettes and an enjoyable recreational device respectively. Our results revealed an inverse correlation between attitude and knowledge scores (Spearman's correlation = -.30, p < .001). Predictors of knowledge included health-related occupation (p = .010), regular exercise (p = .016), healthy diet (p = .026), EC use (p = .026), perception that ECs are not harmful (p = .001), and help in smoking cessation (p = .017). Predictors of attitude included EC use (p = .008), sex (p = .010), and knowledge that most ECs are addictive (p = .006), harmful (p = .014), and impair heart and lung function (p = .047). CONCLUSIONS: Our study revealed a gap in EC knowledge, especially among participants who displayed a positive attitude towards ECs. Hence, measures should be undertaken to regulate its use by instituting more stringent laws and holding nationwide awareness campaigns.
Asunto(s)
Conocimientos, Actitudes y Práctica en Salud , Vapeo/psicología , Adolescente , Adulto , Estudios Transversales , Femenino , Humanos , Líbano , Masculino , Persona de Mediana Edad , Factores Socioeconómicos , Encuestas y Cuestionarios , Vapeo/efectos adversos , Adulto JovenRESUMEN
The operation of the quartz crystal microbalance (QCM) in liquids is plagued by small flexural admixtures to the thickness-shear deformation. The resonator surface moves not only in the transverse direction, but also along the surface normal, thereby emitting compressional waves into the liquid. Using a simple analytical model and laser Doppler vibrometry, we show that the flexural admixtures are stronger on the fundamental mode than on the overtones. The normal amplitude of motion amounts to about 1% of the transverse motion on the fundamental mode. This ratio drops by a factor of two on the overtones. A similar dependence on overtone order is observed in experiments, where the resonator is immersed in a liquid and faces an opposite planar wall, the distance of which varies. Standing compressional waves occur at certain distances. The amplitudes of these are smaller on the overtones than on the fundamental mode. The findings can be rationalized with the tensor form of the small-load approximation.
RESUMEN
Diabetes is a common chronic metabolic disease with a wide range of clinical symptoms and consequences and one of the main causes of death. For the management of diabetes, painless and continuous interstitial fluid (ISF) glucose monitoring is ideal. Here, we demonstrate continuous diabetes monitoring using an integrated microneedle (MN) biosensor with an emergency alert system. MNs are a novel technique in the field of biomedical engineering because of their ability to analyze bioinformation with minimal invasion. In this work we developed a poly(methyl methacrylate) (PMMA) based MN glucose sensor. The device was produced by the 3D printing technique, microfabrication, electrodeposition, and enzyme immobilization step. The in vitro test for the glucose MN sensor showed a linear range from 1.5 to 14 mM with a sensitivity of 1.51 µA mM-1, limit of detection (LOD) of 0.35 mM and good selectivity. Highly repeatable sensing is observed with good reproducibility. The interference-free detection of glucose in the presence of physiologically relevant concentrations of ascorbic acid, uric acid, and mannose is demonstrated, along with the operational stability of the array. After resolving the biofouling consequences linked to on-body sensing, this MN platform would be appealing for minimally invasive electrochemical glucose monitoring. An alert is sent to confidants via email or SMS when the values are abnormal. The application is also able to display the recorded values in the form of a graph to help determine the state of health of the user over a period of time. It can be concluded that continuous monitoring and an emergency alert system are important for keeping an eye on diabetic patients and can send alert in case of an abnormal situation of the patient.
Asunto(s)
Técnicas Biosensibles , Líquido Extracelular , Glucosa , Agujas , Técnicas Biosensibles/instrumentación , Líquido Extracelular/química , Humanos , Glucosa/análisis , Glucosa/metabolismo , Electrodos , Hipoglucemia/diagnóstico , Límite de Detección , Polimetil Metacrilato/químicaRESUMEN
Artificial intelligence (AI) has come to play a pivotal role in revolutionizing medical practices, particularly in the field of pancreatic cancer detection and management. As a leading cause of cancer-related deaths, pancreatic cancer warrants innovative approaches due to its typically advanced stage at diagnosis and dismal survival rates. Present detection methods, constrained by limitations in accuracy and efficiency, underscore the necessity for novel solutions. AI-driven methodologies present promising avenues for enhancing early detection and prognosis forecasting. Through the analysis of imaging data, biomarker profiles, and clinical information, AI algorithms excel in discerning subtle abnormalities indicative of pancreatic cancer with remarkable precision. Moreover, machine learning (ML) algorithms facilitate the amalgamation of diverse data sources to optimize patient care. However, despite its huge potential, the implementation of AI in pancreatic cancer detection faces various challenges. Issues such as the scarcity of comprehensive datasets, biases in algorithm development, and concerns regarding data privacy and security necessitate thorough scrutiny. While AI offers immense promise in transforming pancreatic cancer detection and management, ongoing research and collaborative efforts are indispensable in overcoming technical hurdles and ethical dilemmas. This review delves into the evolution of AI, its application in pancreatic cancer detection, and the challenges and ethical considerations inherent in its integration.
RESUMEN
Background: The relationship between adult ADHD symptoms in People with Multiple Sclerosis (PwMS) is understudied. This study aimed to answer two questions: are PwMS more likely to experience higher ADHD symptoms versus healthy subjects? And what are the correlates of severe ADHD symptoms in PwMS? Methods: This study followed a cross-sectional design with predefined inclusion criteria. The Adult ADHD Self-Report Scale-V1.1 (ASRS) was used to assess the ADHD symptoms severity. Results: Data were analyzed from 171 PwMS and 200 controls. Regression analysis revealed that PwMS were at a significantly (B = 3.05, t = 2.24, 95% CI = 0.37-5.73, p = 0.02) higher risk to report higher ADHD scores versus controls. In addition, PwMS with relapses in the last 6 months and PwMS reporting smartphone addiction were at a significantly higher risk for severe ADHD (B = 7.19, t = 269, 95% CI = 1.91-12.48, p = 0.008) and (B = 9.18, t = 3.47, 95% CI = 3.97-14.41, p = 0.001), respectively. In conclusion, diagnosis with MS in our study was identified as a risk for higher ADHD symptoms. Conclusions: Further research is required to establish this relationship, and holistic medical and psychological interventions are required to improve the cognitive status of PwMS.
RESUMEN
Stroke is the second most common cause of death worldwide, with 50% of survivors experiencing long-term disability. For more than two decades, treatment with intravenous thrombolysis (IVT) and mechanical endovascular thrombectomy (MET), the only approved stroke reperfusion therapies, was restricted to patients within the 4.5-6 hour time window, respectively. Therefore, patients who presented with acute ischemic stroke (AIS) beyond the conventional time window were excluded from reperfusion treatment. This narrative review aims to review the scientific literature on the possibilities of reperfusion therapies for patients who present with an unknown time of stroke onset, and those with stroke onset beyond the conventional 4.5-6 hour time window. Beyond the conventional time window, the eligibility of patients for IVT or MET, the two main therapeutic procedures, is decided based on the concept of penumbral imaging. Penumbral imaging identifies patients with hypoperfused but viable brain tissue, who could benefit from reperfusion. On the other hand, clock-based DWI-fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) can detect stroke that has occurred within 4.5 hours in patients with an unknown time of onset, including patients who awaken with stroke. The introduction of penumbral imaging and MRI-based tissue clocking as imaging biomarkers for stroke has revolutionized stroke therapy, potentially allowing for personalized treatment of eligible stroke patients.
RESUMEN
Dietary patterns can be the primary reason for many chronic diseases such as diabetes and obesity. State-of-the-art wearable sensor technologies can play a critical role in assisting patients in managing their eating habits by providing meaningful statistics on critical parameters such as the onset, duration, and frequency of eating. For an accurate yet fast food intake recognition, this work presents a novel Machine Learning (ML) based framework that shows promising results by leveraging optimized support vector machine (SVM) classifiers. The SVM classifiers are trained on three comprehensive datasets: OREBA, FIC, and CLEMSON. The developed framework outperforms existing algorithms by achieving F1-scores of 92%, 94%, 95%, and 85% on OREBA-SHA, OREBA-DIS, FIC, and CLEMSON datasets, respectively. In order to assess the generalization aspects, the proposed SVM framework is also trained on one of the three databases while being tested on the others and achieves acceptable F1-scores in all cases. The proposed algorithm is well suited for real-time applications since inference is made using a few support vector parameters compared to thousands in peer deep neural networks models.
Asunto(s)
Gestos , Dispositivos Electrónicos Vestibles , Humanos , Aprendizaje Automático , Algoritmos , Redes Neurales de la ComputaciónRESUMEN
Post-traumatic stress disorder (PTSD) is a complex mental health condition affecting individuals exposed to traumatic events. This paper is a narrative review of the existing literature on pharmacological and psychotherapeutic interventions for PTSD. Treatment includes selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), and alpha-1 adrenergic receptor antagonists. By exploring the outcomes of these interventions, the review seeks to provide valuable insights into their potential as PTSD treatment options. The paper also highlights the importance of tailoring treatment plans to individual needs and discusses emerging treatments, such as mindfulness-based therapies, virtual reality therapy, and neurostimulation techniques. By integrating findings from various studies, it aims to offer valuable information to optimize treatment strategies and enhance outcomes for individuals suffering from PTSD. The goal is to support informed decision-making, ultimately leading to more effective and tailored approaches to address the challenges posed by this debilitating condition.
RESUMEN
Acute coronary syndrome (ACS) stands as a leading global cause of mortality, underscoring the importance of effective prevention, early diagnosis, and timely intervention. While medications offer benefits to many patients, revascularization procedures such as coronary artery bypass grafting (CABG), percutaneous coronary intervention (PCI), and emerging hybrid approaches remain pivotal for ACS management. This review delves into the 2018 ESC/EACTS guidelines alongside an analysis of existing literature to shed light on the spectrum of revascularization methods. While both CABG and PCI demonstrate promising outcomes, the optimal choice between the two hinges on a comprehensive assessment of individual patient factors, anatomical complexity guided by advanced imaging, comorbidities, and age. The determination of whether to pursue culprit or total revascularization, as well as immediate or staged revascularization, is contingent upon various factors, including age, disease complexity, and clinical outcomes. This evidence-based decision-making process is orchestrated by a multidisciplinary heart team grounded in ongoing clinical evaluation. The primary objective of this review is to provide valuable insights into revascularization strategies and scrutinize the congruence of current guidelines with recent advancements in the field.
RESUMEN
Background: Addiction disorders pose significant challenges to public health, necessitating innovative treatments. This assesses deep brain stimulation (DBS) as a potential intervention for addiction disorders. Methods: A literature review was carried out with a focus on the role of DBS in addiction disorders and its future implications in neurosurgical research. Results: The online literature shows that DBS precisely modulates certain brain regions to restore addiction-related neural circuits and promote behavioral control. Conclusion: Preclinical evidence demonstrates DBS's potential to rebalance neural circuits associated with addiction, and early clinical trials provide encouraging outcomes in enhancing addiction-related outcomes. Ethical considerations, long-term safety, and personalized patient selection require further investigation.
RESUMEN
The life expectancy of people living with HIV (PLWH) has greatly increased due to advancements in combination antiretroviral treatment (cART). However, this longer life has also increased the prevalence of age-related comorbidities, such as frailty, which now manifest sooner in this group. Frailty, a term coined by the insurance industry, has been broadened to include physical, cognitive, and emotional elements and has been recognized as a critical predictor of negative health outcomes. With the median age of PLWH now in the mid-50s, treating frailty is critical given its link to chronic diseases, cognitive decline, and even death. Frailty assessment tools, such as the Frailty Phenotype (FP) and the Frailty Index (FI), are used to identify vulnerable people. Understanding the pathophysiology of frailty in PLWH indicates the role of immunological mechanisms. Frailty screening and management in this group have progressed, with specialized clinics and programs concentrating on multidisciplinary care. Potential pharmacotherapeutic solutions, as well as novel e-health programs and sensors, are in the future of frailty treatment, but it is critical to ensure that frailty evaluation is not exploited to perpetuate ageist healthcare practices. This narrative review investigates the changing healthcare environment for older people living with HIV (OPLWH), notably in high-income countries. It emphasizes the significance of identifying and managing frailty as a crucial feature of OPLWH's holistic care and well-being.
RESUMEN
To examine the effectiveness of integrated care intervention (ICI) models (stand-alone or combination of self-management, discharge management, case management and multidisciplinary teams models) targeting patients with one or more chronic conditions, and to identify outcome measures/indicators of effectiveness, we conducted a systematic review of published systematic reviews and meta-analyses. Included reviews comprise ICIs targeting adult patients with one or more long-term conditions. We searched MEDLINE, CINAHL and the Cochrane Database of Systematic Reviews: 60 reviews were included in the final analysis; 28 reviews evaluated ICIs focused on self-management, 4 on case management, 10 on discharge management and 5 on multidisciplinary teams; 13 reviews assessed multiple interventions that were labelled as complex. Across all reviews, only 19 reviews included intervention with multiple ICIs. Overall, interventions with multiple components, compared with interventions with single components, were more likely to improve hospital use outcomes effectively. Clinical/lifestyle/condition-specific outcomes were more likely to be improved by self-management interventions. Outcome measures identified could be classified into three main categories: organisational, patient-centred and clinical/lifestyle/condition-specific. The findings of this review may provide inputs to future design and evaluation of ICIs.
RESUMEN
Objectives: First impact assessment analysis of an integrated care model (ICM) to reduce hospital activity in the London Borough of Hillingdon, UK. Methods: We evaluated a population-based ICM consisting of multiple interventions based on self-management, multidisciplinary teams, case management and discharge management. The sample included 331 330 registered Hillingdon residents (at the time of data extraction) between October 2018 and July 2020. Longitudinal data was extracted from the Whole Systems Integrated Care database. Interrupted time series Poisson and Negative binomial regressions were used to examine changes in non-elective hospital admissions (NEL admissions), accident and emergency visits (A&E) and length of stay (LoS) at the hospital. Multiple imputations were used to replace missing data. Subgroup analysis of various groups with and without long-term conditions (LTC) was also conducted using the same models. Results: In the whole registered population of Hillingdon at the time of data collection, gradual decline over time in NEL admissions (RR 0.91, 95% CI 0.90 to 0.92), A&E visits (RR 0.94, 95% CI 0.93 to 0.95) and LoS (RR 0.93, 95% CI 0.92 to 0.94) following an immediate increase during the first months of implementation in the three outcomes was observed. Subgroup analysis across different groups, including those with and without LTCs, showed similar effects. Sensitivity analysis did not show a notable change compared with the original analysis. Conclusion: The Hillingdon ICM showed effectiveness in reducing NEL admissions, A&E visits and LoS. However, further investigations and analyses could confirm the results of this study and rule out the potential effects of some confounding events, such as the emergence of COVID-19 pandemic.
RESUMEN
Academic institutions need to maintain publication lists for thousands of faculty and other scholars. Automated tools are essential to minimize the need for direct feedback from the scholars themselves who are practically unable to commit necessary effort to keep the data accurate. In relying exclusively on clustering techniques, author disambiguation applications fail to satisfy key use cases of academic institutions. Algorithms can perfectly group together a set of publications authored by a common individual, but, for them to be useful to an academic institution, they need to programmatically and recurrently map articles to thousands of scholars of interest en masse. Consistent with a savvy librarian's approach for generating a scholar's list of publications, identity-driven authorship prediction is the process of using information about a scholar to quantify the likelihood that person wrote certain articles. ReCiter is an application that attempts to do exactly that. ReCiter uses institutionally-maintained identity data such as name of department and year of terminal degree to predict which articles a given scholar has authored. To compute the overall score for a given candidate article from PubMed (and, optionally, Scopus), ReCiter uses: up to 12 types of commonly available, identity data; whether other members of a cluster have been accepted or rejected by a user; and the average score of a cluster. In addition, ReCiter provides scoring and qualitative evidence supporting why particular articles are suggested. This context and confidence scoring allows curators to more accurately provide feedback on behalf of scholars. To help users to more efficiently curate publication lists, we used a support vector machine analysis to optimize the scoring of the ReCiter algorithm. In our analysis of a diverse test group of 500 scholars at an academic private medical center, ReCiter correctly predicted 98% of their publications in PubMed.
Asunto(s)
Centros Médicos Académicos/estadística & datos numéricos , Autoria , Bibliometría , Docentes/estadística & datos numéricos , PubMed/estadística & datos numéricos , Programas Informáticos/normas , Universidades/estadística & datos numéricos , Centros Médicos Académicos/normas , Algoritmos , Humanos , Universidades/organización & administraciónRESUMEN
Amiodarone is a drug which frequently causes elevated transaminases. However, acute liver failure has been rarely reported. Here, we present a case of fatal acute liver failure following the administration of intravenous amiodarone. It is important to be aware of this rare but potentially fatal complication of intravenous amiodarone so that it can be withdrawn immediately at the first sign of hepatic impairment.