UNASSIGNED: Inpatient monitoring is recommended for sotalol initiation.
UNASSIGNED: The purpose of this study was to assess the safety of outpatient sotalol commencement.
UNASSIGNED: This is a multicenter, retrospective, observational study of patients initiated on sotalol in an outpatient setting. Serial electrocardiogram monitoring at day 3, day 7, 1 month, and subsequently as clinically indicated was performed. Corrected QT (QTc) interval and clinical events were evaluated.
UNASSIGNED: Between 2008 and 2023, 880 consecutive patients who were commenced on sotalol were evaluated. Indications were atrial fibrillation/flutter in 87.3% (n = 768), ventricular arrhythmias in 9.9% (n = 87), and other arrhythmias in 2.8% (n = 25). The daily dosage at initiation was 131.0 ± 53.2 mg/d. The QTc interval increased from baseline (431 ± 32 ms) to 444 ± 37 ms (day 3) and 440 ± 33 ms (day 7) after sotalol initiation (P < .001). Within the first week, QTc prolongation led to the discontinuation of sotalol in 4 and dose reduction in 1. No ventricular arrhythmia, syncope, or death was observed during the first week. Dose reduction due to asymptomatic bradycardia occurred in 3 and discontinuation due to dyspnea in 3 within the first week. Overall, 1.1% developed QTc prolongation (>500 ms/>25% from baseline); 4 within 3 days, 1 within 1 week, 4 within 60 days, and 1 after >3 years. Discontinuation of sotalol due to other adverse effects occurred in 41 patients within the first month of therapy.
UNASSIGNED: Sotalol initiation in an outpatient setting with protocolized follow-up is safe, with no recorded sotalol-related mortality, ventricular arrhythmias, or syncope. There was a low incidence of significant QTc prolongation necessitating discontinuation within the first month of treatment. Importantly, we observed a small incidence of late QT prolongation, highlighting the need for vigilant outpatient surveillance of individuals on sotalol.

BACKGROUND: Anamorelin, a drug to treat cancer cachexia, binds to ghrelin receptors and improves body weight and appetite. In clinical trials in Japan, patients experienced a 10.7% frequency of stimulant conduction system depression as a severe side effect. Although rare, anamorelin sometimes causes fatal arrhythmias. Because patients with cancer cachexia are often underweight, data on the safety of anamorelin in obese patients are lacking. We report a case of QT interval prolongation after anamorelin administration to an obese patient with non-small cell lung cancer.
METHODS: A female patient with a body mass index of 30 kg/m2 underwent immunotherapy for lung adenocarcinoma. She presented with severe weight loss, anorexia, and fatigue. She had no history of heart disease. On day 12, after administration of anamorelin 100 mg once daily, the patient developed nausea, diarrhea, and anorexia, which were considered cancer immunotherapy-induced immune-related adverse events, and she was admitted to the hospital. An electrocardiogram (ECG) on admission showed a QTc interval of 502 ms. On admission, her hepatic function was Child-Pugh class B, and anamorelin was discontinued the next day. On day 3 after anamorelin discontinuation, the QTc interval was prolonged by up to 557 ms, then decreased to 490 ms on day 6, and improved to 450 ms on day 16. Re-administration of anamorelin was avoided.
CONCLUSIONS: When administering anamorelin to obese patients, we should be aware of the potential for stimulatory conduction system depression, as in underweight patients. Therefore, we should monitor patients by ECG from the early stages of anamorelin administration. Anamorelin is lipophilic, and its volume of distribution is increased in obese patients. Consequently, obese patients may continue to have QT interval prolongation after discontinuation of anamorelin, requiring long-term side-effect monitoring.

UNASSIGNED: ECG abnormalities have been linked to adverse changes in right ventricular (RV) morphology and poor clinical outcomes in repaired Tetralogy of Fallot (rTOF). Our aim was to describe how ECG changes progress in early and intermediate follow-up and whether types of surgical strategy at the time of primary repair affected these changes.
UNASSIGNED: We studied patients with rTOF born 2000-2018 operated at our institution. Seven time points in relation to primary repair, follow-up, and pulmonary valve replacement (PVR) were identified. Patients correct with valve sparing repair (VSR), trans-annular patch (TAP) including with a monocusp valve (TAP + M) and with at least 3 ECGs were included. PQ interval, QRS duration, dispersion, and fragmentation, QTc duration and dispersion, JTc as well as presence of a right bundle branch block (RBBB) were analyzed. Medical records were reviewed for demographic and surgical data.
UNASSIGNED: Two hundred nineteen patients with 882 ECGs were analyzed with a median follow-up time of 12.3 years (8.4, 17) with 41 (19%) needing PVR during the study period. QRS duration increased at time of primary repair to discharge from 66 msec (IQR 12) to 129 msec (IQR 27) (p < 0.0001) and at 1- and 6- year follow-up but showed only a modest and temporary decrease after PVR. QTc increased at the time of primary repair as well as prior to PVR. PQ interval showed a small increase at the time of primary repair, was at its highest prior to PVR and decreased with PVR. Type of surgical repair affected mainly QTc and JTc and was consistently longer in the TAP + M group until PVR. In VSR, QTc and JTc were prolonged initially compared to TAP but were similar after 1 year. After PVR, there were no differences in adverse ECG changes between surgical groups.
UNASSIGNED: PQ interval and QRS duration best correspond to the assumed volume load whereas the relationship with QTc and JTc is more complex, suggesting that these represent more complex remodeling of the myocardium. Before PVR, QTc and JTc are longer in the TAP + M group which may be due to a longer surgical incision.

UNASSIGNED: Ibogaine is a hallucinogenic drug that may be used to treat opioid use disorder (OUD). The relationships between pharmacokinetics (PKs) of ibogaine and its metabolites and their clinical effects on side effects and opioid withdrawal severity are unknown. We aimed to study these relationships in patients with OUD undergoing detoxification supported by ibogaine.
UNASSIGNED: The study was performed in 14 subjects with OUD. They received a single dose of 10mg/kg ibogaine hydrochloride. Plasma PKs of ibogaine, noribogaine, and noribogaine glucuronide were obtained during 24 h. Cytochrome P450 isoenzyme 2D6 (CYP2D6) genotyping was performed. The PKs were analyzed by means of nonlinear mixed effects modeling and related with corrected QT interval (QTc) prolongation, cerebellar ataxia, and opioid withdrawal severity.
UNASSIGNED: The PK of ibogaine were highly variable and significantly correlated to CYP2D6 genotype (p < 0.001). The basic clearance of ibogaine (at a CYP2D6 activity score (AS) of 0) was 0.82 L/h. This increased with 30.7 L/h for every point of AS. The relation between ibogaine plasma concentrations and QTc was best described by a sigmoid Emax model. Spearman correlations were significant (p < 0.03) for ibogaine but not noribogaine with QTc (p = 0.109) and cerebellar effects (p = 0.668); neither correlated with the severity of opioid withdrawal symptoms.
UNASSIGNED: The clearance of ibogaine is strongly related to CYPD2D6 genotype. Ibogaine cardiac side effects (QTc time) and cerebellar effects are most likely more driven by ibogaine rather than noribogaine. Future studies should aim at exploring lower doses and/or applying individualized dosing based on CYP2D6 genotype.

UNASSIGNED: To assess the diagnostic accuracy of a purpose-designed QTc-scoring algorithm versus the established hand-scoring in patients with chronic obstructive pulmonary disease (COPD) undergoing sleep studies.
UNASSIGNED: We collected 62 overnight electrocardiogram (ECG) recordings in 28 COPD patients. QT-intervals corrected for heart rate (QTc, Bazett) were averaged over 1-min periods and quantified, both by the algorithm and by cursor-assisted hand-scoring. Hand-scoring was done blinded to the algorithm-derived results. Bland-Altman statistics and confusion matrixes for three thresholds (460, 480, and 500ms) were calculated.
UNASSIGNED: A total of 32944 1-min periods and corresponding mean QTc-intervals were analysed manually and by computer. Mean difference between manual and algorithm-based QTc-intervals was -1ms, with limits of agreement of -18 to 16ms. Overall, 2587 (8%), 357 (1%), and 0 QTc-intervals exceeding the threshold 460, 480, and 500ms, respectively, were identified by hand-scoring. Of these, 2516, 357, and 0 were consistently identified by the algorithm. This resulted in a diagnostic classification accuracy of 0.98 (95% CI 0.98/0.98), 1.00 (1.00/1.00), and 1.00 (1.00/1.00) for 460, 480, and 500ms, respectively. Sensitivity was 0.97, 1.00, and NA for 460, 480, and 500ms, respectively. Specificity was 0.98, 1.00, and 1.00 for 460, 480, and 500ms, respectively.
UNASSIGNED: Overall, 8% of nocturnal 1-min periods showed clinically relevant QTc prolongations in patients with stable COPD. The automated QTc-algorithm accurately identified clinically relevant QTc-prolongations with a very high sensitivity and specificity. Using this tool, hospital sleep laboratories may identify asymptomatic patients with QTc-prolongations at risk for malignant arrhythmia, allowing them to consult a cardiologist before an eventual cardiac event.

UNASSIGNED: Sickle cell disease, a common genetic disorder in African Americans, manifests an increased risk of sudden death, the basis of which is incompletely understood. Prolongation of heart rate-corrected QT (QTc) interval on the electrocardiogram, a standard clinical measure of cardiac repolarization, may contribute to sudden death by predisposing to torsades de pointes ventricular tachycardia.
UNASSIGNED: We established a cohort study of 293 adult and 121 pediatric sickle cell disease patients drawn from the same geographic region as the Jackson Heart Study (JHS) cohort, in which significant correlates of QT duration have been characterized and quantitatively modeled. Herein, we establish clinical and laboratory correlates of QTc duration in our cohort using stepwise multivariate linear regression analysis. We then compared our adult sickle cell disease data to effect-size predictions from the published JHS statistical model of QT interval duration.
UNASSIGNED: In adult sickle cell disease, gender, diuretic use, QRS duration, serum ALT levels, anion gap, and diastolic blood pressure show positive correlation; hemoglobin levels show inverse correlation; in pediatric sickle cell disease, age, hemoglobin levels, and serum bicarbonate and creatinine levels show inverse correlation. The mean QTc in our adult sickle cell disease cohort is 7.8 milliseconds longer than in the JHS cohort, even though the JHS statistical model predicts that the mean QTc in our cohort should be > 11 milliseconds shorter than in the much older JHS cohort, a differential of > 18 milliseconds.
UNASSIGNED: Sickle cell disease patients have substantial QTc prolongation relative to their age, driven by factors some overlapping, in adult and pediatric sickle cell disease, and distinct from those that have been defined in the general African American community.

Careful observation of the QT interval is important to monitor patients with long QT syndrome and during treatment with potentially QT-prolonging medication. It is also crucial in the development of novel drugs, in particular in case of a potential side effect of QT prolongation and in patients with increased risk of QT prolongation. The 12-lead electrocardiogram (ECG) is the gold standard to evaluate cardiac conduction and repolarization times. Smartwatches and smart devices offer possibilities for ambulatory ECG recording and therefore measuring and monitoring the QT interval. We performed a systematic review of studies on smartwatches and smart devices for QTc analysis. We reviewed PubMed for smartwatches and smart devices that can measure and monitor the QT interval. A total of 31 studies were included. The most frequent devices were (1) KardiaMobile 6L, a Food and Drug Administration-approved device for QTc analyses that provides a 6-lead ECG, (2) an Apple Watch, a smartwatch with an integrated ECG tool that allows recording of a single-lead ECG, and (3) the Withings Move ECG ScanWatch, an analog watch with a built-in single-lead ECG. The KardiaMobile 6L device and the Apple Watch provide accurate measurements of the QT interval, although the Apple Watch is studied in standard and non-standard positions, and the accuracy of QT measurements increased when the smartwatch was moved to alternative positions. Most studies were performed on patients, and limited results were available from healthy volunteers.

The predictive utility of QTc values, calculated through various correction formulas for the incidence of postoperative major adverse cardiovascular and cerebrovascular events (MACCE) in patients experiencing acute myocardial infarction (AMI), warrants further exploration. This study endeavors to ascertain the predictive accuracy of disparate QTc values for MACCE occurrences in patients with perioperative AMI.
A retrospective cohort of three hundred fourteen AMI patients, comprising 81 instances of in-hospital MACCE and 233 controls, was assembled, with comprehensive collection of baseline demographic and clinical data. QTc values were derived employing the correction formulas of Bazett, Fridericia, Hodges, Ashman, Framingham, Schlamowitz, Dmitrienko, Rautaharju, and Sarma. Analytical methods encompassed comparative statistics, Spearman correlation analysis, binary logistic regression models, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA).
QTc values were significantly elevated in the MACCE cohort compared to controls (P < 0.05). Spearman\'s correlation analysis between heart rate and QTc revealed a modest positive correlation for the Sarma formula (QTcBaz) (ρ = 0.46, P < 0.001). Within the multifactorial binary logistic regression, each QTc variant emerged as an independent risk factor for MACCE, with the Sarma formula-derived QTc (QTcSar) presenting the highest hazard ratio (OR = 1.025). ROC curve analysis identified QTcSar with a threshold of 446 ms as yielding the superior predictive capacity (AUC = 0.734), demonstrating a sensitivity of 60.5% and a specificity of 82.8%. DCA indicated positive net benefits for QTcSar at high-risk thresholds ranging from 0 to 0.66 and 0.71-0.96, with QTcBaz, prevalent in clinical settings, showing positive net benefits at thresholds extending to 0-0.99.
For perioperative AMI patients, QTcSar proves more advantageous in monitoring QTc intervals compared to alternative QT correction formulas, offering enhanced predictive prowess for subsequent MACCE incidents.

OBJECTIVE: To analyze the clinical and genetic characteristics of a patient with long QT syndrome type 14 (long QT syndrome-14, LQT14, OMIM # 616247) caused by a de novo CALM1 mutation.
METHODS: The clinical data of the patient were collected, next-generation sequencing technology was used to determine the exome gene sequence of the patient, and the suspected pathogenic locus was verified by Sanger sequencing.
RESULTS: A 5-year and 9-month-old girl was admitted to the hospital due to a syncopal episode. During the attack, the main symptoms were loss of consciousness, cyanosis of the face and lips, and weakness of limbs. The child had multiple seizures in the past, all of which occurred after emotional excitement and activity. She was diagnosed with epilepsy for more than 3 years, but the effect of antiepileptic treatment was not satisfactory. The electrocardiogram was normal in the past. A month ago, convulsions occurred again after exercise, and the electrocardiogram showed QTc 496 ms. The treadmill test showed a significant prolongation of QTc after exercise, and the genetic results suggested a new heterozygous variant of CALM1, c.395A>G; p. (Asp132Gly). Consequently, she was diagnosed with LQT14 and treated with propranolol. During a follow-up of 15 months, there were no seizures or syncope.
CONCLUSIONS: This patient had multiple episodes of convulsions or syncope after emotional stimulation or activity, with intermittent prolongation of the QTc on routine ECG, marked prolongation of the QTc after exercise, and T-wave alternans, which differed from the LQT14 phenotype caused by the previous CALM1 mutation.

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