RESUMEN

Background: Acute heart failure necessitates intensive care, and arterial catheterization is a commonly performed invasive procedure in the intensive care unit (ICU). We aimed to investigate the association between arterial catheterization and outcomes in acute heart failure patients without shock. Methods: We utilized MIMIC-IV database records for acute heart failure patients at Beth Israel Deaconess Medical Center from 2008 to 2019. Employing doubly robust estimation, we examined the relationship between arterial catheterization and outcomes, including 28-day, 90-day, in-hospital mortality, and ICU-free days within 28 days. Results: Of 6936 patients identified, 2078 met inclusion criteria; 347 underwent arterial catheterization during their ICU stay. We observed no significant difference in 28-day mortality (odds ratio [OR]: 0.61, 95 % confidence interval [CI]: 0.31-1.21, P = 0.155), though catheterization was associated with reduced in-hospital mortality (OR: 0.41, 95 % CI: 0.14-0.65, P = 0.02). No significant effects were observed on 90-day mortality or ICU-free days within 28 days. Conclusion: Our findings suggest that arterial catheterization is not associated with 28- and 90-day mortality rates in acute heart failure patients without shock but is linked to lower in-hospital mortality. Additional research and consensus are required to determine the appropriate utilization of arterial catheterization in patients.

RESUMEN

TDP2 gene encodes tyrosyl DNA phosphodiesterase 2, an enzyme required for effective repair of the DNA double-strand breaks (DSBs). Spinocerebellar ataxia autosomal recessive 23 (SCAR23) is a rare disease caused by the pathogenic mutation of TDP2 gene and characterized by intellectual disability, progressive ataxia and refractory epilepsy. Thus far, merely nine patients harboring five different variants (c.425 + 1G > A; c.413_414delinsAA, p. Ser138*; c.400C > T, p. Arg134*; c.636 + 3_ 636 + 6 del; c.4G > T, p. Glu2*) in TDP2 gene have been reported. Here, we describe the tenth patient with a novel variant (c.650del, p. Gly217GlufsTer7) and new phenotype (pituitary tumor and hyperhidrosis).

Asunto(s)

RESUMEN

PURPOSE: This study aims to develop a machine learning-based model for predicting mortality risk in patients with epilepsy admitted to the intensive care unit (ICU), providing clinicians with an accurate prognostic tool to guide individualized treatment. METHODS: We collected clinical data from clinical databases (MIMIC IV and eICU-CRD) of epilepsy patients 24 h after ICU admission. The clinical characteristics of ICU patients with epilepsy were carefully feature selected and processed. MIMIC IV as the training set and eICU-CRD database as the test set. Six models were developed and validated, and the best LightGBM model was selected by performance comparison and analysed for interpretability. RESULTS: The final cohort comprised 429 patients for training and 1217 for testing. The training set exhibited a 90-day mortality rate of 9.32 %, and the test set had an in-hospital 90-day mortality rate of 4.10 %. Utilizing the LightGBM model, we achieved an AUC of 0.956 in the training set. External validation demonstrated promising results with accuracy of 0.898, precision of 0.975, AUC of 0.781, F1 score of 0.945, highlighting the model's potential for guiding clinical decision-making. Significant factors influencing model performance included the severity of illness, as measured by the OASIS score, and clinical parameters like heart rate and body temperature. CONCLUSION: This study introduces a machine learning-based approach to predict mortality risk in ICU epilepsy patients, offering a valuable tool for clinicians to identify high-risk individuals and devise personalized treatment strategies, thus improving patient prognosis and treatment outcomes.

Asunto(s)

RESUMEN

INTRODUCTION: Acute heart failure is a serious condition. Atrial fibrillation is the most frequent arrhythmia in patients with acute heart failure. The occurrence of atrial fibrillation in heart failure patients worsens their prognosis and leads to a substantial increase in treatment costs. There is no tool that can effectively predict the onset of atrial fibrillation in patients with acute heart failure in the ICU currently. MATERIALS AND METHODS: We retrospectively analyzed the MIMIC-IV database of patients admitted to the intensive care unit (ICU) for acute heart failure and who were initially sinus rhythm. Data on demographics, comorbidities, laboratory findings, vital signs, and treatment were extracted. The cohort was divided into a training set and a validation set. Variables selected by LASSO regression and multivariate logistic regression in the training set were used to develop a model for predicting the occurrence of atrial fibrillation in acute heart failure in the ICU. A nomogram was drawn and an online calculator was developed. The discrimination and calibration of the model was evaluated. The performance of the model was tested using the validation set. RESULTS: This study included 2342 patients with acute heart failure, 646 of whom developed atrial fibrillation during their ICU stay. Using LASSO and multiple logistic regression, we selected six significant variables: age, prothrombin time, heart rate, use of vasoactive drugs within 24 h, Sequential Organ Failure Assessment (SOFA) score, and Acute Physiology Score (APS) III. The C-index of the model was 0.700 (95% CI 0.672-0.727) and 0.682 (95% CI 0.639-0.725) in the training and validation sets, respectively. The calibration curves also performed well in both sets. CONCLUSION: We developed a simple and effective model for predicting atrial fibrillation in patients with acute heart failure in the ICU.

Asunto(s)

RESUMEN

PURPOSE: The aim of this study was to determine the predictive value of red blood cell distribution width (RDW) in patients with a primary diagnosis of seizures admitted to the intensive care unit (ICU) in terms of in-hospital mortality. METHODS: This was a retrospective study of the eICU Collaborative Research Database of adult patients (aged 18-88 years) with a primary diagnosis of seizures in 2014 and 2015. The prognostic value of RDW was investigated using a receiver operating characteristic (ROC) curve, multiple logistic regression model, and net reclassification index (NRI). RESULTS: We identified 1568 patients who met the inclusion criteria. High RDW was significantly correlated with in-hospital mortality after adjusting for potential confounders with an odds ratio (OR) of 3.513 (95% confidence interval [CI]:1.699-7.266). The area under the ROC curve of RDW for in-hospital mortality was 0.7225. Compared with the prediction of in-hospital mortality using APACHE IV score alone, the continuous NRI with the RDW variable was 0.3507 (95%CI: 0.0584-0.6431, p < 0.05). The length of stay in the ICU of patients with an RDW >14.65% was significantly increased compared to those with normal RDW (log-rank test, p < 0.0001). CONCLUSION: RDW width can be useful for prediction of in-hospital mortality in patients with seizures admitted to the ICU, and it provides additional prognostic value beyond the APACHE IV score alone.

Asunto(s)

RESUMEN

Alzheimer's disease (AD) is accompanied by ß-amyloid (Aß), neurofibrillary tangles, and neuron cell death, and is one of the most commonly occurring diseases among the elderly. The pathology of AD is complex, involving Aß overproduction and accumulation, tau hyperphosphorylation, and neuronal loss. In addition, chronic cerebral hypoperfusion (CCH) is ubiquitous in the AD patients and plans a pivotal role in triggering and exacerbating the pathophysiological progress of AD. The goal of this study was to investigate the neuroprotective properties of berberine (BBR) and the underlying mechanism. During the study, BBR was administrated to treat the triple-transgenic mouse model of Alzheimer's disease (3×Tg AD). To thoroughly evaluate the effects of the BBR administration, multiple manners were utilized, for instance, 3D arterial spin labeling technique, Morris water maze assay, immunofluorescence staining, TUNEL assay, laser speckle contrast imaging, western blotting, etc. The results showed that BBR ameliorated cognitive deficits in 3×Tg AD mice, reduced the Aß accumulation, inhibited the apoptosis of neurons, promoted the formation of microvessels in the mouse brain by enhancing brain CD31, VEGF, N-cadherin, Ang-1. The new vessels promoted by BBR were observed to have a complete structure and perfect function, which in turn promoted the recovery of cerebral blood flow (CBF). In general, berberine is effective to 3×Tg AD mice, has a neuroprotective effect, and is a candidate drug for the multi-target prevention and treatment of AD.

Asunto(s)

RESUMEN

Aim Cardiac arrest is a global health concern with consistently high mortality. It is also a common condition seen in the intensive care unit (ICU). We aimed to investigate the importance of albumin level on admission, which is a widely available and simple test, to predict in-hospital mortality in cardiac arrest patients. Methods The retrospective study collected data from the eICU Collaborative Research Database. It contains data from 171 hospitals, 276 ICU wards, and 4,529 patients who were treated for cardiac arrest from 2014 to 2015. We analyzed the patients' laboratory results and vital signs during the first 24 hours after admission to the ICU. The primary outcome was in-hospital mortality, and the secondary outcome was the length of ICU stay among survivors. Results In total, 2,414 patients were eligible. After adjusting for severity scores, including the Acute Physiology and Chronic Health Evaluation (APACHE) IV and Sequential Organ Failure Assessment (SOFA) scores, serum albumin was found to be a protective factor for survival (odds ratio of mortality: 0635, 95% confidence interval: 0.458-0.734, P<0.001). Among patients who survived until discharge, those with hypoalbuminemia had a long duration of stay in the ICU (P=0.005). Conclusion The higher albumin level at admission to the ICU was associated with lower mortality in patients with cardiac arrest.

RESUMEN

OBJECTIVE: Sepsis is the leading cause of death in patients admitted to adult intensive care units (ICUs). We aimed to determine the predictive value of red blood cell distribution width (RDW) in patients with sepsis in a large cohort. METHODS: This retrospective observational study used data from the eICU Collaborative Research Database. The prognostic value of RDW was investigated using the receiver operating characteristic (ROC) curve, multiple logistic regression model, integrated discriminatory index (IDI), and net reclassification index (NRI). RESULTS: In total, 9743 patients were included. The area under the ROC curve of the RDW for predicting hospital mortality was 0.631 (95% confidence interval [CI]: 0.616-0.645). Based on the multiple logistic regression model, an RDW of ≥14.5% was correlated with hospital mortality, regardless of Sequential Organ Failure Assessment (SOFA) and Acute Physiology and Chronic Health Evaluation IV (APACHE IV) scores (odds ratio [OR]: 1.838, 95% CI: 1.598-2.119). Using SOFA and APACHE IV scores as reference, the IDI and continuous NRI of RDW for hospital mortality was about 0.3 and 0.014, respectively. CONCLUSIONS: The RDW may be useful in predicting hospital mortality in patients with sepsis, offering extra prognostic value beyond SOFA and APACHE IV scores.

Asunto(s)

RESUMEN

OBJECTIVE: The aim of this study was to determine the outcome of antiepileptic drug (AED) withdrawal in patients who were seizure-free for more than two years. METHODS: Patients with epilepsy who were seizure-free for at least two years and decided to stop AED therapy gradually were followed up every two months for seizure relapse. The inclusion criteria were as follows: (1) diagnosis of epilepsy, defined as the following conditions: ① at least two unprovoked (or reflex) seizures occurring >24 h apart; ② one unprovoked (or reflex) seizure and a probability of further seizures similar to the general recurrence risk (at least 60%) after two unprovoked seizures, occurring over the next 10 years; ③ diagnosis of an epilepsy syndrome; (2) patients remained seizure-free for at least 24 consecutive months during AED therapy; and (3) patients expressed a desire to discontinue AED therapy gradually and agreed to return for regular follow-ups. The time to a seizure relapse and predictive factors were analyzed by survival methods, including sex; age at seizure onset; number of episodes; seizure-free period before AED withdrawal; duration of follow-up after AED withdrawal; AED tapering off period (taper period); results from brain magnetic resonance (MRI); electroencephalogram (EEG) after drug withdrawal; EEG before drug withdrawal; seizure type (classified as generalized, partial, or multiple types based on history); and the number of AEDs administered for long-term seizure control. A log-rank test was used for univariate analysis, and a Cox proportional hazard model was used for multivariate analysis. RESULTS: We selected 94 patients (58 men, 36 women). The relapse ratio was 29.8%. Univariate analysis and multivariate Cox regression analysis indicated that withdrawal times and multiple AEDs, as well as the seizure-free period before withdrawal and abnormal EEG after drug withdrawal were significantly correlated with seizure recurrence and were significant independent predictive factors, with a hazard ratio of 0.839 and 3.971, 0.957, and 3.684, respectively. SIGNIFICANCE: The relapse rate in our study was similar to commonly reported overall rates for epilepsy. Distinguishing variables, such as withdrawal times, multiple AEDs, seizure-free period before withdrawal, and abnormal EEG after drug withdrawal, need to be considered when choosing to withdraw from AEDs. Therefore, our recommendation is that after two years of seizure-free survival, patients could consider withdrawal unless they have hippocampal sclerosis (HS).

Asunto(s)