Early-onset delirium after spontaneous intracerebral hemorrhage

Objective This study aimed at identifying the incidence, predictors, and impact on long-term mortality and dementia of early-onset delirium in a cohort of patients with spontaneous intracerebral hemorrhage. Methods We prospectively recruited consecutive patients in the Prognosis of InTra-Cerebral Hemorrhage (PITCH) cohort and analyzed incidence rate of early-onset delirium (i.e. during the first seven days after intracerebral hemorrhage onset) with a competing risk model. We used a multivariable Fine-Gray model to identify baseline predictors, a Cox regression model to study its impact on the long-term mortality risk, and a Fine-Gray model adjusted for pre-specified confounders to analyze its impact on new-onset dementia. Results The study population consisted of 248 patients (mean age 70 years, 54% males). Early-onset delirium incidence rate was 29.8% (95% confidence interval (CI) 24.3–35.6). Multivariate analysis showed that pre-existing dementia (subhazard ratio (SHR) 2.08, 95%CI 1.32–3.32, p = 0.002), heavy alcohol intake (SHR 1.79, 95%CI 1.13–2.82, p = 0.013), and intracerebral hemorrhage lobar location (SHR 1.56, 95%CI 1.01–2.42, p = 0.049) independently predicted early-onset delirium. Median follow-up was 9.5 years. Early-onset delirium was associated with higher mortality rates during the first five years of follow-up (HR 1.52, 95%CI 1.00–2.31, p = 0.049), but did not predict new-onset dementia (SHR 1.31, 95%CI 0.60–2.87). Conclusion Early-onset delirium is a frequent complication after intracerebral hemorrhage; it is associated with markers of pre-existing brain vulnerability and with higher mortality risk, but not with higher dementia rates during long-term follow-up.

Letter to the Editor: Response to ‘Overlooked Shortcomings of Observational Studies of Interventions in Coronavirus Disease 2019: An Illustrated Review for the Clinician‘ by Tleyjeh et al

We commented on the publication by Tleyjeh et al regarding the overlooked shortcomings of observational studies of interventions in Coronavirus Disease 2019. Although we agree with Tleyjeh and colleagues on the issue of the competing risk bias in observational studies, the recommendations on the application of the Fine-Gray model provided by the authors are incomplete. The Fine-Gray approach may not be suitable in the presence of interval time-dependent covariates, that are often the case in the studies assessing therapeutic interventions for patients with Coronavirus Disease 2019.

Real-world observational study of assessment of CHA2DS2-VASc, C2HEST and HAVOC scores for atrial fibrillation among patients with rheumatological disorders: a nationwide analysis

PurposeThis is a nationwide-based retrospective study aiming to compare the three different scoring systems (CHA2DS2-VASc, C2HEST and HAVOC scores) in the prediction of atrial fibrillation (AF) in patients with rheumatological disease.MethodsWe used the Fine and Gray model to estimate the risk of AF (subhazard ratio and 95% CI). The predictive accuracy and discriminatory ability of the predictive model were evaluated by receiver operating characteristic (ROC) curve.ResultsAmong the three predictive models, the model using CHA2DS2-VASc score had the better discriminative ability with an ROC of 0.79. The model with C2HEST score had an ROC of 0.78. The discriminative ability of the HAVOC score was 0.77, estimated by ROC.ConclusionWe concluded the CHA2DS2-VASc score has better performance in predicting AF compared with C2HEST score or HAVOC score.

Prediction and Allocation of EDP Based on Gray Model and Fuzzy Comprehensive Evaluation

Global warming is accelerating the sea level to rise, which increases the risk of major coastal areas being submerged. Then, the residents may become environmentally displaced persons (EDP). A method of prediction and allocation of EDP is proposed in this paper. Firstly, the gray model is used to predict sea level and the amount of EDP. Then, the evaluation criterion for the responsibility ability of the EDP migration target countries is given based on the entropy and fuzzy comprehensive evaluation method. In addition, a two-way selection mechanism for EDP is constructed. Finally, the amounts of EDP for the next 10 years are predicted, and the allocation plan in 2030 is made by applying the proposed method.

Analysis and Prediction of Trough Track Superelevation Based on Big Data

The detection of the safety status of urban rail transit is an important part of ensuring the operation of the rail. Using the data detected by the rail to analyze and predict the quality of the rail is very important for the research of rail inspection. Based on the existing research, this paper uses big data to analyze the collected superelevation data, and builds a trough-track superelevation big data prediction model based on the combination of the stochastic oscillation sequence gray model and ALO-Elman network to analyze the historical superelevation data and mine information about superelevation trends. In this paper, the average value of superelevation data of the equal-spaced groove track in a certain interval is collected for verification. The experimental results show that the method can reasonably predict the change trend of the ultra-elevation. The change trend is basically in line with the original data change trend, and the deviation is controlled to be small within range.

Assisted peritoneal dialysis: a feasible KRT modality for frail older patients with end-stage kidney disease (ESKD)

Assisted PD is used as an alternative option for the growing group of frail, older ESKD patients unable to perform their own PD. This study was undertaken to investigate the outcomes of assisted PD in older patients by comparing assisted PD patients with self-care PD patients. This study included all patients aged 70 and above who started on PD in our hospital from 2009 to 2018. Patients were followed up until death, PD cessation or to the end of the study (December 31, 2019). Risk factors associated with mortality, peritonitis and technique failure were evaluated using both cause-specific hazards and subdistribution hazards models. 180 patients were enrolled, including 106 (58.9%) males with a median age of 77.5 (77.2–81.2) years. Among the 180 patients, 62 patients (34.4%) were assisted. Patients on assisted PD group were older, more likely to be female, more prevalent in DM and CVD, with a higher Charlson score than patients undergoing self-care PD (P all < 0.05). In the multivariable analysis, assisted patients had a comparable patient survival and peritonitis-free survival compared to self-care PD patients either in the Cox or in the FG models. According to a Cox model, the use of assisted PD was associated with a lower risk of technique failure (cs-HR 0.20, 95% CI 0.04–0.76), but the association lost its statistical significance in the Fine and Gray model. Our results suggest that assisted PD could be a safe and effective KRT modality for older ESKD patients who need assistance.