A comprehensive strategy to address shortage of Erwinia asparaginase in pediatric acute lymphoblastic leukemia.

BACKGROUND: Pegylated form of E. coli derived asparaginase (PEG) is a crucial component of pediatric ALL therapy. Patients who develop a hypersensitivity (HSR) reaction with PEG receive an alternative form - Erwinia asparaginase (EA). However, an international shortage in 2017 had made it challenging to treat these patients. We have developed a comprehensive strategy to address this need. PATIENTS AND METHODS: This is a single center, retrospective analysis. All patients receiving PEG were premedicated to reduce infusion reactions. Patients who developed HSR underwent PEG desensitization. Patients were compared to historic controls. RESULTS: Fifty-six patients were treated within the study period. There was no difference in the frequency of reactions before and after the adoption of universal premedication (p = 0.78). Eight patients (14.2%) developed either ≥ Grade 2 HSR or silent inactivation and 5 patients (62.5%) successfully underwent desensitization. The remaining three patients received EA asparaginase. This intervention led to a decrease in PEG substitution, with 3 patients (5.3%) requiring EA compared to 8 patients (15.09%) in the pre-intervention period. (p = 0.11) PEG desensitization was more cost effective than EA administration. CONCLUSION: PEG desensitization is a safe, cost effective, and practical alternative in children with ALL and a Grade 2 or higher HSR.

Assessing work resumption in hospitals during the COVID-19 epidemic in China using multiscale geographically weighted regression.

The resumption of work and production is one of the key issues during the novel coronavirus (COVID-19) post-epidemic phase. We used location-based service data of mobile devices to assess the work resumption of 22,098 hospitals in mainland China. The multiscale influences of the determinants on work resumption in hospitals, including medical-service capacity, human movement, and epidemic severity, were examined using the multiscale geographically weighted regression technique. This study provides a novel insight into the assessment of work resumption in hospitals and its determinants, and is flexible to be extended to evaluate the work resumption of other industries. The findings can introduce helpful information for other countries to implement the strategies of work recovery during the post-epidemic phase.

Modeling the complete spatiotemporal spread of the COVID-19 epidemic in mainland China.

OBJECTIVES: The novel coronavirus (COVID-19) epidemic is reaching its final phase in China. The epidemic data are available for a complete assessment of epidemiological parameters in all regions and time periods. METHODS: This study aims to present a spatiotemporal epidemic model based on spatially stratified heterogeneity (SSH) to simulate the epidemic spread. A susceptible-exposed/latent-infected-removed (SEIR) model was constructed for each SSH-identified stratum (each administrative city) to estimate the spatiotemporal epidemiological parameters of the outbreak. RESULTS: We estimated that the mean latent and removed periods were 5.40 and 2.13 days, respectively. There was an average of 1.72 latent or infected persons per 10,000 Wuhan travelers to other locations until January 20th, 2020. The space-time basic reproduction number (R0) estimates indicate an initial value between 2 and 3.5 in most cities on this date. The mean period for R0 estimates to decrease to 80%, and 50% of initial values in cities were an average of 14.73 and 19.62 days, respectively. CONCLUSIONS: Our model estimates the complete spatiotemporal epidemiological characteristics of the outbreak in a space-time domain. These findings will help enhance a comprehensive understanding of the outbreak and inform the strategies of prevention and control in other countries worldwide.

First, second and potential third generation spreads of the COVID-19 epidemic in mainland China: an early exploratory study incorporating location-based service data of mobile devices.

OBJECTIVES: The outbreak of atypical pneumonia caused by the novel coronavirus (COVID-19) has currently become a global concern. The generations of the epidemic spread are not well known, yet these are critical parameters to facilitate an understanding of the epidemic. A seafood wholesale market and Wuhan city, China, were recognized as the primary and secondary epidemic sources. Human movements nationwide from the two epidemic sources revealed the characteristics of the first-generation and second-generation spreads of the COVID-19 epidemic, as well as the potential third-generation spread. METHODS: We used spatiotemporal data of COVID-19 cases in mainland China and two categories of location-based service (LBS) data of mobile devices from the primary and secondary epidemic sources to calculate Pearson correlation coefficient,r, and spatial stratified heterogeneity, q, statistics. RESULTS: Two categories of device trajectories had generally significant correlations and determinant powers of the epidemic spread. Bothr and q statistics decreased with distance from the epidemic sources and their associations changed with time. At the beginning of the epidemic, the mixed first-generation and second-generation spreads appeared in most cities with confirmed cases. They strongly interacted to enhance the epidemic in Hubei province and the trend was also significant in the provinces adjacent to Hubei. The third-generation spread started in Wuhan from January 17-20, 2020, and in Hubei from January 23-24. No obvious third-generation spread was detected outside Hubei. CONCLUSIONS: The findings provide important foundations to quantify the effect of human movement on epidemic spread and inform ongoing control strategies. The spatiotemporal association between the epidemic spread and human movements from the primary and secondary epidemic sources indicates a transfer from second to third generations of the infection. Urgent control measures include preventing the potential third-generation spread in mainland China, eliminating it in Hubei, and reducing the interaction influence of first-generation and second-generation spreads.

Contractibility sensor signal evolution predicts cardiovascular events in patients with cardiac resynchronization therapy.

BACKGROUND: While a multicentre trial has demonstrated that the SonR™ contractibility sensor is as effective as echocardiography-guided optimization at improving response to cardiac resynchronization therapy, an association between SonR™ values and clinical endpoints has not been established. AIMS: The primary objective was to assess the predictive value of SonR™ signal evolution regarding cardiovascular events in patients implanted with a cardiac resynchronization therapy device. The secondary objective was to evaluate whether SonR™ signal evolution was associated with cardiovascular death. METHODS: All patients with a SonR™ system implanted between 2012 and 2016 were included in this retrospective study. SonR™ signal evolution was calculated over the first 6 months after implantation: ([month 6 value-month 1 value]/month 1 value)*100. The primary endpoint (cardiovascular events) was a composite of cardiovascular death, hospitalization for acute heart failure or ventricular arrhythmia. RESULTS: Seventy-four patients (median age 67 years; 81% men) were followed up over a median 20 (13; 29) months. Cumulative incidence function showed that SonR™ signal evolution was predictive of cardiovascular events (threshold<10.70%; P=0.023) and predictive of cardiovascular death (P=0.0018). After multivariable analysis, SonR™ signal evolution was independently associated with the onset of cardiovascular events (hazard ratio: 4.03, 95% confidence interval: 1.31-12.43; P=0.015), even after adjustment for left bundle branch block and chronic kidney disease. CONCLUSIONS: In this first study publishing data on SonR™ signals in a real-life setting, SonR™ signal evolution over the first 6 months after cardiac resynchronization implantation was an independent predictor of cardiovascular events at follow-up. This variable could be useful to identify patients at higher risk of further adverse events after cardiac resynchronization implantation.