Evaluation of initial shockable rhythm as an indicator of short no-flow time in cardiac arrest: a national registry study

BackgroundThe duration from collapse to initiation of cardiopulmonary resuscitation (no-flow time) is one of the most important determinants of outcomes after out-of-hospital cardiac arrest (OHCA). Initial shockable cardiac rhythm (ventricular fibrillation or ventricular tachycardia) is reported to be a marker of short no-flow time; however, there is conflicting evidence regarding the impact of initial shockable cardiac rhythm on treatment decisions. We investigated the association between initial shockable cardiac rhythm and the no-flow time and evaluated whether initial shockable cardiac rhythm can be a marker of short no-flow time in patients with OHCA.MethodsPatients aged 18 years and older experiencing OHCA between 2010 and 2016 were selected from a nationwide population-based Japanese database. The association between the no-flow time duration and initial shockable cardiac rhythm was evaluated. Diagnostic accuracy was evaluated using the sensitivity, specificity and positive predictive value.ResultsA total of 177 634 patients were eligible for the analysis. The median age was 77 years (58.3%, men). Initial shockable cardiac rhythm was recorded in 11.8% of the patients. No-flow time duration was significantly associated with lower probability of initial shockable cardiac rhythm, with an adjusted OR of 0.97 (95% CI 0.96 to 0.97) per additional minute. The sensitivity, specificity and positive predictive value of initial shockable cardiac rhythm to identify a no-flow time of <5 min were 0.12 (95% CI 0.12 to 0.12), 0.88 (95% CI 0.88 to 0.89) and 0.35 (95% CI 0.34 to 0.35), respectively. The positive predictive values were 0.90, 0.95 and 0.99 with no-flow times of 15, 18 and 28 min, respectively.ConclusionsAlthough there was a significant association between initial shockable cardiac rhythm and no-flow time duration, initial shockable cardiac rhythm was not reliable when solely used as a surrogate of a short no-flow time duration after OHCA.

A branch and bound method in a permutation flow shop with blocking and setup times

In this paper it is presented an improvement of the branch and bound algorithm for the permutation flow shop problem with blocking-in-process and setup times with the objective of minimizing the total flow time and tardiness, which is known to be NP-Hard when there are two or more machines involved. With that objective in mind, a new machine-based lower bound that exploits some structural properties of the problem. A database with 27 classes of problems, varying in number of jobs (n) and number of machines (m) was used to perform the computational experiments. Results show that the algorithm can deal with most of the problems with less than 20 jobs in less than one hour. Thus, the method proposed in this work can solve the scheduling of many applications in manufacturing environments with limited buffers and separated setup times.

Conditional Operation Rules For Optimal Conjunctive Use of Surface And Groundwater

The current study presents an efficient method for deriving precise operation rules from all subsystems of a distributed conjunctive use system (CUS), including aquifer, river, and reservoir. Distributed aquifer simulation has been performed using the URM method. Given that the historical flow time series can only represent one of the possible situations in the future and its use to determine the performance of the CUS is certainly not very reliable, in this study, river flow uncertainties are implicitly considered. To develop the operation rules, the time series of river flow were generated using autoregressive model. Then, the operation optimization model of the system was implemented with the objective function of minimizing water shortage for different river flow time series. 70% of the data was used for model training and 30% for model validation. Finally, using the decision tree algorithm (M5Rules), the conditional operation rules were extracted and compared with the single linear regression operation rules. Using five efficiency criteria CC, MAE, RMSE, RAE, and RRSE, the comparison of conditional and single linear regression operating rules has been done. The results showed that the the conditional operation rules reduces relative absolute error by a minimum of 39% and a maximum of 71%. If the system is operated according to the conditional rules, in the worst case, the amount of water shortage imposed will be 16.61 MCM over ten years.

Mining the Coopetition Relationship of Urban Public Traffic Lines Based on Time Series Correlation

Along with the evolution of passenger flows within cities, the coordination between public traffic lines should be sustainably optimized with respect to the spatial distribution of the flow, though the lines were planned well at the beginning of the construction. It is critical to determine the coopetition between bus lines to optimize a transit network continuously. A method of mining coopetition relationship (MCBTC, Mining Coopetition relationship between Bus lines based on a Time series Correlation) based on passenger flow is proposed in this study. First, noisy, inconsistent or missing data are eliminated to obtain a passenger flow time series, and the proposed merging algorithm is used to extract the line passenger flow time series (LPFTS, Line Passenger Flow Time Series) by merging the passenger flow of adjacent buses from the same line. Then, to calculate the positive and negative correlation sequence sets, a clustering algorithm is proposed. The two sequence sets represent the competition and cooperation relationships, respectively. The MCBTC method has been tested with a practical data set, and the results show that it is very promising.