Real-Time Safety Audits of Neonatal Delivery Room Resuscitation Areas: Are We Sufficiently Prepared?

2020 ◽  
Author(s):  
Roberto Ortiz-Movilla ◽  
Rosa M. Funes-Moñux ◽  
Laura Domingo-Comeche ◽  
Lucía Martínez-Bernat ◽  
Maite Beato-Merino ◽  
...  
Keyword(s):  
Adverse Events ◽  
Confidence Interval ◽  
Real Time ◽  
Delivery Room ◽  
Random Real ◽  
Key Points ◽  
Day Of The Week ◽  
Set Up ◽  
Radiant Warmer ◽  
Over Time

Objective This study aimed to use real-time safety audits to establish whether preparation of the equipment required for the stabilization and resuscitation of newborns in the delivery room areas is adequate. Study Design This was a descriptive, multicenter study performed at five-level III-A neonatal units in Madrid, Spain. For 1 year, one researcher from each center performed random real-time safety audits (RRTSAs), on different days and during different shifts, of at least three neonatal stabilization areas, either in the delivery room or in the operating room used for caesarean sections. Three factors in each area were reviewed: the set-up of the radiant warmer, the materials, and medication available. The global audit was considered without defect when no errors were detected in any of the audited factors. Possible differences in the results were analyzed as a function of the study month, day of the week, or shift during which the audit had been performed. Results A total of 852 audits were performed. No defects were detected in any of the three factors analyzed in the 534 (62.7%, 95% confidence interval [CI]: 59.3–65.9) cases. Slight defects were detected in 98 (11.5%, 95% CI: 9.4–13.8) cases and serious defects capable of producing adverse events in the newborn during resuscitation were found in 220 (25.8%, 95% CI: 22.9–28.9) cases. No statistically significant differences in the results were found according to the day of the week or time during which the audits were performed. However, the percentage of RRTSAs without defect increased as the study period progressed (first quarter 38.1% vs. the last quarter 84.2%; p < 0.001). Conclusion The percentage of adequately prepared resuscitation areas was low. RRTSAs made it possible to detect errors in the correct availability of the neonatal stabilization areas and improved their preparation by preventing errors from being perpetuated over time. Key Points

scholarly journals Three-year follow-up of treatment-naïve and previously treated patients with CLL and SLL receiving single-agent ibrutinib

Blood ◽  
2015 ◽  
Vol 125 (16) ◽  
pp. 2497-2506 ◽  
Author(s):  
John C. Byrd ◽  
Richard R. Furman ◽  
Steven E. Coutre ◽  
Jan A. Burger ◽  
Kristie A. Blum ◽  
...  
Keyword(s):  
Adverse Events ◽  
Single Agent ◽  
Extended Treatment ◽  
Key Points ◽  
Treatment Naïve ◽  
Previously Treated Patients ◽  
Previously Treated ◽  
Grade 3 ◽  
Over Time

Key Points Three-year follow-up of ibrutinib in CLL demonstrated continued activity with durable responses that improve in quality with extended treatment. Toxicity diminished over time with respect to grade ≥3 cytopenias, fatigue, infections, and adverse events leading to discontinuation.

DEVELOPMENT OF MULTIPLEX REAL-TIME PCR ASSAY FOR SIX PATHOGENS: RAPID TOOL FOR DIAGNOSIS OF BACTERIAL MENINGITIS

2019 ◽  
pp. 60-66
Author(s):  
Viet Quynh Tram Ngo ◽  
Thi Ti Na Nguyen ◽  
Hoang Bach Nguyen ◽  
Thi Tuyet Ngoc Tran ◽  
Thi Nam Lien Nguyen ◽  
...  
Keyword(s):  
Bacterial Meningitis ◽  
Real Time ◽  
Real Time Pcr ◽  
Diagnostic Methods ◽  
Type B ◽  
E Coli ◽  
Pcr Assays ◽  
Set Up ◽  
Etiological Agents ◽  
Suis Serotype

Introduction: Bacterial meningitis is an acute central nervous infection with high mortality or permanent neurological sequelae if remained undiagnosed. However, traditional diagnostic methods for bacterial meningitis pose challenge in prompt and precise identification of causative agents. Aims: The present study will therefore aim to set up in-house PCR assays for diagnosis of six pathogens causing the disease including H. influenzae type b, S. pneumoniae, N. meningitidis, S. suis serotype 2, E. coli and S. aureus. Methods: inhouse PCR assays for detecting six above-mentioned bacteria were optimized after specific pairs of primers and probes collected from the reliable literature resources and then were performed for cerebrospinal fluid (CSF) samples from patients with suspected meningitis in Hue Hospitals. Results: The set of four PCR assays was developed including a multiplex real-time PCR for S. suis serotype 2, H. influenzae type b and N. meningitides; three monoplex real-time PCRs for E. coli, S. aureus and S. pneumoniae. Application of the in-house PCRs for 116 CSF samples, the results indicated that 48 (39.7%) cases were positive with S. suis serotype 2; one case was positive with H. influenzae type b; 4 cases were positive with E. coli; pneumococcal meningitis were 19 (16.4%) cases, meningitis with S. aureus and N. meningitidis were not observed in any CSF samples in this study. Conclusion: our in-house real-time PCR assays are rapid, sensitive and specific tools for routine diagnosis to detect six mentioned above meningitis etiological agents. Key words: Bacterial meningitis, etiological agents, multiplex real-time PCR

Between Jerusalem and Athens

2018 ◽  
Author(s):  
Nurit Yaari
Keyword(s):  
Real Time ◽  
Social Conditions ◽  
Cultural Events ◽  
Greek Drama ◽  
The Past ◽  
Key Points ◽  
Mise En Scene ◽  
Dramatic Writing ◽  
Artistic Performance

How does a theatrical tradition emerge in the fields of dramatic writing and artistic performance? Can a culture, in which theatre played no part in the past, create a theatrical tradition in real time—and how? What was the contribution of classical Greek drama to the evolution of Israeli theatre? How do political and social conditions affect the encounter between cultures—and what role do they play in creating a theatre with a distinctive identity? This book, the first of its kind, attempts to answer these and other questions, by examining the reception of classical Greek drama in the Israeli theatre over the last seventy years. It deals with dramatic and aesthetic issues while analysing translations, adaptations, new writing, mise-en-scène, and ‘post dramatic’ performances of classical Greek drama that were created and staged at key points of the development of Israeli culture amidst fateful political, social, and cultural events in the country’s history.

Eternal Today

2018 ◽  
Author(s):  
Jenni Myllykoski ◽  
Anniina Rantakari
Keyword(s):  
Real Time ◽  
Constitutive Relation ◽  
Human Agency ◽  
Fundamental Characteristic ◽  
Time Study ◽  
Software Company ◽  
Present Experience ◽  
Managerial Strategy ◽  
Over Time ◽  
Strategy Making

This chapter focuses on temporality in managerial strategy making. It adopts an ‘in-time’ view to examine strategy making as the fluidity of the present experience and draws on a longitudinal, real-time study in a small Finnish software company. It shows five manifestations of ‘in-time’ processuality in strategy making, and identifies a temporality paradox that arises from the engagement of managers with two contradictory times: constructed linear ‘over time’ and experienced, becoming ‘in time’. These findings lead to the re-evaluation of the nature of intention in strategy making, and the authors elaborate the constitutive relation between time as ‘the passage of nature’ and human agency. Consequently, they argue that temporality should not be treated merely as an objective background or a subjective managerial orientation, but as a fundamental characteristic of processuality that defines the dynamics of strategy making.

scholarly journals Global Trigger Tool methodology to detect adverse events: pilot study at Academic Hospital of Udine

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
E Scarpis ◽  
S Degan ◽  
D De Corti ◽  
F Mellace ◽  
R Cocconi ◽  
...  
Keyword(s):  
Patient Safety ◽  
Adverse Events ◽  
Academic Hospital ◽  
Trigger Tool ◽  
Hospital Acquired Infections ◽  
Frequent Type ◽  
Global Trigger Tool ◽  
Clinical Records ◽  
Hospital Acquired ◽  
Over Time

Abstract Introduction Identification and measurement of adverse events (AEs) is crucial for patient safety in order to monitor them over time and to implement quality improvement programs, testing if they are effective. Global Trigger Tool (GTT) has been proposed as a low-cost method, being also the most effective to detect AEs. This study aims to describe the number of triggers, the rate and level of AEs identified by GTT and the most frequent type of AE. Methods The Italian version of the GTT was used. Ten paper-based clinical records (CRs) randomly selected every 2 weeks were reviewed from January to April 2019 by three independent reviewers (two nurses, one doctor) at the Academic Hospital of Udine. The AEs rates calculated are: AEs per 1,000 patient-days, AEs per 100 admissions, percentage of admissions with an AE. AEs were classified by harm levels according to National Coordinating Council for Medication Error Reporting and Prevention (NCC MERP). Results CRs reviewed were 80. Mean age of the patients was 69.3±16.4, women were 37.5%. Mean hospitalisation was 16.8±15.3. Nine were the cases of re-hospitalisation within 30 days (11.3%). The total number of trigger was 156. AEs were 31, with at least one AE on 27.5% of admissions, 38.8 AEs per 100 admissions and 23 AEs per 1,000 patient-days. AEs with harm level E, F and H were respectively 5 (16.1%), 24 (77.4%) and 2 (6.5%). The most frequent type of AE were hospital acquired infections with 15 cases (48.4%). Conclusions The most frequent type of AE was the hospital acquired infections. Rates and levels of AEs were higher than other international studies, probably because of the limited number of CRs reviewed. Key messages Global Trigger Tool is an effective method to detect adverse patient safety events in order to monitor them over time. The most frequent type of adverse events was the hospital acquired infections.

scholarly journals Implementation of a deep learning model for automated classification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) in real time

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Song-Quan Ong ◽  
Hamdan Ahmad ◽  
Gomesh Nair ◽  
Pradeep Isawasan ◽  
Abdul Hafiz Ab Majid
Keyword(s):  
Deep Learning ◽  
Aedes Aegypti ◽  
Real Time ◽  
Aedes Albopictus ◽  
Automated Classification ◽  
Expert Performance ◽  
Deep Convolutional Neural Networks ◽  
Significant Difference ◽  
Set Up

AbstractClassification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) by humans remains challenging. We proposed a highly accessible method to develop a deep learning (DL) model and implement the model for mosquito image classification by using hardware that could regulate the development process. In particular, we constructed a dataset with 4120 images of Aedes mosquitoes that were older than 12 days old and had common morphological features that disappeared, and we illustrated how to set up supervised deep convolutional neural networks (DCNNs) with hyperparameter adjustment. The model application was first conducted by deploying the model externally in real time on three different generations of mosquitoes, and the accuracy was compared with human expert performance. Our results showed that both the learning rate and epochs significantly affected the accuracy, and the best-performing hyperparameters achieved an accuracy of more than 98% at classifying mosquitoes, which showed no significant difference from human-level performance. We demonstrated the feasibility of the method to construct a model with the DCNN when deployed externally on mosquitoes in real time.

scholarly journals Characterisation of Textile Embedded Electrodes for Use in a Neonatal Smart Mattress Electrocardiography System

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 999
Author(s):  
Henry Dore ◽  
Rodrigo Aviles-Espinosa ◽  
Zhenhua Luo ◽  
Oana Anton ◽  
Heike Rabe ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Heart Rate ◽  
Intensive Care ◽  
High Resolution ◽  
Neonatal Intensive Care Unit ◽  
Real Time ◽  
Neonatal Intensive Care ◽  
Delivery Room ◽  
Proof Of Concept ◽  
Heart Rate Monitoring

Heart rate monitoring is the predominant quantitative health indicator of a newborn in the delivery room. A rapid and accurate heart rate measurement is vital during the first minutes after birth. Clinical recommendations suggest that electrocardiogram (ECG) monitoring should be widely adopted in the neonatal intensive care unit to reduce infant mortality and improve long term health outcomes in births that require intervention. Novel non-contact electrocardiogram sensors can reduce the time from birth to heart rate reading as well as providing unobtrusive and continuous monitoring during intervention. In this work we report the design and development of a solution to provide high resolution, real time electrocardiogram data to the clinicians within the delivery room using non-contact electric potential sensors embedded in a neonatal intensive care unit mattress. A real-time high-resolution electrocardiogram acquisition solution based on a low power embedded system was developed and textile embedded electrodes were fabricated and characterised. Proof of concept tests were carried out on simulated and human cardiac signals, producing electrocardiograms suitable for the calculation of heart rate having an accuracy within ±1 beat per minute using a test ECG signal, ECG recordings from a human volunteer with a correlation coefficient of ~ 87% proved accurate beat to beat morphology reproduction of the waveform without morphological alterations and a time from application to heart rate display below 6 s. This provides evidence that flexible non-contact textile-based electrodes can be embedded in wearable devices for assisting births through heart rate monitoring and serves as a proof of concept for a complete neonate electrocardiogram monitoring system.

Physical Aggression Is Associated With More Effective Postdecisional Processing of Social Threat

2021 ◽  
pp. 216770262096629
Author(s):  
Grace M. Brennan ◽  
Arielle Baskin-Sommers
Keyword(s):  
Real Time ◽  
Physical Aggression ◽  
Social Threat ◽  
Social Decisions ◽  
Angry Rumination ◽  
Incarcerated Men ◽  
Over Time

Physically aggressive individuals are more likely to decide that others are threatening. Yet no research has examined how physically aggressive individuals’ social decisions unfold in real time. Seventy-five incarcerated men completed a task in which they identified the emotions in faces displaying anger (i.e., threat) and happiness (i.e., nonthreat) at low, moderate, or high ambiguity. Participants then rated their confidence in their decisions either immediately or after a delay, and changes in confidence provided an index of postdecisional processing. Physical aggression was associated with stronger differentiation of threatening and nonthreatening faces under moderate ambiguity. Moreover, physical aggression was associated with steeper decreases in confidence over time following decisions that threatening faces were nonthreatening, indicating more extensive postdecisional processing. This pattern of postdecisional processing mediated the association between physical aggression and angry rumination. Findings suggest a role for postdecisional processing in the maintenance of threat-based social decisions in physical aggression.

ExpanDrogram: Dynamic Visualization of Big Data Segmentation over Time

2021 ◽  
Vol 13 (2) ◽  
pp. 1-27
Author(s):  
A. Khalemsky ◽  
R. Gelbard
Keyword(s):  
Big Data ◽  
Visual Presentation ◽  
Trend Detection ◽  
Dynamic Visualization ◽  
Segmentation Process ◽  
Key Points ◽  
Wide Range ◽  
History Of ◽  
The Individual ◽  
Over Time

In dynamic and big data environments the visualization of a segmentation process over time often does not enable the user to simultaneously track entire pieces. The key points are sometimes incomparable, and the user is limited to a static visual presentation of a certain point. The proposed visualization concept, called ExpanDrogram, is designed to support dynamic classifiers that run in a big data environment subject to changes in data characteristics. It offers a wide range of features that seek to maximize the customization of a segmentation problem. The main goal of the ExpanDrogram visualization is to improve comprehensiveness by combining both the individual and segment levels, illustrating the dynamics of the segmentation process over time, providing “version control” that enables the user to observe the history of changes, and more. The method is illustrated using different datasets, with which we demonstrate multiple segmentation parameters, as well as multiple display layers, to highlight points such as new trend detection, outlier detection, tracking changes in original segments, and zoom in/out for more/less detail. The datasets vary in size from a small one to one of more than 12 million records.

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