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Institution

Saskatchewan Health

GovernmentRegina, Saskatchewan, Canada
About: Saskatchewan Health is a government organization based out in Regina, Saskatchewan, Canada. It is known for research contribution in the topics: Population & Health care. The organization has 442 authors who have published 489 publications receiving 7728 citations.


Papers
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Journal ArticleDOI
TL;DR: In this article, the effect of adding azithromycin to standard antibiotic prophylaxis on the rates of surgical site infection (SSI) in women undergoing both elective and non-elective cesarean deliveries at the Regina General Hospital in Saskatchewan was investigated.
Abstract: Objective The purpose of this quality improvement study was to determine the effect of adding azithromycin to standard antibiotic prophylaxis on the rates surgical site infection (SSI) in women undergoing both elective and non-elective cesarean deliveries at our centre. Methods A before-and-after quality improvement study was conducted at the Regina General Hospital in Regina, Saskatchewan. Data collected from 989 women who had a caesarean delivery between June 1, 2016 and June 30, 2017 were compared with those from 1033 women who had a caesarean delivery between August 1, 2017 and July 31, 2018, after the introduction of adjunctive azithromycin prophylaxis. The primary outcome measure was the change in the incidence of SSI up to 30 days following surgery. Secondary outcome measures included timing of azithromycin prophylaxis and the number of women who did not receive azithromycin. Results Surgical site infection rates decreased from 3.5% to 2.9% after adjunctive azithromycin prophylaxis was introduced. The absolute reduction in SSIs of 0.6% was not statistically significant (P = 0.42). There were no differences in SSI rates between the elective and non-elective subgroups. Conclusion Adding azithromycin to the standard antibiotic prophylaxis for cesarean delivery showed no statistically significant reduction in SSI rates in a population with low baseline rates of SSI.

1 citations

Journal ArticleDOI
TL;DR: Clinicians need to be aware of Cannabinoid Hyperemesis Syndrome (CHS), which may masquerade as other disease states such as uremia in patients with concomitant renal insufficiency, with marijuana legalization.
Abstract: Rationale:With marijuana legalization, clinicians need to be aware of Cannabinoid Hyperemesis Syndrome (CHS), which may masquerade as other disease states such as uremia.Presenting concerns of the ...

1 citations

Journal ArticleDOI
TL;DR: In this article, a pilot project addressed converging needs of students, medical educators, health care workers and IPC and QI champions, and effectively involved students in a novel quality improvement initiative during the early days of the COVID-19 pandemic and provides an example of a creative solution to engage students to safely continue learning while being of service.
Abstract: This pilot project addressed converging needs of students, medical educators, health care workers and IPC and QI champions. It effectively involved students in a novel quality improvement initiative during the early days of the COVID-19 pandemic and provides an example of a creative solution to engage students to safely continue learning while being of service.

1 citations

Proceedings ArticleDOI
05 Jun 2020
TL;DR: Combination of Fast-ICA and adaptive Type-2 Fuzzy filter is utilized for filtering a group of low-dose images and the main novelty is attempting to convert the shot noise distribution to salt and pepper and denoising mapped image using fast independent component analysis.
Abstract: Decreasing the absorbed dosage by patient in x-ray imaging along with keeping image quality is one of the long-term goals of medical imaging field. Using low-dose images, instead of normal-dose images, can decrease the absorbed dosage; however, it also decreases the image quality due to quantum noise. In this paper, combination of Fast-ICA and adaptive Type-2 Fuzzy filter is utilized for filtering a group of low-dose images. Five different phantoms are used for investigating various effect of denoising, such as retaining slice geometry, high resolution, low-contrast, uniformity and bead geometry regions. Due to few numbers of images (8 images for each phantom), using deep learning method is not practical. The main novelty is attempting to convert the shot noise distribution to salt and pepper and denoising mapped image using fast independent component analysis. Concisely, the average and standard deviation of PSNR and SSIM of the proposed algorithm on five phantoms are 36.0 ± 2.7 dB and 0.83 ± 0.2, respectively, which shows a significant improvement comparing to the similar benchmark methods.

1 citations


Authors

Showing all 449 results

NameH-indexPapersCitations
Gary R. Hunter7133716410
Lisa M. Lix5946213778
Peter O'Hare551269246
Edward D. Chan542249014
Paul Babyn5430711466
Roland N. Auer521208564
Paul N. Levett441378486
Alan A. Boulton391835253
Carl D'Arcy381295002
Vikram Misra371164363
Andrew W. Lyon281092449
Denis C. Lehotay27521756
Gary F. Teare26612749
Greg B. Horsman25491727
Emina Torlakovic24961899
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20232
20221
2021116
202088
201959
201836