2 results
Variability in Antimicrobial Use Among Hospitals Participating in the Canadian Nosocomial Infection Surveillance Program
- Wallis Rudnick, Linda Pelude, Michelle Science, Daniel J.G. Thirion, Jeannette Comeau, Bruce Dalton, Johan Delport, Rita Dhami, Joanne Embree, Yannick Émond, Gerald Evans, Charles Frenette, Susan Fryters, Greg German, Jennifer Grant, Jennifer Happe, Kevin Katz, Pamela Kibsey, Justin Kosar, Joanne Langley, Bonita E. Lee, Marie-Astrid Lefebvre, Jerome Leis, Susan McKenna, Allison McGeer, Heather Neville, Anada Silva, Andrew Simor, Kathryn Slayter, Kathryn Suh, Alena Tse-Chang, Karl Weiss, John Conly, CNISP PHAC
-
- Journal:
- Infection Control & Hospital Epidemiology / Volume 41 / Issue S1 / October 2020
- Published online by Cambridge University Press:
- 02 November 2020, p. s509
- Print publication:
- October 2020
-
- Article
-
- You have access Access
- Export citation
-
Background: The association between antimicrobial use (AMU) and emergence of antimicrobial resistance is well documented. The Canadian Nosocomial Infection Surveillance Program (CNISP) has conducted sentinel surveillance of AMU at participating Canadian hospitals since 2009 resulting in the largest pan-Canadian hospital database of dispensed antimicrobials. Objectives: Describe interhospital variability of AMU across Canada. Methods: Hospitals submit annual AMU data based on patient days (PD). Antimicrobials were measured in defined daily doses (DDD) for adults using the WHO Anatomical Therapeutic Chemical (ATC) system. The AMU data among pediatric patients have been available since 2017 using days of therapy (DOT). Surveillance includes systemic antibacterial agents (J01 ATC codes), oral metronidazole, and oral vancomycin. AMU was assessed using quintiles, interquartile ranges (IQR), and relative IQRs (upper- and lower-quartile values divided by the median). Results: Between 2009 and 2018, 20–26 hospitals participated in adult surveillance each year (35 teaching hospitals and 3 nonteaching hospitals participated in ≥1 year). Over this period, overall AMU decreased by 13% at participating adult hospitals from 645 to 560 DDD per 1,000 PD. AMU varied substantially between hospitals, but this variability decreased over time (Fig. 1). In 2009, the IQRs for overall AMU spanned 309 DDD per 1,000 PD, and in 2018 it spanned only 103 DDD per 1,000 PD. This decrease in variability was due to large decreases in use among hospitals with high use in 2009–2010. Among hospitals in the highest use quintile in 2009–2010, AMU decreased, on average, 44 DDD per 1,000 PD each year. Among hospitals in the lowest use quintile in 2009–2010, AMU increased, on average, 6 DDD per 1,000 PD each year. In 2018, antibiotics with the largest absolute IQR variability were cefazolin (61–113 DDD per 1,000 PD), piperacillin-tazobactam (32–64 DDD per 1,000 PD), and vancomycin (24–49 DDD per 1,000 PD). Among antibiotics with ≥1 DDD per 1,000 PD, antibiotics with the largest relative IQR variability were tobramycin (0.3–6 DDD per 1,000 PD), cefadroxil (0.08–9 DDD per 1,000 PD), and linezolid (0.2–3 DDD per 1,000 PD). In 2018, the IQR for overall pediatric AMU (n = 7 teaching hospitals) was 426–581 DOT per 1,000 PD. Antibiotics with the largest IQRs were vancomycin (0.6–58 DOT per 1,000 PD), cefazolin (33–88 DOT per 1,000 PD), and tobramycin (3–57 DOT per 1,000 PD). Among antibiotics with ≥1 DOT per 1,000 PD in 2018, antibiotics with the largest relative IQRs were tobramycin (3–57 DOT per 1,000 PD), cefuroxime (1–6 DOT per 1,000 PD), and amoxicillin (8–42 DOT per 1,000 PD). Conclusions: There is wide variation in overall antibiotic use across hospitals. Variation between AMU at adult hospitals has decreased between 2009 and 2018; in 2018, antibiotics with the largest IQRs were cefazolin and piperacillin-tazobactam. Benchmarking AMU is crucial for informing antimicrobial stewardship efforts.
Funding: CNISP is funded by the Public Health Agency of Canada.
Disclosures: Allison McGeer reports funds to her institution from Pfizer and Merck for projects for which she is the principal investigator. She also reports consulting fees from Sanofi-Pasteur, Sunovion, GSK, Pfizer, and Cidara.
Salivary Biomarkers of Nutritional Status: a Systematic Review
- Danielle Logan, Sara Megan Wallace, Jayne Woodside, Gerald McKenna
-
- Journal:
- Proceedings of the Nutrition Society / Volume 79 / Issue OCE2 / 2020
- Published online by Cambridge University Press:
- 10 June 2020, E388
-
- Article
-
- You have access Access
- Export citation
-
Introduction:
Full nutritional assessments are currently complex and invasive. There is a need for a non-invasive, timely and cost-effective method to assess nutritional status. Evidence indicates the usefulness of saliva in diagnosing oral or systemic disorders. Saliva is suggested to be a reliable and non-invasive matrix in which to measure nutritional biomarkers. The aim of this work was to systematically review the evidence for salivary biomarkers as indicators of nutritional status.
Materials and Methods:Studies identifying salivary biomarkers in relation to nutritional status or dietary intake outcomes were included. A search strategy combined terms “saliva” AND “biomarkers” AND “nutrition”. Four databases were searched, MEDLINE, EMBASE, Web of Science and Scopus. All study designs conducted in humans of all ages, from all countries and settings were included. Non-English and animal studies were excluded. Risk of bias was assessed using the Newcastle-Ottawa Scale and Cochrane Risk of Bias tool where applicable. (PROSPERO Registration Number:CRD42018107667)
Results:6585 papers were identified, 4836 papers remained after removing duplicates, 4715 were irrelevant, 134 full-texts were assessed for eligibility and 64 papers included in the final analysis. A number of potential salivary biomarkers related to nutritional status were identified including: total protein, albumin, prealbumin, transferrin, ferritin and iron. Total protein levels in saliva in malnourished individuals were significantly different to controls in 7/10 studies (70%). In one study conducted in individuals with iron deficiency anaemia (IDA), total protein was significantly different to controls. Albumin levels in malnourished individuals were significantly different to controls in 5/8 studies (62.5%). Prealbumin and transferrin levels in malnourished individuals were significantly different to controls in 3/3 studies (100%). In one study conducted in malnourished individuals, salivary ferritin levels was significantly different to controls. Ferritin levels in individuals with IDA were significantly different to controls in 3/3 studies (100%). Iron levels in individuals with IDA were significantly different in 2/2 studies (100%). However, even within the studies above where significant differences existed, the direction of salivary biomarker differences was sometimes inconsistent. For example, total protein in malnourished individuals was significantly lower than controls in three studies, higher in three studies and one showed mixed findings. In addition, overall the quality of evidence available was very poor.
Discussion:Despite conflicting evidence in salivary nutritional biomarkers in individuals with malnutrition or IDA, saliva may be a useful non-invasive matrix to assess nutritional status. Further high quality research exploring the utility of these biomarkers is required.