Background Dietary recommendations and policies should be guided by rigorous systematic reviews. Reviews that are of poor methodological quality may be ineffective or misleading. Most of the evidence in nutrition comes from nonrandomized studies of nutritional exposures (usually referred to as nutritional epidemiology studies), but to date methodological evaluations of the quality of systematic reviews of such studies have been sparse and inconsistent. Objectives We aimed to investigate the quality of recently published systematic reviews and meta-analyses of nutritional epidemiology studies and to propose guidance addressing major limitations. Methods We searched MEDLINE (January 2018–August 2019), EMBASE (January 2018–August 2019), and the Cochrane Database of Systematic Reviews (January 2018–February 2019) for systematic reviews of nutritional epidemiology studies. We included a random sample of 150 reviews. Results Most reviews were published by authors from Asia (n = 49; 32.7%) or Europe (n = 43; 28.7%) and investigated foods or beverages (n = 60; 40.0%) and cancer morbidity and mortality (n = 54; 36%). Reviews often had important limitations: less than one-quarter (n = 30; 20.0%) reported preregistration of a protocol and almost one-third (n = 42; 28.0%) did not report a replicable search strategy. Suboptimal practices and errors in the synthesis of results were common: one-quarter of meta-analyses (n = 30; 26.1%) selected the meta-analytic model based on statistical indicators of heterogeneity and almost half of meta-analyses (n = 50; 43.5%) did not consider dose–response associations even when it was appropriate to do so. Only 16 (10.7%) reviews used an established system to evaluate the certainty of evidence. Conclusions Systematic reviews of nutritional epidemiology studies often have serious limitations. Authors can improve future reviews by involving statisticians, methodologists, and researchers with substantive knowledge in the specific area of nutrition being studied and using a rigorous and transparent system to evaluate the certainty of evidence.

Despite efforts to improve access to palliative care services, a significant number of patients still have unmet needs throughout their continuum of care. As such, this project was conducted to increase recognition of patients who could benefit from palliative care, increase referrals, and connect regional sites. This study utilized Plan-Do-Study-Act cycles through a quality improvement approach to develop and test the Palliative Care Screening Tool and aimed to screen 100% of patients within 24 hours who were admitted to selected units by February 2017. The intervention was implemented in 3 different units, each within community hospitals. Patients 18 years or older were screened if they were admitted to one of the selected units for the project, regardless of their diagnosis, age, or comorbidities. The percentage of newly admitted patients who were screened and the total number of palliative care consults were assessed as outcome measures. The tool was met with varying compliance among the 3 sites. However, there was an overall increase in consults across all hospital sites, and an increase in the proportion of noncancer patients was demonstrated. Although the aim was not reached, the tool helped to create a shift in the demographic of patients identified as palliative.

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Background: There is no consensus regarding implant size as an independent risk factor for complications in primary breast augmentation. Choosing appropriate implant volume is an integral part of the preoperative planning process. The current study aims to assess the relationship between implant size and the development of complications following augmentation mammaplasty. Methods: A retrospective chart review of patients undergoing primary breast augmentation at the Westmount Institute of Plastic Surgery between January 2000 and December 2021 was conducted. Demographics, implant characteristics, surgical technique, postoperative complications, and follow-up times were recorded. Univariate logistic regression was used to identify independent predictors, which were then included in multivariate logistic regressions of implant volume and implant volume/body mass index (BMI) ratio regarding complications. Results: A total of 1017 patients (2034 breasts) were included in this study. The average implant volume used was 321.4 ± 57.5 cm3 (range: 110–605). Increased volume and volume/BMI ratio were associated with a significant increase in risk of implant rupture (odds ratio = 1.012, P < 0.001 and 1.282, P < 0.001 respectively). Rates of asymmetry were significantly associated with increases in implant volume and volume/BMI ratio (odds ratio = 1.005, P = 0.004 and 1.151, P < 0.001, respectively). No single implant volume or volume/BMI ratio above which risks of complications significantly increase was identified. Conclusions: Implant rupture and postoperative asymmetries are positively correlated with bigger implant volumes. Implant size could likely be a useful independent predictor of certain complications, especially in patients with high implant to BMI ratios.

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