Current practice of reporting HRQL outcomes in RCTs remains highly variable, both with regard to quality of reporting and the patterns of data analysis and presentation. This variation presents challenges for clinicians to apply these data in clinical practice. Consistent reporting practices, which are interpretable by clinicians, are required, as are processes to achieve this consistency in future reports.
The increased risk of CRC associated with an FH of CRC or advanced adenoma warrants more intense screening for CRC. Well-designed prospective studies are needed in order to make definitive evidence-based recommendations about the age to commence screening and appropriate interval between screening tests.
rimary care providers (PCPs) diagnose approximately 1 cancer per month. However, for each malignancy identified, PCPs evaluate many other patients presenting with potential symptoms of cancer. 1 Thresholds for investigation must balance resource use and adverse effects from diagnostic and incidental findings with the risk of missing or delaying a diagnosis of malignancy. A lengthening of the diagnostic interval (Figure 1) 2 can occur because of cognitive errors on the part of the physician, lack of timely access to tests, and lags in patient presentation influenced by knowledge, social context, and beliefs. 3 Such delays can irreparably fracture the patientphysician relationship at a time when medical support is most required. This article provides a 6-step guide (Figure 2) to help PCPs decrease the diagnostic interval and enable a more positive patient outcome.This article is eligible for Mainpro+ certified Self-Learning credits. To earn credits, go to www.cfp.ca and click on the Mainpro link.
Summary
1. We explored patterns of limnological variables (physical, chemical and biological) with relation to landscape position (expressed as lake order) in 86 study lakes located on shield bedrock in south‐central Ontario, Canada.
2. Using anovas with lake order as the categorical variable, landscape position explained significant amounts of variation in major ion chemistry, physical and catchment characteristics, hypolimnetic oxygen, and community composition in algal (diatom, chrysophyte) and invertebrate (chironomid) assemblages preserved in surficial sediments. Several nutrient variables (TP, total phosphorus and TN, total nitrogen) and dissolved organic carbon did not have significant relationships with lake order.
3. The strongest relationships with lake order (as a fraction of variation explained in anovas) included silica concentrations (r2 = 0.40) and SO4 (r2 = 0.29) concentrations, surface area (r2 = 0.50) and hypolimnetic oxygen (r2 = 0.29).
4. Bedrock geology (carbonate metasedimentary versus non‐carbonate bedrock) had strong influences on spatial gradients of pH and major ion chemistry. It was difficult to separate geological influences from spatial influences on limnological variables in this study, as drainage patterns in the region are highly influenced by surface features of underlying geological formations because of the very thin glacial till or exposed bedrock that exists in most catchments.
5. Patterns of limnological variables indicated that low‐order, headwater lakes had the lowest concentrations of major ions, and, from algal inferences of pH change, had been most susceptible to acidic deposition. High‐order, downstream lakes were larger and deeper, and had higher concentrations of hypolimnetic oxygen, indicating that optimal lake trout habitat was primarily located in high‐order lakes.
6. Variance partitioning analyses indicated that lake order as a metric of landscape position explained comparable portions of community variation in algal and invertebrate assemblages compared with geographic position (latitude, longitude) and Cartesian coordinate position (e.g. x, y, x2, y2, etc.) metrics. Lake order explained more community variation in chironomid assemblages compared with other landscape metrics, possibly because of the strong relationships between lake order and lake morphometry variables.
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