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Mitch Steffler Yin Li Sharada Weir Shaun Shaikh Farshad Murtada James G. Wright Jasmin Kantarevic 《CMAJ》2021,193(8):E270
BACKGROUND:New case-mix tools from the Canadian Institute for Health Information offer a novel way of exploring the prevalence of chronic disease and multimorbidity using diagnostic data. We took a comprehensive approach to determine whether the prevalence of chronic disease and multimorbidity has been rising in Ontario, Canada.METHODS:In this observational study, we applied case-mix methodology to a population-based cohort. We used 10 years of patient-level data (fiscal years 2008/09 to 2017/18) from multiple care settings to compute the rolling 5-year prevalence of 85 chronic diseases and multimorbidity (i.e., the co-occurrence of 2 or more diagnoses). Diseases were further classified based on type and severity. We report both crude and age- and sex-standardized trends.RESULTS:The number of patients with chronic disease increased by 11.0% over the 10-year study period to 9.8 million in 2017/18, and the number with multimorbidity increased 12.2% to 6.5 million. Overall increases from 2008/09 to 2017/18 in the crude prevalence of chronic conditions and multimorbidity were driven by population aging. After adjustments for age and sex, the prevalence of patients with ≥ 1 chronic conditions decreased from 70.2% to 69.1%, and the prevalence of multimorbidity decreased from 47.1% to 45.6%. This downward trend was concentrated in minor and moderate diseases, whereas the prevalence of many major chronic diseases rose, along with instances of extreme multimorbidity (≥ 8 conditions). Age- and sex-standardized resource intensity weights, which reflect relative expected costs associated with patient diagnostic profiles, increased 4.6%.INTERPRETATION:Evidence of an upward trend in the prevalence of chronic disease was mixed. However, the change in case mix toward more serious conditions, along with increasing patient resource intensity weights overall, may portend a future need for population health management and increased health system spending above that predicted by population aging.Multimorbidity exists when a patient is diagnosed with 2 or more chronic diseases. Patients with multimorbidity present challenges for physicians managing their care and, as the proportion of these patients in the population increases, for health care system planning. The prevalence of multimorbidity and chronic disease has been strongly associated with primary care use, specialist consultations, number and intensity of inpatient hospital admissions and other types of care.1–7 Among beneficiaries of fee-for-service Medicare in the United States, expenditures for those with 4 or more chronic diseases were reported to be 66 times higher than for those with none.8 One study found that most health spending growth (77.6%) in the US between 1987 and 2011 could be attributed to patients with 4 or more diseases.9Several recent studies have estimated the prevalence of chronic disease and multimorbidity in Canada.3,10–13 Rates of multimorbidity ranged from 10% to 25%, owing to differences in classification systems used to identify chronic disease, including the choice of conditions, and variations in study population. Lack of standardization in measures of chronic disease prevalence and multimorbidity has hampered the evaluation of trends over time and across settings.Ontario provides an ideal setting to evaluate trends in the prevalence of chronic disease because patients have access to a comprehensive set of publicly funded services. The Canadian Institute for Health Information (CIHI) has created a system that maps patient diagnosis data from all health care settings to a set of 226 clinically meaningful health conditions, covering the full spectrum of acute and chronic morbidity (Jeffrey Hatcher, Canadian Institute for Health Information, Ottawa: personal communication, 2017). CIHI’s system has been independently compared with the Johns Hopkins ACG System; CIHI’s system was deemed to be more specific and less sensitive in classifying diagnoses, making it more conservative in identifying health conditions (S. Cheng, ICES, unpublished data, 2016). The purpose of this study was to evaluate trends in the prevalence of chronic disease and multimorbidity in Ontario using CIHI’s comprehensive disease classification system. 相似文献
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Farshad Malihi Azadeh Hosseini-Tabatabaei Hadi Esmaily Reza Khorasani Maryam Baeeri Mohammad Abdollahi 《Central European Journal of Biology》2009,4(3):369-380
Type 1 diabetes mellitus (T1DM) is characterized by an impairment of the insulin-secreting beta cells with an immunologic
base. Inflammatory cytokines such as tumor necrosis factor (TNF)-α and interleukin (IL)-1β, and free radicals are believed
to play key roles in destruction of pancreatic β cells. The present study was designed to investigate the effect of Silybum marianum seed extract (silymarin), a combination of several flavonolignans with immunomodulatory, anti-oxidant, and anti-inflammatory
potential on streptozotocin (STZ)-induced T1DM in mouse. Experimental T1DM was induced in male albino mice by IV injection
of multiplelow- doses of STZ for 5 days. Seventy-two male mice in separate groups received various doses of silymarin (20,
40, and 80 mg/kg) concomitant or after induction of diabetes for 21 days. Blood glucose and pancreatic biomarkers of inflammation
and toxic stress (IL-1β, TNF-α, myeloperoxidase, lipid peroxidation, protein oxidation, thiol molecules, and total antioxidant
capacity) were determined. Silymarin treatment reduced levels of inflammatory cytokines such as TNF-α and IL-1β and oxidative
stress mediators like myeloperoxidase activity, lipid peroxidation, carbonyl and thiol content of pancreatic tissue in an
almost dose dependent manner. No marked difference between the prevention of T1DM and the reversion of this disease by silymarin
was found. Use of silymarin seems to be helpful in T1DM when used as pretreatment or treatment. Benefit of silymarin in human
T1DM remains to be elucidated by clinical trials. 相似文献
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F. Rakhshandehroo R. Pourrahim H. Zamani Zadeh S. Rezaee M. Mohammadi 《Journal of Phytopathology》2005,153(7-8):480-484
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Nahid Shahabadi Saba Hadidi Farshad Shiri 《Journal of biomolecular structure & dynamics》2020,38(1):283-294
AbstractCommunicated by Ramaswamy H. Sarma 相似文献