Low Risk of Pneumocytis Jirovecii Pneumonia in Patients with IBD Receiving Chronic Corticosteroid Therapy Does Not Justify Prophylaxis: A Population Based Study

2011 ◽  
Vol 106 ◽  
pp. S486
Author(s):  
Nicola Gathaiya ◽  
Jelena Catania ◽  
Edward Loftus ◽  
William Sandborn ◽  
William Tremaine ◽  
...  
2021 ◽  
Vol 28 (Supplement_1) ◽  
Author(s):  
M Chlabicz ◽  
J Jamolkowski ◽  
W Laguna ◽  
P Sowa ◽  
M Paniczko ◽  
...  

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): Medical University of Bialystok, Poland Background Cardiovascular disease (CVD) is a major, worldwide problem and remain the dominant cause of premature mortality in the word. Simultaneously the metabolic syndrome is a growing problem. The aim of this study was to investigate the cardiometabolic profile among cardiovascular risk classes, and to estimate CV risk using various calculators. Methods The longitudinal, population-based study, was conducted in 2017-2020. A total of 931 individuals aged 20-79 were included. Anthropometric and biochemical profiles were measured according to a standardized protocols. The study population was divided into CV risk classes according to the latest recommendation. Comparisons variables between subgroups were conducted using Dwass-Steele-Critchlow-Fligner test. To estimate CV risk were used: the  Systematic Coronary Risk Estimation system, Framingham Risk Score and LIFEtime-perspective model for individualizing CardioVascular Disease prevention strategies in apparently healthy people (LIFE-CVD). Results The mean age was 49.1± 15.5 years, 43.2% were male. Percentages of low-risk, moderate-risk, high-risk and very-high CV risk were 46.1%, 22.8%, 13.5%, 17.6%, respectively. Most of the analyzed anthropometric, body composition and laboratory parameters did not differ between the moderate and high CV risk participants, whereas the low risk group differed significantly. In the moderate and high-risk groups, abdominal distribution of adipose tissue dominated with significantly elevated parameters of insulin resistance. Interestingly, estimating lifetime risk of myocardial infarction, stroke or CV death using LIFE-CVD calculator yielded similar results in moderate and high CV risk classes. Conclusion The participants belonging to moderate and high CV risk classes have a very similar unfavorable cardiometabolic profile which may result in the similar lifetime CV risk. This may imply the need for more aggressive pharmacological and non-pharmacological management of CV risk factors in the moderate CV risk population. It would be advisable to consider combining the moderate and high risk classes into one high CV risk class, or it may be worth adding one of the parameters of abdominal fat distribution to the CV risk calculators as an expression of increased insulin resistance. Abstract Figure 1.


2011 ◽  
Vol 6 (1) ◽  
pp. 2 ◽  
Author(s):  
Paolo Giorgi Rossi ◽  
Francesco Chini ◽  
Simonetta Bisanzi ◽  
Elena Burroni ◽  
Giuseppe Carillo ◽  
...  

2010 ◽  
Vol 10 (1) ◽  
Author(s):  
Paolo Giorgi Rossi ◽  
◽  
Simonetta Bisanzi ◽  
Irene Paganini ◽  
Angela Di Iasi ◽  
...  

2019 ◽  
Vol 19 ◽  
pp. 100264 ◽  
Author(s):  
Michala Skovlund Sørensen ◽  
Peter Frederik Horstmann ◽  
Klaus Hindsø ◽  
Michael Mørk Petersen

BMJ Open ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. e033944
Author(s):  
Oskar Bergengren ◽  
Hans Garmo ◽  
Ola Bratt ◽  
Lars Holmberg ◽  
Eva Johansson ◽  
...  

ObjectiveKnowledge about factors influencing choice of and adherence to active surveillance (AS) for prostate cancer (PC) is scarce. We aim to identify which factors most affected choosing and adhering to AS and to quantify their relative importance.Design, setting and participantsIn 2015, we sent a questionnaire to all Swedish men aged ≤70 years registered in the National Prostate Cancer Register of Sweden who were diagnosed in 2008 with low-risk PC and had undergone prostatectomy, radiotherapy or started on AS.Outcome measurements and statistical analysisLogistic regression was used to calculate ORs with 95% CIs for factors potentially affecting choice and adherence to AS.Results1288 out of 1720 men (75%) responded, 451 (35%) chose AS and 837 (65%) underwent curative treatment. Of those starting on AS, 238 (53%) diverted to treatment within 7 years. Most men (83%) choose AS because ‘My doctor recommended AS’. Factors associated with choosing AS over treatment were older age (OR 1.81, 95% CI 1.29 to 2.54), a Charlson Comorbidity Index >2 (OR 1.50, 95% CI 1.06 to 2.13), being unaccompanied when notified of the cancer diagnosis (OR 1.45, 95% CI 1.11 to 1.89). Men with a higher prostate-specific antigen (PSA) at the time of diagnosis were less likely to adhere to AS (OR 0.26, 95% CI 0.10 to 0.63). The reason for having treatment after initial AS was ‘the PSA level was rising’ in 55% and biopsy findings in 36%.ConclusionsA doctor’s recommendation strongly affects which treatment is chosen for men with low-risk PC. Rising PSA values were the main factor for initiating treatment for men on AS. These findings need be considered by healthcare providers who wish to increase the uptake of and adherence to AS.


Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 2798-2798 ◽  
Author(s):  
Daniel Pease ◽  
Julie A Ross ◽  
Phuong L. Nguyen ◽  
Betsy Hirsch ◽  
Adina Cioc ◽  
...  

Abstract Introduction Expanding treatment options for MDS have changed therapeutic decision-making for clinicians. To better characterize therapeutic choices in newly diagnosed MDS, we report the practice patterns captured during the first year of MDS diagnosis for patients enrolled in our statewide population-based study. We highlight a comparison of treatment in community and academic centers. Methods Adults in Minnesota with MDS (AIMMS) is a statewide prospective population-based study conducted by the University of Minnesota (UMN), Mayo Clinic, and Minnesota Department of Health. Starting in April 2010, all newly diagnosed adult cases (ages 20+) of MDS were invited to participate. After patient enrollment, central review was performed consisting of independent hematopathology and cytogenetic review coupled with oncologist chart review assigning prognostic risk scores [International Prognostic Scoring System (IPSS) and IPSS-R (Revised)] and abstracting treatment exposures. All enrolled patients with one year follow-up were included in this analysis. Treatment was divided into supportive, active, transplant, or other. Supportive care included observation, growth factors, and transfusions. Active care included azacitidine, decitabine, lenalidomide, or 7+3 chemotherapy. Academic centers were defined as the UMN and Mayo Clinic; all other centers were designated as community based practices. Results The median patient age was 73 years, with 68% males. IPSS and IPSS-R risk scores were calculated for 100% and 97% of patients, respectively. Treatment choices stratified by IPSS risk group showed 89% low risk, 53% INT-1, 31% INT-2, and 13% high risk with supportive care; active and transplant strategies were utilized for 9% low risk, 44% INT-1, 64% INT-2, and 88% high risk. INT-1 in the community received 70% supportive treatment, in academic 35%. Active treatment for INT-1 was 30% in community and 45% in academic. Community INT-2 received supportive care in 45% of cases, in academic 23%. Transplants were limited to academic centers, with the highest rate in INT-2 at 34%. Among community diagnoses, 100% of high risk, 52% INT-2, 26% INT-1, and 13% low risk were referred to an academic center. Comparison of age <65 and 65+ years showed 83% of transplants occurred in those <65. INT-2/high risk group patients <65 received 95% active therapy or transplant, compared to 51% of those 65+. Discussion This prospective, population based study provides a well-defined patient cohort based on central review of pathologic and clinical data. Evaluation of practice patterns during the first year after diagnosis showed higher utilization of active and transplant treatment strategies as IPSS risk score increased. Further, compared to community, higher utilization occurred for patients at academic centers, suggesting more aggressive treatment in these settings. Age was also a predictor of treatment choice. In addition, referral patterns followed IPSS score. Whether these treatment differences are driven by patient preference and/or translate into improved disease control and decreased mortality requires continued prospective analysis and will be detailed in future reports. Disclosures No relevant conflicts of interest to declare.


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