Open Medicine

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ISSN 1911-2092

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    ABSTRACT: Background: Unexpected death within 24 hours of admission is a real challenge for the clinician in the emergency room. How to diagnose these patients and the right approach to prevent sudden death with 24 hours is still an enigma. The aims of our study were to find the independent factors that may affect the clinical outcome in the first 24 hours of admission to the hospital. Methods: We performed a retrospective study defining unexpected death within 24 hours of admission in our Department of Medicine in the last 6 years. We found 43 patients who died within 24 hours of admission, and compared their clinical and biochemical characteristics to 6055 consecutive patients who were admitted in that period of time and did not die within the first 24 hours of admission. The parameters that were used include gender, age, temperature, clinical and laboratory criteria for SIRS, arterial blood lactate, and arterial blood pH. Results: Most of the patients who died within 24 hours had sepsis with SIRS. These patients were older (78.6±14.7 vs. 65.2±20.2 years [p<.0001]), had higher lactate levels (8.0±4.8 vs. 2.1±1.8mmol/L[p<.0001]), and lower pH (7.2±0.2 vs. 7.4±0.1 [p<.0001]). Logistic regression analysis found that lactate was the strongest independent parameter to predict death within 24 hours of admission (OR1.366 [95% CI 1.235-1.512]), followed by old age (OR 1.048 [95% CI 1.048-1.075] and low arterial blood pH (OR 0.007 [CI <0.001-0.147]). When gender was analyzed, pH was not an independent variable in females (only in males). Conclusions: The significant independent variable that predicted death within 24 hours of admission was arterial blood lactate level on admission. Older age was also an independent variable; low pH affected only males, but was a less dominant variable. We suggest use of arterial blood lactate level on admission as a bio-marker in patients with suspected sepsis admitted to the hospital for risk assessment and prediction of death within 24 hours of admission.
    No preview · Article · Jun 2015 · Open Medicine
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    Preview · Article · Nov 2014 · Open Medicine
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    ABSTRACT: Francophones who live outside the primarily French-speaking province of Quebec, Canada, risk being excluded from research by lack of a sampling frame. We examined the adequacy of random sampling, advertising, and respondent-driven sampling for recruitment of francophones for survey research. We recruited francophones residing in the city of Calgary, Alberta, through advertising and respondentdriven sampling. These 2 samples were then compared with a random subsample of Calgary francophones derived from the 2006 Canadian Community Health Survey (CCHS). We assessed the effectiveness of advertising and respondent-driven sampling in relation to the CCHS sample by comparing demographic characteristics and selected items from the CCHS (specifically self-reported general health status, perceived weight, and having a family doctor). We recruited 120 francophones through advertising and 145 through respondent-driven sampling; the random sample from the CCHS consisted of 259 records. The samples derived from advertising and respondentdriven sampling differed from the CCHS in terms of age (mean ages 41.0, 37.6, and 42.5 years, respectively), sex (proportion of males 26.1%, 40.6%, and 56.6%, respectively), education (college or higher 86.7% , 77.9% , and 59.1%, respectively), place of birth (immigrants accounting for 45.8%, 55.2%, and 3.7%, respectively), and not having a regular medical doctor (16.7%, 34.5%, and 16.6%, respectively). Differences were not tested statistically because of limitations on the analysis of CCHS data imposed by Statistics Canada. The samples generated exclusively through advertising and respondent-driven sampling were not representative of the gold standard sample from the CCHS. Use of such biased samples for research studies could generate misleading results.
    Full-text · Article · Oct 2014 · Open Medicine
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    ABSTRACT: Abstract Based on the pivotal trial showing no clinicallyrelevant differences between pegylated interferon α-2b (Peg-α-2b) and α-2a (Peg-α-2a) combined with ribavirin for treatment of chronic hepatitis C virus (HCV) genotype 1 infection in Ukraine, a cost-minimization analysis was performed using a 1 year time horizon and both a health care and patients’ perspective. A decision tree reflects treatment pathways. Drug costs were based on drug labeling and adjusted to the average body mass in Ukraine. Subgroup analysis was applied to deal with heterogeneity of patient’s weight causing dose changes. A break-even price of Peg-α-2a and Peg-α-2b (based on the average dose) was calculated. Univariate sensitivity analyses and probabilistic sensitivity analysis were carried out to reflect decision uncertainty. For an average body weight, total medical costs per patient differ from US$9220 for Peg-α-2b to US$9513 for Peg-α-2a from a health care perspective, and from US$15,212 to US$15,696 from a patients’ perspective. Sensitivity analyses show these results are robust. With average body weight, the break-even price of Peg-α-2b may be 7.3% higher than Peg-α-2a to have similar total costs.
    No preview · Article · Oct 2014 · Open Medicine
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    Full-text · Article · Oct 2014 · Open Medicine