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I have never been contacted and I have been on the registry about 15-20 years. Do I ever have to come back in and have blood drawn again and update my status?

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August 12, 2011 at 9:47 am

Hi Debra, Your information remains on file, and we will contact you if there is ever a need to have another sample tested. It is important to keep your contact information up to date, though. (The form is here, if needed: )

Thank you so much for your longtime commitment as a registry member! Be The Match

August 11, 2011 at 4:04 pm

I have been contacted just once in over 10 years. If there is such a great need, you would think there would have been more requests. But I’m ready and willing if there is ever a match.

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I have been on the list for maybe 10 years and also never contacted. Sometimes I wonder if I missed something along the way but the upside to not being called is that a person is not sick and their family has not needed me yet and that can be a good thing right? I have a co worker who had a marrow transplant last in the last year and is doing well so far. That makes me all the more committed to donating. I have been giving blood since I was a senior in high school (now 43) and an organ donor as well. I would like to see more people join the registry as well as the other things.

August 11, 2011 at 5:01 pm

I have been on the registry for about 15 years now and have never been contacted. I hope I can donate before I age out in 5 years.

August 11, 2011 at 5:18 pm

What a blessing it must be to get that phone call you may be a match. I hope I get the privilege to donate someday. I too have been on the registry for 15 plus years but I have to believe that special someone has not needed my marrow yet. Like Jim M. I have been donating blood for over 34 years and up to 22 gallons, and I know I’m helping people that was but what a honor being able to donate marrow. Thanks to everyone who cares enough to sign up.

June 28, 2018 at 12:09 am

I was a recipient of a BMT from an unrelated donor.

The only way they were able to even keep me alive long enough to find me a donor is through those little pints of blood that people give on their lunch hours.

The evidence base to optimize CDI testing is weak. Clinical criteria for the diagnosis of CDI have altered as awareness of CDI has increased. Notably, the number and frequency of diarrheal stools required to justify CDI testing have declined over the past 40 years. Tedesco et al defined diarrhea as >5 loose stools per day in 1974 [ 167 ]; Teasley et al as >6 loose stools over a period of 36 hours in 1983 [ 168 ]; Fekety et al as liquid stools or >4 bowel movements per day for at least 3 days in 1989 [ 169 ]; and Johnson et al as ≥3 loose or watery bowel movements in 24 hours in 2013 [ 170 ]. Using the latter definition of diarrhea, Dubberke et al and Peterson et al (also using additional clinical criteria) have examined the frequency of these symptoms in patients whose stool is submitted for CDI testing [ 171 , 172 ]. Peterson et al that found 39% of patients did not meet the minimal diarrhea definition and were dropped from further analysis [ 172 ].

Dubberke et al used a clinical definition of ≥3 diarrheal bowel movements (type 6 or 7 stool on the Bristol Stool Chart) [ 173 ] in the 24 hours preceding stool collection, or diarrhea plus patient-reported abdominal pain or cramping. They found that 36% of patients failed to meet the clinical definition but were retained in the study [ 171 ]. The authors caution that even in the presence of clinical diarrheal symptoms, there may be confounding clinical issues such as laxative use, which was found in 19% within the previous 48 hours [ 171 ].

Clinicians can improve laboratory test relevance by only testing patients likely to have C. difficile disease. This includes not routinely performing testing on stool from a patient who has received a laxative within the previous 48 hours. Laboratories can improve specificity by rejecting specimens that are not liquid or soft (ie, take the shape of the container). In addition, laboratories may wish to collaborate with available quality improvement teams such as infection prevention and control and antibiotic stewardship, to assess appropriateness of testing in the population from which samples are submitted. This may involve periodic chart review in a series of patients to assess for clinical risk factors, signs, and symptoms suggestive of CDI.

Two diagnostic testing recommendations based on institutional and laboratory preagreed criteria for patient stool submission are prefaced by questions VII and VIII ( Figure 2 ).

Use a stool toxin test as part of a multistep algorithm (ie, glutamate dehydrogenase [GDH] plus toxin; GDH plus toxin, arbitrated by NAAT; or NAAT plus toxin) rather than a NAAT alone for all specimens received in the clinical laboratory when there are no preagreed institutional criteria for patient stool submission ( Figure 2 ) (weak recommendation, low quality of evidence).

There is a variety of available options for laboratory testing to support the diagnosis of CDI, and these are well described in several recent reviews [ 174 , 175 ]. In brief, these methods detect either the organism or one or both of its major toxins (A and B) directly in stool. Table 3 lists these methods in decreasing order of analytical sensitivity. Toxigenic culture (TC) uses a prereduced selective agar, cycloserine-cefoxitin-fructose agar or a variant of it, followed by anaerobic incubation for several days. Once there is growth, the organism is identified by several methods including matrix-assisted laser desorption/ionization–time of flight mass spectrometry, although the characteristic “horse barn odor” often heralds its presence. To enhance the recovery of the organism, a spore selection step, whether heat or alcohol shock, is applied to the stool prior to inoculating media. Once an organism is identified, a toxin test must be performed on the isolate to confirm its toxigenic potential. TC, although not standardized, has been one of the reference methods against which other methods are compared.

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Undoctored Can Make You Smarter Than Your Doctor

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By Dr. William Davis

There are three ways to raise blood levels of ketones and obtain the potential benefits from them: physiological ketosis via strict carbohydrate limitation or fasting; supplementation of medium-chain triglyceride (MCT) oils that are metabolized in the liver to ketones; and actually taking the ketone, beta-hydroxybutyrate. In this Undoctored Blog post, I’d like to discuss exogenous ketones. While fascinating with potential for substantial health benefits, there are some very real dangers with the current products on the market, so much that I have reported two of the products to the FDA.

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Early research on supplemental exogenous ketones demonstrated fascinating effects, such as protection from hypoglycemia (as ketones are an alternative source of brain energy), protection from seizures (including in Navy seals who breathe high levels of oxygen that can cause fatal underwater seizures), and improved aerobic performance in trained athletes.

More recent research has uncovered or confirmed additional effects of supplemental exogenous ketones:

The effect on weight and whether exogenous ketones might be a strategy for enhancing weight loss are simply not yet clear given current data.

Exogenous ketones generate higher levels of blood ketones than MCTs, about 10-fold higher. While the low ketone levels generated by MCT supplementation have been demonstrated to partially reverse the memory deficits of Alzheimer’s dementia, exogenous ketones have the potential for greater memory-improving effects, with maximum effect likely occurring at a beta-hydroxybutyrate blood level of 4 mmol/L or higher, the level at which ketone transport into the brain is maximized. No clinical studies with exogenous ketones on dementia have been performed yet, however.

Another exciting but speculative application of exogenous ketones is in cancer treatment. Because cancers are known to be glucose-dependent (accounting, for instance, for increased labeled glucose uptake on PET scans), could cancer be reduced/reversed by administering insulin to lower blood glucose to levels that would otherwise be fatal by concurrently administering exogenous ketones to provide an alternative source of energy not usable by cancer cells? The feasibility of this combined treatment has already been demonstrated, but efficacy in treating cancer has not.

The URGE study aimed to evaluate the effectiveness of a guideline-based open access ‘fast-track’ investigation service for two common urological problems, benign prostatic hyperplasia (BPH) and microscopic haematuria. General practices were allocated randomly to two groups; one group received guidelines for the appropriate referral of BPH patients for the open access ‘fast-track’ system whilst the other group acted as a control for BPH patients (but did receive guidelines for microscopic haematuria).

Data were collected on two cohorts of patients, one referred before (an indicator of baseline performance) and another referred after the introduction of the fast-track service. Data were collected on pre-referral general practice management, hospital and general practice care following referral, and patient outcome.

For the purposes of this article, we focus on the evaluation of the effectiveness of the intervention for BPH patients only. Data for a single outcome are used: waiting time from the date of patient referral to first appointment at hospital. Waiting time was measured in days and was found to have a skewed distribution that was log transformed to normality. Therefore, geometric means are quoted throughout; the effect sizes and the corresponding 95% confidence intervals (CIs) relate to the ratio of mean waiting time in the intervention group compared with the control group. Data were available on 513 patients (211 before and 312 after the introduction of the fast-track service) referred from 54 general practices from the North East of Scotland.

The traditional approach to the analysis of cluster randomized trials has been to calculate a summary measure for each cluster, such as a cluster mean or proportion. Because each cluster then provides only one data point, the data can be considered to be independent, allowing standard statistical tests to be used.

For example, within the URGE trial, the mean waiting times post-intervention for each general practice could be calculated (when different patients are included pre- and post-, only post data comparisons can be made using simple analyses) (see Table 1). The overall group means can then be compared using a standard t -test resulting in a significance of t 48 = 3.99, P = 0.0003. This results in an effect size of 0.65 (95% CI: 0.53–0.81); in other words, the waiting time was on average 35% less in the guideline group (Table 2). When the size of the clusters varies widely, it is preferable to carry out a weighted t -test, using cluster sizes as the weights. 11 This weighted analysis returns an effect size of 0.65 (95% CI: 0.54–0.78), with a significance of t 48 = 4.72, P = 0.00003.

Standard statistical techniques such as multiple regression can also be used when data have been summarized at a cluster level. These analyses, however, can only adjust for cluster level covariates directly, but can incorporate patient level covariates through a two-stage process. 12


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