True Results Review

True Results Review

True Results Review

9.5.1 What is Heterogeneity and How Can It Be Used?

It is inevitable that studies included in a systematic overview will not be the same. Heterogeneity is any variation among systematic reviews. Different types of heterogeneity can be distinguished. The variability among the outcomes, participants and interventions studied can be called clinical diversity. Variability in study design and risk for bias could be called methodological diversity. Statistics heterogeneity refers to variation in intervention effects in different studies. This is either a result of methodological diversity or clinical diversity. The observation of intervention effects that are different than expected is statistical heterogeneity. This can be due to the fact that they differ more from one another than one might expect. As such, statistical heterogeneity will be referred to as heterogeneity.

The intervention effect will be affected by patient characteristics, specific interventions, or clinical variation. Clinical variation could lead to heterogeneity. In other words, the true intervention effect will be different in different studies.

Differences between studies in terms of methodological factors, such as use of blinding and concealment of allocation, or if there are differences between studies in the way the outcomes are defined and measured, may be expected to lead to differences in the observed intervention effects. Significant statistical heterogeneity arising from methodological diversity or differences in outcome assessments suggests that the studies are not all estimating the same quantity, but does not necessarily suggest that the true intervention effect varies. Particularly, heterogeneity due to methodological diversity alone would suggest that studies are biased. However, empirical evidence indicates that design factors can have an effect on clinical trial outcomes. Further discussion appears in Chapter The scope of a review will largely determine the extent to which studies included in a review are diverse. Sometimes, a review might include several studies that address different questions. For example, when multiple interventions are available for the same condition (see also Chapter 5 Section ). It is important to separate out the studies of each intervention and analyse them. When a large number of studies can be compared in terms of outcomes, intervention and participants, meta-analysis may only be performed. In a meta analysis, it is better to look at the results from multiple clinical trials than in one. It is common to say that systematic reviews can bring together oranges and apples, but that they may not yield the same result. This is true if apples and oranges are of intrinsic interest on their own, but may not be if they are used to contribute to a wider question about fruit. A meta-analysis, for example, may be able to evaluate the average drug effect in a group of drugs by adding results from different trials that each evaluated the effects of the same drug.

Reviewing the methodological and clinical implications of studies may provide a unique opportunity to examine how they relate to results. These investigations must be identified a priori, which means that they should be cited if possible. in the systematic review protocol. It is legitimate for a systematic review to focus on examining the relationship between some clinical characteristic(s) of the studies and the size of intervention effect, rather than on obtaining a summary effect estimate across a series of studies (see Section ). Although meta-regression isn’t used in Rev., it may be useful for such purposes. Refer to Section 3.2.

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Good Media Models and Bad Media Models

It doesn’t take too much to inform readers about the problems they face. This NPR story about a blood test for cancer never mentions sensitivity or specificity, and yet it effectively communicates the problems associated with false-positive and false-negative results. According to experts, a negative result can give “false assurance to the patient”, while a false positive might cause patients to go on expensive and unnecessary medical trips. We also liked this CNN article regarding a test that detects Parkinson’s. The story was well-written and provided a lot of context. However, the reviewers lauded its sensitivity/specificity value. The authors suggested they could go further and explain that low specificity tests can lead to high false-positive rates (where more people don’t believe they have the disease), but they did not say how.

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This is a growing trend in news media, which tends to understate test results and overlook potential hazards.

A Guardian report claimed that an experimental blood test could detect autism in children. It also suggested that this test might lead to earlier diagnosis. However, the Guardian did not offer any evidence to support its claims. The Guardian also failed to warn parents of the potential dangers that false positive or false negative results could cause to their children.

A USA Today article about a genetic test in breast cancer has also been criticized. A reviewer stated that the article “doesn’t give enough information to allow readers to make an informed decision about whether or not they want 23and. Do the me test. Let’s say, for example, how high are false-positives. Or false negatives? So what does it mean for breast cancer incidence?

Richard Hoffman MD, MPH is the director of Division of General Internal Medicine, University of Iowa Carver College of Medicine, and Iowa City VA Medical Center. “The problem about the accuracy statistic, it’s that it’s meaningless,” he said. He pointed out that accuracy in medicine is defined as the product of positive and negative true results divided by the entire set of test results. This calculation is explained in detail in the link above. This means even an ineffective test that cannot detect disease patients would still have high accuracy, even though most of the patients are healthy. If 10 people out of 100 have the disease, and it is not detected by the test, then 90% of true negatives are used to determine the patient’s diagnosis.” he stated.

It is not always clear whether stories use the Medical Literature’s definition of accuracy, or the general term accuracy. That can lead to further confusion.

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How We Picked

We split air purifiers into three distinct “sizes”: those designed for small spaces like kids’ bedrooms, dorm rooms, and offices; those for general living spaces such as enclosed living rooms and master bedrooms; and those for large spaces like combined living/cooking/dining spaces or spaces with cathedral ceilings. The price ranges for each category are also affected by the area. The purifier you require to maintain clean air will be more costly. Over-sizing is good practice. You can run the purifier in a slow and more quiet setting, while still cleaning your air.

In order to classify purifiers, we use air changes per an hour (or ACH) in hypothetical rooms measuring 150, 350, 500, and 500 feet. This assumes 8-foot ceilings. This measure is used to determine how many purifiers can circulate air in a space in 60 minutes. It also provides an initial baseline for categorizing purifiers and comparing them. A purifier should be able to circulate 4 ACH in order to be considered sufficient for each space. Our eight-year experience in testing has proven that 4 ACH allows for rapid and complete purification of high polluted air. We also know that any lower performance will lead to significantly reduced performance.

Using ACH to categorize air purifiers overcomes a common problem in the way manufacturers rate their air purifiers in their advertising. Because it is easy for potential customers to measure their space and choose the purifier that best suits them, most manufacturers offer square-footage ratings. If you have two different rooms, the square-footage rating is meaningless. Manufacturers often use different methods to calculate square-footage ratings, which can lead to hugely exaggerated claims. ACH can be used to get a real picture about a machine’s potential.

Important to remember that our minimum 4ACH is calculated based upon the highest volume air a purifier can handle on its highest setting. This setting would be used in extreme pollution situations, like when dealing with wildfire smoke. But on their highest setting, most purifiers are too loud above 50 decibels to be tolerable as a background for conversation, sleep, or TV watching. Our picks are able to keep your air fresh in the recommended room size on a quiet, medium setting.

HEPA certified purifiers generally pass our tests. True HEPA is defined in North America as removing at least 99.97% (or more) of particles with a diameter of less than 0.3 microns. Referring to human hairs, they are usually 20-180 microns wide. This 0.3 micron size is not an accident: the Association of Home Appliance Manufacturers (a trade association) considers this to be the hardest particle to get rid of by HEPA-type, physical filtration. The physics behind HEPA filter filtration are explained in How HEPA filters Work. We have two picks that we think will be great for larger spaces: the Blue Pure 311+ and the Blue Pure 311+. Although neither Blueair model has been certified true-HEPA rated by AHAM, they both have clean air delivery rate (CADRs) of 350 or 250. They performed extremely well during our tests, which measures each purifier’s ability to capture HEPA-standard, 0.3 micron particles. The CADR numbers are the volume of purified air a purifier produces at its highest setting. CADR testing measures the effectiveness of purifiers on different pollutants, such as tobacco smoke and pollen. The tests correspond to particles of 0.09 – 1.0 microns; 0.5 – 3.0 microns; and 5.0 – 11.0microns. The HEPA-0.3-micron standard fits within the same scale as the tobacco-smoke testing. Blue Pure 411 series models employ the same filtration methods as the 211+ or 311Auto.

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Apart from evaluating the above objective measures, we also weigh the actual value of each purifier, and do not set any price limits for every room size. To judge value, we compare specs (especially ACH), estimated upkeep and electricity costs over the course of five years’ operation, our test results, the findings of other independent reviews, ratings from owners, and manufacturers’ histories of reliability and customer service. This step lets us eliminate the many purifiers that cost far more up front than their specs and ratings justify.

Smart functionality does not come first in our minds. It is generally a way to get more information about and have more control over a purifier using an app. Smart functionality is not something we consider a necessity. Our years of experience have shown that an air purifier can create and maintain excellent air quality when it’s allowed to operate continuously at a moderate temperature. Although we understand the benefits of smart functionality, some purifier owners might find the remote control or voice command useful. The separate guide on air quality monitors has also been created. This is a standalone device that doesn’t control purifier’s operations but gives us a better understanding of the effect they have on our air quality.

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Is the accuracy of blood glucose meters reliable? New Data On 18 Meters

Adam Brown and Jeemin Kimon

Six out of 18 meters were not passed by the Diabetes Technology Society’s Blood Glucose Measure Surveillance Program. Is yours among the six that made it?

You want more information like this?

Diabetes Technology Society (DTS), recently published long-awaited information from its Blood Glucose Surveillance Program (BGMS). This rigorous test verified the accuracy of 18 blood glucose meters (BGMs) that are widely used in the US. The FDA-cleared meters could be purchased at retail stores and then tested in three different locations with over 1000 people, including 840 diabetics. It was troubling that only six devices of the 18 tested met the DTS passing standards for meter accuracy. These were either within 15% or 15mg/dl of laboratory values in almost 95%.

The devices that passed were:

Contour Next (formerly Bayer) from Ascensia – 100% Accu Chek Aviva Plus Roche Roche – 98% Walmart Reli. On Confirm (Micro) from Arkray – 97% CVS Advanced from Agamatrix – 97% Free. Style Lite by Abbott – 96% ACCU-Chek smart. Roche View – 95% These devices failed:

Walmart Reli. Arkray Prime for 92%. Touch Verio from Life. Scan– 92% PRODIGY Auto Code From Prodigy — 90% One. Touch Ultra 2 from life. Scan – 90% Walmart Reli. Ultima from Abbott: 89% Contour Classic by Bayer; 89% Embrace at Omnis Health. 88% True Results from HDI/Nipro. 88% True Track. Bio. Sense Medical 76% Advocate redi-code+ of Diabetic Supply of Suncoast 76% Gmate Smart of Philosys – 71%. The full information and accuracy data can be found here. Although all of the meters received FDA approval at some time, this study shows they do not have the same accuracy. When reviewing new meters, the FDA reviews company-reported trials. This study looked at meters purchased directly from retailers and tested them at respected research centres. You should note that the accuracy standards set by this study exceeded FDA standards.

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