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Occasionally, a heart attack happens without causing any pain. This is usually diagnosed when you have a heart tracing (electrocardiogram, or ECG) at a later stage.

Some people collapse and die suddenly if they have a large portion of heart muscle damaged. This is not very common.

Dial 999/112/911 for an ambulance immediately .

Dial 999/112/911 for an ambulance immediately

Then, if you have some, take one aspirin tablet (see below for the reason for this). You will normally be admitted straight to hospital.

If you think someone is having a heart attack, look for the four Ps:

Many people develop chest pains that are not due to a heart attack. For example, you can have quite bad chest pains with heartburn, and with gallbladder problems or with pains from conditions of the muscles in the chest wall. Therefore, tests are usually done to confirm a heart attack. These are:

A rough idea as to the severity of the heart attack (the amount of heart muscle that is damaged) can be gauged by:

Another chemical that may be measured in a blood test is called creatine kinase. This too is released from heart muscle cells during a heart attack.

Your ECG will be monitored for a few days to check on the heart rhythm. Various blood tests will be done to check on your general well-being.

Other tests may be done in some cases. This may be to clarify the diagnosis (if the diagnosis is not certain) or to diagnose complications such as heart failure if this is suspected. For example, an ultrasound scan of the heart (echocardiogram, or 'echo') or a test called a myocardial perfusion scan may be done.

Also, before discharge from hospital, you may be advised to have tests to assess the severity of the fatty patches or plaques (atheroma) in the coronary arteries - for example:

The following is a typical situation and mentions the common treatments that are usually offered. However, each case is different and treatments may vary depending on your situation.

As soon as possible after a heart attack is suspected you will be given a dose of aspirin. Aspirin reduces the stickiness of platelets. Platelets are tiny particles in the blood that trigger the blood to clot. It is the platelets that become stuck on to a patch of atheroma inside an artery that go on to form the clot.

Other antiplatelet medicines called clopidogrel or under cheap online Crocs White Ballerinas Relaxed Fit hot sale official sale online free shipping big sale buy cheap big discount AtQGWht
may be given. They work in a different way to aspirin and help reduce platelet stickiness.

See separate leaflet calledAspirin and other Antiplatelet Medicines .

These are usually given for a few days to help prevent further blood clots from forming.

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Photo illustration by Slate. Photos by Kellogg’s, Altoids, and Betty Crocker.

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» Experimental Design »

A Simple Example

Probably the easiest way to begin understanding factorial designs is by looking at an example. Let's imagine a design where we have an educational program where we would like to look at a variety of program variations to see which works best. For instance, we would like to vary the amount of time the children receive instruction with one group getting 1 hour of instruction per week and another getting 4 hours per week. And, we'd like to vary the setting with one group getting the instruction in-class (probably pulled off into a corner of the classroom) and the other group being pulled-out of the classroom for instruction in another room. We could think about having four separate groups to do this, but when we are varying the amount of time in instruction, what setting would we use: in-class or pull-out? And, when we were studying setting, what amount of instruction time would we use: 1 hour, 4 hours, or something else?

With factorial designs, we don't have to compromise when answering these questions. We can have it both ways if we cross each of our two time in instruction conditions with each of our two settings. Let's begin by doing some defining of terms. In factorial designs, a factor is a major independent variable. In this example we have two factors: time in instruction and setting. A level is a subdivision of a factor. In this example, time in instruction has two levels and setting has two levels. Sometimes we depict a factorial design with a numbering notation. In this example, we can say that we have a 2 x 2 (spoken "two-by-two) factorial design. In this notation, the number of numbers tells you how many factors there are and the number values tell you how many levels. If I said I had a 3 x 4 factorial design, you would know that I had 2 factors and that one factor had 3 levels while the other had 4. Order of the numbers makes no difference and we could just as easily term this a 4 x 3 factorial design. The number of different treatment groups that we have in any factorial design can easily be determined by multiplying through the number notation. For instance, in our example we have 2 x 2 = 4 groups. In our notational example, we would need 3 x 4 = 12 groups.

factor

We can also depict a factorial design in design notation. Because of the treatment level combinations, it is useful to use subscripts on the treatment (X) symbol. We can see in the figure that there are four groups, one for each combination of levels of factors. It is also immediately apparent that the groups were randomly assigned and that this is a posttest-only design.

Now, let's look at a variety of different results we might get from this simple 2 x 2 factorial design. Each of the following figures describes a different possible outcome. And each outcome is shown in table form (the 2 x 2 table with the row and column averages) and in graphic form (with each factor taking a turn on the horizontal axis). You should convince yourself that the information in the tables agrees with the information in both of the graphs. You should also convince yourself that the pair of graphs in each figure show the exact same information graphed in two different ways. The lines that are shown in the graphs are technically not necessary -- they are used as a visual aid to enable you to easily track where the averages for a single level go across levels of another factor. Keep in mind that the values shown in the tables and graphs are group averages on the outcome variable of interest. In this example, the outcome might be a test of achievement in the subject being taught. We will assume that scores on this test range from 1 to 10 with higher values indicating greater achievement. You should study carefully the outcomes in each figure in order to understand the differences between these cases.

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