# Thread: Total complications in both groups

1. ## Total complications in both groups

Hi,

I have the following question:

In my study I compare two kinds of surgery options. Group A has 9 patients and group B has 6 patients. When comparing the seperate complications there is no significant difference. But now I want to compare the total of complications between group A and group B.

Group A (9 pt): total 11 complications in 6 patients (3 patients had no complications
Group B (6 pt): total 2 complications, both in the same patient (5 patients had no complication)

Which test suits my question best?

Thanks

2. ## Re: Total complications in both groups

Are you saying you want to collapse all complication types to create a composite outcome. Say, any outcome (y/n; e.g., site infection, readmission, rejection, etc.)?

3. ## Re: Total complications in both groups

I want to compare the total amount of complications between group A (9 patients) en group B (6 patients) (11 vs 2 complications) and see if there is a significant difference.

4. ## Re: Total complications in both groups

Check out Fisher's exact test.

Side note, you will have limited generalizability of results if the intervention was not randomized.

5. ## Re: Total complications in both groups

Originally Posted by chabby
Which test suits my question best?
Hi Chabby,

Count data is typically best examined through a Poisson model. If there are any differences between patients regarding length of time during which a complication could be observed, this can also be handled via the model offset. I don't believe you have to worry about that in your case, though. So that should help simplify things. Alternatively, you could compare groups via a non-parametric test such as Kruskal-Wallis or Mann-Whitney and report median (1st, 3rd quartiles). A third alternative is to do a two-sample Student's t-test and report mean +/- standard deviation. These 3 ways are listed in the order that I recommend. If you aren't comfortable with the Poisson method, then I would say go with the non-parametric approach. However, as hlsmith indicates, if there are differences between groups, it can confound your results. A Poisson model could help adjust for differences.

6. ## Re: Total complications in both groups

I must not have read the fine details. Mostater is correct in proposing a Poisson model. That would be my first choice as well.

However the OP may be limited in their modeling and controlling for other covariates, given the very small sample size.

7. ## Re: Total complications in both groups

Thanks for all the help, but I'm still not finished asking.

One of my teachers recommends the following:
Every complication is one patient and then make a cross-tab.

With the next information:
Group A (9 pt): total 11 complications in 6 patients (3 patients had no complications
Group B (6 pt): total 2 complications, both in the same patient (5 patients had no complication)

You will get this cross-tab:

Group A Group B
Complication 11 2
No complication 3 5

He mentioned just to run a fisher's exact test then.

But I thought this would not be allowed.

8. ## Re: Total complications in both groups

If I were you, I would categorise patientsinto having 1 or more complications or no complications at all; then you should be able to do Fishers.

9. ## Re: Total complications in both groups

Originally Posted by chabby
He mentioned just to run a fisher's exact test then.

But I thought this would not be allowed.
When comparing frequencies between groups as you just described, Fisher's is perfectly allowed. This is different than comparing # of complications between groups. Now you are comparing # of patients having complications between groups. So use Fisher's for that analysis.

10. ## Re: Total complications in both groups

You will have to modify your previous numbers for using the Fisher's Test:

lllllllllllllllllllComplication(s) No Complication
Group A.......... 6.................3
Group B...........1................ 5

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