Depression and Complement factor abnormal
Summary:
Complement factor abnormal is reported only by a few people with Depression.
The study analyzes which people have Complement factor abnormal with Depression. It is created by eHealthMe based on 1 person who has Complement factor abnormal and Depression from the Food and Drug Administration (FDA), and is updated regularly.
What is Depression?
Depression is found to be associated with 3,168 drugs and 4,124 conditions by eHealthMe. Check the latest studies of Depression.
What is Complement factor abnormal?
Complement factor abnormal is found to be associated with 7 drugs and 28 conditions by eHealthMe. Check the latest studies of Complement factor abnormal.
1 person who has Depression and Complement Factor Abnormal is studied.

Gender of people who have Depression and experienced Complement Factor Abnormal *:
- female: 100 %
- male: 0.0 %
Age of people who have Depression and experienced Complement Factor Abnormal *:
- 0-1: 0.0 %
- 2-9: 0.0 %
- 10-19: 0.0 %
- 20-29: 100 %
- 30-39: 0.0 %
- 40-49: 0.0 %
- 50-59: 0.0 %
- 60+: 0.0 %
Common drugs taken by these people *:
- Lyrica: 1 person, 100.00%
- Cymbalta: 1 person, 100.00%
Common symptoms for these people *:
- Renal Disorder (kidney disease): 1 person, 100.00%
- Muscle Twitching: 1 person, 100.00%
- Lupus-Like Syndrome (a disease symptom matches with lupus an immune disease): 1 person, 100.00%
- Joint Pain: 1 person, 100.00%
- Bone Pain: 1 person, 100.00%
* Approximation only. Some reports may have incomplete information.
Do you take medications and have Complement factor abnormal?
- Check whether Complement factor abnormal is associated with a drug or a conditionRelated publications that referenced our studies
- Pang, T., & Gudi, A., "Chest pain following the use of fluvoxamine in depression", Proceedings of Singapore Healthcare, 2018 Jan .
- Pang, T., & Gudi, A., "Chest pain following the use of fluvoxamine in depression", Proceedings of Singapore Healthcare, 2018 Jan .
Related studies:
Treatments, associated drugs and conditions:
- Depression (652,136 reports)
- Complement factor abnormal (343 reports)
All the drugs that are associated with Complement factor abnormal:
- Complement factor abnormal (7 drugs)
All the conditions that are associated with Complement factor abnormal:
- Complement factor abnormal (28 conditions)
How the study uses the data?
How to use the study?
DO NOT STOP MEDICATIONS without first consulting your doctor. If there are any serious or long term adverse effects discovered in the study, discuss the study with your doctor to ensure that proper medication management will be in place if applicable.
The study is based on Complement factor abnormal and Depression, and their synonyms.
Who is eHealthMe?
With medical big data and proven AI/ML algorithms, eHealthMe provides a platform for everyone to run phase IV clinical trials. We study millions of patients and 5,000 more each day. Results of our real-world drug study have been referenced on 800+ peer-reviewed medical publications, including The Lancet, Mayo Clinic Proceedings, and Nature. Our analysis results are available to researchers, health care professionals, patients (testimonials), and software developers (open API).
WARNING, DISCLAIMER, USE FOR PUBLICATION
WARNING: Please DO NOT STOP MEDICATIONS without first consulting a physician since doing so could be hazardous to your health.
DISCLAIMER: All material available on eHealthMe.com is for informational purposes only, and is not a substitute for medical advice, diagnosis, or treatment provided by a qualified healthcare provider. All information is observation-only. Our phase IV clinical studies alone cannot establish cause-effect relationship. Different individuals may respond to medication in different ways. Every effort has been made to ensure that all information is accurate, up-to-date, and complete, but no guarantee is made to that effect. The use of the eHealthMe site and its content is at your own risk.
If you use this eHealthMe study on publication, please acknowledge it with a citation: study title, URL, accessed date.
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