Primary diagnosis this week Atrial Fibriluation

After completing this week’s Practicum Experience, reflect on a patient with a known history of a cardiovascular disorder such as a blood clot or arrhythmia. Describe the patient’s personal and medical history, drug therapy and treatments, and follow-up care.

Primary diagnosis this week Atrial Fibriluation

Please review an example of what I need.

Pattern Recognition

As advanced practice nurses (APN’s) become proficient and knowledgeable in the disease process, it will become second nature to utilize pattern recognition in diagnosing patients and providing quality patient care.  Pattern recognition is used to diagnose certain conditions that have very unique symptoms (Strzoda, 2010).  The purpose of this paper is to reflect on the importance of pattern recognition in regards to patient diagnosis and explain how the use of pattern recognition may be helpful or potentially harmful in assisting the APN in correctly diagnosing patients.

Pattern Recognition in Healthcare

            Many times in the healthcare field pattern recognition is used to diagnose and treat patients with a number of different conditions. Utilizing this style of diagnosis is very efficient and time saving in a fast paced healthcare setting. There are a number of conditions that present with certain symptoms in which the APN may diagnose a patient before walking into the exam room.

 One diagnosis that has very distinct symptoms is a urinary tract infection (UTI).  Symptoms that a patient who has a UTI may complain of include pain or burning upon urination, urinary urgency and frequency, dark-colored urine with a foul odor, suprapubic and low back pain, and costovertebral tenderness.  Utilizing pattern recognition with symptoms such as these will allow the APN to make the likely diagnosis of UTI.  Another method of diagnosing UTI utilizing pattern recognition and without the above symptoms is reviewing a urinalysis.  At times there are patients who present to the clinic for other reasons such as a routine medication follow-up or lab work.  Lab results from a complete blood count (CBC) may show elevated white blood cells (WBC’s) and urinalysis results may reveal elevated leukocytes, protein, and blood in the urine.  While the patient is asymptomatic, he/she has very indicative lab results that suggest a UTI. 

Pattern Recognition: Helpful or Harmful

            Pattern recognition is a helpful tool that allows APN’s to recognize that certain signs and/or symptoms are directly associated with certain diseases or conditions.  As mentioned earlier this method is very efficient and time saving.  It allows APN’s who practice in busy settings to diagnose and even write prescriptions for patients based on their symptoms before walking in to the exam room. 

            While there are many positives in regards to pattern recognition, there are also negatives.  A major problem with utilizing this method in the healthcare setting is misdiagnosing.  At times APN’s may prematurely diagnose a patient without considering other options or conditions that may be of concern for the patient (“Basic Strategies for Diagnosis,” 2011).  When diagnosing a patient with a UTI based on their presenting symptoms it is important to follow-up with the patient to assure the symptoms have subsided with the prescribed treatment and there is not a possibility of a urethral issue.  Other diagnoses that may be misinterpreted with pattern recognition are as follows: Bell’s palsy being mistaken for a stroke or vice versa and Parkinson’s disease may be mistaken for essential hand tremors. 

Conclusion

Pattern recognition is an efficient way to provide health care to patients in a fast paced setting.  It can be conveniently utilized to diagnose and treat patients before walking into the exam room.  While it is helpful in many ways, pattern recognition must be used sparingly and follow-up is required in order to rule out any underlying conditions that may be a result of the presenting symptoms.  Proper follow-up will confirm that the APN made the correct diagnosis and assure the symptoms have been effectively treated with prescribed medications.

References

Basic strategies for diagnosis. (2011). Retrieved from http://ebp.uga.edu/courses/Chapter%201%20-%20Diagnostic%20process/4%20-%20Diagnostic%20strategies.html

Strzoda, K. (2010). Evaluation of Macrocyosis. American Family Physician, 79(3), 203-214.

ANSWER

Journal Entry 4: Atrial Fibrillation

For the heart to have an efficient blood pumping, the myocardium must be electrically stimulated as well as respond in a rhythmic pattern (activation and deactivation) called normal sinus rhythm. However, there are a number of conditions likely to affect normal cardiac rhythm (Akbilgic, Howe & Davis, 2016). One of such conditions that cause an irregular pattern of myocardium stimulation and signal propagation is called atrial fibrillation (AF or AFib). Atrial fibrillation is one of the most prevalent abnormal heart rhythm conditions with severe consequences. The condition increases the risk of blood clots, heart failure, stroke, and other heart-related complications. Statistics indicate that more than 3 million Americans are living with atrial fibrillation. Pattern recognition is used as a differential diagnosis of sinus rhythm and atrial fibrillation. This essay seeks to explain the significance of pattern recognition in relation to the accurate diagnosis of patients in addition to explaining how pattern recognition is helpful in assisting APNs in properly diagnosing patients.

Pattern Recognition in Healthcare

Different zero-crossing methods are used to differentiate between atrial fibrillation and sinus rhythm of different patients. These techniques include fast Fourier transform (FFT) analysis, sine-wave crossings, threshold crossings, and threshold crossings of the derivative of the signal (Batista, 2014). Past study indicates that the sine-wave crossing approach is more suitable because there is no need to differentiate or normalize the signal. In addition, the algorithm is simple to implement and in real time. The differentiation helps APNs to correctly diagnose and treat the patient. Pattern recognition is a helpful practice that guides APN’s to understand various signs and symptoms that directly relate to heart complications (Abdul-Kadir, Safri & Othman, 2016). 

Conclusion

Atrial fibrillation is a severe condition that causes irregular heartbeat, hence increasing the risk of heart disease, stroke, and heart failure. Major signs include weakness, dizziness, and fatigue. Pattern recognition plays a fundamental role in helping APNs to make the correct diagnosis, which contributes to therapy success. In addition, pattern recognition helps APNs to determine the correct follow-up procedure based on the degree and severity of the symptoms. In addition, pattern recognition promotes accuracy in the diagnosis of AFib hence helping …