diagnostic checklist
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Author(s):  
Nithya Venkataramani ◽  
Ravi Sachidananda ◽  
Rajesh Karalumangala Nagarajaiah

<p class="abstract"><strong>Background:</strong> Vertigo is a complex symptom which can be present in multiple conditions, some of which are life threatening. Diagnosing a patient with vertigo could sometimes be challenging and there is a need for a comprehensive, yet easily reproducible diagnostic model with emphasis on the red flag signs. A simple way to achieve this is a checklist. The aim of the study was to propose a diagnostic checklist for patients presenting with vertigo to an ENT clinic to aid diagnosis and prevent diagnostic errors.</p><p class="abstract"><strong>Methods:</strong> A diagnostic checklist was used in all patients who presented with the symptom of vertigo, necessary tests were conducted and referrals were done when required.  </p><p class="abstract"><strong>Results:</strong> Out of eighty-five patients who presented with symptom of dizziness to ENT clinic, all patients received a definitive diagnosis treatment plan with the help of checklist.</p><p class="abstract"><strong>Conclusions:</strong> Checklist is an effective way to ensure elaborate assessment of the patient with emphasis on the red flag signs. It is a very important tool to arrive at diagnosis and formulate treatment plan.</p>


2021 ◽  
Vol 86 ◽  
pp. 1-14
Author(s):  
Melissa A. Collier-Meek ◽  
Lisa M.H. Sanetti ◽  
Kaitlin Gould ◽  
Brittany A. Pereira

2020 ◽  
Vol 25 (1) ◽  
pp. 1-16
Author(s):  
Ansley C. Hodges ◽  
Jamie Villacorta ◽  
David A. Wilder ◽  
Hallie Ertel ◽  
Nga Luong

2020 ◽  
Vol 34 (4) ◽  
pp. 853-867
Author(s):  
Nazia Nawaz ◽  
Syeda Farhana Jahangir ◽  
Nighat Shaheen

The present study was designed to develop a Computer Software for computer based diagnosis of schizophrenia, mania, and patients having major depression on the basis of their nonverbal communicative patterns. The study was conducted into two phases. The first phase consisted of (a), recording videos of non verbal communicative patterns of patients in order to assign behavioural patterns to each on the basis of observations of recorded videos by a panel of three clinical psychologists named as Aware Group and (b), defining of those patterns (for each disorder) by practitioners called the Unaware Group as they were unknown to the behaviors posed by the patients recorded in the videos, in order to verify the assigned patterns by the Aware Group. The second phase comprised of developing the diagnostic software and its validation on the basis of obtained information. Results revealed that non-verbal behavioural patterns associated with each disorder are significant tools that can be used as differential diagnostic criteria by the clinicians. The findings concluded that nonverbal behavioural cues can reliably be used for diagnosing different mental disorders with an accuracy of 97%, 100%, and 97% for Schizophrenia, Major Depression, and Mania, respectively.


2020 ◽  
Vol 53 (2) ◽  
pp. 1170-1176 ◽  
Author(s):  
David A. Wilder ◽  
Daniel Cymbal ◽  
Jamie Villacorta

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