What Causes Anisocoria?
Discussion Anisocoria is a common physical finding caused by the mechanical imbalance of the iris dilator (sympathetic innervation causing dilation) and sphincter muscles (parasympathetic innervation causes miosis). Which pupil is abnormal is important to determine. “Anisocoria greater in the light signifies an abnormal large pupil, whereas anisocoria in the dark indicates an abnormal small pupil.” The pupillary size should be noted along with any changes with accommodation, extra ocular movements and lighting. The time it takes to revert to the baseline pupillary size can also be helpful. Any ptosis, lacrimation and pain should be noted. Evidence of papilledema should be looked for. Additionally, a thorough head and neck examination and neurological examination are important to look for additional diagnostic clues. While a generalist may not be able to interpret all of these signs and symptoms, gathering this information and discussion with an ophthalmologist and/or neurologist can be helpful. Physiologic anisocoria is common with approximately 15-30% of the normal population having this physical finding. “Physiologic anisocoria should be longstanding, neurologically isolated, less than 1 mm in size discrepancy, and stable in light and dark conditions.” Old photographs may be helpful and reassuring. Evaluation for anisocoria may include pharmacologic testing, and imaging of the head and/or neck and potentially other body areas. Learning Point The diff...
Conclusion: We estimate causal coupling between PNS and SNS through MVAR modeling of EDA and HRV time-series. Significance: Our results suggest promising future applicability to investigate more complex contexts such as affective and pathological scenarios.
Obstructive sleep apnea is a common sleep disorder with a high prevalence and often accompanied by significant snoring activity. To diagnose this condition, polysomnography is the standard method, where a neck microphone could be added to record tracheal sounds. These can then be used to study the characteristics of breathing, snoring or apnea. In addition cardiac sounds, also present in the acquired data, could be exploited to extract heart rate. The paper presents new algorithms for estimating heart rate from tracheal sounds, especially in very loud snoring environment. The advantage is that it is possible to reduce the ...
Conclusion: The differential characteristics of EDA contributed highly to the accuracy of pain stimulation level detection of the classifiers. The external validity dataset was not considered in the study. Significance: Our approach has the potential for accurate pain quantification using EDA.
Conditions: Postoperative Pain; Postoperative Nausea Intervention: Other: Patient interview Sponsor: Oslo University Hospital Recruiting
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Condition: Anesthesia Interventions: Drug: Duloxetine 60mg; Drug: Placebo Sponsor: Ain Shams University Completed
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Conditions: Pain; Mental Disorders Intervention: Behavioral: Real-time videoconference-based Exercise program Sponsors: Ander Espin; Caser Residencial Betharram; Fundación Aspaldiko Recruiting
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