Endoscopic retrograde cholangiopancreatography (ERCP)-related complications should be promptly and properly managed in accordance with the type and severity of the complication and the comorbidity of the patient. Neurologic complications occur very rarely, but despite of the prompt management, the patient status can severely deteriorate and sometimes result in fatality. A female patient visited SAM Medical Center for abdominal pain and yellow skin. She has taken a current medication for essential hypertension since 10 years ago. Initial laboratory findings showed obstructive jaundice and abdominal computed tomography (CT) showed two common bile duct stones with moderate dilation of bile duct. Her vital sign with oxygen saturation was stable until the first attack of seizure 12 hours later after removal of stones through the ERCP. Emergent brain CT and magnetic resonance imaging revealed multiple cerebral infarctions of both hemispheres with right predominance of middle cerebral artery territory and no evidence of air emboli. She died four days later despite of intensive care including high oxygen therapy and intravenous broad spectrum antibiotics with antiplatelet drug. We report a rare, delayed occurrence of a fatal multiple cerebral infarctions 12 hours after ERCP.
Abdominal Pain ; Anti-Bacterial Agents ; Bile Ducts ; Brain ; Cerebral Infarction* ; Cholangiopancreatography, Endoscopic Retrograde* ; Common Bile Duct ; Comorbidity ; Female ; Humans ; Hypertension ; Critical Care ; Jaundice, Obstructive ; Magnetic Resonance Imaging ; Middle Cerebral Artery ; Oxygen ; Seizures ; Skin ; Vital Signs

Higenamine was widely used as traditional remedy for the treatment of rheumatoid arthritis. Nitric oxide (NO) may be a critical mediator in this inflammatory disease. Synovial tissue from humans with inflammatory arthritis expresses NOS2 (iNOS) mRNA and protein, and generates NO in vitro. We therefore, investigated the effect of higenamine on the induction of nitric oxide synthase (NOS) promoted by lipopolysaccharide (LPS). Prophylactic application of higenamine selectively prevented LPS-primed initiation of L-arginine-induced relaxation and restored phenylephrine(PE)-induced contraction in rat aorta. LPS-stimulated nitrite production in the incubation medium was reduced by higenamine. Furthermore, RT-PCR and Northern analysis indicated that higenamine reduced iNOS expression primed by LPS in rat aorta. These results suggest that higenamine prevents LPS-promoted induction of NOS in vascular smooth muscle.
Animals ; Aorta* ; Arthritis ; Arthritis, Rheumatoid ; Humans ; Muscle, Smooth, Vascular ; Nitric Oxide ; Nitric Oxide Synthase ; Rats* ; Relaxation ; RNA, Messenger*

OBJECTIVES: To develop a simple algorithm for prescreening of obstructive sleep apnea (OSA) on the basis of respiratorysounds recorded during polysomnography during all sleep stages between sleep onset and offset. METHODS: Patients who underwent attended, in-laboratory, full-night polysomnography were included. For all patients, audiorecordings were performed with an air-conduction microphone during polysomnography. Analyses included allsleep stages (i.e., N1, N2, N3, rapid eye movement, and waking). After noise reduction preprocessing, data were segmentedinto 5-s windows and sound features were extracted. Prediction models were established and validated with10-fold cross-validation by using simple logistic regression. Binary classifications were separately conducted for threedifferent threshold criteria at apnea hypopnea index (AHI) of 5, 15, or 30. Prediction model characteristics, includingaccuracy, sensitivity, specificity, positive predictive value (precision), negative predictive value, and area under thecurve (AUC) of the receiver operating characteristic were computed. RESULTS: A total of 116 subjects were included; their mean age, body mass index, and AHI were 50.4 years, 25.5 kg/m2, and23.0/hr, respectively. A total of 508 sound features were extracted from respiratory sounds recorded throughoutsleep. Accuracies of binary classifiers at AHIs of 5, 15, and 30 were 82.7%, 84.4%, and 85.3%, respectively. Predictionperformances for the classifiers at AHIs of 5, 15, and 30 were AUC, 0.83, 0.901, and 0.91; sensitivity, 87.5%,81.6%, and 60%; and specificity, 67.8%, 87.5%, and 94.1%. Respective precision values of the classifiers were89.5%, 87.5%, and 78.2% for AHIs of 5, 15, and 30. CONCLUSION: This study showed that our binary classifier predicted patients with AHI of ≥15 with sensitivity and specificityof >80% by using respiratory sounds during sleep. Since our prediction model included all sleep stage data, algorithmsbased on respiratory sounds may have a high value for prescreening OSA with mobile devices.
Apnea ; Area Under Curve ; Body Mass Index ; Classification ; Humans ; Logistic Models ; Machine Learning ; Noise ; Polysomnography ; Respiratory Sounds ; ROC Curve ; Sensitivity and Specificity ; Sleep Apnea, Obstructive ; Sleep Stages ; Sleep, REM