Hypothermia is defined as a significant drop in core body temperature below 35°C (95°F). It is traditionally staged as mild, moderate, severe, and profound at temperatures of 35°C to 32°C (95°F to 89.6°F), 32°C to 28°C (89.6°F to 82.4°F), <28°C (<82.4°F), and <24°C (75.2°F), respectively. It can also be classified into the same stages by clinical presentations. We present a patient that fits into two different stages based on core body temperature and clinical presentation.  A 58-year-old homeless male with a history of seizures and alcohol use presented via emergency medical services after spending the night outside and uncovered with a core body temperature of 25.1°C (77.1°F) via a urinary bladder thermometer, meeting criteria for severe, near profound, hypothermia. However, he was alert and communicating, shivering, with tachycardia, tachypnea, normal oxygen saturation, and elevated blood pressure, suggestive of mild hypothermia clinically. Passive and active external and internal rewarming were utilized to treat, with the removal of wet clothing, forced air patient warming system, warm blankets, and warm lactated ringers given intravenously. He was soon transferred to the intensive care unit and first returned to normothermic levels after approximately 10 hours from presentation. An electrocardiogram was obtained after resolution of shivering and revealed atrial fibrillation without Osborn waves. He remained in the hospital for the following week to treat his atrial fibrillation, hypothermia-induced rhabdomyolysis, and alcohol withdrawal. He was discharged without neurologic deficits and medically stable with appropriate resources.  This case demonstrates a unique presentation of severe hypothermia. To our knowledge, there has not been a reported case of severe hypothermia that does not involve severe central nervous system depression, severe slowing of vitals, and/or comatose status. These clinical symptoms normally begin during moderate hypothermic levels near 32°C (89.6°F), yet our patient presented without any central nervous system depression and with accelerated vitals that are more consistent with mild hypothermia yet had a core temperature of 25.1°C (77.1°F). Treatment was dictated by his core body temperature rather than clinical presentation. Because of this incongruence between symptoms and true severity of disease in hypothermia, we recommend diagnosis and treatment of hypothermia always be confirmed and based on core body temperature via a low-reading thermometer instead of clinical presentation alone.

Individuals with chronic alcohol use can be asymptomatic for a prolonged period of time and then exhibit signs of advanced heart and liver diseases with an abrupt onset. Herein, we present a case of a 60-year-old male with severe alcohol use disorder who presented with newly diagnosed atrial fibrillation (AF) with rapid ventricular response (RVR), dilated cardiomyopathy (DCM), and alcohol-associated cirrhosis following an episode of binge drinking.

OBJECTIVE: We have developed a peak detection algorithm for accurate determination of heart rate, using photoplethysmographic (PPG) signals from a smartwatch, even in the presence of various cardiac rhythms, including normal sinus rhythm (NSR), premature atrial contraction (PAC), premature ventricle contraction (PVC), and atrial fibrillation (AF). Given the clinical need for accurate heart rate estimation in patients with AF, we developed a novel approach that reduces heart rate estimation errors when compared to peak detection algorithms designed for NSR.
METHODS: Our peak detection method is composed of a sequential series of algorithms that are combined to discriminate the various arrhythmias described above. Moreover, a novel Poincaré plot scheme is used to discriminate between basal heart rate AF and rapid ventricular response (RVR) AF, and to differentiate PAC/PVC from NSR and AF. Training of the algorithm was performed only with Samsung Simband smartwatch data, whereas independent testing data which had more samples than did the training data were obtained from Samsung\'s Gear S3 and Galaxy Watch 3.
RESULTS: The new PPG peak detection algorithm provides significantly lower average heart rate and interbeat interval beat-to-beat estimation errors-30% and 66% lower-and mean heart rate and mean interbeat interval estimation errors-60% and 77% lower-when compared to the best of the seven other traditional peak detection algorithms that are known to be accurate for NSR. Our new PPG peak detection algorithm was the overall best performers for other arrhythmias.
CONCLUSIONS: The proposed method for PPG peak detection automatically detects and discriminates between various arrhythmias among different waveforms of PPG data, delivers significantly lower heart rate estimation errors for participants with AF, and reduces the number of false negative peaks.
CONCLUSIONS: By enabling accurate determination of heart rate despite the presence of AF with rapid ventricular response or PAC/PVCs, we enable clinicians to make more accurate recommendations for heart rate control from PPG data.