Ulcer Bleeding in the United States: Epidemiology, Treatment Success, and Resource Utilization.

BACKGROUND AND GOALS: Peptic ulcer disease is the most frequent cause of upper gastrointestinal bleeding. We sought to establish the epidemiology and hemostasis success rate of the different treatment modalities in this setting. METHODS: Retrospective cohort study using the National Inpatient Sample. Non-elective adult admissions with a principal diagnosis of ulcer bleeding were included. The primary outcome was endoscopic, radiologic and surgical hemostasis success rate. Secondary outcomes were patients' demographics, in-hospital mortality and resource utilization. On subgroup analysis, gastric and duodenal ulcers were studied separately. Confounders were adjusted for using multivariate regression analysis. RESULTS: A total of 136,425 admissions (55% gastric and 45% duodenal ulcers) were included. The mean patient age was 67 years. The majority of patients were males, Caucasians, of lower income and high comorbidity burden. The endoscopic, radiological and surgical therapy and hemostasis success rates were 33.6, 1.4, 0.1, and 95.1%, 89.1 and 66.7%, respectively. The in-hospital mortality rate was 1.9% overall, but 2.4% after successful and 11.1% after failed endoscopic hemostasis, respectively. Duodenal ulcers were associated with lower adjusted odds of successful endoscopic hemostasis, but higher odds of early and multiple endoscopies, endoscopic therapy, overall and successful radiological therapy, in-hospital mortality, longer length of stay and higher total hospitalization charges and costs. CONCLUSIONS: The ulcer bleeding endoscopic hemostasis success rate is 95.1%. Rescue therapy is associated with lower hemostasis success and more than a ten-fold increase in mortality rate. Duodenal ulcers are associated with worse treatment outcomes and higher resource utilization compared with gastric ulcers.

Diagnosis at gut point: rapid identification of pneumoperitoneum via point-of-care ultrasound.

Undifferentiated abdominal pain is a common presentation often requiring immediate medical or surgical intervention. Providing an accurate diagnosis involves a detailed patient history and thorough physical exam. Point of care ultrasound is gaining acceptance as a rapid diagnostic tool that can be used to accurately detect life-threatening conditions while potentially avoiding unnecessary radiation exposure and facilitating rapid treatment. Detection of pneumoperitoneum with point-of-care ultrasound is a simple procedure that relies heavily on the experience of the investigating practitioner. Standard technique involves placing a high-frequency linear-array transducer in the right upper quadrant, where abdominal free air is most likely to accumulate. Detection of the 'gut point', which is the transition of abdominal wall sliding to lack thereof in a single image, is the pathognomonic finding of pneumoperitoneum. If visualization is difficult, moving the patient to the left lateral decubitus position or using the scissors technique can provide additional image views. This representative case report and review highlights the use of abdominal POCUS for the diagnosis of pneumoperitoneum. Ultrasound should continue to be explored by clinicians to narrow the differential diagnosis of acute abdominal pain.

Neural response to pictorial health warning labels can predict smoking behavioral change.

In order to improve our understanding of how pictorial health warning labels (HWLs) influence smoking behavior, we examined whether brain activity helps to explain smoking behavior above and beyond self-reported effectiveness of HWLs. We measured the neural response in the ventromedial prefrontal cortex (vmPFC) and the amygdala while adult smokers viewed HWLs. Two weeks later, participants' self-reported smoking behavior and biomarkers of smoking behavior were reassessed. We compared multiple models predicting change in self-reported smoking behavior (cigarettes per day [CPD]) and change in a biomarkers of smoke exposure (expired carbon monoxide [CO]). Brain activity in the vmPFC and amygdala not only predicted changes in CO, but also accounted for outcome variance above and beyond self-report data. Neural data were most useful in predicting behavioral change as quantified by the objective biomarker (CO). This pattern of activity was significantly modulated by individuals' intention to quit. The finding that both cognitive (vmPFC) and affective (amygdala) brain areas contributed to these models supports the idea that smokers respond to HWLs in a cognitive-affective manner. Based on our findings, researchers may wish to consider using neural data from both cognitive and affective networks when attempting to predict behavioral change in certain populations (e.g. cigarette smokers).