Landrydenton6374

Pseudo-pulseless electrical activity (pseudo-PEA) is a lifeless form of profound cardiac shock characterized by measurable cardiac mechanical activity without clinically detectable pulses. Pseudo-PEA may constitute up to 40% of reported cases of cardiac arrest. Resuscitation from pseudo-PEA is often associated with hypotension refractory to catecholamine pressors. We hypothesized that this post-resuscitation state may be associated with hypocalcemic hypotension responsive to intravenous calcium.

Using pre-existing data from our hypoxic swine pseudo-PEA model, we measured blood pressure, hemodynamics, and electrolytes. Physiological data were analyzed on a heartbeat by heartbeat basis. The midpoint of the calcium response was defined using change of curvature feature detection. Hemodynamic parameters were shifted such that the value at the midpoint was equal to zero.

In 9 animals with refractory hypotension, we administered 37 boluses of intravenous calcium in the dosage range of 5-20 mg. Comparisons were made between the average values in the time period 40-37 s before the midpoint and 35-40 s after the midpoint. Of the 37 administered boluses, 34 manifested a change in the blood pressure, with mean aortic pressure, systolic and diastolic pressures all increasing post bolus administration.

Administration of intravenous calcium may be associated with a pressor-like response in refractory hypotension after resuscitation from pseudo-PEA. Relative ionized hypocalcemia may cause hypotension after resuscitation from pseudo-PEA. Therapy with intravenous calcium should be further investigated in this setting.

Administration of intravenous calcium may be associated with a pressor-like response in refractory hypotension after resuscitation from pseudo-PEA. Relative ionized hypocalcemia may cause hypotension after resuscitation from pseudo-PEA. SAR131675 order Therapy with intravenous calcium should be further investigated in this setting.

To investigate the different pathophysiologies of obstructive sleep apnea (OSA) phenotypes using cluster analysis. Differences between leptin/adiponectin levels in the resulting OSA phenotypes were also examined.

In total, 1057 OSA patients were selected, and a retrospective survey of clinical records, polysomnography results, and blood gas data was conducted. Patients were grouped into four clusters by their OSA severity, PaCO2, body mass index (BMI), and sleepiness. A k-means cluster analysis was performed, resulting in a division into four subpopulations. The Tukey or Games-Howell tests were used for intergroup comparisons.

Among the 20 clinical OSA items, four common factors (Epworth Sleepiness Scale [ESS], BMI, Apnea-Hypopnea Index [AHI], and PaCO2) were extracted by principal component analysis, and a cluster analysis was performed using the k-means method, resulting in four distinct phenotypes. The Clusters 1 (middle age, symptomatic severe OSA) and 4 (young, obese, symptomatic very severe OSA) eatment that cannot be determined by the AHI.

To evaluate the utility of choroidal thickness (CT) measurement by enhanced depth imaging optical coherence tomography (EDI-OCT) for central serous chorioretinopathy (CSC) diagnosis.

Cross-sectional comparative study of 62 consecutive patients 38 with acute CSC and 24 with macular subretinal fluid from differential diagnoses (DD). Subfoveolar choroidal thickness was measured using EDI 9-mm horizontal protocol. We evaluated sensitivity, specificity and intraclass correlation coefficient.

Mean subfoveolar CT was greater in CSC group than in DD group (465.45 ± 115.42μm vs. 347.54 ± 111.27μm, p < 0.001). The best threshold measure was 390μm in patients younger than 50years giving a sensitivity of 89.7% (CI 95% 73.6-100%) and a specificity of 75% (CI 95% 40.9-87.3%). For patients older than 50years best threshold measure was found at 400μm giving a sensitivity of 45.5% (CI 95% 21.3-72%) and a specificity of 80% (CI 95% 58.4-91.9%). Intraclass correlation coefficient for CT measurement was 0.87 (CI 95% 0.74-0.93).

CT measurement with EDI-OCT helps to differentiate CSC from other causes of macular subretinal fluid in patients younger than 50years.

CT measurement with EDI-OCT helps to differentiate CSC from other causes of macular subretinal fluid in patients younger than 50 years.

Serological markers can assist in accurate differentiation between Crohn's disease (CD) and ulcerative colitis (UC). One such marker is anti-glycoprotein 2 (anti-GP2) which was shown to be a specific marker for CD in adult patients. The aim of our study was to assess the utility of anti-GP2 and GP2 as biomarkers for pediatric CD, and determine whether they correlate with disease activity.

Serum samples were tested by ELISA for anti-GP2 isoform 4 IgG and IgA, and also for GP2. Results were correlated with demographic and clinical data.

The cohort consisted of 53 pediatric patients with CD, 42 with UC, and 53 controls. Levels of anti-GP2 were significantly increased in pediatric patients with CD in comparison with patients with UC, and control subjects, with high positive predictive value for both IgG and IgA (97.9% and 82.6%, respectively). While specificity of anti-GP2 IgG and IgA was very high (98.7% and 90.0%, respectively), sensitivity was low (42.0% and 35.5% for IgG and IgA, respectively). In CD, anti-GP2 correlated with disease activity, and decreased in treatment-naïve patients following successful induction therapy. A higher IgA anti-GP2 was also demonstrated in patients with ileo-colonic involvement, and was associated with a younger age. Finally, positive GP2 level was identified in only 1/211 serum samples.

A positive anti-GP2 level is highly associated with CD, while a negative result does not exclude CD. Additional studies are required to determine whether these markers can be used in pediatric patients with CD for risk stratification.

A positive anti-GP2 level is highly associated with CD, while a negative result does not exclude CD. Additional studies are required to determine whether these markers can be used in pediatric patients with CD for risk stratification.