Objective: To extract pulmonary and cardiovascular metrics from chest CTs of patients with coronavirus disease 2019 (COVID-19) using a fully automated deep learning-based approach and assess their potential to predict patient management. Materials and Methods: All initial chest CTs of patients who tested positive for severe acute respiratory syndrome coronavirus 2 at our emergency department between March 25 and April 25, 2020, were identified (n = 120). Three patient management groups were defined: group 1 (outpatient), group 2 (general ward), and group 3 (intensive care unit [ICU]). Multiple pulmonary and cardiovascular metrics were extracted from the chest CT images using deep learning. Additionally, six laboratory findings indicating inflammation and cellular damage were considered. Differences in CT metrics, laboratory findings, and demographics between the patient management groups were assessed. The potential of these parameters to predict patients’ needs for intensive care (yeso) was analyzed using logistic regression and receiver operating characteristic curves. Internal and external validity were assessed using 109 independent chest CT scans. Results: While demographic parameters alone (sex and age) were not sufficient to predict ICU management status, both CT metrics alone (including both pulmonary and cardiovascular metrics; area under the curve [AUC] = 0.88; 95% confidence interval [CI] = 0.79–0.97) and laboratory findings alone (C-reactive protein, lactate dehydrogenase, white blood cell count, and albumin; AUC = 0.86; 95% CI = 0.77–0.94) were good classifiers. Excellent performance was achieved by a combination of demographic parameters, CT metrics, and laboratory findings (AUC = 0.91; 95% CI = 0.85–0.98). Application of a model that combined both pulmonary CT metrics and demographic parameters on a dataset from another hospital indicated its external validity (AUC = 0.77; 95% CI = 0.66–0.88). Conclusion Chest CT of patients with COVID-19 contains valuable information that can be accessed using automated image analysis. These metrics are useful for the prediction of patient management.

Objective: To extract pulmonary and cardiovascular metrics from chest CTs of patients with coronavirus disease 2019 (COVID-19) using a fully automated deep learning-based approach and assess their potential to predict patient management. Materials and Methods: All initial chest CTs of patients who tested positive for severe acute respiratory syndrome coronavirus 2 at our emergency department between March 25 and April 25, 2020, were identified (n = 120). Three patient management groups were defined: group 1 (outpatient), group 2 (general ward), and group 3 (intensive care unit [ICU]). Multiple pulmonary and cardiovascular metrics were extracted from the chest CT images using deep learning. Additionally, six laboratory findings indicating inflammation and cellular damage were considered. Differences in CT metrics, laboratory findings, and demographics between the patient management groups were assessed. The potential of these parameters to predict patients’ needs for intensive care (yeso) was analyzed using logistic regression and receiver operating characteristic curves. Internal and external validity were assessed using 109 independent chest CT scans. Results: While demographic parameters alone (sex and age) were not sufficient to predict ICU management status, both CT metrics alone (including both pulmonary and cardiovascular metrics; area under the curve [AUC] = 0.88; 95% confidence interval [CI] = 0.79–0.97) and laboratory findings alone (C-reactive protein, lactate dehydrogenase, white blood cell count, and albumin; AUC = 0.86; 95% CI = 0.77–0.94) were good classifiers. Excellent performance was achieved by a combination of demographic parameters, CT metrics, and laboratory findings (AUC = 0.91; 95% CI = 0.85–0.98). Application of a model that combined both pulmonary CT metrics and demographic parameters on a dataset from another hospital indicated its external validity (AUC = 0.77; 95% CI = 0.66–0.88). Conclusion Chest CT of patients with COVID-19 contains valuable information that can be accessed using automated image analysis. These metrics are useful for the prediction of patient management.

PURPOSE: Premature adrenarche (PA) often leads to polycystic ovary syndrome (PCOS). Higher anti-mullerian hormone (AMH) levels are reported in PCOS. We studied the androgen profile and AMH profiles in Hispanic girls with PA (aged 5–8 years) and age and body mass index (BMI) matched controls. METHODS: Retrospective review of electronic medical records of girls who met the inclusion criteria for premature adrenarche were done. RESULTS: PA girls (n=76) were matched to control girls (n=12) for age (mean±standard deviation) (6.7±1 years vs. 6.2±1.3 years) and BMI (20±10 kg/m2 vs. 17.8±2.7 kg/m2). Dehydroepiandrostenedione sulfate (63.3±51.3 μg/dL vs. 29.8±17.3 μg/dL, P < 0.001) and testosterone levels (11.4±4.8 ng/dL vs. 8.2±2.9 ng/dL, P=0.001) were significantly higher in the PA group than controls. AMH values ( < 14 years: reference range, 0.49–3.15 ng/mL) were 3.2±2.2 ng/mL vs. 4.6± 3.2 ng/mL respectively in the PA and control groups and were not different (P=0.4). AMH did not show a correlation with bone age (P=0.1), and testosterone (P=0.9) in the PA group. 17-hydroxyprogesterone levels (17-OHP ng/dL) were 39.5±30.5 ng/dL vs. 36.8±19.8 ng/dL in PA versus control girls. The concentration of 17-OHP was not statistically different between the control and PA groups. CONCLUSIONS: Higher AMH was not observed in PA girls and no correlation with BA and androgen levels was observed.
17-alpha-Hydroxyprogesterone ; Adrenarche* ; Anti-Mullerian Hormone* ; Body Mass Index ; Child* ; Cohort Studies* ; Electronic Health Records ; Female* ; Hispanic Americans* ; Humans ; Polycystic Ovary Syndrome ; Reference Values ; Retrospective Studies ; Testosterone

No abstract available.
Chondroma* ; Hand*

Although breast implants have been in clinical use for almost 6 decades and have undergone considerable development during this time, implant rupture is still a dreaded long-term complication. Some obvious external factors, such as trauma, can lead to implant rupture, but many studies have reported a high rate of “spontaneous” implant rupture. Herein, we present two cases with the aim of raising awareness of a new possible cause of “spontaneous” implant rupture: mechanical irritation by bony protrusions.
Breast Implants* ; Breast* ; Exostoses ; Female ; Mammaplasty ; Rupture* ; Silicone Elastomers

BACKGROUND AND PURPOSE: Standard operating procedures (SOP) incorporating plasma levels of rivaroxaban might be helpful in selecting patients with acute ischemic stroke taking rivaroxaban suitable for IVthrombolysis (IVT) or endovascular treatment (EVT). METHODS: This was a single-center explorative analysis using data from the Novel-Oral-Anticoagulants-in-Stroke-Patients-registry (clinicaltrials.gov:NCT02353585) including acute stroke patients taking rivaroxaban (September 2012 to November 2016). The SOP included recommendation, consideration, and avoidance of IVT if rivaroxaban plasma levels were < 20 ng/mL, 20‒100 ng/mL, and >100 ng/mL, respectively, measured with a calibrated anti-factor Xa assay. Patients with intracranial artery occlusion were recommended IVT+EVT or EVT alone if plasma levels were ≤100 ng/mL or >100 ng/mL, respectively. We evaluated the frequency of IVT/EVT, door-to-needle-time (DNT), and symptomatic intracranial or major extracranial hemorrhage. RESULTS: Among 114 acute stroke patients taking rivaroxaban, 68 were otherwise eligible for IVT/EVT of whom 63 had plasma levels measured (median age 81 years, median baseline National Institutes of Health Stroke Scale 6). Median rivaroxaban plasma level was 96 ng/mL (inter quartile range [IQR] 18‒259 ng/mL) and time since last intake 11 hours (IQR 4.5‒18.5 hours). Twenty-two patients (35%) received IVT/EVT (IVT n=15, IVT+EVT n=3, EVT n=4) based on SOP. Median DNT was 37 (IQR 30‒60) minutes. None of the 31 patients with plasma levels >100 ng/mL received IVT. Among 14 patients with plasma levels ≤100 ng/mL, the main reason to withhold IVT was minor stroke (n=10). No symptomatic intracranial or major extracranial bleeding occurred after treatment. CONCLUSIONS: Determination of rivaroxaban plasma levels enabled IVT or EVT in one-third of patients taking rivaroxaban who would otherwise be ineligible for acute treatment. The absence of major bleeding in our pilot series justifies future studies of this approach.
Arteries ; Hemorrhage ; Humans ; National Institutes of Health (U.S.) ; Plasma* ; Rivaroxaban* ; Stroke*

Background: A urethral obstruction (UO) is an emergency commonly observed in male cats, which can result in significant clinical and laboratory alterations, leading to complications and death. Objectives: This study aimed to correlate symmetric dimethylarginine (SDMA) with the urea, creatinine, potassium, and bicarbonate levels in cats with UO. In addition, the correlation between clinical score and time of obstruction was evaluated. Methods: Thirty male cats were selected and allocated into a control group (CG, n = 13) and an obstruction group (OG, n = 17). The laboratory analyses were conducted before treatment (M0) and at different times after treatment (12 h [M12], 24 h [M24], and 48 h [M48]).Correlations were established between SDMA and creatinine, urea, bicarbonate, potassium, time of obstruction, and the clinical score. Results: A strong correlation (r > 0.6) was observed between SDMA and creatinine, urea, and potassium in the OG. Furthermore, there was substantial agreement (kappa value) between SDMA and creatinine at M24. A higher clinical score was associated with a longer time of obstruction. In the OG, at M48, the SDMA and creatinine levels were 50% and 41.2% higher, respectively. Conclusions A correlation was observed between SDMA and creatinine in obstructed cats, and significant agreement between these values was observed 24 h after the unblocking treatment. A correlation among SDMA, urea, and potassium was observed. Approximately 9% more cats continued to have elevated SDMA levels after 48 h of treatment compared to creatinine. This suggests a slightly lower sensitivity of the latter biomarker but does not exclude the possibility of congruent and normalized values after a longer evaluation period.

Objective: During the COVID-19 pandemic, face mask wearing was mandated in Port Moresby in July 2020, but compliance was observed to be low. We aimed to determine the frequency of face mask wearing by the general public in Papua New Guinea under the mask mandate. Methods: To estimate compliance with the mandate, we analysed photographs of people gathering in Port Moresby published between 29 September and 29 October 2020. Photo-epidemiology was performed on the 40 photographs that met pre-defined selection criteria for inclusion in our study. Results: Among the total of 445 fully visible photographed faces, 53 (11.9%) were observed wearing a face mask over mouth and nose. Complete non-compliance (no faces wearing masks) was observed in 19 (4.3%) photographs. Physical distancing was observed in 10% of the 40 photographs. Mask compliance in indoor settings (16.4%) was higher than that observed in outdoor settings (9.8%), and this difference was statistically significant (P <0.05). Mask compliance was observed in 8.9% of large-sized gatherings (>30 people), 12.7% of medium-sized gatherings (11–30 people) and 25.0% of small-sized gatherings (4–10 people; photographs with <4 people were excluded from analysis). Discussion: We found very low population compliance with face mask mandates in Papua New Guinea during the pre-vaccine pandemic period. Individuals without face coverings and non-compliant with physical distancing guidelines are considered to be in a high-risk category for COVID-19 transmission particularly in medium- and large-sized gatherings. A new strategy to enforce public health mandates is required and should be clearly promoted to the public.