Using the Resected Kidney for Transplantation After Nephrectomy for Nutcracker Syndrome.

Nutcracker syndrome (NCS) is the clinical manifestation of unilateral renal venous hypertension. It develops secondary to the nutcracker phenomenon caused by compression of the left renal vein between the superior mesenteric artery and the aorta. We present the case of a 43-year-old female with a history of left flank pain, pelvic congestion, and hematuria secondary to NCS. The patient frequently required high-dose non-steroidal anti-inflammatory medications with minimal relief. She initiated a kidney donor evaluation after electing to undergo a nephrectomy for the possible long-term resolution of NCS symptoms. If diagnosed early, NCS does not generate pathology within the kidney. This finding allows an individual with medically refractory NCS to avoid the morbidity of a complex surgical procedure by instead donating their kidney. Attention to this treatment modality could provide individuals with NCS resolution of symptoms while providing someone with end-stage renal disease with a life-saving organ.

SurvMaximin: Robust Federated Approach to Transporting Survival Risk Prediction Models

ObjectiveFor multi-center heterogeneous Real-World Data (RWD) with time-to-event outcomes and high-dimensional features, we propose the SurvMaximin algorithm to estimate Cox model feature coefficients for a target population by borrowing summary information from a set of health care centers without sharing patient-level information. Materials and MethodsFor each of the centers from which we want to borrow information to improve the prediction performance for the target population, a penalized Cox model is fitted to estimate feature coefficients for the center. Using estimated feature coefficients and the covariance matrix of the target population, we then obtain a SurvMaximin estimated set of feature coefficients for the target population. The target population can be an entire cohort comprised of all centers, corresponding to federated learning, or can be a single center, corresponding to transfer learning. ResultsSimulation studies and a real-world international electronic health records application study, with 15 participating health care centers across three countries (France, Germany, and the U.S.), show that the proposed SurvMaximin algorithm achieves comparable or higher accuracy compared with the estimator using only the information of the target site and other existing methods. The SurvMaximin estimator is robust to variations in sample sizes and estimated feature coefficients between centers, which amounts to significantly improved estimates for target sites with fewer observations. ConclusionsThe SurvMaximin method is well suited for both federated and transfer learning in the high-dimensional survival analysis setting. SurvMaximin only requires a one-time summary information exchange from participating centers. Estimated regression vectors can be very heterogeneous. SurvMaximin provides robust Cox feature coefficient estimates without outcome information in the target population and is privacy-preserving.

International Analysis of Electronic Health Records of Children and Youth Hospitalized With COVID-19 Infection in 6 Countries.

Importance: Additional sources of pediatric epidemiological and clinical data are needed to efficiently study COVID-19 in children and youth and inform infection prevention and clinical treatment of pediatric patients. Objective: To describe international hospitalization trends and key epidemiological and clinical features of children and youth with COVID-19. Design, Setting, and Participants: This retrospective cohort study included pediatric patients hospitalized between February 2 and October 10, 2020. Patient-level electronic health record (EHR) data were collected across 27 hospitals in France, Germany, Spain, Singapore, the UK, and the US. Patients younger than 21 years who tested positive for COVID-19 and were hospitalized at an institution participating in the Consortium for Clinical Characterization of COVID-19 by EHR were included in the study. Main Outcomes and Measures: Patient characteristics, clinical features, and medication use. Results: There were 347 males (52%; 95% CI, 48.5-55.3) and 324 females (48%; 95% CI, 44.4-51.3) in this study's cohort. There was a bimodal age distribution, with the greatest proportion of patients in the 0- to 2-year (199 patients [30%]) and 12- to 17-year (170 patients [25%]) age range. Trends in hospitalizations for 671 children and youth found discrete surges with variable timing across 6 countries. Data from this cohort mirrored national-level pediatric hospitalization trends for most countries with available data, with peaks in hospitalizations during the initial spring surge occurring within 23 days in the national-level and 4CE data. A total of 27 364 laboratory values for 16 laboratory tests were analyzed, with mean values indicating elevations in markers of inflammation (C-reactive protein, 83 mg/L; 95% CI, 53-112 mg/L; ferritin, 417 ng/mL; 95% CI, 228-607 ng/mL; and procalcitonin, 1.45 ng/mL; 95% CI, 0.13-2.77 ng/mL). Abnormalities in coagulation were also evident (D-dimer, 0.78 ug/mL; 95% CI, 0.35-1.21 ug/mL; and fibrinogen, 477 mg/dL; 95% CI, 385-569 mg/dL). Cardiac troponin, when checked (n = 59), was elevated (0.032 ng/mL; 95% CI, 0.000-0.080 ng/mL). Common complications included cardiac arrhythmias (15.0%; 95% CI, 8.1%-21.7%), viral pneumonia (13.3%; 95% CI, 6.5%-20.1%), and respiratory failure (10.5%; 95% CI, 5.8%-15.3%). Few children were treated with COVID-19-directed medications. Conclusions and Relevance: This study of EHRs of children and youth hospitalized for COVID-19 in 6 countries demonstrated variability in hospitalization trends across countries and identified common complications and laboratory abnormalities in children and youth with COVID-19 infection. Large-scale informatics-based approaches to integrate and analyze data across health care systems complement methods of disease surveillance and advance understanding of epidemiological and clinical features associated with COVID-19 in children and youth.

Predicting the Evolution of COVID-19 Mortality Risk: a Recurrent Neural Network Approach

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSThe propagation of COVID-19 in Spain prompted the declaration of the state of alarm on March 14, 2020. On 2 December 2020, the infection had been confirmed in 1,665,775 patients and caused 45,784 deaths. This unprecedented health crisis challenged the ingenuity of all professionals involved. Decision support systems in clinical care and health services management were identified as crucial in the fight against the pandemic. MethodsThis study applies Deep Learning techniques for mortality prediction of COVID-19 patients. Two datasets with clinical information (medication, laboratory tests, vital signs etc.) were used. They are comprised of 2,307 and 3,870 COVID-19 infected patients admitted to two Spanish hospital chains. Firstly, we built a sequence of temporal events gathering all the clinical information for each patient. Next, we used the temporal sequences to train a Recurrent Neural Network (RNN) model with an attention mechanism exploring interpretability. We conducted extensive experiments and trained the RNNs in different settings, performing hyperparameter search and cross-validation. We ensembled resulting RNNs to reduce variability and enhance sensitivity. ResultsWe assessed the performance of our models using global metrics, by averaging the performance across all the days in the sequences. We also measured day-by-day metrics starting from the day of hospital admission and the outcome day and evaluated the daily predictions. Regarding sensitivity, when compared to more traditional models, our best two RNN ensemble models outperform a Support Vector Classifier in 6 and 16 percentage points, and Random Forest in 23 and 18 points. For the day-by-day predictions from the outcome date, the models also achieved better results than baselines showing its ability towards early predictions. ConclusionsWe have shown the feasibility of our approach to predict the clinical outcome of patients infected with SARS-CoV-2. The result is a time series model that can support decision-making in healthcare systems and aims at interpretability. The system is robust enough to deal with real world data and it is able to overcome the problems derived from the sparsity and heterogeneity of the data. In addition, the approach was validated using two datasets showing substantial differences. This not only validates the robustness of the proposal but also meets the requirements of a real scenario where the interoperability between hospitals datasets is difficult to achieve.

International Comparisons of Harmonized Laboratory Value Trajectories to Predict Severe COVID-19: Leveraging the 4CE Collaborative Across 342 Hospitals and 6 Countries: A Retrospective Cohort Study

ObjectivesTo perform an international comparison of the trajectory of laboratory values among hospitalized patients with COVID-19 who develop severe disease and identify optimal timing of laboratory value collection to predict severity across hospitals and regions. DesignRetrospective cohort study. SettingThe Consortium for Clinical Characterization of COVID-19 by EHR (4CE), an international multi-site data-sharing collaborative of 342 hospitals in the US and in Europe. ParticipantsPatients hospitalized with COVID-19, admitted before or after PCR-confirmed result for SARS-CoV-2. Primary and secondary outcome measuresPatients were categorized as "ever-severe" or "never-severe" using the validated 4CE severity criteria. Eighteen laboratory tests associated with poor COVID-19-related outcomes were evaluated for predictive accuracy by area under the curve (AUC), compared between the severity categories. Subgroup analysis was performed to validate a subset of laboratory values as predictive of severity against a published algorithm. A subset of laboratory values (CRP, albumin, LDH, neutrophil count, D-dimer, and procalcitonin) was compared between North American and European sites for severity prediction. ResultsOf 36,447 patients with COVID-19, 19,953 (43.7%) were categorized as ever-severe. Most patients (78.7%) were 50 years of age or older and male (60.5%). Longitudinal trajectories of CRP, albumin, LDH, neutrophil count, D-dimer, and procalcitonin showed association with disease severity. Significant differences of laboratory values at admission were found between the two groups. With the exception of D-dimer, predictive discrimination of laboratory values did not improve after admission. Sub-group analysis using age, D-dimer, CRP, and lymphocyte count as predictive of severity at admission showed similar discrimination to a published algorithm (AUC=0.88 and 0.91, respectively). Both models deteriorated in predictive accuracy as the disease progressed. On average, no difference in severity prediction was found between North American and European sites. ConclusionsLaboratory test values at admission can be used to predict severity in patients with COVID-19. Prediction models show consistency across international sites highlighting the potential generalizability of these models.

Pravastatin Transdermal Patches: Effect of The Formulation and Two Different Lengths of Microneedles on In-vitro Percutaneous Absorption Studies.

Transdermal patches loaded with pravastatin was previously characterized in another published study by Serrano-Castañeda et al; 2015. These transdermal patches (TP) were generated by the plate casting technique, the in-vitro percutaneous absorption studies of TP were evaluated for three different formulations with different quantities of Pluronic F-127 (PF-127): i) without PF-127 (TP W), ii) 1% of PF-127 (TP 1%), and iii) 3% of PF-127 (TP 3%) using solid microneedles as a penetration enhancer with two different lengths: i) 0.25 mm and ii) 2.25 mm and iii) in-vitro permeation studies by passive diffusion. The fluxes (F), time lag (tLag) and permeability constants (Kp) for each formulation were: TP W (F:38.5µg/cm2*h, tLag:18.97h and Kp:5.9x10-3 cm/h), TP W with microneedles of 0.25 mm (F:103.3 µg/cm2*h, tLag: 20.76 h and Kp: 0.0158 cm/h), TP W and microneedles of 2.25 mm (F:105.2µg/cm2*h, tLag: 21.16 h and Kp: 0.0159cm/h), TP 1% (F:90 µg/cm2*h, tLag: 19.48 h and Kp: 0.0137 cm/h), TP 1% with microneedles of 0.25 mm (F:111.4µg/cm2*h, tLag:19.11h and Kp:0.017cm/h), and TP 1% with microneedles of 2.25 mm (F:115.2µg/cm2*h, tLag:16.73h and Kp:0.017cm/h), TP 3% (F:40.9µg/cm2*h, tLag:20.45h and Kp:0.0062 cm/h), TP 3% with microneedles of 0.25 mm (F:67.1 µg/cm2*h, tLag: 21.79h and Kp:0.0102cm/h) and TP 3% with microneedles of 2.25 (F:70.5 µg/cm2*h, tLag:20.44h and Kp:0.0107cm/h). Results show that the formulation of TP affects the pravastatina flux and Kp parameters, however the length of microneedles only has important effect on tLag.

Design and Evaluation of Losartan Transdermal Patch by Using Solid Microneedles as A Physical Permeation Enhancer.

The development of a losartan potassium patch for the treatment of hypertension showed that a combination of hydrophobic and hydrophilic polymers, using as a plasticizer citroflex and succinic acid as a cohesion promoter result in homogeneous films. The effect of the Eudragit® E100, PVP K30, citroflex and succinic acid in the bioadhesion, postwetting bioadhesion, resistance to rupture and drug release, was studied. The succinic acid in synergy with the plasticizer (citroflex) modifies the characteristics of the polymeric matrix of Eudragit® E100, increasing the release and the resistance to rupture of transdermal patches. For the case of the hydrophilic polymer PVP K30, it increases the bioadhesion and drug release by creating porous matrices. From a previous experimental design, the optimal formulation was acquired, and this formulation was physicochemically characterized. A transdermal patch was obtained with the next dimensions and characteristics: 28.46 ± 0.055 mm in diameter and 0.430 ± 0.008 mm in thickness, a bioadhesion of 1063.05 ± 60.33 gf, postwetting bioadhesion 995.9 ± 72.53 gf significantly decreased. The breaking strength was of 1301.5 ± 96.5 gf, surface pH patch of 6, constriction of 0% at 7 days, and 94.0366 ± 1.8617% of losartan content. The 93% of the drug is released at 4 h (n = 6), adjusting to the kinetic model of Higuchi and Peppas. In the in-vitro penetration studies by passive diffusion, a flow (J) of 42.2 µg/cm2h, a permeability constant (kp) of 2.1793E-03 cm/h and a latency time (tL) of 17.20 h and with the use of microneedles a flow (J) of 61.7 µg/cm2h, a permeability constant (kp) of 3.1869E-03 cm/h and a latency time (tL) of 17.74 h were obtained.

Serum Concentrations of Selenium and Copper in Patients Diagnosed with Pancreatic Cancer / Journal of the Korean Cancer Association, 대한암학회지

PURPOSE: Understanding of the etiology and pathogenesis of pancreatic cancer (PaCa) is still insufficient. This study evaluated the associations between concentrations of selenium (Se) and copper (Cu) in the serum of PaCa patients. MATERIALS AND METHODS: The study included 100 PaCa patients and 100 control subjects from the same geographical region in Poland. To determine the average concentration of Se, Cu, and ratio Cu:Se in the Polish population, assay for Se and Cu was performed in 480 healthy individuals. Serum levels of Se and Cu were measured using inductively coupled plasma mass spectrometry. RESULTS: In the control group, the average Se level was 76 µg/L and Cu 1,098 µg/L. The average Se level among PaCa patients was 60 µg/L and the mean Cu level was 1,432 µg/L. The threshold point at which any decrease in Se concentration was associated with PaCa was 67.45 µg/L. The threshold point of Cu level above which there was an increase in the prevalence of PaCa was 1,214.58 µg/L. In addition, a positive relationship was observed between increasing survival time and Se plasma level. CONCLUSION: This retrospective study suggests that low levels of Se and high levels of Cu might influence development of PaCa and that higher levels of Se are associated with longer survival in patients with PaCa. The results suggest that determining the level of Se and Cu could be incorporated into a risk stratification scheme for the selection and surveillance control examination to complement existing screening and diagnostic procedures.

Breast cancer susceptibility genes.

In 1999 it has been recognized that 3 BRCA1 abnormalities - 5382insC, C61G and 4153delA - constitute almost 90% of all germline mutations of this gene in Poland. Due to the above findings we started performing the cheap and quick large scale testing for BRCA1 mutations and, these days, we have almost 4,000 carriers diagnosed and under direct or indirect supervision what is probably the largest number in the world. Additionally, the above results pushed us to hypothesize that genetic homogeneity will be seen in Poland in studies of other genes. Actually, the next studies allowed us to identify genes / changes associated with moderate / low breast cancer risk and showed, similarly to BRCA1, high level of genetic homogeneity. This series included BRCA2, C5972T, CHEK2 del5395; 1100delC, I157T or IVS2 + 1G > A, CDKN2A (p16) A148T, XPD Asp312Asn and Lys751Gln, CYP1B1 R48G, A119S and L43V. The results of the above studies led us in 2004 already to hypothesize that >90% of all cancers have genetic (constitutional) background. Two years later we were able to show a panel of markers covering 92% of consecutive breast cancers in Poland, and we formulated the hypothesis that all cancers have a genetic background. These days we are demonstrating for the first time that genetic components to malignancy play a role in all cancers. We are presenting it on examples of late-onset breast cancers from Poland, but it seems to be justified to expect that similar results can be achieved from other malignancies.

Implementation of laparoscopic colectomy with fast-track care in an academic medical center: benefits of a fully ascended learning curve and specialty expertise.

BACKGROUND: There are few data describing successful institutional "conversion" from open colectomy/standard care techniques to laparoscopic colectomy/fast-track care. PURPOSE: To assess the benefits of transitioning an institution from open to laparoscopic colectomy with fast-track care while avoiding a learning curve. METHOD: Twenty consecutive laparoscopic colorectal resections (LCRs) performed by a colorectal surgeon were compared with 20 matched open colorectal resections (OCRs) performed by general surgeons before the arrival of the colorectal surgeon. RESULTS: Surgical procedures were as follows: sigmoidectomy: OCR 16 and LCR 11; right colectomy: OCR 3 and LCR 8; and total colectomy: OCR 1 and LCR 1. The mean operative time for sigmoidectomy was 250 and 109 minutes for OCR and LCR, respectively, and for right colectomy 181 and 97 minutes for OCR and LCR, respectively (P < .001). Morbidity was OCR 45% versus LCR 25%. There was no mortality. LCR showed significantly lower length of stay and direct cost (3.6 vs. 8.3 days; 4,993 dollars vs. 11,383 dollars; both P < .001). CONCLUSIONS: The data clearly show an institutional benefit for the implementation of specialty-based advanced laparoscopic procedures.