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To determine the 30-day surgical readmission rate after major gynecologic oncology surgeries at a high-volume academic institution and correlated risk factors. Retrospective cohort study was conducted of surgical admissions from January 2016 – December 2019 at a single institution. Data were extracted from patient charts, including reason for readmission and length of stay. A readmission rate was calculated. Nested case control design was used to identify correlations between readmission and patient specific risk-factors. Multivariable logistic regression models were used to determine risk factors with readmission. A total of 2152 patients were included. The readmission rate was 3.5%, most commonly due to GI disturbance and surgical site infection. Average readmission length was 5 days. Prior to adjusting for covariates, insurance status, primary diagnosis, index admission length, and disposition at discharge differed between patients who were and were not readmitted. After adjusting for co-variates, younger patients, index admission >2 days, and higher Charlson co-morbidity index were associated with readmission. Our surgical readmission rate was lower than previously reported rates in gynecologic oncology patients. Patient factors associated with readmission included younger age, longer index hospital admission, and higher medical co-morbidity index scores. Provider factors and institutional practice patterns could contribute to the decreased readmission rate. These findings underscore the importance of standardizing how we calculate readmission rate and interpret these data. Varying readmission rates and institutional practice patterns deserve closer scrutiny to inform best practice and future policies. • Postoperative readmission rate after major gynecologic oncology surgery was 3.5%; lower than previously reported rates. • Readmission cause was most commonly gastrointestinal complication and surgical site infection. • Younger age, longer index hospital admission, and higher medical co-morbidity index were associated with readmission. • Provider practice patterns warrant further study regarding contribution to readmission rate. [ABSTRACT FROM AUTHOR]

The electroacoustic resonator is an efficient electro-active device for noise attenuation in enclosed cavities or acoustic waveguides. It is made of a loudspeaker (the actuator) and one or more microphones (the sensors). So far, the desired acoustic behaviour, expressed in terms of a linear-time-invariant relationship between sound pressure and vibrational motion (the acoustical impedance), has been more efficiently achieved by a model-inversion strategy which is implemented by driving the electrical current in the loudspeaker coil, based upon the measured pressure. The corrector transfer function is defined in the Laplace domain and digitally executed by the classical infinite-impulse-response technique, though a state–space representation could be employed. In this work, we are interested in enforcing a nonlinear behaviour at low sound excitation levels, where the electroacoustic resonator would normally behave as a linear-time-invariant system. Hence, in order to transform its acoustical response from linear to nonlinear, the model-inversion technique must be reformulated in time domain. The state–space representation of the relationship between the input measured pressure and the output electrical current gives the right perspective and the solution to this problem. We provide the conception of this model-inversion control algorithm capable of transforming a linear-time-invariant acoustical response to potentially any causal acoustical response of the electroacoustic resonator. Such control strategy is tested by targeting a Duffing acoustical response with tunable parameters. Both numerical simulations and experimental tests in quasi-open field validate the approach. The results provided in this contribution open the doors for conceiving non-conventional absorbers which can exploit nonlinear phenomena for noise mitigation even at low excitation amplitudes. [ABSTRACT FROM AUTHOR]

Human gut microbiota species which are next-generation probiotics (NGPs) candidates are of high interest as they have shown the potential to treat intestinal inflammation and other diseases. Unfortunately, these species are often not robust enough for large-scale cultivation, especially in maintaining diversity in co-culture production. In this study, we describe interactions between human gut microbiota species in the cultivation process with unique substrates. We also demonstrated that it is possible to change the species ratio in co-culture by changing the ratio of carbon sources. We screened 25 different bacterial species based on their metabolic capabilities. After evaluating unique substrate possibilities, we chose Anaerostipes caccae (A. caccae), Bacteroides thetaiotaomicron (B. thetaiotaomicron), and Bacteroides vulgatus (B. vulgatus) as subjects for further study. D-sorbitol, D-xylose, and D-galacturonic acid were selected as substrates for A. caccae , B. thetaiotaomicron , and B. vulgatus respectively. All three species were cultivated as both monocultures and in co-cultures in serial batch fermentations in an isothermal microcalorimeter. Positive interactions were detected between the species in both co-cultures (A. caccae + B. thetaiotaomicron ; A. caccae + B. vulgatus) resulting in higher heat production compared to the sum of the monocultures. The same positive cross-feeding interactions took place in larger-scale cultivation experiments. We confirmed acetate and lactate cross-feeding between A. caccae and B. thetaiotaomicron with flux balance analysis (FBA). Changing the ratio of the selected carbon sources in the medium changed the species ratio accordingly. Such robustness is the basis for developing more efficient industrial co-culture processes including the production of NGPs. • The growth of 25 bacterial species was evaluated in chemically defined medium. • A. caccae , B. thetaiotaomicron , and B. vulgatus were chosen as model organisms. • Stable co-culture was achieved throughout three consecutive batches. • Trophic interactions of A. caccae and Bacteroides spp. boost species' growth rates. • Unique substrates help to control biomass concentrations in co-culture production. [ABSTRACT FROM AUTHOR]

In recent years, the Risk of Ovarian Malignancy Algorithm (ROMA) score has emerged as a useful tool in the triage of women with pelvic masses. Previously, triage of women with pelvic masses to management by either benign gynecology or gynecologic oncology was performed with an initial clinical risk assessment (ICRA) alone, involving a detailed history, exam, basic laboratory tests, and imaging. We sought to determine whether use of ROMA, which is calculated using CA125, HE4, and menopausal status for triage of women with pelvic masses, provides cost savings compared to triage based on ICRA alone. A health-economic decision model was developed to assess clinical and cost differences associated with referrals for patients presenting to their gynecologist or primary care physician with an adnexal mass. In our study, we modeled the differences of two clinical pathways that included 1) use of ICRA alone and 2) use of ROMA as a determining factor in referral to a gynecologic oncologist. Using previously reported accuracy rates and patient characteristics from a prospective, multicenter, blinded clinical trial (ClinicalTrial. gov identifier NCT00987649), we assessed triage of women with a pelvic mass using ICRA alone or ROMA and modeled the related lab testing, imaging, surgical procedures, and associated costs. Costs were estimated using current Medicare reimbursement rates. A total of 423 patients with pelvic masses were included. Total healthcare costs for patients triaged for epithelial ovarian cancer (EOC) using ICRA alone were higher than when triaged by ROMA ($2,461,301 vs $2,428,628), a cost savings of 1.3%. While lab costs increased 55% when using ROMA ($16,006 vs $24,809), all other costs decreased, including total laparoscopy ($1,931,568 vs $1,896,314, -1.8% difference), total laparotomy ($436,910 vs $430,689, -1.4% difference), and total surgery ($2,368,479 vs $2,327,003, -1.8% difference) (Table 1). Repeat surgeries resulting from false negative ICRA were also reduced when using ROMA (8 vs 3), a 64% decrease. Notably, total healthcare costs were further reduced when including patients with low malignant potential (LMP) tumors ($2,646,738 vs $2,558,834, -3.3% difference) and analysis of all cancers ($2,847,829 vs $2,728,247, -4.2% difference). A similar reduction in repeat surgeries was noted in patients with LMP tumors (19 for ICRA, 7 for ROMA, -61% difference) and in all cancers (29 for ICRA, 14 for ROMA, -53% difference). [Display omitted] Triage of women with a pelvic mass using the more sensitive ROMA score compared to ICRA alone lowers overall healthcare costs. With fewer false negatives than ICRA alone, the ROMA score improves initial detection of malignancy and reduces second surgical treatments in women with pelvic masses. [ABSTRACT FROM AUTHOR]

Each year in the U.S. over two million women will be diagnosed with an ovarian cyst or pelvic mass of which approximately 200,000 will require surgery. Of these women, 22,000 (~11%) will ultimately be diagnosed with epithelial ovarian cancer (EOC). Multiple studies have demonstrated that women with EOC managed by a gynecologic oncologist and at high volume institutions for EOC have improved survival rates. Despite these facts, less than 50% of women diagnosed with EOC are cared for by gynecologic oncologists or at high volume institutions. The Risk of Ovarian Malignancy Algorithm (ROMA) was developed to assist in the triage of women at high risk for EOC to gynecologic oncologists. ROMA has been cleared by the FDA for risk assessment and triage in women presenting with an ovarian cyst or pelvic mass. The objective of this study was to demonstrate the performance of ROMA in a large population of women presenting with a pelvic mass. This is the largest collection of patients evaluated with ROMA to date. A meta-analysis was conducted by pooling data from 5 pelvic mass trials. This study was institutional review board (IRB)-exempt due to the secondary use of preexisting data. Data was combined into one cohort for analysis of ROMA. As per ROMA design, the sensitivity, PPV and NPV were calculated at a set specificity of ~75%. All samples were run on the Abbott ARCHITECT platform for both CA125 and HE4. A total of 2,004 patients were included in the analysis (837 premenopausal and 1,167 postmenopausal). There were 448 EOCs (89 stage I, 45 stage II, 284 stage III, 24 stage IV and 6 unstaged), 83 Borderline/LMP tumors, 1,224 benign masses, 23 non-epithelial ovarian cancers, 165 other gynecological cancers, 59 non-gynecologic metastatic cancers, and 2 mesotheliomas. For the detection of benign vs EOC only in pre and postmenopausal women, at a specificity of 75.0%, ROMA achieved a sensitivity of 91.3%, a PPV of 57.2% and a NPV 95.9%. In postmenopausal women, there were 554 benign cases and 379 EOCs. At a specificity of 75.3%, ROMA achieved a sensitivity of 92.3%, a PPV of 71.9% and a NPV of 93.5%. In premenopausal patients, there were 670 benign cases and 69 EOCs. At a specificity of 74.8%, ROMA achieved a sensitivity of 85.5%, a PPV of 25.9% and a NPV of 98.0%. An analysis of the ability of ROMA to differentiate early stage EOC from benign in pre and post-menopausal women revealed a sensitivity of 76.1%, a specificity of 75.0%, a PPV of 25.0% a NPV of 96.6%. ROMA detected over 98% of all late stage III and IV EOCs. ROMA has been shown in multiple independent prospective trials to be an accurate tool for pelvic mass risk assessment. This is the largest collection to date to validate the performance characteristics of ROMA. ROMA should be used as one of the tools for pelvic mass risk assessment to assist in the triage of patients at high risk for EOC to gynecologic oncologists. [ABSTRACT FROM AUTHOR]

Pelvic masses can be classified as low risk (likely benign) and high risk (likely malignant) based on an initial clinical risk assessment (ICRA). The clinical assessment impacts the management and referral plan that patients receive. The objective of this study was to compare the ICRA and referral performances of primary care physicians (PCPs) and generalist gynecologists (GYNs) in the evaluation of a pelvic mass to the risk of ovarian malignancy algorithm (ROMA). Results from a prospective, multicenter trial (ClinicalTrial. gov identifier NCT00987649), evaluating women with a pelvic mass that had an ICRA performed by a non-gynecologic oncologist were used for this study. ICRA included history, physical exam, any combination of imaging (ultrasound, CT scan, MRI) and CA125 all at the physician's discretion. Types of imaging utilized in evaluation and ROMA scores were determined, and statistical parameters were calculated for the ability of ICRA and ROMA to differentiate between benign and malignant masses. A total of 398 patients were included in the analysis (229 premenopausal, 169 postmenopausal), with 332 being evaluated by GYNs and 66 by PCPs. A total of 40 patients (10.1%) were diagnosed with epithelial ovarian cancer (EOC). False negative assessments for EOC comprised 5.7% and 1.4% of the subjects with a benign ICRA as determined by PCPs versus GYNs respectively (p=0.138). PCPs ICRA achieved a sensitivity of 88.2% and specificity of 67.3% compared with GYNs ICRA with a sensitivity of 82.6% and a specificity of 88.3%. The IRCA accuracy for PCPs was 72.7% versus an accuracy of 88.0% for GYNs (p=0.003). In premenopausal women the PCP ICRA achieved a sensitivity of 50.0% with a specificity of 68.2%. The GYNs ICRA sensitivity was 40.0% with a specificity of 93.0%. The accuracy for PCPs was 66.7% compared with 91.7% for GYNs (p<0.001). In postmenopausal women the PCPs ICRA achieved a sensitivity of 93.3% with a specificity of 66.7%. The GYNs ICRA sensitivity was 94.4% with a specificity of 79.8%. The accuracy for PCPs was 76.2% compared with 81.9% for GYNs (p=0.501). PCPs were approximately 2.2x more likely to include CT scans in their initial evaluation (60.6% vs. 27.5%) and were less likely to include ultrasound (56.1% vs 84.6%), which overall is a more cost intensive approach. In the 398 patients, the ROMA score achieved a sensitivity of 95.0% with a specificity of 75.4%. Use of the ROMA score alone for triage would have resulted in 4 more patients with EOC being directly referred to a gynecologic oncologist that were not referred through ICRA alone. GYNs more accurately use ICRA to stratify pelvic masses into benign and malignant categories, particularly in premenopausal women, and they tend to take a more cost-effective approach to initial risk assessment compared to PCPs. Use of the ROMA identifies additional EOC cases not identified by ICRA. [ABSTRACT FROM AUTHOR]

• The Gini index is used to measure differentiation in house size as a proxy to interpret inequality across a large environmental lidar dataset that documented a palimpsest of Maya archaeological settlement and landscapes. • We identify consistent patterns and Gini coefficients across the Maya lowlands, with notably lower values in peripheral areas, including coastal zones and the Western lowlands. • Despite the narrow lidar transects, the results of this study align with regional and site-based approaches across the Maya area. The emergence and expansion of inequality have been topics of household archaeology for decades. Traditionally, this question has been informed by ethnographic, ethnohistoric and/or comparative studies. Within sites and regions, comparative physical, spatial, and architectural studies of households offer an important baseline of information about status, wealth, and well-being, especially in the Maya lowlands where households are accessible in the archaeological record. Between sites, more research is necessary to assess how these physical measurements of household remains compare. This paper investigates the intersection of landscape, household, and community based on a multi-scalar analysis of households using the Gini index across southeastern Mexico, in the context of a broader study of land use, land management, and settlement patterns. Notably, this paper represents a region-wide analysis of nearly continuous LiDAR data within and outside of previously documented prehispanic Maya settlements. While we conclude that the Gini index is useful for establishing a comparative understanding of settlement, we also recognize that the index is a starting point to identify other ways to study how household to community-level social and economic variability intersects with diverse ecological patterns. Highlighting the opportunities and limitations with applying measures like the Gini index across culturally, temporally, and geographically heterogeneous areas, we illustrate how systematic studies of settlement can be coupled to broader studies of landscape archaeology to interpret changing patterns of land management and settlement across the Maya lowlands. [ABSTRACT FROM AUTHOR]

Lysosomal storage disorders (LSD) are a group of inherited metabolic diseases mainly caused by a deficiency of lysosomal hydrolases, resulting in a gradual accumulation of non-degraded substrates in different tissues causing the characteristic clinical manifestations of such disorders. Confirmatory tests of suspected LSD individuals include enzymatic and genetic testing. A well-oriented clinical suspicion can improve the cost-effectiveness of confirmatory tests and reduce the time expended to achieve the diagnosis. Thus, this work aims to retrospectively study the influence of clinical orientation on the diagnostic yield of enzymatic tests in LSD by retrieving clinical, biochemical, and genetic data obtained from subjects with suspicion of LSD. Our results suggest that the clinical manifestations at the time of diagnosis and the initial clinical suspicion can have a great impact on the diagnostic yield of enzymatic tests, and that clinical orientation performed in specialized clinical departments can contribute to improve it. In addition, the analysis of enzymatic tests as the first step in the diagnostic algorithm can correctly guide subsequent confirmatory genetic tests, in turn increasing their diagnostic yield. In summary, our results suggest that initial clinical suspicion plays a crucial role on the diagnostic yield of confirmatory enzymatic tests in LSD. • Well-oriented clinical suspicion improves diagnostic yield of confirmatory tests in LSD • High clinical specialization improves the cost-effectiveness of laboratory tests • Enzymatic testing is still important to guide genetic testing • Nonspecific clinical manifestations decrease the diagnostic yield of enzymatic tests • The demand management of laboratory tests contributes to increase diagnostic yield [ABSTRACT FROM AUTHOR]