Prediction of 30-day unplanned hospital readmission through survival analysis.

Background and Objective: Unplanned hospital readmissions are a severe and recurrent problem that affects all health systems. Estimating the risk of being readmitted the following days after discharge is difficult since many heterogeneous factors can influence this. The extensive work concerning this problem proposes solutions mostly based on classification machine-learning models. Survival analysis methods could make a better match with the assessment of readmission risk and are yet to become well-established in this field. Methods: We compare different statistical and machine learning survival analysis models trained with right-censored all-cause hospital admission data with covariates available at the moment of discharge. The main focus is on tree-ensemble regression methods based on the assumption of proportional hazards. These models are more thoroughly evaluated at a 30-day time period after discharge, although the actual prediction could be set to any time up to 90 days. Results: The mean performance obtained by each of the proposed survival models ranges from 0.707 to 0.716 C-Index and 0.709 to 0.72 ROC-AUC at a 30-day time period after discharge. The model with the lower performance on both metrics was Cox Proportional Hazards, while the model marking the upper end on both ranges is an XGBoost Regression model with a Cox objective function. Conclusions: Our findings indicate that survival models perform well addressing the hospital readmission problem, machine-learning models getting the edge over statistical methods. There seems to be an improvement over classification models when attempting to predict at a 30-day period since discharge, perhaps due to a better handling of cases nearing the 30-day boundary. Some preprocessing steps, such as limiting the observation period to 90 days after discharge, are also highlighted since they resulted in a performance boost.

SEQENS: An ensemble method for relevant gene identification in microarray data.

This paper describes an ensemble feature identification algorithm called SEQENS, and measures its capability to identify the relevant variables in a case-control study using a genetic expression microarray dataset. SEQENS uses Sequential Feature Search on multiple sample splitting to select variables showing stronger relation with the target, and a variable relevance ranking is finally produced. Although designed for feature identification, SEQENS could also serve as a basis for feature selection (classifier optimisation). Cliff, a ranking evaluation metric is also presented and used to assess the feature identification algorithms when a groundtruth of relevant variables is available. To test performance, three types of synthetic groundtruths emulating fictitious diseases are generated from ten randomly chosen variables following different target pattern distributions using the E-MTAB-3732 dataset. Several sample-to-dimensionality ratios ranging from 300 to 3,000 observations and 854 to 54,675 variables are explored. SEQENS is compared with other feature selection or identification state-of-the-art methods. On average, the proposed algorithm identifies better the relevant genes and exhibits a stronger stability. The algorithm is available to the community.

Bilateral Seminal Vesicle Invasion Is Not Associated with Worse Outcomes in Locally Advanced Prostate Carcinoma.

Background and Objectives: Patients with seminal vesicle invasion (SVI) are a highly heterogeneous group. Prognosis can be affected by many clinical and pathological characteristics. Our aim was to study whether bilateral SVI (bi-SVI) is associated with worse oncological outcomes. Materials and Methods: This is an observational retrospective study that included 146 pT3b patients treated with radical prostatectomy (RP). We compared the results between unilateral SVI (uni-SVI) and bi-SVI. The log-rank test and Kaplan-Meier curves were used to compare biochemical recurrence-free survival (BCR), metastasis-free survival (MFS), and additional treatment-free survival. Cox proportional hazard models were used to identify predictors of BCR-free survival, MFS, and additional treatment-free survival. Results: 34.93% of patients had bi-SVI. The median follow-up was 46.84 months. No significant differences were seen between the uni-SVI and bi-SVI groups. BCR-free survival at 5 years was 33.31% and 25.65% (p = 0.44) for uni-SVI and bi-SVI. MFS at 5 years was 86.03% vs. 75.63% (p = 0.1), and additional treatment-free survival was 36.85% vs. 21.93% (p = 0.09), respectively. In the multivariate analysis, PSA was related to the development of BCR [HR 1.34 (95%CI: 1.01-1.77); p = 0.03] and metastasis [HR 1.83 (95%CI: 1.13-2.98); p = 0.02]. BCR was also influenced by lymph node infiltration [HR 2.74 (95%CI: 1.41-5.32); p = 0.003]. Additional treatment was performed more frequently in patients with positive margins [HR: 3.50 (95%CI: 1.65-7.44); p = 0.001]. Conclusions: SVI invasion is an adverse pathology feature, with a widely variable prognosis. In our study, bilateral seminal vesicle invasion did not predict worse outcomes in pT3b patients despite being associated with more undifferentiated tumors.

Decision support through risk cost estimation in 30-day hospital unplanned readmission.

Unplanned hospital readmissions mean a significant burden for health systems. Accurately estimating the patient's readmission risk could help to optimise the discharge decision-making process by smartly ordering patients based on a severity score, thus helping to improve the usage of clinical resources. A great number of heterogeneous factors can influence the readmission risk, which makes it highly difficult to be estimated by a human agent. However, this score could be achieved with the help of AI models, acting as aiding tools for decision support systems. In this paper, we propose a machine learning classification and risk stratification approach to assess the readmission problem and provide a decision support system based on estimated patient risk scores.

Nanomotion Detection Method for Testing Antibiotic Resistance and Susceptibility of Slow-Growing Bacteria.

Infectious diseases are caused by pathogenic microorganisms and are often severe. Time to fully characterize an infectious agent after sampling and to find the right antibiotic and dose are important factors in the overall success of a patient's treatment. Previous results suggest that a nanomotion detection method could be a convenient tool for reducing antibiotic sensitivity characterization time to several hours. Here, the application of the method for slow-growing bacteria is demonstrated, taking Bordetella pertussis strains as a model. A low-cost nanomotion device is able to characterize B. pertussis sensitivity against specific antibiotics within several hours, instead of days, as it is still the case with conventional growth-based techniques. It can discriminate between resistant and susceptible B. pertussis strains, based on the changes of the sensor's signal before and after the antibiotic addition. Furthermore, minimum inhibitory and bactericidal concentrations of clinically applied antibiotics are compared using both techniques and the suggested similarity is discussed.

Ultradeformable Archaeosomes for Needle Free Nanovaccination with Leishmania braziliensis Antigens.

Total antigens from Leishmania braziliensis promastigotes, solubilized with sodium cholate (dsLp), were formulated within ultradeformable nanovesicles (dsLp-ultradeformable archaeosomes, (dsLp-UDA), and dsLp-ultradeformable liposomes (dsLp-UDL)) and topically administered to Balb/c mice. Ultradeformable nanovesicles can penetrate the intact stratum corneum up to the viable epidermis, with no aid of classical permeation enhancers that can damage the barrier function of the skin. Briefly, 100 nm unilamellar dsLp-UDA (soybean phosphatidylcholine: Halorubrum tebenquichense total polar lipids (TPL): sodium cholate, 3:3:1 w:w) of -31.45 mV Z potential, containing 4.84 ± 0.53% w/w protein/lipid dsLp, 235 KPa Young modulus were prepared. In vitro, dsLp-UDA was extensively taken up by J774A1 and bone marrow derive cells, and the only that induced an immediate secretion of IL-6, IL-12p40 and TNF-α, followed by IL-1ß, by J774A1 cells. Such extensive uptake is a key feature of UDA ascribed to the highly negatively charged archaeolipids of the TPL, which are recognized by a receptor specialized in uptake and not involved in downstream signaling. Despite dsLp alone was also immunostimulatory on J774A1 cells, applied twice a week on consecutive days along 7 weeks on Balb/c mice, it raised no measurable response unless associated to UDL or UDA. The highest systemic response, IgGa2 mediated, 1 log lower than im dsLp Al2O3, was elicited by dsLp-UDA. Such findings suggest that in vivo, UDL and UDA acted as penetration enhancers for dsLp, but only dsLp-UDA, owed to its pronounced uptake by APC, succeeded as topical adjuvants. The actual TPL composition, fully made of sn2,3 ether linked saturated archaeolipids, gives the UDA bilayer resistance against chemical, physical and enzymatic attacks that destroy ordinary phospholipids bilayers. Together, these properties make UDA a promising platform for topical drug targeted delivery and vaccination, that may be of help for countries with a deficient healthcare system.

Bordetella biofilms: a lifestyle leading to persistent infections.

Bordetella bronchiseptica and B. pertussis are Gram-negative bacteria that cause respiratory diseases in animals and humans. The current incidence of whooping cough or pertussis caused by B. pertussis has reached levels not observed since the 1950s. Although pertussis is traditionally known as an acute childhood disease, it has recently resurged in vaccinated adolescents and adults. These individuals often become silent carriers, facilitating bacterial circulation and transmission. Similarly, vaccinated and non-vaccinated animals continue to be carriers of B. bronchiseptica and shed bacteria resulting in disease outbreaks. The persistence mechanisms of these bacteria remain poorly characterized. It has been proposed that adoption of a biofilm lifestyle allows persistent colonization of the mammalian respiratory tract. The history of Bordetella biofilm research is only a decade long and there is no single review article that has exclusively focused on this area. We systematically discuss the role of Bordetella factors in biofilm development in vitro and in the mouse respiratory tract. We further outline the implications of biofilms to bacterial persistence and transmission in humans and for the design of new acellular pertussis vaccines.

Outer membrane protein OmpQ of Bordetella bronchiseptica is required for mature biofilm formation.

Bordetella bronchiseptica, an aerobic Gram-negative bacterium, is capable of colonizing the respiratory tract of diverse animals and chronically persists inside the hosts by forming biofilm. Most known virulence factors in Bordetella species are regulated by the BvgAS two-component transduction system. The Bvg-activated proteins play a critical role during host infection. OmpQ is an outer membrane porin protein which is expressed under BvgAS control. Here, we studied the contribution of OmpQ to the biofilm formation process by B. bronchiseptica. We found that the lack of expression of OmpQ did not affect the growth kinetics and final biomass of B. bronchiseptica under planktonic growth conditions. The ΔompQ mutant strain displayed no differences in attachment level and in early steps of biofilm formation. However, deletion of the ompQ gene attenuated the ability of B. bronchiseptica to form a mature biofilm. Analysis of ompQ gene expression during the biofilm formation process by B. bronchiseptica showed a dynamic expression pattern, with an increase of biofilm culture at 48 h. Moreover, we demonstrated that the addition of serum anti-OmpQ had the potential to reduce the biofilm biomass formation in a dose-dependent manner. In conclusion, we showed for the first time, to the best of our knowledge, evidence of the contribution of OmpQ to a process of importance for B. bronchiseptica pathobiology. Our results indicate that OmpQ plays a role during the biofilm development process, particularly at later stages of development, and that this porin could be a potential target for strategies of biofilm formation inhibition.

Bordetella pertussis Isolates from Argentinean Whooping Cough Patients Display Enhanced Biofilm Formation Capacity Compared to Tohama I Reference Strain.

Pertussis is a highly contagious disease mainly caused by Bordetella pertussis. Despite the massive use of vaccines, since the 1950s the disease has become re-emergent in 2000 with a shift in incidence from infants to adolescents and adults. Clearly, the efficacy of current cellular or acellular vaccines, formulated from bacteria grown in stirred bioreactors is limited, presenting a challenge for future vaccine development. For gaining insights into the role of B. pertussis biofilm development for host colonization and persistence within the host, we examined the biofilm forming capacity of eight argentinean clinical isolates recovered from 2001 to 2007. All clinical isolates showed an enhanced potential for biofilm formation compared to the reference strain Tohama I. We further selected the clinical isolate B. pertussis 2723, exhibiting the highest biofilm biomass production, for quantitative proteomic profiling by means of two-dimensional fluorescence difference gel electrophoresis (2D-DIGE) coupled with mass spectrometry, which was accompanied by targeted transcriptional analysis. Results revealed an elevated expression of several virulence factors, including adhesins involved in biofilm development. In addition, we observed a higher expression of energy metabolism enzymes in the clinical isolate compared to the Tohama I strain. Furthermore, all clinical isolates carried a polymorphism in the bvgS gene. This mutation was associated to an increased sensitivity to modulation and a faster rate of adhesion to abiotic surfaces. Thus, the phenotypic biofilm characteristics shown by the clinical isolates might represent an important, hitherto underestimated, adaptive strategy for host colonization and long time persistence within the host.

FHA-mediated cell-substrate and cell-cell adhesions are critical for Bordetella pertussis biofilm formation on abiotic surfaces and in the mouse nose and the trachea.

Bordetella spp. form biofilms in the mouse nasopharynx, thereby providing a potential mechanism for establishing chronic infections in humans and animals. Filamentous hemagglutinin (FHA) is a major virulence factor of B. pertussis, the causative agent of the highly transmissible and infectious disease, pertussis. In this study, we dissected the role of FHA in the distinct biofilm developmental stages of B. pertussis on abiotic substrates and in the respiratory tract by employing a murine model of respiratory biofilms. Our results show that the lack of FHA reduced attachment and decreased accumulation of biofilm biomass on artificial surfaces. FHA contributes to biofilm development by promoting the formation of microcolonies. Absence of FHA from B. pertussis or antibody-mediated blockade of surface-associated FHA impaired the attachment of bacteria to the biofilm community. Exogenous addition of FHA resulted in a dose-dependent inhibitory effect on bacterial association with the biofilms. Furthermore, we show that FHA is important for the structural integrity of biofilms formed on the mouse nose and trachea. Together, these results strongly support the hypothesis that FHA promotes the formation and maintenance of biofilms by mediating cell-substrate and inter-bacterial adhesions. These discoveries highlight FHA as a key factor in establishing structured biofilm communities in the respiratory tract.