Risk Factors Analysis of Surgical Infection Using Artificial Intelligence: A Single Center Study

Background: Surgical site infections (SSIs) have a major role in the evolution of medical care. Despite centuries of medical progress, the management of surgical infection remains a pressing concern. Nowadays, the SSIs continue to be an important factor able to increase the hospitalization duration, cost, and risk of death, in fact, the SSIs are a leading cause of morbidity and mortality in modern health care. Methods: A study based on statistical test and logistic regression for unveiling the association between SSIs and different risk factors was carried out. Successively, a predictive analysis of SSIs on the basis of risk factors was performed. Results: The obtained data demonstrated that the level of surgery contamination impacts significantly on the infection rate. In addition, data also reveals that the length of postoperative hospital stay increases the rate of surgical infections. Finally, the postoperative length of stay, surgery department and the antibiotic prophylaxis with 2 or more antibiotics are a significant predictor for the development of infection. Conclusions: The data report that the type of surgery department and antibiotic prophylaxis there are a statistically significant predictor of SSIs. Moreover, KNN model better handle the imbalanced dataset (48 infected and 3983 healthy), observing highest accuracy value

Implementation and validation of a new method to model voluntary departures from emergency departments

In the literature, several organizational solutions have been proposed for determining the probability of voluntary patient discharge from the emergency department. Here, the issue of self-discharge is analyzed by Markov theory-based modeling, an innovative approach diffusely applied in the healthcare field in recent years. The aim of this work is to propose a new method for calculating the rate of voluntary discharge by defining a generic model to describe the process of first aid using a “behavioral” Markov chain model, a new approach that takes into account the satisfaction of the patient. The proposed model is then implemented in MATLAB and validated with a real case study from the hospital “A. Cardarelli” of Naples. It is found that most of the risk of self-discharge occurs during the wait time before the patient is seen and during the wait time for the final report; usually, once the analysis is requested, the patient, although not very satisfied, is willing to wait longer for the results. The model allows the description of the first aid process from the perspective of the patient. The presented model is generic and can be adapted to each hospital facility by changing only the transition probabilities between states

Health technology assessment through Six Sigma Methodology to assess cemented and uncemented protheses in total hip arthroplasty

The purpose of this study is to use Health Technology Assessment (HTA) through the Six Sigma (SS) and DMAIC (Define, Measure, Analyse, Improve, Control) problem-solving strategies for comparing cemented and uncemented prostheses in terms of the costs incurred for Total hip arthroplasty (THA) and the length of hospital stay (LOS). Multinomial logistic regression analysis for modelling the data was also performed. Quantitative parameters extracted from gait analysis, electromyography and computed tomography images were used to compare the approaches, but the analysis did not show statistical significance. The variables regarding costs were studied with the Mann-Whitney and Kruskal-Wallis tests. No statistically significant difference between cemented and uncemented prosthesis for the total cost of LOS was found, but the cost of the surgeon had an influence on the overall expenses, affecting the cemented prosthetic approach. The material costs of surgery for the uncemented prosthesis and the cost of theatre of surgery for the cemented prosthesis were the most influential. Multinomial logistic regression identified the Vastus Lateralis variable as statistically significant. The overall accuracy of the model is 93.0%. The use of SS and DMAIC cycle as tools of HTA proved that the cemented and uncemented approaches for THA have similar costs and LO

Management of the Diabetic Patient in the Diagnostic Care Pathway

Diabetes is a complex pathology both for the affected patients and for the medical specialists who follow them. Furthermore, since diabetes is a pathology with a high prevalence and incidence, it is essential to intervene effectively in therapeutic actions through the application of common guidelines. Therefore, in order to improve the management of the diabetic patient, the aim of the work is to define a Diagnostic Therapeutic Assistance Pathway (PDTA). A questionnaire-based approach is adopted for data collection from 136 patients at the Clinical Dermatology Unit of the University Hospital “Federico II”. In most cases (64%) the diagnosis was made by the General Practitioner, 15% of patients obtained the diagnosis at the ASL and 12% at the Polyclinic of Naples AOU “Federico II” and the remaining part from the diabetologist specialist. The second access is generally carried out at the “Federico II” AOU (66%), followed by the ASL (17%), by a doctor specialized in diabetology (12%) while no patient has turned to the General Practitioner for the treatment of diabetes. The final visit is carried out at the “Federico II” AOU in almost cases. The data obtained follow the Italian guidelines: the patients get the diagnosis from the Family Doctor and then they are addressed either to ASL or to diabetologists specialists. For the subsequent visits, most of them prefer to turn to the “Federico II” AOU, especially when they have complications associated with the diseases as they are followed in a more careful and satisfying manner

A health technology assessment between two pharmacological therapies through Six Sigma: the case study of bone cancer

Purpose: Head and neck cancers are multi-factorial diseases that can affect many sides of people's life and are due to a lot of risk factors. According to their characteristics, the treatment can be surgical, use of radiation or chemotherapy. The use of a surgical treatment can lead to surgical infections that are a main theme in medicine. At the University hospital of Naples “Federico II”, two antibiotics were employed to tackle the issue of the infections and they are compared in this paper to find which one implies the lowest length of hospital stay (LOS) and the reduction of infections. Design/methodology/approach: The Six Sigma methodology and its problem-solving strategy DMAIC (define, measure, analyse, improve, control), already employed in the healthcare sector, were used as a tool of a health technology assessment between two drugs. In this paper the DMAIC roadmap is used to compare the Ceftriaxone (administered to a group of 48 patients) and the association of Cefazolin plus Clindamycin (administered to a group of 45 patients). Findings: The results show that the LOS of patients treated with Ceftriaxone is lower than those who were treated with the association of Cefazolin plus Clindamycin, the difference is about 41%. Moreover, a lower number of complications and infections was found in patients who received Ceftriaxone. Finally, a greater number of antibiotic shifts was needed by patients treated with Cefazolin plus Clindamycin. Research limitations/implications: While the paper enhances clearly the advantages for patients' outcomes regarding the LOS and the number of complications, it did not analyse the costs of the two antibiotics. Practical implications: Employing the Ceftriaxone would allow the Department of Maxillofacial Surgery to obtain lower LOS and a limited number of complications/infections for recovered patients, consequently reducing the hospitalization costs. Originality/value: There is a double value in this paper: first of all, the comparison between the two antibiotics gives an answer to one of the main issues in medicine that is the reduction of hospital-acquired infections; secondly, the Six Sigma through its DMAIC cycle can be employed also to compare two biomedical technologies as a tool of health technology assessment studies

Lean six sigma approach for reducing length of hospital stay for patients with femur fracture in a university hospital

Surgical intervention within 48 h of hospital admission is the gold standard procedure for the management of elderly patients with femur fractures, since the increase in preoperative waiting time is correlated with the onset of complications and longer overall length of stay (LOS) in the hospital. However, national evidence demonstrates that there is still the need to provide timely intervention for this type of patient, especially in some regions of central southern Italy. Here we discuss the introduction of a diagnostic–therapeutic assistance pathway (DTAP) to reduce the preoperative LOS for patients undergoing femur fracture surgery in a university hospital. A Lean Six Sigma methodology, based on the DMAIC cycle (Define, Measure, Analyze, Improve, Control), is implemented to evaluate the effectiveness of the DTAP. Data were retrospectively collected and analyzed from two groups of patients before and after the implementation of DTAP over a period of 10 years. The statistics of the process measured before the DTAP showed an average preoperative LOS of 5.6 days (standard deviation of 3.2), thus confirming the need for corrective actions to reduce the LOS in compliance with the national guidelines. The influence of demographic and anamnestic variables on the LOS was evaluated, and the impact of the DTAP was measured and discussed, demonstrating the effectiveness of the improvement actions implemented over the years and leading to a significant reduction in the preoperative LOS, which decreased to an average of 3.5 days (standard deviation of 3.60). The obtained reduction of 39% in the average LOS proved to be in good agreement with previously developed DTAPs for femur fracture available in the literature

Optical Properties of Guanine Nanowires: Experimental and Theoretical Study

International audienceLong nanowires formed by ca. 800 guanine tetrads (G4-wires) are studied in phosphate buffer containing sodium cations. Their room temperature optical properties are compared to those of the monomeric chromophore 2-deoxyguanine monophosphate (dGMP). When going from dGMP to G4-wires, both the absorption and the fluorescence spectra change. Moreover, the fluorescence quantum yield increases by a factor of 7.3 whereas the average fluorescence lifetime increases by more than 2 orders of magnitude, indicating emission associated with weakly allowed transitions. The behavior of G4-wires is interpreted in the light of a theoretical study performed in the frame of the exciton theory combining data from molecular dynamics and quantum chemistry. These calculations, carried out for a quadruplex composed of three tetrads, reveal the existence of various exciton states having different energies and oscillator strengths. The degree of delocalization of the quadruplex Franck−Condon excited states is larger than those found for longer duplexes following the same methodology. The slower excited-state relaxation in G4-wires compared to dGMP is explained by emission from exciton states, possibly limited on individual tetrads, whose coherence is reserved by the reduced mobility of guanines due to multiple Hoogsteen hydrogen bonds

Green solvents and restoration: Application of biomass-derived solvents in cleaning procedures

Blends of solvents from non-renewable sources, often polluting and toxic to humans, are routinely used in the restoration of painted artifacts. Here we present the application of three different green solvents (and their mixtures) as a viable alternative to the standard triad of solvents (acetone, ethanol, and isooctane) used in the solubility test for cleaning polychromic artworks. Solketal (SOLK), γ-valerolactone (GVL), and 2-ethylhexyl pelargonate (ARGO) were selected among the solvents achievable from bio-based synthons such as glycerol, levulinic acid, and pelargonic acid, which are mainly produced from biomass and renewable feedstocks as exhausted vegetable oils, carbohydrates, and lignocellulose. Specifically, ARGO solvent was prepared by esterification reaction and characterized by nuclear magnetic resonance (NMR) and mass spectroscopy coupled to gas chromatography (GC–MS). Hansen solubility parameters for each solvent were determined by a group contribution method, thus enabling their placement in the Teas graph. Their penetration ability in wooden specimens was investigated by evaluating the volume retention of each solvent with different coated specimens. The solvent ability of the selected compounds was tested by visible and UV observations on specimens prepared with film-forming substances (Dammar, Mastic, Shellac, Paraloid® B72 and linseed oil) brushed onto glass plates. Our results pointed out the suitability of this solvent triad for application to panel painting surfaces. The effectiveness of mixtures made with the above green solvent was successfully tested to remove a terpenic varnish from a 16th century oil painting on a wooden panel

Broad-spectrum coronavirus 3C-like protease peptidomimetic inhibitors effectively block SARS-CoV-2 replication in cells: Design, synthesis, biological evaluation, and X-ray structure determination

Despite the approval of vaccines, monoclonal antibodies and restrictions during the pandemic, the demand for new efficacious and safe antivirals is compelling to boost the therapeutic arsenal against the COVID-19. The viral 3-chymotrypsin-like protease (3CLpro) is an essential enzyme for replication with high homology in the active site across CoVs and variants showing an almost unique specificity for Leu-Gln as P2-P1 residues, allowing the development of broad-spectrum inhibitors.The design, synthesis, biological activity, and cocrystal structural information of newly conceived peptidomimetic covalent reversible inhibitors are herein described. The inhibitors display an aldehyde warhead, a Gln mimetic at P1 and modified P2-P3 residues. Particularly, functionalized proline residues were inserted at P2 to stabilize the beta-turn like bioactive conformation, modulating the affinity. The most potent compounds displayed low/sub-nM potency against the 3CLpro of SARS-CoV-2 and MERS-CoV and inhibited viral replication of three human CoVs, i.e. SARS-CoV-2, MERS-CoV, and HCoV 229 in different cell lines. Particularly, derivative 12 exhibited nM-low mu M antiviral activity depending on the virus, and the highest selectivity index. Some compounds were co-crystallized with SARS-CoV-2 3CLpro validating our design. Altogether, these results foster future work toward broad-spectrum 3CLpro inhibitors to challenge CoVs related pandemics

DNA/RNA: Building Blocks of Life Under UV Irradiation

International audienceDuring the last 10 years, intense experimental and theoretical work has proven the existence of ultrafast nonradiative decay routes for UV-excited monomeric nucleic acid bases, accounting for their high photostability. This mechanism has been explained by the occurrence of easily accessible conical intersections connecting the first excited ππ* state with the ground state. However, recent studies of substituent and solvent effects indicate that the situation is more complicated than what was initially thought, notably by the presence of dark excited states. Moreover, the actual shape of the excited-state potential energy surface may induce nonexponential dynamics. Further efforts are needed in order to clarify how various environmental factors affect the structural and dynamical aspects of the nucleic acid base excited states