Bacterial and Fungal Keratitis in a Tertiary Care Hospital from Romania.

Infectious keratitis is a significant global problem that can lead to corneal blindness and visual impairments. This study aimed to investigate the etiology of infectious bacterial and fungal keratitis, identify the causative pathogens and their antimicrobial resistance patterns, and analyze the risk factors associated with the development of infectious keratitis. The study was observational and retrospective, involving 226 eyes from 223 patients presented at the Ophthalmology Clinic of the County Clinical Emergency Hospital of Craiova, Romania. The inclusion criteria included corneal ulceration/abscess/infiltrate present on slit-lamp examination and positive microbiological sampling for bacteria or fungi. The study found that the most common causes of infectious keratitis were coagulase-negative staphylococci (35.40%), Staphylococcus aureus (11.06%), and Pseudomonas aeruginosa (14.16%). The Gram-positive bacteria showed high resistance rates to penicillin, moderate rates to gentamycin and clindamycin, and low resistance to chinolones. The Gram-negative bacteria were highly resistant to ampicillin and amoxicillin-clavulanic acid, while third-generation cephalosporins, quinolones, and carbapenems were effective. Systemic antibiotics, such as vancomycine, piperacillin-tazobactam, amikacin, and ceftazidime, show promise against keratitis with low resistance rates, whereas carbapenems and topical aminoglycosides had higher resistance, leaving moxifloxacin as a potential topical option for Gram-positive bacteria and Pseudomonas aeruginosa, albeit with resistance concerns for Klebsiella spp. Although fungal keratitis was rare, Fusarium spp. and Candida albicans were the leading fungal pathogens, with incidences of 2.65% and 2.21%, respectively. Candida albicans was broadly susceptible to most antifungals, while Fusarium solani, Curvularia lunata, and Alternaria alternata exhibited resistance to many antifungals. Amphotericin B and caspofungin can be used as systemic antifungals in fungal keratitis. The study also identified risk factors for keratitis such as ocular trauma (65.92%, OR: 2.5), contact lens wear (11.94%, OR: 1.8), and corneal scarring/leukoma (10.17%, OR: 1.6). Keratitis was more frequent in individuals over 60 years old. The findings of this study have implications for the development of effective diagnostic, therapeutic, and preventive strategies for infectious keratitis.

The Role of the Fatty Liver Index (FLI) in the Management of Non-Alcoholic Fatty Liver Disease: A Systematic Review.

Currently, non-alcoholic fatty liver disease is the most common liver disease worldwide, with a prevalence of 32%. It is much more common among men (40%) and among patients with metabolic comorbidities such as obesity, diabetes and dyslipidemia. Being an asymptomatic disease, the diagnosis is often established on the basis of imaging methods, with an important role given to abdominal ultrasonography, computed tomography and magnetic resonance imaging. In order to facilitate diagnosis, experts have introduced a series of blood biomarkers. Two biomarker panels are currently validated for the diagnosis of non-alcoholic fatty liver disease: the fatty liver index, and the hepatic steatosis index. The fatty liver index has been in use in medical practice for over 17 years and has demonstrated its accuracy in various studies that compared it with other diagnostic methods, highlighted its role in screening patients with cardiovascular risk and validated the effects of different diets and drugs that are proposed for the treatment of the disease. In the management of non-alcoholic fatty liver disease, the fatty liver index is an important algorithm in the diagnosis and prognosis of patients with metabolic risk. Taking into account the diversity of drugs to be approved in the treatment of non-alcoholic fatty liver disease, the fatty liver index will become an effective tool in monitoring the effects of these therapies.

Factors Contributing to Surgical Site Infections: A Comprehensive Systematic Review of Etiology and Risk Factors.

Surgical site infections persist as a substantial concern within the realm of hospital-acquired infections. This enduring issue is further compounded by the mounting challenge of antibiotic resistance, a surge in surgical interventions, and the presence of comorbidities among patients. Thus, a comprehensive exploration of all discernible risk factors, as well as proactive preventive and prophylactic strategies, becomes imperative. Moreover, the prevalence of multidrug-resistant microorganisms has reached alarming proportions. Consequently, there is an acute need to investigate and scrutinize all potential therapeutic interventions to counter this burgeoning threat. Consequently, the primary objective of this review is to meticulously assess the origins and risk elements intertwined with surgical site infections across a diverse spectrum of surgical procedures. As the medical landscape continues to evolve, this critical analysis seeks to provide a nuanced understanding of the multi-faceted factors contributing to surgical site infections, with the overarching aim of facilitating more effective management and mitigation strategies. By exploring these dimensions comprehensively, we endeavor to enhance patient safety and the quality of surgical care in this era of evolving healthcare challenges.

COVID-19 infection: from stress-related cortisol levels to adrenal glands infarction.

Cortisol is a key element in acute stress including a severe infection. However, in coronavirus-associated disease, 20% of subjects experience hypocortisolemia due to direct or immune damage of pituitary and adrenal glands. One extreme form of adrenal insufficiency is found in 2∕3 of cases with viral and post-viral adrenal infarction (AI) (with∕without adrenal hemorrhage) that is mostly associated with a severe coronavirus disease 2019 (COVID-19) infection; it requires prompt glucocorticoid intervention. Some reports are incidental findings at computed tomography (CT)∕magnetic resonance imaging (MRI) scans for non-adrenal complications like pulmonary spreading and others are seen on post-mortem analysis. This is a review of PubMed-accessible, English papers focusing on AI in addition to the infection, between March 1, 2020 and November 1, 2021. Exclusion criteria were acute adrenal insufficiency without the histopathological (HP) and∕or imaging report of adrenal enlargement, necrosis, etc., respective adrenal failure due to pituitary causes, or non-COVID-19-related adrenal events. We identified a total of 84 patients (different levels of statistical evidence), as follows: a retrospective study on 51 individuals, two post-mortem studies comprising nine, respectively 12 patients, a case series of five subjects, seven single-case reports. HP aspects include necrosis associated with ischemia, cortical lipid degeneration (+/- focal adrenalitis), and infarcts at the level of adrenal cortex, blood clot into vessels, acute fibrinoid necrosis in arterioles and capsules, as well as subendothelial vacuolization. Collateral potential contributors to adrenal damage are thrombotic events, coagulation anomalies, antiphospholipid syndrome, endothelial dysfunction, severe COVID-19 infection with multiorgan failure, etc. Clinical picture is variable from acute primary adrenal insufficiency to asymptomatic or mild evolution, even a retrospective diagnostic; it may be a part of long COVID-19 syndrome; glucocorticoid therapy for non-adrenal considerations might mask cortisol deficient status due to AI∕hemorrhage. Despite its rarity, the COVID-19-associated AI/hemorrhage represents a challenging new chapter, a condition that is essential to be recognized due to its gravity since prompt intervention with glucocorticoid replacement is lifesaving.

A Rare Case of Endophthalmitis with Rhizobium radiobacter, Soon after a Resolved Keratitis: Case Report.

BACKGROUND: Rhizobium (Agrobacterium) species are plant aerobic bacteria, which in some cases can produce endophthalmitis in humans after corneal trauma. CASE PRESENTATION: A 42-year-old female patient presented in the Emergency Department of the Emergency County Hospital of Craiova, Romania, reporting pain, epiphora, and blurry vision in her right eye for about five days. This initial infectious keratitis episode was successfully resolved, but after 20 days she presented again after trauma with a leaf with corneal abscess. In the conjunctival secretion, R. radiobacter was identified. Despite antibiotherapy, the patient's state did not improve, and ultimately the eye was eviscerated. METHODS: A search was performed in the ProQuest, PubMed, and ScienceDirect databases for the terms Agrobacterium, Rhizobium, radiobacter, and eye. We eliminated non-human studies, editorials and commentaries, and non-relevant content, and excluded the duplicates. RESULTS: In total, 138 studies were initially obtained, and then we selected 26 studies for retrieval. After the selection process, we ended up including 17 studies in our analysis. Most studies reported R. radiobacter endophthalmitis after ocular surgical procedures or outdoor activities that involve exposure to soil. CONCLUSION: R. radiobacter is a rare cause of endophthalmitis after eye trauma that generally responds well to usual antibiotherapy, but occasionally can evolve to severe, leading to the loss of the eye.

TEM,CTX-M,SHV Genes in ESBL-Producing Escherichia coli and Klebsiella pneumoniae Isolated from Clinical Samples in a County Clinical Emergency Hospital Romania-Predominance of CTX-M-15.

BACKGROUND: CTX-M betalactamases have shown a rapid spread in the recent years among Enterobacteriaceae and have become the most prevalent Extended Spectrum Beta-Lactamases (ESBLs) in many parts of the world. The introduction and dissemination of antibiotic-resistant genes limits options for treatment, increases mortality and morbidity in patients, and leads to longer hospitalization and expensive costs. We aimed to identify the beta-lactamases circulating encoded by the genes blaCTX-M-15, blaSHV-1 and blaTEM-1 in Escherichia coli (E. coli) and Klebsiella pneumoniae (K. pneumoniae) strains. Furthermore, we established the associated resistance phenotypes among patients hospitalized in the Intensive Care Unit (ICU) from County Clinical Emergency Hospital of Craiova, Romania. METHODS: A total of 46 non-duplicated bacterial strains (14 strains of E. coli and 32 strains of K. pneumoniae), which were resistant to ceftazidime (CAZ) and cefotaxime (CTX) by Kirby-Bauer disk diffusion method, were identified using the automated VITEK2 system. Detection of ESBL-encoding genes and other resistance genes was carried out by PCR. RESULTS: E. coli strains were resistant to 3rd generation cephalosporins and moderately resistant to quinolones, whereas K. pneumoniae strains were resistant to penicillins, cephalosporins, and sulfamides, and moderately resistant to quinolones and carbapenems. Most E. coli strains harbored blaCTX-M-15 gene (13/14 strains), a single strain had the blaSHV-1 gene, but 11 strains harbored blaTEM-1 gene. The mcr-1 gene was not detected. We detected tet(A) gene in six strains and tet(B) in one strain. In K. pneumoniae strains we detected blaCTX-M-15 in 23 strains, blaSHV-1 in all strains and blaTEM-1 in 14 strains. The colistin resistance gene mcr-1 was not detected. The tetracycline gene tet(A) was detected in 11 strains, but the gene tet(B) was not detected in any strains. CONCLUSIONS: The development in antibiotic resistance highlights the importance of establishing policies to reduce antibiotic use and improving the national resistance surveillance system in order to create local antibiotic therapy guidelines.

The New Entity of Subacute Thyroiditis amid the COVID-19 Pandemic: From Infection to Vaccine.

This is a review of full-length articles strictly concerning subacute thyroiditis (SAT) in relation to the SARS-CoV-2 virus infection (SVI) and COVID-19 vaccine (COV) that were published between the 1st of March 2020 and the 21st of March 2022 in PubMed-indexed journals. A total of 161 cases were reported as follows: 81 cases of SAT-SVI (2 retrospective studies, 5 case series, and 29 case reports), 80 respective cases of SAT-COV (1 longitudinal study, 14 case series, 17 case reports; also, 1 prospective study included 12 patients, with 6 patients in each category). To our knowledge, this represents the largest cohort of reported cases until the present time. SAT-SVI was detected in adults aged between 18 and 85 years, mostly in middle-aged females. SAT-COVID-19 timing classifies SAT as viral (synchronous with infection, which is an original feature of SATs that usually follow a viral infection) and post-viral (during the recovery period or after infection, usually within 6 to 8 weeks, up to a maximum 24 weeks). The clinical spectrum has two patterns: either that accompanying a severe COVID-19 infection with multi-organ spreading (most frequent with lung involvement) or as an asymptomatic infection, with SAT being the single manifestation or the first presentation. Either way, SAT may remain unrecognized. Some data suggest that more intense neck pain, more frequent fever, and more frequent hypothyroidism at 3 months are identified when compared with non-SAT-SVI, but other authors have identified similar presentations and outcomes. Post-COVID-19 fatigue may be due to residual post-SAT hypothyroidism. The practical importance of SAT-SVI derives from the fact that thyroid hormone anomalies aggravate the general status of severe infections (particular concerns being tachycardia/arrhythmias, cardiac insufficiency, and ischemic events). If misdiagnosed, SAT results in unnecessary treatment with anti-thyroid drugs or even antibiotics for fever of unknown cause. Once recognized, SAT does not seem to require a particular approach when compared with non-COVID-19 cases, including the need for glucocorticoid therapy and the rate of permanent hypothyroidism. A complete resolution of thyroid hormone anomalies and inflammation is expected, except for cases with persistent hypothyroidism. SAT-COV follows within a few hours to a few weeks, with an average of 2 weeks (no particular pattern is related to the first or second vaccine dose). Pathogenesis includes molecular mimicry and immunoinflammatory anomalies, and some have suggested that this is part of ASIA syndrome (autoimmune/inflammatory syndrome induced by adjuvants). An alternative hypothesis to vaccine-related increased autoimmunity is vaccine-induced hyperviscosity; however, this is supported by incomplete evidence. From what we know so far concerning the risk factors, a prior episode of non-SVI-SAT is not associated with a higher risk of SAT-COV, nor is a previous history of coronavirus infection by itself. Post-vaccine SAT usually has a less severe presentation and a good outcome. Generally, the female sex is prone to developing any type of SAT. HLA susceptibility is probably related to both new types of SATs. The current low level of statistical evidence is expected to change in the future. Practitioners should be aware of SAT-COV, which does not restrict immunization protocols in any case.

Role of antioxidants and oxidative stress in the evolution of acute pancreatitis (Review).

Acute pancreatitis (AP) is a severe disease with a high prevalence and 3 to 15% mortality worldwide, which can represent an important challenge for the physician. Oxidative stress and antioxidants are involved in AP progression. The mechanisms responsible for the onset and progression of AP are still poorly understood. Previous studies have highlighted the important contribution of antioxidants and oxidative stress in AP. The existence of a relationship between oxidative stress and antioxidants in AP is unquestionable, although a more accurate understanding of the mechanistic pathways involved is required to create a solid basis for potential prevention or treatment strategies. Further investigation is needed to clarify the role of antioxidant status and the severity of AP and to determine the association between oxidative stress and pancreatic enzyme activities. Antioxidant therapy may represent an interesting option for the management of patients with AP, although additional information about the effectiveness of this potential treatment is required.

COVID-19 and Artificial Intelligence: An Approach to Forecast the Severity of Diagnosis.

(1) Background: The new SARS-COV-2 pandemic overwhelmed intensive care units, clinicians, and radiologists, so the development of methods to forecast the diagnosis' severity became a necessity and a helpful tool. (2) Methods: In this paper, we proposed an artificial intelligence-based multimodal approach to forecast the future diagnosis' severity of patients with laboratory-confirmed cases of SARS-CoV-2 infection. At hospital admission, we collected 46 clinical and biological variables with chest X-ray scans from 475 COVID-19 positively tested patients. An ensemble of machine learning algorithms (AI-Score) was developed to predict the future severity score as mild, moderate, and severe for COVID-19-infected patients. Additionally, a deep learning module (CXR-Score) was developed to automatically classify the chest X-ray images and integrate them into AI-Score. (3) Results: The AI-Score predicted the COVID-19 diagnosis' severity on the testing/control dataset (95 patients) with an average accuracy of 98.59%, average specificity of 98.97%, and average sensitivity of 97.93%. The CXR-Score module graded the severity of chest X-ray images with an average accuracy of 99.08% on the testing/control dataset (95 chest X-ray images). (4) Conclusions: Our study demonstrated that the deep learning methods based on the integration of clinical and biological data with chest X-ray images accurately predicted the COVID-19 severity score of positive-tested patients.

Assessment of Deep Learning Methods for Differentiating Autoimmune Disorders in Ultrasound Images.

At present, deep learning becomes an important tool in medical image analysis, with good performance in diagnosing, pattern detection, and segmentation. Ultrasound imaging offers an easy and rapid method to detect and diagnose thyroid disorders. With the help of a computer-aided diagnosis (CAD) system based on deep learning, we have the possibility of real-time and non-invasive diagnosing of thyroidal US images. This paper proposed a study based on deep learning with transfer learning for differentiating the thyroidal ultrasound images using image pixels and diagnosis labels as inputs. We trained, assessed, and compared two pre-trained models (VGG-19 and Inception v3) using a dataset of ultrasound images consisting of 2 types of thyroid ultrasound images: autoimmune and normal. The training dataset consisted of 615 thyroid ultrasound images, from which 415 images were diagnosed as autoimmune, and 200 images as normal. The models were assessed using a dataset of 120 images, from which 80 images were diagnosed as autoimmune, and 40 images diagnosed as normal. The two deep learning models obtained very good results, as follows: the pre-trained VGG-19 model obtained 98.60% for the overall test accuracy with an overall specificity of 98.94% and overall sensitivity of 97.97%, while the Inception v3 model obtained 96.4% for the overall test accuracy with an overall specificity of 95.58% and overall sensitivity of 95.58.

Study of Cognitive Disfunctions in Thyroid Pathology.

Thyroid pathology is characterized by abnormal values of thyroid hormones that can affect the brain and can lead to cognitive impairment (attention, memory, mood), depression and anxiety. The aim of the study is to evaluate the association between the cognitive disorders and thyroid disease and the link between thyroid hormone levels FT4 and TSH in depression and anxiety. We included 130 individuals from Endocrinology Clinic of Craiova, over a period of 6 years (2014-2020), none of whom was taking thyroid medication and antidepressants. The most important symptom found in thyroid pathology is depression, which occurs in those with long-lasting illness. We obtained that 45.38% of the cases were diagnosed with depression and 46.92% with anxiety. Depressive symptoms were assessed with Hamilton scale and anxiety symptoms with the Beck scale. Regarding the impaired cognitive function, we found it in 34.7% of cases of hypothyroidism (loss of memory / lack of concentration) and for the cases with hyperthyroidism, we found changes in 51,42%.

Prevalence and Antimicrobial Resistance of Klebsiella Strains Isolated from a County Hospital in Romania.

The study evaluated the evolution of the incidence of infections with Klebsiella in the County Clinical Emergency Hospital of Craiova (SCJUC), Romania. Also, we monitored antibiotic resistance over more than two years and detected changes in resistance to various antimicrobial agents. Our study included 2062 patients (823 women and 1239 men) hospitalised in SCJUC during the period 1st of September 2017 to 30 June 2019. In 458 patients (22.21%) from the 2062 total patients, the collected samples (1116) were positive and from those, we isolated 251 strains of Klebsiella spp. We conducted a longitudinal analysis of the prevalence of Klebsiella spp. over calendar months, which showed a prevalence in surgical wards that ranged between 5.25% and 19.49% in June 2018, while in medical wards the variation was much wider, between 5.15% and 17.36% in April 2018. Klebsiella spp. strains showed significant resistance to Amoxicillin/Clavulanate, Aztreonam and Cephalosporins such as Ceftriaxone, Ceftazidime and Cefepime. We examined the possible link with the consumption of antibiotics in the same month by performing a multiple linear regression analysis. The evolution of antibiotic resistance in Klebsiella was correlated with the variation of resistance in other bacteria, which suggests common resistance mechanisms in the hospital environment. By performing the regression for dependency between antibiotic resistance and antibiotic consumption, we observed some correlations between antibiotic consumption and the development of antibiotic resistance after 1, 2 and even 3 months (e.g., resistance to meropenem was influenced by the consumption in the hospital ward of imipenem 1 month and two months before, but only 1 month before by the consumption of meropenem). The clustering of strains showed filiation between multiresistant Klebsiella spp. strains isolated from specific patients from the ICU. The evolution of prevalence and antibiotic resistance in Klebsiella correlated with the resistance in other bacteria, which suggest common resistance mechanisms in the hospital environment, and also with the consumption of antibiotics.

The Study of Clinical and Biochemical Parameters in Assessing the Response to the Antiviral Therapy in the Chronic Viral Hepatitis B.

Background and Objectives: Hepatitis B virus infection remains a major public health concern. The interaction between hepatitis B virus (HBV) hepatitis B virus and the host inflammatory response is an important contributing factor driving liver damage and diseases outcomes. The management of chronic hepatitis B virus infection is an area of massive unmet clinical need worldwide. Our primary aim for this study was to evaluate biological response rates and sustained virological response in patients with chronic hepatitis B treated with Peg-IFN α-2a/b. The second aim of the study was the identification of metabolic changes and insulin resistance. Materials and Methods: We enrolled in this study 166 patients who fulfilled all inclusion and exclusion criteria. These treatment-naive patients with chronic HBV were treated with Pegylated Interferon α-2a/b. HBV infection was defined by the presence of HBV serological markers (HBsAg, anti-HBsAb, anti-HBcAb, HBeAg, anti HBeAb) by Enzyme-Linked Immuno Sorbent Assay (ELISA) and serum HBV-DNA levels were estimated by a commercially available quantitative polymerase chain reaction (PCR) assay. Results: Patients' recovery progress has been evaluated by determining the following: age, gender; biochemical tests; alanine aminotransferase, aspartate aminotransferase; serological assays for HBV serological markers (HBsAg, anti-HBsAc/Ab, anti-HBcAc/Ab, HBeAg, anti HBeAc/Ab); molecular tests to detect viral particles, testing for HBV DNA (PCR) to confirm the diagnosis and quantify the number of viral copies in the blood (viremia); liver ultrasound-performed through epigastric and intercostal approach (transversal and longitudinal sections). Conclusions: Our results indicated that only HOMA index values, that of fasting insulin, together with baseline HBV DNA, alanine aminotransferase values, mean blood glucose at the beginning of treatment may be predictive of the early viral response in chronic hepatitis B.

Intelligent Diagnosis of Thyroid Ultrasound Imaging Using an Ensemble of Deep Learning Methods.

Background and Objectives: At present, thyroid disorders have a great incidence in the worldwide population, so the development of alternative methods for improving the diagnosis process is necessary. Materials and Methods: For this purpose, we developed an ensemble method that fused two deep learning models, one based on convolutional neural network and the other based on transfer learning. For the first model, called 5-CNN, we developed an efficient end-to-end trained model with five convolutional layers, while for the second model, the pre-trained VGG-19 architecture was repurposed, optimized and trained. We trained and validated our models using a dataset of ultrasound images consisting of four types of thyroidal images: autoimmune, nodular, micro-nodular, and normal. Results: Excellent results were obtained by the ensemble CNN-VGG method, which outperformed the 5-CNN and VGG-19 models: 97.35% for the overall test accuracy with an overall specificity of 98.43%, sensitivity of 95.75%, positive and negative predictive value of 95.41%, and 98.05%. The micro average areas under each receiver operating characteristic curves was 0.96. The results were also validated by two physicians: an endocrinologist and a pediatrician. Conclusions: We proposed a new deep learning study for classifying ultrasound thyroidal images to assist physicians in the diagnosis process.

A Cross-Sectional Study to Assess Thyroid Function in Infants and Children in a City from South-Western Romania.

Thyroid hormones are critical regulators of growth, myelination of the nervous system, metabolism, and organ function. The most prevalent endocrinopathies in childhood are related to thyroid disorders. Thyroid problems in children and adolescents have a significantly different etiology and clinical presentation than in adults. Thus, pediatric medical care involves an understanding of the unique features of thyroid function and dysfunction during childhood and adolescence. The etiology and clinical manifestations of thyroid disorders in children and adolescents are vastly different from those in adults. The particular aspects of thyroid function and malfunction in childhood and adolescence are hence part of pediatric medical therapy. To prevent persistent nervous system damage and developmental problems, it is vital to recognize and treat thyroid dysfunction in neonates as early as possible. The purpose of the research was to understand more how children's thyroid problems function, structure, and prevalence. The research examined 30 children under the age of 16 years who had symptoms that were linked to thyroid problems. In addition to demographic and family information, thyroid ultrasounds and blood samples for the detection of T3, T4, and TSH were obtained. Females surpassed males by a small majority (2.33:1 ratio).Out of the total children included in the study, 14(46.7%) cases for autoimmune thyroiditis, 2(6.67%) cases for congenital hypothyroidism, 1(3.33%) case for hyperthyroidism, 1(3.33%) case for hyperthyroidism-Graves disease, 8(26.7%) cases for hypothyroidism and 4(13.3%) cases for subclinical hypothyroidism.

Skin Diseases Classification Using Deep Leaning Methods.

Due to the high incidence of skin tumors, the development of computer aided-diagnosis methods will become a very powerful diagnosis tool for dermatologists. The skin diseases are initially diagnosed visually, through clinical screening and followed in some cases by dermoscopic analysis, biopsy and histopathological examination. Automatic classification of dermatoscopic images is a challenge due to fine-grained variations in lesions. The convolutional neural network (CNN), one of the most powerful deep learning techniques proved to be superior to traditional algorithms. These networks provide the flexibility of extracting discriminatory features from images that preserve the spatial structure and could be developed for region recognition and medical image classification. In this paper we proposed an architecture of CNN to classify skin lesions using only image pixels and diagnosis labels as inputs. We trained and validated the CNN model using a public dataset of 10015 images consisting of 7 types of skin lesions: actinic keratoses and intraepithelial carcinoma/Bowen disease (akiec), basal cell carcinoma (bcc), benign lesions of the keratosis type (solar lentigine/seborrheic keratoses and lichen-planus like keratosis, bkl), dermatofibroma (df), melanoma (mel), melanocytic nevi (nv) and vascular lesions (angiomas, angiokeratomas, pyogenic granulomas and hemorrhages, vasc).

Predictors of early and sustained virological response of viral hepatitis C.

Due to complex interplay between host and viral factors, pathogenesis of chronic hepatitis C (CHC) is considered a challenging issue. Infection with hepatitis C virus (HCV) is not confined only to liver but can induce disturbances in many other organs and systems. Our primary aim for this study was to evaluate biological response rates and sustained virological response (SVR) in patients diagnosed with CHC, treated with Interferon-alpha (IFN-α), Pegylated (PEG)-IFN-α2a or -α2b plus Ribavirin. The second aim of the study was the identification of predictive factors for a favorable response to antiviral therapy in patients diagnosed with CHC. We enrolled in this study 210 patients diagnosed with CHC who have accomplished all inclusion and exclusion criteria, treated with PEG-IFN plus Ribavirin. Patients' recovery progress has been evaluated by determining: age, gender; biochemical tests: alanine aminotransferase (ALT), aspartate aminotransferase (AST); serological assays - detect anti-HCV antibody and molecular assays - detect, quantify and/or characterize hepatitis C viral load (ribonucleic acid) (HCV-RNA); liver histopathological (HP) examination. According to their response to treatment, they were classified into responders (n=145) and non-responders (n=65). Liver biopsies were histopathologically evaluated for necroinflammatory grade and fibrosis stage according to the modified Ishak and Metavir scoring systems for chronic hepatitis. Demographic, laboratory, and HP results were introduced in statistical analysis. These parameters were included in area under curve (AUC) analysis in order to estimate their degree of influence on getting early virological response (EVR) and SVR. Our study demonstrates that factors connected to treatment failure in CHC are linked to older age, high hepatitis C viral load, and impaired glucose tolerance at beginning of treatment [high fasting glucose and insulin, high homeostatic model assessment of insulin resistance (HOMA-IR) index] and also to liver histology features (high fibrosis score, liver steatosis, iron infiltration, and more or less high necroinflammatory activity). Analyzing results of our study shows that HOMA-IR index, serum insulin levels, baseline HCV-RNA, baseline mean blood glucose and HP score like Ishak fibrosis score, steatosis score and liver iron score may have a predictive value for obtaining an EVR in patients diagnosed with CHC.