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A suitable, non-invasive biomarker for assessing endoscopic disease activity (EDA) in ulcerative colitis (UC) has yet to be identified. Our study aimed to develop a cost-effective and non-invasive machine learning (ML) method that utilizes the cost-free Inflammatory Bowel Disease Questionnaire (IBDQ) score and low-cost biological predictors to estimate EDA. Four random forest (RF) and four multilayer perceptron (MLP) classifiers were proposed. The results show that the inclusion of IBDQ in the list of predictors that were fed to the models improved accuracy and the AUC for both the RF and the MLP algorithms. Moreover, the RF technique performed noticeably better than the MLP method on unseen data (the independent patient cohort). This is the first study to propose the use of IBDQ as a predictor in an ML model to estimate UC EDA. The deployment of this ML model can furnish doctors and patients with valuable insights into EDA, a highly beneficial resource for individuals with UC who need long-term treatment.

BACKGROUND Many scores have been suggested to assess the severity of acute pancreatitis upon onset. The extrapancreatic necrosis volume is a novel, promising score that appears to be superior to other scores investigated so far. AIM To evaluate the discriminatory power of extrapancreatic necrosis volume to identify severe cases of acute pancreatitis. METHODS A total of 123 patients diagnosed with acute pancreatitis at Institute of Gastroenterology and Hepatology, St Spiridon Hospital between January 1, 2017 and December 31, 2019 were analyzed retrospectively. Pancreatitis was classified according to the revised Atlanta classification (rAC) as mild, moderate, or severe. Severity was also evaluated by computed tomography and classified according to the computed tomography severity index (CTSI) and the modified CTSI (mCTSI). The results were compared with the extrapancreatic volume necrosis to establish the sensitivity and specificity of each method. RESULTS The CTSI and mCTSI imaging scores and the extrapancreatic necrosis volume were highly correlated with the severity of pancreatitis estimated by the rAC (r = 0.926, P < 0.001 and r = 0.950, P < 0.001; r = 0.784, P < 0.001, respectively). The correlation of C-reactive protein with severity was positive but not as strong, and was not significant (r = 0.133, P = 0.154). The best predictor for the assessment of severe pancreatitis was the extrapancreatic necrosis volume [area under the curve (AUC) = 0.993; 95% confidence interval (CI): 0.981-1.005], with a 99.5% sensitivity and 99.0% specificity at a cutoff value of 167 mL, followed by the mCTSI 2007 score (AUC = 0.972; 95%CI: 0.946-0.999), with a 98.0% sensitivity and 96.5% specificity, and the CTSI 1990 score (AUC = 0.969; 95%CI: 0.941-0.998), with a 97.0% sensitivity and 95.0% specificity. CONCLUSION Radiological severity scores correlate strongly and positively with disease activity. Extrapancreatic necrosis volume shows the best diagnostic accuracy for severe cases.

Background Colonoscopy with biopsy is the "gold" standard for evaluating disease activity in inflammatory bowel diseases (IBD). Current research is geared toward finding non-invasive, cost-efficient methods that estimate disease activity. We aimed to develop a neural network (NN) model for the non-invasive prediction of histologic activity in IBD using routinely available clinical-biological parameters. Methods Standard clinical-biological parameters and histologic activity from 371 ulcerative colitis (UC) and 115 Crohn's disease (CD) patient records were collected. A training set, a test set, and a validation set were used for building/validating 2 models for each disease. All models had binary output predicting the active/inactive histologic disease status. For both diseases, the first model used both clinical and biological inputs, while the second used only biological data. Results First UC model obtained an accuracy of 95.59% on the test set and 96.67% on the validation set. The second UC model achieved accuracies of 88.24% and 86.67% on the test and validation sets, respectively. The First CD classifier resulted in 90.48% accuracy on the test set and 91.67% on the validation set. Finally, the second CD classifier obtained an accuracy of 85.71% on the test set and 91.67% on the validation set. Conclusions An accurate and non-invasive artificial intelligence system to predict histologic disease activity in IBD is designed. Our models achieved similar or better results compared to the documented performance of fecal calprotectin (the best non-invasive IBD biomarker to date). Given these favorable results, we anticipate the future utility in the clinical setting of a non-invasive disease activity prediction.

The COVID-19 pandemic rapidly became a worldwide healthcare emergency affecting millions of people, with poor outcomes for patients with chronic conditions and enormous pressure on healthcare systems. Pulmonary fibrosis (PF) has been cited as a risk factor for a more severe evolution of COVID-19, primarily because its acute exacerbations are already associated with high mortality. We reviewed the available literature on biochemical, pathophysiological, and pharmacological mechanisms of PF and COVID-19 in an attempt to foresee the particular risk of infection and possible evolution of PF patients if infected with SARS-COV-2. We also analyzed the possible role of medication and risk factors (such as smoking) in the disease’s evolution and clinical course. We found out that there is a complexity of interactions between coexisting idiopathic pulmonary fibrosis/interstitial lung disease (ILD) and COVID-19 disease. Also, patients recovering from severe COVID-19 disease are at serious risk of developing PF. Smokers seem to have, in theory, a chance for a better outcome if they develop a severe form of COVID-19 but statistically are at much higher risk of dying if they become critically ill.

Background. The purpose of this review is to depict current research and impact of artificial intelligence/machine learning (AI/ML) algorithms on dialysis and kidney transplantation. Published studies were presented from two points of view: What medical aspects were covered? What AI/ML algorithms have been used? Methods. We searched four electronic databases or studies that used AI/ML in hemodialysis (HD), peritoneal dialysis (PD), and kidney transplantation (KT). Sixty-nine studies were split into three categories: AI/ML and HD, PD, and KT, respectively. We identified 43 trials in the first group, 8 in the second, and 18 in the third. Then, studies were classified according to the type of algorithm. Results. AI and HD trials covered: (a) dialysis service management, (b) dialysis procedure, (c) anemia management, (d) hormonal/dietary issues, and (e) arteriovenous fistula assessment. PD studies were divided into (a) peritoneal technique issues, (b) infections, and (c) cardiovascular event prediction. AI in transplantation studies were allocated into (a) management systems (ML used as pretransplant organ-matching tools), (b) predicting graft rejection, (c) tacrolimus therapy modulation, and (d) dietary issues. Conclusions. Although guidelines are reluctant to recommend AI implementation in daily practice, there is plenty of evidence that AI/ML algorithms can predict better than nephrologists: volumes, Kt/V, and hypotension or cardiovascular events during dialysis. Altogether, these trials report a robust impact of AI/ML on quality of life and survival in G5D/T patients. In the coming years, one would probably witness the emergence of AI/ML devices that facilitate the management of dialysis patients, thus increasing the quality of life and survival.

The altered magnesium status in inflammatory bowel disease (IBD) patients may have a significant clinical imprint considering its role in cell signaling and genomic stability, as well as its involvement in IBD patients’ fatigue. Our study pioneers the investigation of magnesium hair concentration patterns in an adult population of IBD patients. The hair magnesium concentration in IBD patients is compared to healthy controls in order to identify correlations between the magnesium status and relevant parameters related to disease activity, psychological status, and sleep quality. We report a significantly lower hair magnesium concentration within the IBD group compared to healthy controls (95%CI: 0.006–0.062; p = 0.017) and lower levels in CD compared to UC (95%CI: −0.061–−0.002; p = 0.038). We identified a borderline statistical significance between the hair magnesium concentration and UC disease activity (95%CI; −0.679–0.008; p = 0.055) and a significantly lower magnesium concentration in patients who reported increased sleep latency (95%CI −0.65–−0.102; p = 0.011) or decreased sleep duration (95%CI −0.613–−0.041; p = 0.028). Our results advance several hypotheses with substantial clinical impact to be confirmed in future studies. Magnesium levels appear to be modified in IBD patients, which suggests it either plays a primary role in disease pathophysiology or a is result of the disease’s evolution. Magnesium could be used in predictive models for clinical/subclinical disease activity. Moreover, magnesium supplementation may improve IBD evolution and sleep quality for patients with a deficit of this mineral. However, confirmatory evidence-based studies are needed to generate specific dosing, time of supplementation, and optimum monitoring of magnesium status in IBD patients.

The altered magnesium status in inflammatory bowel disease (IBD) patients may have a significant clinical imprint considering its role in cell signaling and genomic stability, as well as its involvement in IBD patients’ fatigue. Our study pioneers the investigation of magnesium hair concentration patterns in an adult population of IBD patients. The hair magnesium concentration in IBD patients is compared to healthy controls in order to identify correlations between the magnesium status and relevant parameters related to disease activity, psychological status, and sleep quality. We report a significantly lower hair magnesium concentration within the IBD group compared to healthy controls (95%CI: 0.006–0.062; p = 0.017) and lower levels in CD compared to UC (95%CI: −0.061–−0.002; p = 0.038). We identified a borderline statistical significance between the hair magnesium concentration and UC disease activity (95%CI; −0.679–0.008; p = 0.055) and a significantly lower magnesium concentration in patients who reported increased sleep latency (95%CI −0.65–−0.102; p = 0.011) or decreased sleep duration (95%CI −0.613–−0.041; p = 0.028). Our results advance several hypotheses with substantial clinical impact to be confirmed in future studies. Magnesium levels appear to be modified in IBD patients, which suggests it either plays a primary role in disease pathophysiology or a is result of the disease’s evolution. Magnesium could be used in predictive models for clinical/subclinical disease activity. Moreover, magnesium supplementation may improve IBD evolution and sleep quality for patients with a deficit of this mineral. However, confirmatory evidence-based studies are needed to generate specific dosing, time of supplementation, and optimum monitoring of magnesium status in IBD patients.

Background and Objectives: Anemia is the most frequent complication of inflammatory bowel diseases. Clinically, anemia can affect important quality-of-life (QoL) components, such as exercise capacity, cognitive function, and the ability to carry out social activities. The disease activity has a significant impact on QoL, mainly due to clinical manifestations, which are more severe during the periods of disease activity. Our aim was to estimate the impact of anemia on QoL in patients with Crohn’s disease. Material and Methods. We made a prospective study on 134 patients with Crohn’s disease (CD) in a Romanian tertiary center. The CD diagnosis was established by colonoscopy and histopathological examination. In particular cases, additional examinations were required (small bowel capsule endoscopy, computed tomography enterography, and magnetic resonance enterography). Anemia was defined according to the World Health Organization’s definition, the activity of the disease was assessed by Crohn’s disease activity index (CDAI) score, and the QoL was evaluated by Inflammatory Bowel Disease Questionnaire 32 (IBDQ 32). Results: 44.8% patient had anemia, statistically related to the activity of the disease and corticoids use. We found a strong association between QoL and disease activity on all four sub-scores: patients with more severe activity had a significantly lower IBDQ (260.38 ± 116.96 vs. 163.85 ± 87.20, p = 0.001) and the presence of anemia (127.03 vs. 148.38, p = 0.001). In multiple regression analyses, both disease activity and anemia had an impact on the QoL. Conclusions: Anemia has high prevalence in the CD in northeastern region of Romania. Anemia was more common in female patients, in patients undergoing corticosteroid treatment, and in those with active disease. Both anemia and disease activity had a strong negative and independent impact on QoL.

The World Health Organization warns about the threat of the COVID-19 sixth wave. Our aim was to propose the first validated Romanian questionnaire to assess people’s level of education and attitudes towards general measures to protect against COVID-19 infection. Our study was conducted on a sample of 194 people. The first version of the questionnaire consisted of 40 items. Items that did not meet psychometric criteria were removed. Latent components/factors were identified through exploratory factorial analysis (EFA). The Cronbach’s alpha coefficient was used to assess internal fidelity. The EFA identified three factors. Factor 1 was named “Compliance with protective measures”, factor 2 was “Attitudes toward vaccination” and factor 3 was “Attitudes regarding potential COVID-19 therapies”. The final version of the questionnaire consists of 16 items. The test’s final score predicted the presence of vaccination with an accuracy of 0.773. The questionnaire score, the diagnosis of diabetes, the advice provided by healthcare workers and the medical profession proved to be significant predictors of vaccination. The implementation of our questionnaire within national programs could identify populational areas that need specific interventions to reach vaccination targets and prevent a full-blown sixth wave of the COVID-19 pandemic in Romania.

(1) Background: Data suggest that patients with coronary chronic total occlusion (CTO) managed with percutaneous coronary intervention (PCI) could have better outcomes than those treated with optimal medical therapy alone. We aimed to systematically review dedicated scoring systems used to predict successful PCI in patients with CTO. (2) Methods: Electronic databases of MEDLINE (PubMed), Embase, and Cochrane were searched. (3) Results: 32 studies were included. We provided insights into all available predictive models of PCI success in CTO including predictive performance, validations, and comparisons between different scores and models’ limitations. Considering the differences in the population included, coronary lesions, and techniques applied across clinical studies, the most used scores displayed a modest to good predictive value, as follows: J-CTO (AUC, 0.55–0.868), PROGRESS-CTO (AUC, 0.557–0.788), CL (AUC, 0.624–0.800), CASTLE (AUC, 0.633–0.68), and KCCT (AUC, 0.703–0.776). As PCI for CTO is one of the most complex interventions, using dedicated scoring systems could ensure an adequate case selection as well as preparation for an appropriate recanalization technique in order to increase chances of successful procedure. (4) Conclusion: Clinical models appear to be valuable tools for the prediction of PCI success in CTO patients. Clinicians should be aware of the limitations of each model and should be able to correctly select the most appropriate score according to real-life case particularities such as lesion complexity and operator experience in order to maximize success and achieve the best patients’ outcomes.

Background and objectives: cardiovascular complications (CVC) are the leading cause of death in patients with chronic kidney disease (CKD). Standard cardiovascular disease risk prediction models used in the general population are not validated in patients with CKD. We aim to systematically review the up-to-date literature on reported outcomes of computational methods such as artificial intelligence (AI) or regression-based models to predict CVC in CKD patients. Materials and methods: the electronic databases of MEDLINE/PubMed, EMBASE, and ScienceDirect were systematically searched. The risk of bias and reporting quality for each study were assessed against transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) and the prediction model risk of bias assessment tool (PROBAST). Results: sixteen papers were included in the present systematic review: 15 non-randomized studies and 1 ongoing clinical trial. Twelve studies were found to perform AI or regression-based predictions of CVC in CKD, either through single or composite endpoints. Four studies have come up with computational solutions for other CV-related predictions in the CKD population. Conclusions: the identified studies represent palpable trends in areas of clinical promise with an encouraging present-day performance. However, there is a clear need for more extensive application of rigorous methodologies. Following the future prospective, randomized clinical trials, and thorough external validations, computational solutions will fill the gap in cardiovascular predictive tools for chronic kidney disease.

Early prognosis of severe disease and preventive actions hang around as the mainstay in managing the novel SARS-COV-2 outbreak due to the lack of robust therapeutic strategies. Krebs von den Lungen-6 (KL-6 or KL-6/MUC1) is a relatively new discovered transmembrane mucoprotein that was shown to be a good predictor of disease severity in interstitial lung diseases (ILD). We aimed to systematically research the literature in order to assess the relationship between the KL-6 biomarker and prognosis of SARS-CoV-2 infection. A literature search was performed in PubMed, Embase, and Cochrane library databases from inception to 8 March 2021. After eligibility assessment, eight studies were finally included in the present systematic review. All included studies are observational and single-center. The data gathered suggests the importance of prognostic implications of KL-6 in COVID-19 as patients with a more severe disease had significantly higher levels of KL-6 at admission. Moreover, the KL-6 biomarker was associated with COVID-19 severity, lung lesion areas on computed tomography, pulmonary fibrosis, and coagulation disorders. The association with mortality is unclear and needs further research. More extensive trials are required to prove that facile, inexpensive, and good predictors of severe outcomes, such as KL-6, could be safely integrated into the clinical decision-making in patients with COVID-19.

Background and Aims: Both inflammatory bowel diseases (IBD) and ankylosing spondylitis (AS) can be considered chronic immune disorders sharing common etiopathogenetic mechanisms. Changes in the composition of the intestinal microbiota, which can lead to an abnormal mucosal response, could be the missing link between these two diseases. Our study evaluate the composition of intestinal microbiota and to characterize gut dysbiosis in patients with IBD and AS. Methods: We conducted a prospective case-control study that enrolled 124 patients [20 Crohn’s disease (CD), 27 ulcerative colitis (UC), 28 AS, 17 IBD + AS and 32 controls). Intestinal microbiota analysis was performed by real-time polymerase chain reaction in stool samples. Results: The total quantity of bacteria was decreased in all investigated groups compared to the control group. In studied groups, we noticed an increased percentage of Bacteroides and Escherichia coli (E.coli) and a decreased percentage of Clostridium coccoides, Clostridium leptum, and Faecalibacterium prausnitzii compared to the control group. The percentages of Bifidobacterium (p=0.010) as well as Lactobacillus group (p=0.023) were higher in the L3 form of CD patients. In the E2 form of UC, the quantity of Bacteroides was much higher compared to the E3 form (p=0.004). In AS patients, significant correlations were observed only for the Bifidobacterium species, significantly increased in the axial form compared to peripheral disease (p=0.035). Statistically significant correlations were demonstrated between the Crohn Disease Activity Index score and the total bacterial group (p=0.023, r=-0.507), respectively Bacteroides (p=0.021, r=-0.511) and between the Mayo score and Lactobacillus (p=0.001), respectively E. coli (p=0.001). In IBD + AS group, the Crohn Disease Activity Index score was inversely correlated with the total bacterial group (p=0.010) and directly correlated with Lactobacillus (p=0.047). Conclusions: Intestinal dysbiosis is associated with both IBD and AS. In the association of IBD with AS, dysbiosis is intermediate, but it is associated with the more severe articular disease. Bifidobacterium and Lactobacillus (commonly used as probiotics!) were found to be increased in the association between active IBD and active AS. Further studies are needed to understand how dysbiosis regulates the gut immune system and contributes to intestinal and articular inflammation.

Coinfection with both SARS-CoV-2 and influenza viruses seems to be a real and severe problem. However, coinfection is far from a simple matter, and cannot be considered having more unfavorable outcomes as a direct consequence. In reality, the aftermath is powerfully nuanced by the presence of risk factors and specific molecular mechanisms. Our objective was to raise awareness around the unpredictable association between COVID-19 pandemics and the upcoming flu season, and make arguments about the need to develop new routine testing protocols for both viruses, at least during the period with an expected high incidence. Our reasoning is built around the various impacts that the whole range of risk groups, common immunological mechanisms, and complex interactions, such as influenza vaccination, will have on patients’ prognosis. We show that the more flawed clinical course is due to managing only one of the infections (and, subsequently, neglecting the other condition).

Background and objectives: The biological treatment is a promising therapeutic option for ulcerative colitis (UC) patients, being able to induce subclinical and long-term remission. However, the relatively high costs and the potential toxicity have led to intense debates over the most appropriate criteria for starting, stopping, and managing biologics in UC. Our aim was to build a machine learning (ML) model for predicting disease activity at one year in UC patients treated with anti-Tumour necrosis factor &alpha, agents as a useful tool to assist the clinician in the therapeutic decisions. Materials and Methods: Clinical and biological parameters and the endoscopic Mayo score were collected from 55 UC patients at the baseline and one year follow-up. A neural network model was built using the baseline endoscopic activity and four selected variables as inputs to predict whether a UC patient will have an active or inactive endoscopic disease at one year, under the same therapeutic regimen. Results: The classifier achieved an excellent performance predicting the disease activity at one year with an accuracy of 90% and area under curve (AUC) of 0.92 on the test set and an accuracy of 100% and an AUC of 1 on the validation set. Conclusions: Our proposed ML solution may prove to be a useful tool in assisting the clinicians&rsquo, decisions to increase the dose or switch to other biologic agents after the model&rsquo, s validation on independent, external cohorts of patients.

BackgroundThe novel coronavirus SARS-CoV-2 causing COVID-19 disease is yielding a global outbreak with serious threats to public health. In this paper, we aimed to review the current knowledge about COVID-19 infectious risk status in inflammatory bowel disease (IBD) patients requiring immunosuppressive medication. Also, we focused on several molecular insights that could explain why IBD patients appear to not have higher risks of infection and worse outcome in COVID-19 than the general population, in attempt to provide scientific support for safer decisions in IBD patient care.MethodsPubMed electronic database was interogated for relevant articles involving data about common molecular pathways and shared treatment strategies between SARS-CoV-2, SARS-CoV-1, MERS-CoV and inflammatory bowel diseases. In addition, Neural Covidex, an artificial intelligence tool, was used to answer queries about pathogenic coronaviruses and possible IBD interactions using the COVID-19 Open Research Dataset (CORD-19).DiscussionsFew molecular and therapeutic interactions between IBD and pathogenic coronaviruses were explored. First, we showed how the activity of soluble angiotensin-converting enzyme 2, CD209L alternate receptor and phosphorylated α subunit of eukaryotic translation initiation factor 2 might exert protective impact in IBD in case of coronavirus infection. Second, IBD medication was discussed in the context of possible beneficial effects on COVID-19 pathogeny including “cytokine storm” prevention and treatment, immunomodulation, interferon signaling blocking, viral endocytosis inhibition.ConclusionsUsing current understanding of SARS-CoV-2 as well as other pathogenic coronaviruses immunopathology, we showed why IBD patients should not be considered at an increased risk of infection or more severe outcomes. Whether our findings are entirely applicable to the pathogenesis, disease susceptibility and treatment management of SARS-CoV-2 infection in IBD must be further explored.

Background The management of patients with coexisting severe aortic stenosis (AS) and coronary artery disease (CAD) is still facing a great deal of uncertainty when it comes to choosing between the entire surgical versus the complete percutaneous approaches, after accurately balancing risks versus outcomes. Aim To evaluate clinical outcomes and mortality of transcatheter aortic valve replacement (TAVR) plus percutaneous coronary intervention (PCI) compared with surgical aortic valve replacement (SAVR) plus coronary arteries bypass grafting (CABG) procedures in patients with concomitant AS and CAD. Methods Electronic databases of PubMed, EMBASE, and SCOPUS were searched for relevant articles assessing outcome parameters of interest. The study endpoints were the rate of overall myocardial infarction and stroke within 30 days and the rate of 30-day mortality and 2-year mortality between patients with TAVR/PCI and those with SAVR/CABG. Results Random-effect meta-analysis did not reveal any significant difference between 30-day safety outcomes: myocardial infarction (TAVR/PCI vs SAVR/CABG: odds ratio [OR]: 0.52; 95% confidence interval [CI]: 0.20-1.33; I2 = 0%), stroke (TAVR/PCI vs SAVR/CABG: OR: 0.88; 95% CI: 0.45-1.73; I2 = 0%). No significant difference in 30-day mortality (OR: 0.72; 95% CI: 0.43-1.21; I2 = 0%) and 2-year mortality (OR: 1.50; 95% CI: 0.77-2.94; I2 = 81%) rate was noted between patients with TAVR/PCI and those with SAVR/CABG. Conclusions When comparing the total percutaneous and total surgical treatment, no significant difference in short-term safety outcomes or early and late mortality was observed. More evidence is needed to guide the clinical decision.

BackgroundThe threat of contagious infectious diseases is constantly evolving, as demographic explosion, travel globalization and changes in human lifestyle increase the risk of spreading pathogens, leading to accelerated changes in disease landscape. Of particular interest is the aftermath of superimposing viral epidemics (especially SARS-CoV-2) over long-standing diseases, such as tuberculosis (TB), which remains a significant disease for public health worldwide and especially in emerging economies.Methods and ResultsPubMed electronic database was requested for relevant articles linking TB, influenza and SARS-CoV viruses and subsequently assessed eligibility according to inclusion criteria. Using a data mining approach, we also queried the COVID-19 Open Research Dataset (CORD-19). We aimed to answer the following questions: What can be learned from other coronavirus outbreaks (with a focus on TB patients)? Is coinfection (TB and SARS-CoV-2) more severe? Is there a vaccine for SARS-CoV-2? How does the TB vaccine affect COVID19? How does one diagnosis affect the other?DiscussionsFew essential elements about TB and SARS-CoV coinfections were discussed. First, lessons from the past outbreaks (other coronaviruses), as well as influenza pandemic / seasonal outbreaks have taught the importance of infection control to avoid the severe impact on TB patients. Second, although challenging due to data scarcity, investigating the pathological pathways linking TB and SARS-CoV-2 leads to the idea that their coexistence might yield a more severe clinical evolution. Finally, we addressed the issues of vaccination and diagnostic reliability in the context of coinfection.ConclusionsBecause viral respiratory infections and TB impede the host’s immune responses, it can be assumed that their harmful synergism may contribute to more severe clinical evolution. Despite the rapidly growing number of cases, the data needed to predict the impact of the COVID-19 pandemic on patients with latent TB and TB sequelae still lies ahead.

In the current context of COVID-19 pandemic, a rapid and accessible screening tool based on image processing of chest X-rays (CXRs) using machine learning (ML) approaches would be much needed. Initially, we intended to create and validate an ML software solution able to discriminate on the basis of the CXR between SARS-CoV-2-induced bronchopneumonia and other bronchopneumonia etiologies.A systematic search of PubMed, Scopus and arXiv databases using the following search terms [“artificial intelligence” OR “deep learning” OR “neural networks”], AND [“COVID-19” OR “SARS-CoV-2”] AND [“chest X-ray” OR “CXR” OR “X-ray”] found 14 recent studies. Most of them declared to be able to confidently identify COVID-19 based on CXRs using deep neural networks. Firstly, weaknesses of artificial intelligence (AI) solutions were analyzed, tackling the issues with datasets (from both medical and technical points of view) and the vulnerability of used algorithms. Then, arguments were provided for why our study design is stronger and more realistic than the previously quoted papers, balancing the possible false expectations with facts.The authors consider that the potential of AI use in COVID-19 diagnosis on CXR is real. However, scientific community should be careful in interpreting statements, results and conclusions regarding AI use in imaging. It is therefore necessary to adopt standards for research and publication of data, because it seems that in the recent months scientific reality suffered manipulations and distortions. Also, a call for responsible approaches to the imaging methods in COVID-19 is raised. It seems mandatory to follow some rigorous approaches in order to provide with adequate results in daily routine. In addition, the authors intended to raise public awareness about the quality of AI protocols and algorithms and to encourage public sharing of as many CXR images with common quality standards.

Pulmonary arterial hypertension (PH) has a high prevalence in chronic kidney disease (CKD) patients, especially those undergoing kidney transplantation (KT). We aimed to systematically review and calculate the pooled effect size of the literature evaluating the association between pre-existing PH documented by transthoracic echocardiography (TTE) or invasively and adverse outcomes following KT. The primary composite outcome extracted from the included studies was represented by the mortality from any cause following KT and delayed graft function (DGF), graft dysfunction, or graft failure. The secondary outcomes were represented by individual components of the primary composite outcome. Twelve studies meeting the inclusion criteria were selected. The main finding is that pre-existing PH was associated with increased mortality and a higher rate of DGF, kidney graft dysfunction, or failure in KT recipients. The effect remained significant for all outcomes irrespective of PH evaluation, invasively or using TTE. Consequently, patients with PH defined only by TTE were at higher risk of death, DGF, or graft failure. Our findings support the routine assessment of PH in patients on the KT waitlist. PH might represent an extensively available and valuable tool for risk stratification in KT patients. These data should be confirmed in large prospective clinical trials.

The increasing production of modern medication emerges as a new source of environmental pollution. The scientific community is interested in developing alternative, ecological therapies in asthma. Halotherapy proved its benefits in asthma diagnosis, treatment, and prevention and may represent a reliable therapeutic addition to the allopathic treatment, due to its ecological and environment-friendly nature, in order to prevent or prolong the time to exacerbations in patients with asthma. We aimed to review up-to-date research regarding halotherapy benefits in asthma comprehensively. We searched the electronic databases of PubMed, MEDLINE, EMBASE for studies that evaluated the exposure of asthmatic patients to halotherapy. Eighteen original articles on asthma were included. Five studies in adults and five in children assessed the performance of hypertonic saline bronchial challenges to diagnose asthma or vocal cord dysfunction in asthmatic patients. Three papers evaluated the beneficial effects of halotherapy on mucociliary clearance in asthmatic adults. The therapeutic effect of halotherapy on acute or chronic asthma was appraised in three studies in adults and one in children. The preventive role was documented in one paper reporting the ability of halotherapy to hinder nocturnal asthma exacerbations. All studies seem to sustain the overall positive effects of halotherapy as adjuvant therapy on asthma patients with no reported adverse events. Halotherapy is a crucial natural ally in asthma, but further evidence-based studies on larger populations are needed.

The issue of the COVID-19 pandemic occupies the agenda of the whole world. The pivot of this pandemic is a crucial element that has become almost as important as the virus itself, namely the lockdown. Although, the rationale for lockdown is well-sustained by strong epidemiological arguments, exploring the 'other' unwanted consequences of the contemporary COVID-19 pandemic is mandatory for coagulating a robust agreed position against the numerous problems generated by the SARS-CoV-2 virus. Starting from the rationale of the lockdown, in this paper we explored and exposed the other consequences of the COVID-19 pandemic measures such as the use or abuse of human rights and freedom restrictions, economic issues, marginalized groups and eclipse of all other diseases. Our scientific attempt is to coagulate a stable position and integrate current opposing views by advancing the idea that rather than applying the uniform lockdown policy, one could recommend instead an improved model targeting more strict and more prolonged lockdowns to vulnerable risk/age groups while enabling less stringent measures for the lower-risk groups, minimizing both economic losses and deaths. Rigorous (and also governed by freedom) debating may be able to synchronize the opposed perspectives between those advocating an extreme lockdown (e.g., most of the epidemiologists and health experts), and those criticizing all restrictive measures (e.g., economists and human rights experts). Confronting the multiple facets of the public health mitigation measures is the only way to avoid contributing to history with yet another failure, as seen in other past epidemics.

Background. The threat of contagious infectious diseases is constantly evolving as demographic explosion, travel globalization, and changes in human lifestyle increase the risk of spreading pathogens, leading to accelerated changes in disease landscape. Of particular interest is the aftermath of superimposing viral epidemics (especially SARS-CoV-2) over long-standing diseases, such as tuberculosis (TB), which remains a significant disease for public health worldwide and especially in emerging economies.Methods and Results. The PubMed electronic database was systematically searched for relevant articles linking TB, influenza, and SARS-CoV viruses and subsequently assessed eligibility according to inclusion criteria. Using a data mining approach, we also queried the COVID-19 Open Research Dataset (CORD-19). We aimed to answer the following questions: What can be learned from other coronavirus outbreaks (focusing on TB patients)? Is coinfection (TB and SARS-CoV-2) more severe? Is there a vaccine for SARS-CoV-2? How does the TB vaccine affect COVID-19? How does one diagnosis affect the other?Discussions. Few essential elements about TB and SARS-CoV coinfections were discussed. First, lessons from past outbreaks (other coronaviruses) and influenza pandemic/seasonal outbreaks have taught the importance of infection control to avoid the severe impact on TB patients. Second, although challenging due to data scarcity, investigating the pathological pathways linking TB and SARS-CoV-2 leads to the idea that their coexistence might yield a more severe clinical evolution. Finally, we addressed the issues of vaccination and diagnostic reliability in the context of coinfection.Conclusions. Because viral respiratory infections and TB impede the host’s immune responses, it can be assumed that their lethal synergism may contribute to more severe clinical evolution. Despite the rapidly growing number of cases, the data needed to predict the impact of the COVID-19 pandemic on patients with latent TB and TB sequelae still lies ahead. The trial is registered withNCT04327206,NCT01829490, andNCT04121494.