Understanding clinical outcomes and factors influencing mortality in intensive care unit patients with COVID-19-associated candidemia.

BACKGROUND: During the COVID pandemic, research has shown an increase in candidemia cases following severe COVID infection and the identification of risk factors associated with candidemia. However, there is a lack of studies that specifically explore clinical outcomes and mortality rates related to candidemia after COVID infection. OBJECTIVES: The aim of this international study was to evaluate the clinical outcomes and identify factors influencing mortality in patients who developed candidemia during their COVID infection. PATIENTS/METHODS: This study included adult patients (18 years of age or older) admitted to the intensive care unit (ICU) and diagnosed with COVID-associated candidemia (CAC). The research was conducted through ID-IRI network and in collaboration with 34 medical centres across 18 countries retrospectively, spanning from the beginning of the COVID pandemic until December 2021. RESULTS: A total of 293 patients diagnosed with CAC were included. The median age of the patients was 67, and 63% of them were male. The most common Candida species detected was C. albicans. The crude 30-day mortality rate was recorded at 62.4%. The logistic regression analysis identified several factors significantly impacting mortality, including age (odds ratio [OR] 1.04, 95% confidence interval [CI] 1.02-1.07, p < .0005), SOFA score (OR 1.307, 95% CI 1.17-1.45, p < .0005), invasive mechanical ventilation (OR 7.95, 95% CI 1.44-43.83, p < .017) and duration of mechanical ventilation (OR 0.98, 95% CI 0.96-0.99, p < .020). CONCLUSIONS: By recognising these prognostic factors, medical professionals can customise their treatment approaches to offer more targeted care, leading to improved patient outcomes and higher survival rates for individuals with COVID-associated candidemia.

Profiles of multidrug-resistant organisms among patients with bacteremia in intensive care units: an international ID-IRI survey.

Evaluating trends in antibiotic resistance is a requisite. The study aimed to analyze the profile of multidrug-resistant organisms (MDROs) among hospitalized patients with bacteremia in intensive care units (ICUs) in a large geographical area. This is a 1-month cross-sectional survey for blood-borne pathogens in 57 ICUs from 24 countries with different income levels: lower-middle-income (LMI), upper-middle-income (UMI), and high-income (HI) countries. Multidrug-resistant (MDR), extensively drug-resistant (XDR), or pan-drug-resistant isolates were searched. Logistic regression analysis determined resistance predictors among MDROs. Community-acquired infections were comparable to hospital-acquired infections particularly in LMI (94/202; 46.5% vs 108/202; 53.5%). Although MDR (65.1%; 502/771) and XDR (4.9%; 38/771) were common, no pan-drug-resistant isolate was recovered. In total, 32.1% of MDR were Klebsiella pneumoniae, and 55.3% of XDR were Acinetobacter baumannii. The highest MDR and XDR rates were in UMI and LMI, respectively, with no XDR revealed from HI. Predictors of MDR acquisition were male gender (OR, 12.11; 95% CI, 3.025-15.585) and the hospital-acquired origin of bacteremia (OR, 2.643; 95%CI, 1.462-3.894), and XDR acquisition was due to bacteremia in UMI (OR, 3.344; 95%CI, 1.189-5.626) and admission to medical-surgical ICUs (OR, 1.481; 95% CI, 1.076-2.037). We confirm the urgent need to expand stewardship activities to community settings especially in LMI, with more paid attention to the drugs with a higher potential for resistance. Empowering microbiology laboratories and reports to direct prescribing decisions should be prioritized. Supporting stewardship in ICUs, the mixed medical-surgical ones in particular, is warranted.

Laboratory parameters predicting mortality of adult in-patients with COVID-19 associated cytokine release syndrome treated with high-dose tocilizumab.

Large randomized clinical trials in severe Coronavirus Disease 2019 (COVID-19) patients have proven efficacy of intravenous tocilizumab. Our aim was to describe the laboratory parameters predicting in-hospital mortality of patients with tocilizumab administration in COVID-19 associated cytokine release syndrome (CRS).We evaluated high-dose (8 mg/kg) intravenous tocilizumab administration in severe and critically ill COVID-19 adult patients fulfilling predefined strict CRS criteria. A single-centre, prospective, observational cohort study was carried out among consecutive adult (≥18 years of age) in-patients with COVID-19 between April 1 and December 31, 2020. The primary endpoint was 28-day all-cause mortality. The changes in laboratory parameters from baseline on day 7 and 14 after administration of tocilizumab were analysed.In total, 1801 patients were admitted to our centre during the study period. One hundred and six patients received tocilizumab, and among them 62 (58.5%) required intensive care unit admittance while 25 (23.6%) deceased. At day 7 after tocilizumab administration, inflammatory markers (CRP, IL-6, ferritin) and lactate dehydrogenase (LDH) values were significantly lower among survivors. Subsequently, at day 14, differences of IL-6 and LDH levels has become more pronounced between subgroups. Restoration of absolute lymphocyte count (ALC) by day 7 and 14 was insufficient among patients who died.In our cohort, administration of high-dose tocilizumab for COVID-19 patients with CRS demonstrated clinical and sustained biochemical parameter improvement in 76.4%. In this patient population high and increasing LDH, IL-6, and low ALC levels had a predictive role for mortality.

Publisher Correction: A robotic multidimensional directed evolution approach applied to fluorescent voltage reporters.

In the version of this article originally published, the bottom of Figure 4f,g was partially truncated in the PDF. The error has been corrected in the PDF version of this article.

A robotic multidimensional directed evolution approach applied to fluorescent voltage reporters.

We developed a new way to engineer complex proteins toward multidimensional specifications using a simple, yet scalable, directed evolution strategy. By robotically picking mammalian cells that were identified, under a microscope, as expressing proteins that simultaneously exhibit several specific properties, we can screen hundreds of thousands of proteins in a library in just a few hours, evaluating each along multiple performance axes. To demonstrate the power of this approach, we created a genetically encoded fluorescent voltage indicator, simultaneously optimizing its brightness and membrane localization using our microscopy-guided cell-picking strategy. We produced the high-performance opsin-based fluorescent voltage reporter Archon1 and demonstrated its utility by imaging spiking and millivolt-scale subthreshold and synaptic activity in acute mouse brain slices and in larval zebrafish in vivo. We also measured postsynaptic responses downstream of optogenetically controlled neurons in C. elegans.

A novel id-iri score: development and internal validation of the multivariable community acquired sepsis clinical risk prediction model.

We aimed to develop a scoring system for predicting in-hospital mortality of community-acquired (CA) sepsis patients. This was a prospective, observational multicenter study performed to analyze CA sepsis among adult patients through ID-IRI (Infectious Diseases International Research Initiative) at 32 centers in 10 countries between December 1, 2015, and May 15, 2016. After baseline evaluation, we used univariate analysis at the second and logistic regression analysis at the third phase. In this prospective observational study, data of 373 cases with CA sepsis or septic shock were submitted from 32 referral centers in 10 countries. The median age was 68 (51-77) years, and 174 (46,6%) of the patients were females. The median hospitalization time of the patients was 15 (10-21) days. Overall mortality rate due to CA sepsis was 17.7% (n = 66). The possible predictors which have strong correlation and the variables that cause collinearity are acute oliguria, altered consciousness, persistent hypotension, fever, serum creatinine, age, and serum total protein. CAS (%) is a new scoring system and works in accordance with the parameters in third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). The system has yielded successful results in terms of predicting mortality in CA sepsis patients.

Clinical and microbiological characteristics and outcomes of community-acquired sepsis among adults: a single center, 1-year retrospective observational cohort study from Hungary.

BACKGROUND: Community-acquired sepsis is a life-threatening systemic reaction, which starts within ≤72 h of hospital admittance in an infected patient without recent exposure to healthcare risks. Our aim was to evaluate the characteristics and the outcomes concerning community-acquired sepsis among patients admitted to a Hungarian high-influx national medical center. METHODS: A retrospective, observational cohort study of consecutive adult patients hospitalized with community-acquired sepsis during a 1-year period was executed. Clinical and microbiological data were collected, patients with pre-defined healthcare associations were excluded. Sepsis definitions and severity were given according to ACCP/SCCM criteria. The primary outcome was in-hospital all-cause mortality. Secondary outcomes were intensive care unit (ICU) admittance, length-of-stay (LOS), source control and bacteraemia rates. Statistical differences were explored with classical comparison tests, predictors of in-hospital all-cause mortality were modelled by multivariate logistic regression. RESULTS: 214 patients (median age 60.0 ± 33.1 years, 57% female, median Charlson score 4.0 ± 5.0) were included, 32.7% of them (70/214) had severe sepsis, and 28.5% (61/214) had septic shock. Prevalent sources of infections were genitourinary (53/214, 24.8%) and abdominal (52/214, 24.3%). The causative organisms were dominantly E. coli (60/214, 28.0%), S. pneumoniae (18/214, 8.4%) and S. aureus (14/214, 6.5%), and bacteraemia was documented in 50.9% of the cases (109/214). In-hospital mortality was high (30/214, 14.0%), and independently associated with shock, absence of fever, male gender and the need for ICU admittance, but source control and de-escalation of empirical antimicrobial therapy were protective. ICU admittance was 27.1% (58/214), source control was achieved in 18.2% (39/214). Median LOS was 10.0 ± 8.0, ICU LOS was 8.0 ± 10.8 days. CONCLUSIONS: Community-acquired sepsis poses a significant burden of disease with characteristic causative agents and sources. Patients at a higher risk for poor outcomes might be identified earlier by the contributing factors shown above.

Microglia control the spread of neurotropic virus infection via P2Y12 signalling and recruit monocytes through P2Y12-independent mechanisms.

Neurotropic herpesviruses can establish lifelong infection in humans and contribute to severe diseases including encephalitis and neurodegeneration. However, the mechanisms through which the brain's immune system recognizes and controls viral infections propagating across synaptically linked neuronal circuits have remained unclear. Using a well-established model of alphaherpesvirus infection that reaches the brain exclusively via retrograde transsynaptic spread from the periphery, and in vivo two-photon imaging combined with high resolution microscopy, we show that microglia are recruited to and isolate infected neurons within hours. Selective elimination of microglia results in a marked increase in the spread of infection and egress of viral particles into the brain parenchyma, which are associated with diverse neurological symptoms. Microglia recruitment and clearance of infected cells require cell-autonomous P2Y12 signalling in microglia, triggered by nucleotides released from affected neurons. In turn, we identify microglia as key contributors to monocyte recruitment into the inflamed brain, which process is largely independent of P2Y12. P2Y12-positive microglia are also recruited to infected neurons in the human brain during viral encephalitis and both microglial responses and leukocyte numbers correlate with the severity of infection. Thus, our data identify a key role for microglial P2Y12 in defence against neurotropic viruses, whilst P2Y12-independent actions of microglia may contribute to neuroinflammation by facilitating monocyte recruitment to the sites of infection.

Clinical and microbiological characteristics of adult invasive Haemophilus influenzae infections: results of a 14-year single-center experience from Hungary.

To describe the characteristics of adult invasive H. influenzae disease, 34 patients diagnosed at a single tertiary center between 2004 and 2017 were analyzed in a retrospective case series study. The annual estimated incidence was 0.1 cases/100.000 inhabitants. Dominant source of infection was pneumonia accompanied by sepsis (62%) and caused by nontypeable strains (74%) with low ampicillin resistance (14%). Survival (94%) and complication rates were high (35%). Main empirical treatments were ceftriaxone or levofloxacine.

[Thousand faces of Streptococcus pneumonia (pneumococcus) infections]. / A Streptococcus pneumoniae (pneumococcus) -infekciók ezer arca.

Incidence and mortality rates of infections caused by Streptococcus pneumoniae (pneumococcus) are high worldwide and in Hungary among paediatric as well as adult populations. Pneumococci account for 35-40% of community acquired adult pneumonias requiring hospitalization, while 25-30% of Streptococcus pneumoniae pneumonias are accompanied by bacteraemia. 5-7% of all infections are fatal but this rate is exponentially higher in high risk patients and elderly people. Mortality could reach 20% among patients with severe invasive pneumococcal infections. Complications may develop despite administration of adequate antibiotics. The authors summarize the epidemiology of pneumococcal infections, pathogenesis of non-invasive and invasive disease and present basic clinical aspects through demonstration of four cases. Early risk stratification, sampling of hemocultures, administration of antibiotics and wider application of active immunization could reduce the mortality of invasive disease. Anti-pneumococcal vaccination is advisable for adults of ≥50 years and high risk patients of ≥18 years who are susceptible to pneumococcal disease.

Continuous distribution of cancer cells in the cell cycle unveiled by AI-segmented imaging of 37,000 HeLa FUCCI cells.

Classification of live or fixed cells based on their unlabeled microscopic images would be a powerful tool for cell biology and pathology. For such software, the first step is the generation of a ground truth database that can be used for training and testing AI classification algorithms. The Application of cells expressing fluorescent reporter proteins allows the building of ground truth datasets in a straightforward way. In this study, we present an automated imaging pipeline utilizing the Cellpose algorithm for the precise cell segmentation and measurement of fluorescent cellular intensities across multiple channels. We analyzed the cell cycle of HeLa-FUCCI cells expressing fluorescent red and green reporter proteins at various levels depending on the cell cycle state. To build the dataset, 37,000 fixed cells were automatically scanned using a standard motorized microscope, capturing phase contrast and fluorescent red/green images. The fluorescent pixel intensity of each cell was integrated to calculate the total fluorescence of cells based on cell segmentation in the phase contrast channel. It resulted in a precise intensity value for each cell in both channels. Furthermore, we conducted a comparative analysis of Cellpose 1.0 and Cellpose 2.0 in cell segmentation performance. Cellpose 2.0 demonstrated notable improvements, achieving a significantly reduced false positive rate of 2.7 % and 1.4 % false negative. The cellular fluorescence was visualized in a 2D plot (map) based on the red and green intensities of the FUCCI construct revealing the continuous distribution of cells in the cell cycle. This 2D map enables the selection and potential isolation of single cells in a specific phase. In the corresponding heatmap, two clusters appeared representing cells in the red and green states. Our pipeline allows the high-throughput and accurate measurement of cellular fluorescence providing extensive statistical information on thousands of cells with potential applications in developmental and cancer biology. Furthermore, our method can be used to build ground truth datasets automatically for training and testing AI cell classification. Our automated pipeline can be used to analyze thousands of cells within 2 h after putting the sample onto the microscope.

Characteristics of Enterococcus species bloodstream infections among adults with and without onco-hematological malignancies: Experiences from the national center of Hungary.

Introduction: Over the past decade, enterococcal bloodstream infection (BSI) shows increasing incidence globally among the elderly and in patients with comorbidities. In this study, we aimed to assess microbiological and clinical characteristics and long-term outcomes of BSIs caused by Enterococcus spp. in adult patients with and without active onco-hematological malignancies hospitalized at a national referral institute. Methods: A prospective analysis of consecutive enterococcal BSI cases was conducted in the National Institute of Hematology and Infectious Diseases (Budapest, Hungary) between December 2019 and April 2022. We compared characteristics and outcomes at 30-days and 1 year after diagnosis among patients with and without onco-hematological malignancies. Results: In total, 141 patients were included (median age 68 ± 21 years, female sex 36.9%), 37% (52/141) had active onco-hematological malignancies. The distribution of species was as follows: 50.4% Enterococcus faecalis, 46.1% Enterococcus faecium, 1.4% Enterococcus avium and Enterococcus gallinarum, and 0.7% Enterococcus raffinosus. No statistically significant differences in all-cause mortality rates were observed between patient subgroups at 30 days (32.7 vs. 28.1%; P = 0.57) and 1 year (75.0 vs. 60.7%; P = 0.09). Conclusion: Enterococcal bloodstream infections yielded a relevant burden of morbidity, but with no statistical difference in long-term outcomes of adult patients with and without active onco-hematological malignancies.

Single-cell classification based on label-free high-resolution optical data of cell adhesion kinetics.

Selecting and isolating various cell types is a critical procedure in many applications, including immune therapy, regenerative medicine, and cancer research. Usually, these selection processes involve some labeling or another invasive step potentially affecting cellular functionality or damaging the cell. In the current proof of principle study, we first introduce an optical biosensor-based method capable of classification between healthy and numerous cancerous cell types in a label-free setup. We present high classification accuracy based on the monitored single-cell adhesion kinetic signals. We developed a high-throughput data processing pipeline to build a benchmark database of ~ 4500 single-cell adhesion measurements of a normal preosteoblast (MC3T3-E1) and various cancer (HeLa, LCLC-103H, MDA-MB-231, MCF-7) cell types. Several datasets were used with different cell-type selections to test the performance of deep learning-based classification models, reaching above 70-80% depending on the classification task. Beyond testing these models, we aimed to draw interpretable biological insights from their results; thus, we applied a deep neural network visualization method (grad-CAM) to reveal the basis on which these complex models made their decisions. Our proof-of-concept work demonstrated the success of a deep neural network using merely label-free adhesion kinetic data to classify single mammalian cells into different cell types. We propose our method for label-free single-cell profiling and in vitro cancer research involving adhesion. The employed label-free measurement is noninvasive and does not affect cellular functionality. Therefore, it could also be adapted for applications where the selected cells need further processing, such as immune therapy and regenerative medicine.

Comprehensive study of retention influencing gas chromatographic parameters affecting linear retention indices.

Retention in gas chromatographic systems has a central role in the identification of compounds even if detectors providing spectral information are used. But linear retention indices (LRI) of a single compound originating from multiple sources tend to vary greatly, probably due to differences in the experimental settings of the determinations. The effect of gas chromatographic parameters on LRI has been investigated using 41 compounds - previously identified from food contact plastics - and n-alkanes (n-C7-n-C40) used as reference series. As the reproducibility of LRIs under the same conditions is generally very good, the smallest changes in the settings often caused statistically significant, though irrelevant changes in the LRI values. Therefore, a multicriterial scoring-ranking system has been worked out to highlight the LRI value differences. Our results highlight that column length, heating rate, and film thickness can all be the reasons of the varying published LRI values. We also demonstrated that for the reproduction of LRI data, the chemistry (and not simply the polarity) of the stationary phase is crucial.

Optical sensor reveals the hidden influence of cell dissociation on adhesion measurements.

Cell adhesion experiments are important in tissue engineering and for testing new biologically active surfaces, prostheses, and medical devices. Additionally, the initial state of adhesion (referred to as nascent adhesion) plays a key role and is currently being intensively researched. A critical step in handling all adherent cell types is their dissociation from their substrates for further processing. Various cell dissociation methods and reagents are used in most tissue culture laboratories (here, cell dissociation from the culture surface, cell harvesting, and cell detachment are used interchangeably). Typically, the dissociated cells are re-adhered for specific measurements or applications. However, the impact of the choice of dissociation method on cell adhesion in subsequent measurements, especially when comparing the adhesivity of various surfaces, is not well clarified. In this study, we demonstrate that the application of a label-free optical sensor can precisely quantify the effect of cell dissociation methods on cell adhesivity, both at the single-cell and population levels. The optical measurements allow for high-resolution monitoring of cellular adhesion without interfering with the physiological state of the cells. We found that the choice of reagent significantly alters cell adhesion on various surfaces. Our results clearly demonstrate that biological conclusions about cellular adhesion when comparing various surfaces are highly dependent on the employed dissociation method. Neglecting the choice of cellular dissociation can lead to misleading conclusions when evaluating cell adhesion data from various sources and comparing the adhesivity of two different surfaces (i.e., determining which surface is more or less adhesive).

Favipiravir does not improve viral clearance in mild to moderate COVID-19 - A systematic review and meta-analysis of randomized controlled trials.

Purpose: Favipiravir has been used in the therapy of COVID-19, including patients with mild to moderate symptoms in certain countries. The aim of our systematic review and meta-analysis was to investigate its efficacy and safety in mild-to-moderate COVID-19 infections. Methods: The PubMed, Embase, Web of Science, and Cochrane databases were systematically reviewed for articles reporting the results of randomized controlled trials published until January 6, 2023, resulting in the identification of 20 eligible studies. Results: There were no significant differences in viral clearance time (HR = 1.20, p = 0.09) compared to those without favipiravir therapy. However, in the subgroup analyses, favipiravir treatment significantly increased viral clearance by 59 % (HR = 1.59, p < 0.01) and 42 % (HR = 1.42, p < 0.01], I2 = 20 %) compared to the comparator group in patients with moderate severity of COVID-19 and in the inpatient care setting, respectively. Favipiravir had no beneficial effects in the case of patients with mild symptoms and treated in ambulatory care. Conclusions: The use of favipiravir is questionable in the treatment of outpatients with COVID-19 with mild symptoms. Moderate beneficial effects in the case of patients with moderate symptoms and inpatients should be treated with care due to the limitations of the analysed trials.

Secondary infections and long-term outcomes among hospitalized elderly and non-elderly patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and treated with baricitinib: a comparative study from the national centre of Hungary.

Baricitinib is considered a first-line treatment for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected adult patients with an associated cytokine storm syndrome (CSS). Our objective was to compare rates of secondary infections and long-term outcomes of elderly and non-elderly patients who received baricitinib for COVID-19. We conducted a single-centre observational study between November 2020 and September 2023, focusing on hospitalized adult SARS-CoV-2 patients with CSS, categorized as elderly (≥ 65 years) and non-elderly (< 65 years). Enrolment, severity stratification, and diagnosis of infectious complications followed predefined criteria. Outcomes of all-cause mortality and rates of non-severe and severe secondary infections were assessed at 1-year post-treatment initiation. Kaplan-Meier analysis was performed for survival analysis. In total, 490 patients were enrolled (median age 65 ± 23 (21-100) years (years, median ± IQR, min-max); 49.18% elderly; 59.59% male). Elderly patients were admitted to the hospital significantly earlier (7 ± 5 days vs. 8 ± 4 days; p = 0.02), experienced a higher occurrence of severe COVID-19 (121/241, 50.21% vs. 98/249, 39.36%; p = 0.02), and required the use of non-invasive ventilation at baseline (167/225, 74.22% vs. 153/236, 64.83%; p = 0.03). At 1 year, all-cause mortality was significantly higher in the elderly subgroup (111/241, 46.06% vs. 29/249, 11.65%; p < 0.01). At 90 days and 1 year, rates of any severe secondary infection were also more prevalent among the elderly (56/241, 23.24% vs. 37/249 14.86%; p = 0.02 and 58/241, 24.07% vs. 39/249, 15.66%; p = 0.02). In conclusion, elderly SARS-CoV-2-infected patients experience a more severe clinical course, higher secondary infection rates, and increased risk for long-term mortality, regardless of immunomodulatory therapy.

Effective virus-specific T-cell therapy for high-risk SARS-CoV-2 infections in hematopoietic stem cell transplant recipients: initial case studies and literature review.

The COVID-19 pandemic has exacerbated mortality rates among immunocompromised patients, accentuating the need for novel, targeted therapies. Transplant recipients, with their inherent immune vulnerabilities, represent a subgroup at significantly heightened risk. Current conventional therapies often demonstrate limited effectiveness in these patients, calling for innovative treatment approaches. In immunocompromised transplant recipients, several viral infections have been successfully treated by adoptive transfer of virus-specific T-cells (VST). This paper details the successful application of SARS-CoV-2-specific memory T-cell therapy, produced by an interferon-γ cytokine capture system (CliniMACS® Prodigy device), in three stem cell transplant recipients diagnosed with COVID-19 (case 1: alpha variant, cases 2 and 3: delta variants). These patients exhibited persistent SARS-CoV-2 PCR positivity accompanied by bilateral pulmonary infiltrates and demonstrated only partial response to standard treatments. Remarkably, all three patients recovered and achieved viral clearance within 3 to 9 weeks post-VST treatment. Laboratory follow-up investigations identified an increase in SARS-CoV-2-specific T-cells in two of the cases. A robust anti-SARS-CoV-2 S (S1/S2) IgG serological response was also recorded, albeit with varying titers. The induction of memory T-cells within the CD4 + compartment was confirmed, and previously elevated interleukin-6 (IL-6) and IL-8 levels normalized post-VST therapy. The treatment was well tolerated with no observed adverse effects. While the need for specialized equipment and costs associated with VST therapy present potential challenges, the limited treatment options currently available for COVID-19 within the allogeneic stem cell transplant population, combined with the risk posed by emerging SARS-CoV-2 mutations, underscore the potential of VST therapy in future clinical practice. This therapeutic approach may be particularly beneficial for elderly patients with multiple comorbidities and weakened immune systems.

["When it rains, it pours" - de novo diagnosed multiple myeloma with invasive Streptococcus pneumoniae infection in severe COVID-19 complicated with cytokine storm]. / "A baj nem jár egyedül" ­ de novo diagnosztizált myeloma multiplex invazív Streptococcus pneumoniae fertozéssel citokinviharral szövodött COVID­19-ben.

With the appearance of SARS-CoV-2, the range of infections, considered the most common cause of death for people with multiple myeloma, has expanded. Although the omicron variant (PANGO B.1.1.529) of SARS-CoV-2, that dominates the world at the time of manuscript writing, is less likely to cause fatal infection in immunocompetent patients compared to the delta variant (PANGO B.1.617.2), its transmissibility did not decrease. The likelihood of a severe or critical course of COVID-19 in patients with multiple myeloma is increased by the humoral and cellular immunosuppression caused by the malignancy itself, its targeted hematological treatment, and other comorbidities associated with the disease (e.g., chronic kidney failure). Antiviral therapies, monoclonal antibody preparations used as pre- or post-exposure prophylaxis, and possibly convalescent plasma therapy, started as early as possible might prevent the clinical progression of COVID-19. While the incidence of community-acquired co-infections accompanying COVID-19 in the average population is not exceptionally high, in people with multiple myeloma, Streptococcus pneumoniae infection that follows respiratory viral diseases is approximately 150 times more likely to cause invasive disease. As a result of modern oncohematological treatment, multiple myeloma has now become a chronic disease accompanied by relapses, and those affected should be immunized against the above two pathogens. In our manuscript, we describe the case of an adult patient with severe COVID-19 complicated by cytokine storm and invasive Streptococcus pneumoniae infection who was diagnosed with de novo multiple myeloma during hospital care, and, finally, we briefly review the related literature data. Orv Hetil. 2023; 164(20): 763-769.

Classification-based deep neural network vs mixture density network models for insulin sensitivity prediction problem.

Model-based glycemic control (GC) protocols are used to treat stress-induced hyperglycaemia in intensive care units (ICUs). The STAR (Stochastic-TARgeted) glycemic control protocol - used in clinical practice in several ICUs in New Zealand, Hungary, Belgium, and Malaysia - is a model-based GC protocol using a patient-specific, model-based insulin sensitivity to describe the patient's actual state. Two neural network based methods are defined in this study to predict the patient's insulin sensitivity parameter: a classification deep neural network and a Mixture Density Network based method. Treatment data from three different patient cohorts are used to train the network models. Accuracy of neural network predictions are compared with the current model- based predictions used to guide care. The prediction accuracy was found to be the same or better than the reference. The authors suggest that these methods may be a promising alternative in model-based clinical treatment for patient state prediction. Still, more research is needed to validate these findings, including in-silico simulations and clinical validation trials.