Multimodal data fusion using sparse canonical correlation analysis and cooperative learning: a COVID-19 cohort study.

Through technological innovations, patient cohorts can be examined from multiple views with high-dimensional, multiscale biomedical data to classify clinical phenotypes and predict outcomes. Here, we aim to present our approach for analyzing multimodal data using unsupervised and supervised sparse linear methods in a COVID-19 patient cohort. This prospective cohort study of 149 adult patients was conducted in a tertiary care academic center. First, we used sparse canonical correlation analysis (CCA) to identify and quantify relationships across different data modalities, including viral genome sequencing, imaging, clinical data, and laboratory results. Then, we used cooperative learning to predict the clinical outcome of COVID-19 patients: Intensive care unit admission. We show that serum biomarkers representing severe disease and acute phase response correlate with original and wavelet radiomics features in the LLL frequency channel (cor(Xu1, Zv1) = 0.596, p value < 0.001). Among radiomics features, histogram-based first-order features reporting the skewness, kurtosis, and uniformity have the lowest negative, whereas entropy-related features have the highest positive coefficients. Moreover, unsupervised analysis of clinical data and laboratory results gives insights into distinct clinical phenotypes. Leveraging the availability of global viral genome databases, we demonstrate that the Word2Vec natural language processing model can be used for viral genome encoding. It not only separates major SARS-CoV-2 variants but also allows the preservation of phylogenetic relationships among them. Our quadruple model using Word2Vec encoding achieves better prediction results in the supervised task. The model yields area under the curve (AUC) and accuracy values of 0.87 and 0.77, respectively. Our study illustrates that sparse CCA analysis and cooperative learning are powerful techniques for handling high-dimensional, multimodal data to investigate multivariate associations in unsupervised and supervised tasks.

Predictors of Severity of Influenza-Related Hospitalizations: Results From the Global Influenza Hospital Surveillance Network (GIHSN).

BACKGROUND: The Global Influenza Hospital Surveillance Network (GIHSN) has since 2012 provided patient-level data on severe influenza-like-illnesses from >100 participating clinical sites worldwide based on a core protocol and consistent case definitions. METHODS: We used multivariable logistic regression to assess the risk of intensive care unit admission, mechanical ventilation, and in-hospital death among hospitalized patients with influenza and explored the role of patient-level covariates and country income level. RESULTS: The data set included 73 121 patients hospitalized with respiratory illness in 22 countries, including 15 660 with laboratory-confirmed influenza. After adjusting for patient-level covariates we found a 7-fold increase in the risk of influenza-related intensive care unit admission in lower middle-income countries (LMICs), compared with high-income countries (P = .01). The risk of mechanical ventilation and in-hospital death also increased by 4-fold in LMICs, though these differences were not statistically significant. We also find that influenza mortality increased significantly with older age and number of comorbid conditions. Across all severity outcomes studied and after controlling for patient characteristics, infection with influenza A/H1N1pdm09 was more severe than with A/H3N2. CONCLUSIONS: Our study provides new information on influenza severity in underresourced populations, particularly those in LMICs.

Multimodal Biomedical Data Fusion Using Sparse Canonical Correlation Analysis and Cooperative Learning: A Cohort Study on COVID-19.

Through technological innovations, patient cohorts can be examined from multiple views with high-dimensional, multiscale biomedical data to classify clinical phenotypes and predict outcomes. Here, we aim to present our approach for analyzing multimodal data using unsupervised and supervised sparse linear methods in a COVID-19 patient cohort. This prospective cohort study of 149 adult patients was conducted in a tertiary care academic center. First, we used sparse canonical correlation analysis (CCA) to identify and quantify relationships across different data modalities, including viral genome sequencing, imaging, clinical data, and laboratory results. Then, we used cooperative learning to predict the clinical outcome of COVID-19 patients. We show that serum biomarkers representing severe disease and acute phase response correlate with original and wavelet radiomics features in the LLL frequency channel (corr(Xu1, Zv1) = 0.596, p-value < 0.001). Among radiomics features, histogram-based first-order features reporting the skewness, kurtosis, and uniformity have the lowest negative, whereas entropy-related features have the highest positive coefficients. Moreover, unsupervised analysis of clinical data and laboratory results gives insights into distinct clinical phenotypes. Leveraging the availability of global viral genome databases, we demonstrate that the Word2Vec natural language processing model can be used for viral genome encoding. It not only separates major SARS-CoV-2 variants but also allows the preservation of phylogenetic relationships among them. Our quadruple model using Word2Vec encoding achieves better prediction results in the supervised task. The model yields area under the curve (AUC) and accuracy values of 0.87 and 0.77, respectively. Our study illustrates that sparse CCA analysis and cooperative learning are powerful techniques for handling high-dimensional, multimodal data to investigate multivariate associations in unsupervised and supervised tasks.

Evaluation of machine learning algorithms for renin-angiotensin-aldosterone system inhibitors associated renal adverse event prediction.

BACKGROUND: Renin-angiotensin-aldosterone system inhibitors (RAASi) are commonly used medications. Renal adverse events associated with RAASi are hyperkalemia and acute kidney injury. We aimed to evaluate the performance of machine learning (ML) algorithms in order to define event associated features and predict RAASi associated renal adverse events. MATERIALS AND METHODS: Data of patients recruited from five internal medicine and cardiology outpatient clinics were evaluated retrospectively. Clinical, laboratory, and medication data were acquired via electronic medical records. Dataset balancing and feature selection for machine learning algorithms were performed. Random forest (RF), k-nearest neighbor (kNN), naïve Bayes (NB), extreme gradient boosting (xGB), support vector machine (SVM), neural network (NN), and logistic regression (LR) were used to create a prediction model. RESULTS: 409 patients were included, and 50 renal adverse events occurred. The most important features predicting the renal adverse events were the index K and glucose levels, as well as having uncontrolled diabetes mellitus. Thiazides reduced RAASi associated hyperkalemia. kNN, RF, xGB and NN algorithms have the highest and similar AUC (≥ 98%), recall (≥ 94%), specifity (≥ 97%), precision (≥ 92%), accuracy (≥ 96%) and F1 statistics (≥ 94%) performance metrics for prediction. CONCLUSION: RAASi associated renal adverse events can be predicted prior to medication initiation by machine learning algorithms. Further prospective studies with large patient numbers are needed to create scoring systems as well as for their validation.

Human memory T cell dynamics after aluminum-adjuvanted inactivated whole-virion SARS-CoV-2 vaccination.

This study evaluates the functional capacity of CD4+ and CD8+ terminally-differentiated effector (TEMRA), central memory (TCM), and effector memory (TEM) cells obtained from the volunteers vaccinated with an aluminum-adjuvanted inactivated whole-virion SARS-CoV-2 vaccine (CoronaVac). The volunteers were followed for T cell immune responses following the termination of a randomized phase III clinical trial. Seven days and four months after the second dose of the vaccine, the memory T cell subsets were collected and stimulated by autologous monocyte-derived dendritic cells (mDCs) loaded with SARS-CoV-2 spike glycoprotein S1. Compared to the placebo group, memory T cells from the vaccinated individuals significantly proliferated in response to S1-loaded mDCs. CD4+ and CD8+ memory T cell proliferation was detected in 86% and 78% of the vaccinated individuals, respectively. More than 73% (after a short-term) and 62% (after an intermediate-term) of the vaccinated individuals harbored TCM and/or TEM cells that responded to S1-loaded mDCs by secreting IFN-γ. The expression of CD25, CD38, 4-1BB, PD-1, and CD107a indicated a modulation in the memory T cell subsets. Especially on day 120, PD-1 was upregulated on CD4+ TEMRA and TCM, and on CD8+ TEM and TCM cells; accordingly, proliferation and IFN-γ secretion capacities tended to decline after 4 months. In conclusion, the combination of inactivated whole-virion particles with aluminum adjuvants possesses capacities to induce functional T cell responses.

The Collateral Benefit of COVID Pandemic: Improved Pharmacological Venous Thromboembolism Prophylaxis Practices in Non-COVID Patients.

Background: COVID-19 creates a hypercoagulable state with a wide spectrum of clinical manifestations. Of those, venous thromboembolism (VTE) is prevalent, and numerous studies have highlighted the importance of VTE prophylaxis. Pre-pandemic VTE prophylaxis practices have already been poor, despite guidelines. We hypothesized that the gap between guidelines and practices might have been closed due to increased awareness. Materials and Methods: Non-COVID-19 patients hospitalized in the internal medicine ward of a university hospital between January 1st, 2021, and June 30th, 2021, were assessed. VTE risk and thromboprophylaxis requirements were assessed using the Padua Prediction Score (PPS). The results were compared with the findings of the study conducted in the same setting before the pandemic. Results: A total of 267 patients were included, and 81 patients (30.3%) received prophylaxis. A total of 128 patients' (47.9%) PPS was ≥ 4, and 69 patients (53.9%) received prophylaxis; 12 low-risk patients (8.6%) received prophylaxis although it was not indicated. Compared to the pre-pandemic figures, both appropriate prophylaxis use and overuse rates have risen. While the increment rate of appropriate prophylaxis was statistically significant, the increment rate of overuse did not reach statistical significance. Patients hospitalized for infectious diseases and respiratory failure were more likely to receive appropriate prophylaxis. Conclusion: We have demonstrated a significant increase in appropriate pharmacologic prophylaxis rates among high-risk patients. Besides all the collateral damage the pandemic has created, it might also have brought collateral benefits with regards to VTE prophylaxis.

Clinical outcomes and economic burden of seasonal influenza and other respiratory virus infections in hospitalized adults.

The cost of influenza and other respiratory virus infections should be determined to analyze the real burden of these diseases. We aimed to investigate the clinical outcomes and cost of illness due to respiratory virus infections in hospitalized adult patients. Hospitalized patients who had nasal swab sampling for a suspected viral infection between August 1, 2018 to March 31, 2019 were included. Outcome variables were oxygen requirement, mechanical ventilation need, intensive care unit admission, and cost. At least one viral pathogen was detected in 125 (47.7%) of 262 patients who were included in the study. Fifty-five (20.9%) of the patients were infected with influenza. Influenza-positive patients had higher rates for respiratory support, intensive care unit admission, and mortality compared to all other patients. The average cost of hospitalization per person was 2879.76 USD in the influenza-negative group, while the same cost was 3274.03 USD in the influenza-positive group. Although all of the vaccinated influenza-positive patients needed oxygen support, neither of them required invasive mechanical ventilation or intensive care unit admission. The average hospitalization cost per person was 779.70 USD in the vaccinated group compared to 3762.01 USD in the unvaccinated group. Disease-related direct cost of influenza in the community was estimated as 22 776 075.61 USD in the 18-65 years of age group and 15 756 120.02 USD in the 65 years of age and over group per year. Influenza, compared to other respiratory virus infections, can lead to untoward clinical outcomes and mortality as well as higher direct medical costs in adults.

Pertussis prevalence among adult patients with acute cough.

BACKGROUND: Bordetella pertussis infection remains an important health problem in adults due to the increasing prevalence in recent years. Pertussis in adults can be easily overlooked or misdiagnosed. We aimed to determine the prevalence of pertussis in adult patients with acute cough and the clinical features of the pertussis cases. METHODS: Internal Medicine and Pulmonology inpatient wards and outpatient clinics were screened between March 2017 and June 2018. Patients with cough duration between 1 week and 1 month were enrolled. Those who were on antibiotics for more than 5 days were excluded. A total of 115 patients were enrolled. Nasopharyngeal swabs were taken and real-time polymerase chain reaction analyses were done. RESULTS: According to the pertussis case definition, 47.8% of the patients were diagnosed with probable pertussis. We found the prevalence of pertussis as 3.5% in our cohort. All of the patients with pertussis had a history of paroxysmal cough with a mean duration of 20 days. DISCUSSION: These results show that pertussis continues to be a health problem for adults and may present with acute cough. The growing number of adult pertussis cases suggest that vaccination of children is inadequate to prevent pertussis and the concept of 'lifelong vaccination' should be strengthened.

Efficacy, Immunogenicity, and Safety of the Two-Dose Schedules of TURKOVAC versus CoronaVac in Healthy Subjects: A Randomized, Observer-Blinded, Non-Inferiority Phase III Trial.

We present the interim results of the efficacy, immunogenicity, and safety of the two-dose schedules of TURKOVAC versus CoronaVac. This was a randomized, observer-blinded, non-inferiority trial (NCT04942405). Volunteers were 18-55 years old and randomized at a 1:1 ratio to receive either TURKOVAC or CoronaVac at Day 0 and Day 28, both of which are 3 µg/0.5 mL of inactivated severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) adsorbed to aluminum hydroxide. The primary efficacy outcome was the prevention of polymerase chain reaction (PCR)-confirmed symptomatic coronavirus disease 2019 (COVID-19) at least 14 days after the second dose in the modified per-protocol (mPP) group. Safety analyses were performed in the modified intention-to-treat (mITT) group. Between 22 June 2021 and 7 January 2022, 1290 participants were randomized. The mITT group consisted of 915 participants, and the mPP group consisted of 732 participants. During a median follow-up of 90 (IQR 86-90) days, the relative risk reduction with TURKOVAC compared to CoronaVac was 41.03% (95% CI 12.95-60.06) for preventing PCR-confirmed symptomatic COVID-19. The incidences of adverse events (AEs) overall were 58.8% in TURKOVAC and 49.7% in CoronaVac arms (p = 0.006), with no fatalities or grade four AEs. TURKOVAC was non-inferior to CoronaVac in terms of efficacy and demonstrated a good safety and tolerability profile.

Community-acquired pneumonia - An EFIM guideline critical appraisal adaptation for internists.

BACKGROUND: In real-life settings, guidelines frequently cannot be followed since many patients are multimorbid and/or elderly or have other complicating conditions which carry an increased risk of drug-drug interactions. This document aimed to adapt recommendations from existing clinical practice guidelines (CPGs) to assist physicians' decision-making processes concerning specific and complex scenarios related to acute CAP. METHODS: The process for the adaptation procedure started with the identification of unsolved clinical questions (PICOs) in patients with CAP and continued with critically appraising the updated existing CPGs and choosing the recommendations, which are most applicable to these specific scenarios. RESULTS: Seventeen CPGs were appraised to address five PICOs. Twenty-seven recommendations were endorsed based on 7 high, 9 moderate, 10 low, and 1 very low-quality evidence. The most valid recommendations applicable to the clinical practice were the following ones: Respiratory virus testing is strongly recommended during periods of increased respiratory virus activity. Assessing the severity with a validated prediction rule to discriminate where to treat the patient is strongly recommended along with reassessing the patient periodically for improvement as expected. In adults with multiple comorbidities, polypharmacy, or advanced age, it is strongly recommended to check for possible drug interactions before starting treatment. Strong graded recommendations exist on antibiotic treatment and its duration. Recommendations on the use of biomarkers such as C-reactive protein or procalcitonin to improve severity assessment are reported. CONCLUSION: This document provides a simple and reliable updated guide for clinical decision-making in the management of complex patients with multimorbidity and CAP in the real-life setting.

Physicians' responsibility toward environmental degradation and climate change: A position paper of the European Federation of Internal Medicine.

The current data on climate change and environmental degradation are dramatic. The consequences of these changes are already having a significant impact on people's health. Physicians - as advocates of the patients, but also as citizens - have an ethical obligation to be involved in efforts to stop these changes. The European Federation of Internal Medicine (EFIM) strongly encourages the Internal Medicine societies and internists across Europe to play an active role in matters related to climate change and environmental degradation. At a national level, this includes advocating the adoption of measures that reduce greenhouse gas (GHG) emissions and environmental degradation and contributing to policy decisions related to these issues. At a hospital level and in clinical practice, supporting actions by the health sector to reduce its ecological footprint is vital. At the level of EFIM and its associated internal societies, promoting educational activities and developing a toolkit to prepare internists to better care for citizens who suffer from the consequences of climate change. In addition to advocating and implementing effective actions to reduce the ecological footprint of the health industry, recommending the introduction of these themes in scientific programs of Internal Medicine meetings and congresses and the pre- and postgraduate medical training. At a personal level, internists must be active agents in advocating sustainable practices for the environment, increasing the awareness of the community about the health risks of climate change and environmental degradation, and being role models in the adoption of environmentally friendly behaviour.

A Quality Improvement Study on Delirium Awareness Day: In Pursuit of Missed Delirium Diagnoses.

The current study aimed to screen for delirium in hospitalized older adults and assess the validity of the Turkish version of the 4A's Test (4AT-TR) as a feasible tool to integrate in routine patient care. The point prevalence of delirium according to clinical evaluation in routine practice was detected among all patients aged ≥60 years in 12 pilot wards. Delirium screening was then conducted by two arms: (a) nurses using the 4AT-TR and (b) geriatricians according to Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) criteria. Prevalence of delirium according to clinical impression was 3.3% (n = 4), whereas prevalence was 12.4% (n = 17) according to DSM-5 criteria and 13.8% (n = 17) according to the 4AT-TR. The 4AT-TR performed by nurses had a sensitivity of 66.6% and specificity of 93.5%. Area under the receiver operating characteristic curve for delirium diagnosis was 0.819 (p < 0.001). Most delirium cases remain undetected unless a routine and formal delirium assessment is integrated in hospital care of high-risk patients. The 4AT-TR performed by nurses seems to be a valid tool for determining delirium in hospitalized older adults. [Journal of Gerontological Nursing, 48(8), 43-51.].

[Longitudinal Assessment of Anti-Spike-1 antibody Responses in a Group of Hospitalized Patients with SARS-CoV-2 Infection]. / Hastaneye Yatan SARS-CoV-2 Enfeksiyonlu Bir Grup Hastanin Anti-Spike-1 Antikor Yanitlarinin Boylamsal Degerlendirilmesi.

The coronavirus disease-2019 (COVID-19) has become a global cause of death/injury, particularly for those with limited access to vaccination programs and healthcare systems. The risk of re-infection is not negligible due to the emergence of new variants and the decrease in immunity of those who have recovered COVID-19 before. In this study, it was aimed to show longitudinally the change in antibody levels of patients hospitalized for COVID-19 who had an antibody response in the early stages of their infection and to reveal a response pattern that would help to predict patients whose antibody responses decreased or persisted over time. This observational, single-center study included 38 non-critical patients admitted to COVID-19 wards. Anti-spike-1 IgG levels were investigated by the "enzyme-linked immunosorbent assay (ELISA)" method in two different samples taken at different times in each patient. Two distinct anti-spike-1 IgG antibody response patterns were detected in the study; the first pattern was that with low antibody production at first who had an increase in antibody levels after an average of six months, and the second pattern was that the initially high antibody levels decreased after an average of six months. This paradoxical kinetic may blur physicians' predictions of antibody response. In general, anti-spike-1 antibody levels showed a moderate decrease after six months, but production seems to continue (mean ∆IgG= -0.77; σ= 4; p= 0.24). Higher antibody levels were observed at the beginning in patients with concomitant bacterial pneumonia (mean initial IgG= 7.67; σ= 3.54) (p= 0.03). Although the production of S1-IgG in patients recovered from severe acute respiratory system coronavirus2 (SARS-CoV-2) was modestly reduced compared to the beginning measurements, the production in general persisted during the study period. It appears that IgG responses increase or remain constant in individuals with relatively low IgG index values when controlled after an average of 180 days, while IgG tends to decrease in individuals with high IgG index values.

Relative Vaccine Effectiveness of the Third Dose of CoronaVac or BNT162b2 Following a Two-Dose CoronaVac Regimen: A Prospective Observational Cohort Study from an Adult Vaccine Center in Turkey.

Coronavirus disease 2019 (COVID-19) continues to pose a threat to public health with the potential for the emergence of new variants. Vaccines are the milestones to control and slow down the damage of the pandemic. As of January 2021, a two-dose regimen with CoronaVac was authorized in Turkey. Due to the waning seroprevalence rate of SARS-CoV-2 over time, BNT162b2 or CoronaVac has been administered as the third dose following a two-dose CoronaVac regimen as a national vaccination policy. As of 14 January 2021, 5243 volunteers who received two doses of the CoronaVac vaccine at Hacettepe University Adult Vaccine Center were followed prospectively. In our study, relative vaccine effectiveness (VEff) for the third dose of the CoronaVac was 58.24% and 87.27% for BNT162b2 in preventing symptomatic COVID-19 cases. There were no hospitalizations, intensive care unit admissions, or deaths in third-dose booster groups with either BNT162b2 or CoronaVac, yielding 100% effectiveness. Both homologous or heterologous third-dose boosters provided further protection against severe COVID-19 and should be prioritized as an effective strategy to combat the COVID-19 pandemic.

Independent predictors of in-hospital mortality and the need for intensive care in hospitalized non-critical COVID-19 patients: a prospective cohort study.

One of the most helpful strategies to deal with ongoing coronavirus pandemics is to use some prudence when treating patients infected with SARS-CoV-2. We aimed to evaluate the clinical, demographic, and laboratory parameters that might have predictive value for in-hospital mortality and the need for intensive care and build a model based on them. This study was a prospective, observational, single-center study including non-critical patients admitted to COVID-19 wards. Besides classical clinic-demographic features, basic laboratory parameters obtained on admission were tested, and then new models for each outcome were developed built on the most significant variables. Receiver operating characteristics (ROC) analyses were performed by calculating each model's probability. A total of 368 non-critical hospitalized patients were recruited, the need for ICU care was observed in 70 patients (19%). The total number of patients who died in either ICU or wards was 39 (10.6%). The first two models (based on clinical features and demographics) were developed to predict ICU and death, respectively; older age, male sex, active cancer, and low baseline saturation were noted to be independent predictors. The area under the curve values of the first two models were noted 0.878 and 0.882 (p < .001; confidence interval [CI] 95% [0.837-0.919], p < .001; CI 95% [0.844-0.922]). Following two models, the third and fourth were based on laboratory parameters with clinic-demographic features. Initial lower sodium and lower albumin levels were determined as independent factors in predicting the need for ICU care; higher blood urea nitrogen and lower albumin were independent factors in predicting in-hospital mortality. The area under the curve values of the third and fourth model was noted 0.938 and 0.929, respectively (p < .001; CI 95% [0.912-0.965], p < .001; CI 95% [0.895-962]). By integrating the widely available blood tests results with simple clinic demographic data, non-critical patients can be stratified according to their risk level. Such stratification is essential to filter the patients' non-critical underlying diseases and conditions that can obfuscate the physician's predictive capacity.

A COVID-19 first evaluation clinic at a university hospital in Turkey.

BACKGROUND: We aimed to analyze the usefulness of such a reserved area for the admission of the patients' symptoms suggesting COVID-19 and compare the demographic and clinical characteristics of the patients with COVID-19 and without COVID-19 who were admitted to C1 during the first month of the COVID-19 outbreak in our hospital. METHODS: A new area was set up in Hacettepe University Adult Hospital to limit the contact of COVID-19 suspicious patients with other patients, which was named as COVID-19 First Evaluation Outpatient Clinic (C1). C1 had eight isolation rooms and two sampling rooms for SARS-CoV-2 polymerase-chain-reaction (PCR). All rooms were negative-pressurized. Patients who had symptoms that were compatible with COVID-19 were referred to C1 from pretriage areas. All staff received training for the appropriate use of personal protective equipment and were visited daily by the Infection Prevention and Control team. RESULTS: One hundred and ninety-eight (29.4%) of 673 patients who were admitted to C1were diagnosed with COVID-19 between March 20, 2020, and April 19, 2020. SARS-CoV-2 PCR was positive in 142 out of 673 patients. Chest computerized tomography (CT) was performed in 421 patients and COVID-19 was diagnosed in 56 of them based on CT findings despite negative PCR. Four hundred and ninety-three patients were tested for other viral and bacterial infections with multiplex real-time reverse-transcriptase PCR (RTPCR). Blood tests that included complete blood count, renal and liver functions, d-dimer levels, ferritin, C- reactive protein, and procalcitonin were performed in 593 patients. Only one out of 44 healthcare workers who worked at C1 was infected by SARS-CoV-2. DISCUSSION: Early diagnosis of infected patients and ensuring adequate isolation are very important to control the spread of COVID-19. The purpose of setting up the COVID-19 first evaluation outpatient clinic was to prevent the overcrowding of ER due to mild or moderate infections, ensure appropriate distancing and isolation, and enable emergency services to serve for real emergencies. A wellplanned outpatient care area and teamwork including internal medicine, microbiology, and radiology specialists under the supervision of infectious diseases specialists allowed adequate management of the mild-to-moderate patients with suspicion of COVID-19.

ONC201/TIC10 Is Empowered by 2-Deoxyglucose and Causes Metabolic Reprogramming in Medulloblastoma Cells in Vitro Independent of C-Myc Expression.

The purpose of this study was to examine whether the imipridone ONC201/TIC10 affects the metabolic and proliferative activity of medulloblastoma cells in vitro. Preclinical drug testing including extracellular flux analyses (agilent seahorse), MTT assays and Western blot analyses were performed in high and low c-myc-expressing medulloblastoma cells. Our data show that treatment with the imipridone ONC201/TIC10 leads to a significant inihibitory effect on the cellular viability of different medulloblastoma cells independent of c-myc expression. This effect is enhanced by glucose starvation. While ONC201/TIC10 decreases the oxidative consumption rates in D458 (c-myc high) and DAOY (c-myc low) cells extracellular acidification rates experienced an increase in D458 and a decrease in DAOY cells. Combined treatment with ONC201/TIC10 and the glycolysis inhibitor 2-Deoxyglucose led to a synergistic inhibitory effect on the cellular viability of medulloblastoma cells including spheroid models. In conclusion, our data suggest that ONC201/TIC10 has a profound anti-proliferative activity against medulloblastoma cells independent of c-myc expression. Metabolic targeting of medulloblastoma cells by ONC201/TIC10 can be significantly enhanced by an additional treatment with the glycolysis inhibitor 2-Deoxyglucose. Further investigations are warranted.