Virtual reality and live scenario simulation: options for training medical students in mass casualty incident triage

Introduction Multicasualty triage is the process of establishing the priority of care among casualties in disaster management. Recent mass casualty incidents (MCI) revealed that health personnel are unfamiliar with the triage protocols. The objective of this study is to compare the relative impact of two simulation-based methods for training medical students in mass casualty triage using the Simple Triage and Rapid Treatment (START) algorithm. Methods A prospective randomized controlled longitudinal study. Medical students enrolled in the emergency medicine course were randomized into two groups (A and B). On day 1, group A students were exposed to a virtual reality (VR) scenario and group B students were exposed to a live scenario (LS), both exercises aiming at triaging 10 victims in a limited period of time (30 seconds/victim). On day 2 all students attended a 2-hour lecture about medical disaster management and START. On day 3 group A and B students were exposed to a LS and to a VR scenario respectively. The vital signs and clinical condition of the 10 victims were identical in the two scenarios. Ability of the groups to manage a simulated triage scenario was then compared (times and triage accuracy). Results Groups A and B were composed of 25 and 28 students respectively. During day 1 group A LS triage accuracy was 58%, while the average time to assess all patients was 4 minutes 28 seconds. The group B VR scenario triage accuracy was 52%, while the average time to complete the assessment was 5 minutes 18 seconds. During day 3 the triage accuracy for group A VR simulation was 92%, while the average time was 3 minutes 53 seconds. Group B triage accuracy during the LS was 84%, with an average time of 3 minutes 25 seconds. Triage scores improved significantly during day 3 (P < 0.001) in the two groups. The time to complete each scenario decreased significantly from day 1 to day 3. Conclusions The study demonstrates that the training course generates significant improvement in triage accuracy and speed. It also reveals that VR simulation compared to live exercises has equivalent results in prompting critical decisions in mass casualty drills. In the beginning the average time to complete the VR scenario was higher than the LS. This could be due to the fact that on day 1 very detailed VR victims created a higher challenge for untaught students. However, the higher triage accuracy recorded at the end of day 3 in VR could be explained by a lower stress level compared to the LS, which could be creating a more stressful environment in taught students

Comparison of two disaster drills' management performed by trained and not-trained students: key times evaluation

Introduction The aim of this report is to compare two disaster exercises' management of students with different backgrounds. To our knowledge nobody has ever compared two exercises, probably because of the difficulty in their evaluation. We implemented a tool for an objective evaluation [1] and we used it for this purpose. Methods Both drills represented a ceiling collapse over a crowded room with a similar amount of casualties and similar severity index. The START triage system was used. The trained students (T) were attending the European Master in Disaster Medicine (EMDM), while the not-trained students (NT) were at the beginning of an introductory course in disaster medicine. During the exercises we recorded key victim-provider interaction times [2] using victim-based data collection. Each victim had their own data card to record triage and time information. Results In this preliminary report we present data regarding the scene length of stay (LOS) and triage to collecting area/advanced medical post time (T-AMP). The LOS was 67.5 (50.0 to 111.0) minutes (25 to 75 IQR) for T as compared with 145.0 (110.0 to 150.0) minutes (25 to 75 IQR) for NT (P < 0.001). Stratification according to assigned triage code showed no difference for high-priority codes (reds and yellows) as opposed to the green code (55.0 (47.0 to 75.0) minutes for T vs 145.0 (141.0 to 155.0) minutes for NT with P < 0.01). T-AMP was 10.0 (3.0 to 34.5) minutes for T as compared with 63.5 (19.5 to 104.3) minutes for NT (P < 0.001). Stratification according to triage code showed no difference for red codes between T and NT but showed a difference for yellow codes (36.5 (15.0 to 82.0) vs 71.0 (30.0 to 99.0) minutes) and green codes (7.0 (3.0 to 12.0) vs 85.0 (17.3 to 115.0) minutes) with P < 0.01. Conclusions Both teams evacuated red codes before the yellow ones in similar time. T-AMP was shorter considering global, yellow and green codes for T as opposed to NT. Global and green LOS was also shorter in the T group as opposed to NT. Training seems to influence global exercise management, less affecting red codes but with an impact on yellow and green evacuation strategies

Mining of self-organizing map gene-expression portraits reveals prognostic stratification of HPV-positive head and neck squamous cell carcinoma

Patients (pts) with head and neck squamous cell carcinoma (HNSCC) have different epidemiologic, clinical, and outcome behaviors in relation to human papillomavirus (HPV) infection status, with HPV-positive patients having a 70% reduction in their risk of death. Little is known about the molecular heterogeneity in HPV-related cases. In the present study, we aim to disclose the molecular subtypes with potential biological and clinical relevance. Through a literature review, 11 studies were retrieved with a total of 346 gene-expression data points from HPV-positive HNSCC pts. Meta-analysis and self-organizing map (SOM) approaches were used to disclose relevant meta-gene portraits. Unsupervised consensus clustering provided evidence of three biological subtypes in HPV-positive HNSCC: Cl1, immune-related; Cl2, epithelial\u2013mesenchymal transition-related; Cl3, proliferation-related. This stratification has a prognostic relevance, with Cl1 having the best outcome, Cl2 the worst, and Cl3 an intermediate survival rate. Compared to recent literature, which identified immune and keratinocyte subtypes in HPV-related HNSCC, we confirmed the former and we separated the latter into two clusters with different biological and prognostic characteristics. At present, this paper reports the largest meta-analysis of HPV-positive HNSCC studies and offers a promising molecular subtype classification. Upon further validation, this stratification could improve patient selection and pave the way for the development of a precision medicine therapeutic approach

Gene Expression Clustering and Selected Head and Neck Cancer Gene Signatures Highlight Risk Probability Differences in Oral Premalignant Lesions

Background: Oral premalignant lesions (OPLs) represent the most common oral precancerous conditions. One of the major challenges in this field is the identification of OPLs at higher risk for oral squamous cell cancer (OSCC) development, by discovering molecular pathways deregulated in the early steps of malignant transformation. Analysis of deregulated levels of single genes and pathways has been successfully applied to head and neck squamous cell cancers (HNSCC) and OSCC with prognostic/predictive implications. Exploiting the availability of gene expression profile and clinical follow-up information of a well-characterized cohort of OPL patients, we aim to dissect tissue OPL gene expression to identify molecular clusters/signatures associated with oral cancer free survival (OCFS). Materials and methods: The gene expression data of 86 OPL patients were challenged with: an HNSCC specific 6 molecular subtypes model (Immune related: HPV related, Defense Response and Immunoreactive; Mesenchymal, Hypoxia and Classical); one OSCC-specific signature (13 genes); two metabolism-related signatures (3 genes and signatures raised from 6 metabolic pathways associated with prognosis in HNSCC and OSCC, respectively); a hypoxia gene signature. The molecular stratification and high versus low expression of the signatures were correlated with OCFS by Kaplan\u2013Meier analyses. The association of gene expression profiles among the tested biological models and clinical covariates was tested through variance partition analysis. Results: Patients with Mesenchymal, Hypoxia and Classical clusters showed an higher risk of malignant transformation in comparison with immune-related ones (log-rank test, p = 0.0052) and they expressed four enriched hallmarks: \u201cTGF beta signaling\u201d \u201cangiogenesis\u201d, \u201cunfolded protein response\u201d, \u201capical junction\u201d. Overall, 54 cases entered in the immune related clusters, while the remaining 32 cases belonged to the other clusters. No other signatures showed association with OCFS. Our variance partition analysis proved that clinical and molecular features are able to explain only 21% of gene expression data variability, while the remaining 79% refers to residuals independent of known parameters. Conclusions: Applying the existing signatures derived from HNSCC to OPL, we identified only a protective effect for immune-related signatures. Other gene expression profiles derived from overt cancers were not able to identify the risk of malignant transformation, possibly because they are linked to later stages of cancer progression. The availability of a new well-characterized set of OPL patients and further research is needed to improve the identification of adequate prognosticators in OPLs

Lung response to prone positioning in mechanically-ventilated patients with COVID-19

Background: Prone positioning improves survival in moderate-to-severe acute respiratory distress syndrome (ARDS) unrelated to the novel coronavirus disease (COVID-19). This benefit is probably mediated by a decrease in alveolar collapse and hyperinflation and a more homogeneous distribution of lung aeration, with fewer harms from mechanical ventilation. In this preliminary physiological study we aimed to verify whether prone positioning causes analogue changes in lung aeration in COVID-19. A positive result would support prone positioning even in this other population. Methods: Fifteen mechanically-ventilated patients with COVID-19 underwent a lung computed tomography in the supine and prone position with a constant positive end-expiratory pressure (PEEP) within three days of endotracheal intubation. Using quantitative analysis, we measured the volume of the non-aerated, poorly-aerated, well-aerated, and over-aerated compartments and the gas-to-tissue ratio of the ten vertical levels of the lung. In addition, we expressed the heterogeneity of lung aeration with the standardized median absolute deviation of the ten vertical gas-to-tissue ratios, with lower values indicating less heterogeneity. Results: By the time of the study, PEEP was 12 (10–14)&nbsp;cmH2O and the PaO2:FiO2 107 (84–173)&nbsp;mmHg in the supine position. With prone positioning, the volume of the non-aerated compartment decreased by 82 (26–147)&nbsp;ml, of the poorly-aerated compartment increased by 82 (53–174) ml, of the normally-aerated compartment did not significantly change, and of the over-aerated compartment decreased by 28 (11–186)&nbsp;ml. In eight (53%) patients, the volume of the over-aerated compartment decreased more than the volume of the non-aerated compartment. The gas-to-tissue ratio of the ten vertical levels of the lung decreased by 0.34 (0.25–0.49)&nbsp;ml/g per level in the supine position and by 0.03 (− 0.11 to 0.14) ml/g in the prone position (p &lt; 0.001). The standardized median absolute deviation of the gas-to-tissue ratios of those ten levels decreased in all patients, from 0.55 (0.50–0.71) to 0.20 (0.14–0.27) (p &lt; 0.001). Conclusions: In fifteen patients with COVID-19, prone positioning decreased alveolar collapse, hyperinflation, and homogenized lung aeration. A similar response has been observed in other ARDS, where prone positioning improves outcome. Therefore, our data provide a pathophysiological rationale to support prone positioning even in COVID-19

A microRNA prognostic signature in patients with diffuse intrinsic pontine gliomas through non-invasive liquid biopsy

Diffuse midline gliomas (DMGs) originate in the thalamus, brainstem, cerebellum and spine. This entity includes tumors that infiltrate the pons, called diffuse intrinsic pontine gliomas (DIPGs), with a rapid onset and devastating neurological symptoms. Since surgical removal in DIPGs is not feasible, the purpose of this study was to profile circulating miRNA expression in DIPG patients in an effort to identify a non-invasive prognostic signature with clinical impact. Using a high-throughput platform, miRNA expression was profiled in serum samples collected at the time of MRI diagnosis and prior to radiation and/or systemic therapy from 47 patients enrolled in clinical studies, combining nimotuzumab and vinorelbine with concomitant radiation. With progression-free survival as the primary endpoint, a semi-supervised learning approach was used to identify a signature that was also tested taking overall survival as the clinical endpoint. A signature comprising 13 circulating miRNAs was identified in the training set (n = 23) as being able to stratify patients by risk of disease progression (log-rank p = 0.00014; HR = 7.99, 95% CI 2.38–26.87). When challenged in a separate validation set (n = 24), it confirmed its ability to predict progression (log-rank p = 0.00026; HR = 5.51, 95% CI 2.03–14.9). The value of our signature was also confirmed when overall survival was considered (log-rank p = 0.0021, HR = 4.12, 95% CI 1.57–10.8). We have identified and validated a prognostic marker based on the expression of 13 circulating miRNAs that can shed light on a patient’s risk of progression. This is the first demonstration of the usefulness of nucleic acids circulating in the blood as powerful, easy-to-assay molecular markers of disease status in DIPG. This study provides Class II evidence that a signature based on 13 circulating miRNAs is associated with the risk of disease progression

A probabilistic sediment cascade model of sediment transfer in the Illgraben

We present a probabilistic sediment cascade model to simulate sediment transfer in a mountain basin (Illgraben, Switzerland) where sediment is produced by hillslope landslides and rockfalls and exported out of the basin by debris flows and floods. The model conceptualizes the fluvial system as a spatially lumped cascade of connected reservoirs representing hillslope and channel storages where sediment goes through cycles of storage and remobilization by surface runoff. The model includes all relevant hydrological processes that lead to runoff formation in an Alpine basin, such as precipitation, snow accumulation, snowmelt, evapotranspiration, and soil water storage. Although the processes of sediment transfer and debris flow generation are described in a simplified manner, the model produces complex sediment discharge behavior which is driven by the availability of sediment and antecedent wetness conditions (system memory) as well as the triggering potential (climatic forcing). The observed probability distribution of debris flow volumes and their seasonality in 2000–2009 are reproduced. The stochasticity of hillslope sediment input is important for reproducing realistic sediment storage variability, although many details of the hillslope landslide triggering procedures are filtered out by the sediment transfer system. The model allows us to explicitly quantify the division into transport and supply-limited sediment discharge events. We show that debris flows may be generated for a wide range of rainfall intensities because of variable antecedent basin wetness and snowmelt contribution to runoff, which helps to understand the limitations of methods based on a single rainfall threshold for debris flow initiation in Alpine basins

Gene Expression Clustering and Selected Head and Neck Cancer Gene Signatures Highlight Risk Probability Differences in Oral Premalignant Lesions

BACKGROUND: Oral premalignant lesions (OPLs) represent the most common oral precancerous conditions. One of the major challenges in this field is the identification of OPLs at higher risk for oral squamous cell cancer (OSCC) development, by discovering molecular pathways deregulated in the early steps of malignant transformation. Analysis of deregulated levels of single genes and pathways has been successfully applied to head and neck squamous cell cancers (HNSCC) and OSCC with prognostic/predictive implications. Exploiting the availability of gene expression profile and clinical follow-up information of a well-characterized cohort of OPL patients, we aim to dissect tissue OPL gene expression to identify molecular clusters/signatures associated with oral cancer free survival (OCFS). MATERIALS AND METHODS: The gene expression data of 86 OPL patients were challenged with: an HNSCC specific 6 molecular subtypes model (Immune related: HPV related, Defense Response and Immunoreactive; Mesenchymal, Hypoxia and Classical); one OSCC-specific signature (13 genes); two metabolism-related signatures (3 genes and signatures raised from 6 metabolic pathways associated with prognosis in HNSCC and OSCC, respectively); a hypoxia gene signature. The molecular stratification and high versus low expression of the signatures were correlated with OCFS by Kaplan-Meier analyses. The association of gene expression profiles among the tested biological models and clinical covariates was tested through variance partition analysis. RESULTS: Patients with Mesenchymal, Hypoxia and Classical clusters showed an higher risk of malignant transformation in comparison with immune-related ones (log-rank test, p = 0.0052) and they expressed four enriched hallmarks: "TGF beta signaling" "angiogenesis", "unfolded protein response", "apical junction". Overall, 54 cases entered in the immune related clusters, while the remaining 32 cases belonged to the other clusters. No other signatures showed association with OCFS. Our variance partition analysis proved that clinical and molecular features are able to explain only 21% of gene expression data variability, while the remaining 79% refers to residuals independent of known parameters. CONCLUSIONS: Applying the existing signatures derived from HNSCC to OPL, we identified only a protective effect for immune-related signatures. Other gene expression profiles derived from overt cancers were not able to identify the risk of malignant transformation, possibly because they are linked to later stages of cancer progression. The availability of a new well-characterized set of OPL patients and further research is needed to improve