Rapid identification of pediatric brain tumors with differential mobility spectrometry.

Introduction: Brain tumors are a major source of disease burden in pediatric population, with the most common tumor types being pilocytic astrocytoma, ependymoma and medulloblastoma. In every tumor entity, surgery is the cornerstone of treatment, but the importance of gross-total resection and the corresponding patient prognosis is highly variant. However, real-time identification of pediatric CNS malignancies based on the histology of the frozen sections alone is especially troublesome. We propose a novel method based on differential mobility spectrometry (DMS) analysis for rapid identification of pediatric brain tumors. Methods: We prospectively obtained tumor samples from 15 pediatric patients (5 pilocytic astrocytomas, 5 ependymomas and 5 medulloblastomas). The samples were cut into 36 smaller specimens that were analyzed with the DMS. Results: With linear discriminant analysis algorithm, a classification accuracy (CA) of 70% was reached. Additionally, a 75% CA was achieved in a pooled analysis of medulloblastoma vs. gliomas. Discussion: Our results show that the DMS is able to differentiate most common pediatric brain tumor samples, thus making it a promising additional instrument for real-time brain tumor diagnostics.

The association between GRACE score at admission for myocardial infarction and the incidence of sudden cardiac arrests in long-term follow-up - the MADDEC study.

Background. Sudden cardiac arrest (SCA), often also leading to sudden cardiac death (SCD), is a common complication in coronary artery disease. Despite the effort there is a lack of applicable prediction tools to identify those at high risk. We tested the association between the validated GRACE score and the incidence of SCA after myocardial infarction. Material and methods. A retrospective analysis of 1,985 patients treated for myocardial infarction (MI) between January 1st 2015 and December 31st 2018 and followed until the 31st of December of 2021. The main exposure variable was patients' GRACE score at the point of admission and main outcome variable was incident SCA after hospitalization. Their association was analyzed by subdistribution hazard (SDH) model analysis. The secondary endpoints included SCA in patients with no indication to implantable cardioverter-defibrillator (ICD) device and incident SCD. Results. A total of 1985 patients were treated for MI. Mean GRACE score at baseline was 118.7 (SD 32.0). During a median follow-up time of 5.3 years (IQR 3.8-6.1 years) 78 SCA events and 52 SCDs occurred. In unadjusted analyses one SD increase in GRACE score associated with over 50% higher risk of SCA (SDH 1.55, 95% CI 1.29-1.85, p < 0.0001) and over 40% higher risk for SCD (1.42, 1.12-1.79, p = 0.0033). The associations between SCA and GRACE remained statistically significant even with patients without indication for ICD device (1.57, 1.30-1.90, p < 0.0001) as well as when adjusting with patients LVEF and omitting the age from the GRACE score to better represent the severity of the cardiac event. The association of GRACE and SCD turned statistically insignificant when adjusting with LVEF. Conclusions. GRACE score measured at admission for MI associates with long-term risk for SCA.

What is already known about this subject?Nearly 50% of cardiac mortality is caused by sudden cardiac death, often due to sudden cardiac arrest.Despite the effort, there is a lack of applicable prediction tools to identify those at high risk.What does this study add?This study shows that GRACE score measured at the point of admission for myocardial infarction can be used to evaluate patients' risk for sudden cardiac arrest in a long-term follow-up.How might this impact on clinical practice?Based on our findings, the GRACE score at the point of admission could significantly affect the patients' need for an ICD device after hospitalization for MI and should be considered as a contributing factor when evaluating the patients' follow-up care.

Confounding factors in peripheral thermal recovery time after active cooling.

OBJECTIVES: The effectiveness of normal physiological thermoregulation complicates differentiation between pathologic changes in medical thermography associated with peripheral artery disease and a number of other clinical conditions. In this study we investigate a number of potential confounding factors to the thermal recovery rate after active limb cooling, with the main focus on age and sex. APPROACH: The source data consists of 53 healthy individuals with no diagnosed cardiovascular disease or reported symptoms and with a mean age of 38.4 (± 12.1) years. The sample population was further divided into male (N = 14) and female groups (N = 39). The thermal recovery time was measured using two thermal cameras from both lower limbs on plantar and dorsal sides. The active cooling was achieved using moldable cold pads placed on the plantar and dorsal side of the lower limb. The recovery was measured until the temperature had reached a stable level. The recovery time was determined from an exponential fit to the measured data. RESULTS: The correlation between the thermal recovery time constant and age varied from low to moderate linear correlation (0.31 ≤ ⍴ ≤ 70), depending on the inspected region of interest, with a higher statistically significant correlation in the medial regions. The contralateral limb temperature differences or the thermal time constants did not have statistically significant differences between the male and female sexes. Further, the secondary metrics such as participant's body mass, body-mass index, or systolic blood pressure had low or no correlation with the thermal recovery time in the study group. CONCLUSION: The thermal recovery time constant after active cooling appears as a relatively independent metric from the majority of the measured potential confounding factors. Age should be accounted for when performing thermal recovery measurements. However, dynamic thermal imaging and its methodologies require further research and exploration.

Ventricular Arrhythmias and Hemodynamic Collapse During Acute Coronary Syndrome- Increased Risk for Sudden Cardiac Death?

AIM: In acute phase of acute coronary syndrome (ACS), ventricular tachycardia (VT) and/or ventricular fibrillation (VF) leading to resuscitation are not considered to be associated with increased long-term sudden cardiac death (SCD) because the cause - acute ischemia - is believed to be reversible.Aim of this study was to investigate whether ventricular arrhythmias leading to sudden cardiac arrest during ACS associate with the risk of incident SCD in patients with normal or mildly impaired left ventricular ejection fraction (LVEF). METHODS: This study is based on a retrospective analysis of all 8,062 consecutive ACS patients undergoing coronary angiography with baseline LVEF ≥40% between 2007-2018 (follow-up until December 31st, 2021). The primary outcome was SCD equivalent life-threatening ventricular arrhythmias (LTVA) composing of true SCDs, aborted SCDs by successful resuscitation or appropriate ICD therapy. The risk of sudden LTVA was estimated with multivariate subdistribution hazard model using other deaths as competing events. RESULTS: Two-hundred and thirteen (n=211, 2.6%) patients suffered acute phase VF/VT leading to resuscitation and survived to discharge and most happened before angiography (80.6%, N=170) and were VF (92.9%, N=196). During a median follow-up of 7.6 years, 3.9% (N=316) of all the patients had LTVA (10.0% in VF/VT group vs 3.8% in other patients). VF/VTs during ACS associated with an increased risk for future SCD (HR 3.07; 95% CI 1.94-4.85, p<0.001). Most LTVAs occurred in patients without ICDs. CONCLUSIONS: VF/VT in ACS associates with remarkably high long-term risk for SCD in patients with LVEF ≥40%.

This retrospective study comprising of over 8,000 patients without significant heart failure after acute coronary syndrome indicates that patients with potentially fatal ventricular arrhythmias during hospitalization for acute coronary syndrome are at 3-fold risk of sudden cardiac death or equivalent events in long-term when compared to those without ventricular arrhythmias Further study is required to confirm our findings and to assess whether electrophysiological examination or implantable cardioverter defibrillator therapy could be useful to prevent sudden cardiac death in these patients.

Computed tomography -defined sarcopenia is associated with long-term survival among patients undergoing open thoracic aortic reconstruction.

BACKGROUND AND OBJECTIVE: As markers of sarcopenia, psoas muscle areas and indexes measured from computed tomography images have been found to predict long-term mortality in cardiothoracic as well as other surgical cohorts. Our objective was to investigate the association between psoas muscle status, taking into account muscle density in addition to area, and survival among patients undergoing open thoracic aortic reconstruction. METHODS: This was a retrospective registry study of a total of 451 patients treated with open surgery for thoracic aortic pathology. Psoas muscle area and density were measured from preoperative computed tomography images at the L3 and L4 lumbar levels. In addition, lean psoas muscle area was calculated by averaging sex-specific values of psoas muscle area and density. The association between mortality and psoas muscle status was analyzed with adjusted Cox-regression analysis. RESULTS: The median age of the study population was 63 (interquartile range (IQR): 53-70) years. The majority were male (74.7%, n = 337) and underwent elective procedures (58.1% n = 262). Surgery of the ascending aorta was carried out in 90% of the patients, and 15% (n = 67) had concomitant coronary artery bypass surgery. Aortic dissection was present in 34.6% (n = 156) patients. Median follow-up time was 4.3 years (IQR: 2.2-7.4). During the follow-up, 106 patients (23.5%) died, with 55.7% of deaths occurring within the first four postoperative weeks. Psoas muscle parameters were not associated with perioperative mortality, but significant independent associations with long-term mortality were observed for psoas muscle area, density, and lean psoas muscle area with hazard ratios (HRs) of 0.63 (95% confidence interval (CI): 0.45-0.88), 0.62 (95% CI: 0.46-0.83), and 0.47 (95% CI: 0.32-0.69), respectively (all per 1-SD increase). CONCLUSIONS: Psoas muscle sarcopenia status is associated with long-term mortality after open thoracic aortic surgery.

Thrombus Aspirates From Patients With Acute Ischemic Stroke Are Infiltrated by Viridans Streptococci.

BACKGROUND: Acute ischemic stroke may be due to embolism from ruptured atherosclerotic carotid arteries. DNA of oral bacteria, mainly the viridans streptococci group, has been detected in thrombus aspirates of patients with ischemic stroke as well as in carotid endarterectomy samples. Because viridans streptococci are known to possess thrombogenic properties, we studied whether their presence in thrombus aspirates and in carotid artery specimens can be confirmed using bacterial immunohistochemistry. METHODS AND RESULTS: Thrombus aspirates from 61 patients with ischemic stroke (70.5% men; mean age, 66.8 years) treated with mechanical thrombectomy, as well as carotid endarterectomy samples from 20 symptomatic patients (65.0% men; mean age, 66.2 years) and 48 carotid artery samples from nonstroke autopsy cases (62.5% men; mean age, 66.4 years), were immunostained with an antibody cocktail against 3 species (Streptococcus sanguinis, Streptococcus mitis, and Streptococcus gordonii) of viridans streptococci. Of the thrombus aspirates, 84.8% were immunopositive for viridans streptococci group bacteria, as were 80.0% of the carotid endarterectomy samples, whereas immunopositivity was observed in 31.3% of the carotid artery samples from nonstroke autopsies. Most streptococci were detected inside neutrophil granulocytes, but there were also remnants of bacterial biofilm as well as free bacterial infiltrates in some samples. CONCLUSIONS: Oral streptococci were found in aspirated thrombi of patients with acute ischemic stroke as well as in carotid artery samples. Our results suggest that viridans streptococci group bacteria may play a role in the pathophysiology of ischemic stroke.

Psoas muscle quantified muscle status and long-term mortality after cardiovascular interventions.

RESULTS: In the meta-analysis, psoas muscle measurements were significantly associated with mortality among men (p < 0.05), with high heterogeneity in the associations across all cohorts. There was very little difference in the association between PMA and PMD and mortality (HR 0.83, 95% CI 0.69-0.99, p = 0.002; HR 0.85, 95% CI 0.77-0.94, p = 0.041 for one SD increase in PMA and PMD in the random effects model). Combining PMA and PMD into one composite variable by multiplying their values together showed the most robust association in terms of the magnitude of the effect size in men (HR, 0.77; 95% CI 0.73-0.87, p < 0.001). Indexing PMA to body size did not result in any significant differences in this association. Among women, psoas muscle measurements were not associated with long-term mortality in this meta-analysis. CONCLUSIONS: Different psoas muscle measurements were significantly and very similarly associated with mortality among men but not among women. No single measurement stands out, although combining PMA and PMD seems to be a slightly stronger estimate in terms of effect size and should be considered in further studies.

Significant sarcopenia affecting survival in patients undergoing heavy invasive operations may be preoperatively assessed using images of psoas muscle (PM) from routine computerized tomography but the optimal method for evaluation is unclear. A meta-analysis of individual participant data of over two thousand patients undergoing cardiovascular interventions shows that different PM measurements of surface area and density were significantly and very similarly associated with mortality among men but not among women. Combining PM area with PM density to one estimate of lean psoas muscle area seems to provide the strongest hazard estimate among men.

Early Warning Software for Emergency Department Crowding.

Emergency department (ED) crowding is a well-recognized threat to patient safety and it has been repeatedly associated with increased mortality. Accurate forecasts of future service demand could lead to better resource management and has the potential to improve treatment outcomes. This logic has motivated an increasing number of research articles but there has been little to no effort to move these findings from theory to practice. In this article, we present first results of a prospective crowding early warning software, that was integrated to hospital databases to create real-time predictions every hour over the course of 5 months in a Nordic combined ED using Holt-Winters' seasonal methods. We show that the software could predict next hour crowding with an AUC of 0.94 (95% CI: 0.91-0.97) and 24 hour crowding with an AUC of 0.79 (95% CI: 0.74-0.84) using simple statistical models. Moreover, we suggest that afternoon crowding can be predicted at 1 p.m. with an AUC of 0.84 (95% CI: 0.74-0.91).

Transformers for cardiac patient mortality risk prediction from heterogeneous electronic health records.

With over 17 million annual deaths, cardiovascular diseases (CVDs) dominate the cause of death statistics. CVDs can deteriorate the quality of life drastically and even cause sudden death, all the while inducing massive healthcare costs. This work studied state-of-the-art deep learning techniques to predict increased risk of death in CVD patients, building on the electronic health records (EHR) of over 23,000 cardiac patients. Taking into account the usefulness of the prediction for chronic disease patients, a prediction period of six months was selected. Two major transformer models that rely on learning bidirectional dependencies in sequential data, BERT and XLNet, were trained and compared. To our knowledge, the presented work is the first to apply XLNet on EHR data to predict mortality. The patient histories were formulated as time series consisting of varying types of clinical events, thus enabling the model to learn increasingly complex temporal dependencies. BERT and XLNet achieved an average area under the receiver operating characteristic curve (AUC) of 75.5% and 76.0%, respectively. XLNet surpassed BERT in recall by 9.8%, suggesting that it captures more positive cases than BERT, which is the main focus of recent research on EHRs and transformers.

Less is more - The Finnish Prehospital Stroke Scale prospective validation.

OBJECTIVES: The current bifurcation of the acute stroke care pathway requires prehospital separation of strokes caused by large vessel occlusion. The first four binary items of the Finnish Prehospital Stroke Scale (FPSS) identify stroke in general, while the fifth binary item alone identifies stroke due to large vessel occlusion. The straightforward design is both easy for paramedics and statistically beneficial. We implemented FPSS based Western Finland Stroke Triage Plan, including medical districts of a comprehensive stroke center and four primary stroke centers. PATIENTS AND METHODS: The prospective study population was consecutive recanalization candidates transported to the comprehensive stroke center within the first six months of implementing the stroke triage plan. Cohort 1 consisted of n=302 thrombolysis- or endovascular treatment candidates transported from the comprehensive stroke center hospital district. Cohort 2 comprised ten endovascular treatment candidates transferred directly to the comprehensive stroke center from the medical districts of four primary stroke centers. RESULTS: In Cohort 1, FPSS sensitivity for large vessel occlusion was 0.66, specificity 0.94, positive predictive value 0.70, and negative predictive value 0.93. Of the ten Cohort 2 patients, nine had large vessel occlusion, and one had an intracerebral hemorrhage. CONCLUSIONS: FPSS is straightforward enough to be implemented in primary care services to identify candidates for endovascular treatment and thrombolysis. When used by paramedics, it predicted two-thirds of large vessel occlusions with the highest specificity and positive predictive value reported to date.

Assessment of chronic limb threatening ischemia using thermal imaging.

OBJECTIVES: Current chronic limb threatening ischemia (CLTI) diagnostics require expensive equipment, using ionizing radiation or contrast agents, or summative surrogate methods lacking in spatial information. Our aim is to develop and improve contactless, non-ionizing and cost-effective diagnostic methods for CLTI assessment with high spatial accuracy by utilizing dynamic thermal imaging and the angiosome concept. APPROACH: Dynamic thermal imaging test protocol was suggested and implemented with a number of computational parameters. Pilot data was measured from 3 healthy young subjects, 4 peripheral artery disease (PAD) patients and 4 CLTI patients. The protocol consists of clinical reference measurements, including ankle- and toe-brachial indices (ABI, TBI), and a modified patient bed for hydrostatic and thermal modulation tests. The data was analyzed using bivariate correlation. RESULTS: The thermal recovery time constant was on average higher for the PAD (88%) and CLTI (83%) groups with respect to the healthy young subjects. The contralateral symmetry was high for the healthy young group and low for the CLTI group. The recovery time constants showed high negative correlation to TBI (ρ = -0.73) and ABI (ρ = -0.60). The relation of these clinical parameters to the hydrostatic response and absolute temperatures (|ρ|<0.3) remained unclear. CONCLUSION: The lack of correlation for absolute temperatures or their contralateral differences with the clinical status, ABI and TBI disputes their use in CLTI diagnostics. Thermal modulation tests tend to augment the signs of thermoregulation deficiencies and accordingly high correlations were found with all reference metrics. The method is promising for establishing the connection between impaired perfusion and thermography. The hydrostatic modulation test requires more research with stricter test conditions.

The Detection of Bacteria in the Maxillary Sinus Secretion of Patients With Acute Rhinosinusitis Using an Electronic Nose: A Pilot Study.

OBJECTIVE: Detecting bacteria as a causative pathogen of acute rhinosinusitis (ARS) is a challenging task. Electronic nose technology is a novel method for detecting volatile organic compounds (VOCs) that has also been studied in association with the detection of several diseases. The aim of this pilot study was to analyze maxillary sinus secretion with differential mobility spectrometry (DMS) and to determine whether the secretion demonstrates a different VOC profile when bacteria are present. METHODS: Adult patients with ARS symptoms were examined. Maxillary sinus contents were aspirated for bacterial culture and DMS analysis. k-Nearest neighbor and linear discriminant analysis were used to classify samples as positive or negative, using bacterial cultures as a reference. RESULTS: A total of 26 samples from 15 patients were obtained. After leave-one-out cross-validation, k-nearest neighbor produced accuracy of 85%, sensitivity of 67%, specificity of 94%, positive predictive value of 86%, and negative predictive value of 84%. CONCLUSIONS: The results of this pilot study suggest that bacterial positive and bacterial negative sinus secretion release different VOCs and that DMS has the potential to detect them. However, as the results are based on limited data, further conclusions cannot be made. DMS is a novel method in disease diagnostics and future studies should examine whether the method can detect bacterial ARS by analyzing exhaled air.

Incidence of sudden cardiac arrest and sudden cardiac death after unstable angina pectoris and myocardial infarction.

BACKGROUND: Sudden cardiac arrests (SCA) and sudden cardiac deaths (SCD) are believed to account for a large proportion of deaths due to cardiovascular causes. The purpose of this study is to provide comprehensive information on the epidemiology of SCAs and SCDs after acute coronary syndrome. METHODS: The incidence of SCA (including SCDs) was studied retrospectively among 10,316 consecutive patients undergoing invasive evaluation for acute coronary syndrome (ACS) between 2007 and 2018 at Tays Heart Hospital (sole provider of specialized cardiac care for a catchment area of over 0.5 million residents). Baseline and follow-up information was collected by combining information from the hospital's electronic health records, death certificate data, and a full-disclosure review of written patient records and accounts of the circumstances leading to death. RESULTS: During 12 years of follow-up, the cumulative incidence of SCAs (including SCDs) was 9.8% (0.8% annually) and that of SCDs 5.4% (0.5% annually). Cumulative incidence of SCAs in patients with ST-elevation myocardial infarction, non-ST-elevation myocardial infarction and unstable angina pectoris were: 11.9%,10.2% and 5.7% at 12 years. SCAs accounted for 30.5% (n = 528/1,732) of all deaths due to cardiovascular causes. The vast majority of SCAs (95.6%) occurred in patients without implantable cardioverter defibrillator (ICD) devices or among patients with no recurrent hospitalizations for coronary artery disease (89.1%). CONCLUSIONS: SCAs accounted for less than a third of all deaths due to cardiovascular causes among patients with previous ACS. Incidence of SCA is highest among STEMI and NSTEMI patients. After the hospital discharge, most of SCAs happen to NSTEMI patients.

Multivariable Analysis of Pre-operative Brain Atrophy as a Predictor of Long Term Mortality After Carotid Endarterectomy.

OBJECTIVE: Brain atrophy is associated with an increased mortality rate in elderly trauma patients and in patients treated with mechanical thrombectomy for acute ischaemic stroke. In the setting of ischaemic stroke, the association between brain atrophy and death is stronger than that of sarcopenia. It has previously been shown that lower masseter area, as a marker of sarcopenia, is linked to lower survival after carotid endarterectomy (CEA). The aim of this study was to investigate whether brain atrophy is also associated with long term mortality in patients undergoing CEA. METHODS: A cohort of patients treated with CEA between 2004 and 2010 was retrieved from the Tampere University Hospital vascular registry and those with available pre-operative computed tomography (CT) imaging were analysed retrospectively. CT images were evaluated for brain atrophy index (BAI) and masseter muscle surface area and density. The association between BAI and mortality was investigated with Cox regression. RESULTS: Two hundred and thirty-three patients with a median (interquartile range [IQR]) age of 71 years (64.0, 77.0) were included. Most patients were operated on for symptomatic stenosis (n = 203; 87.1%). The median (IQR) duration of follow up was 115.0 months (66.0, 153.0), and 155 patients (66.5%) died during follow up. BAI was statistically significantly correlated with age (r = .489), average masseter density (r = -.202), and smoking (r = -.186; all p <.005). Increased BAI was statistically significantly associated with overall mortality (hazard ratio [HR] 1.45, 95% confidence interval [CI] 1.25 - 1.68, per one standard deviation [SD] increase) in the univariable analysis, and the association remained (HR 1.23, 95% CI 1.04 - 1.46, per one SD increase) in the multivariable models. Age, peripheral artery disease, and chronic obstructive pulmonary disease were also independently associated with mortality. The optimal cutoff value for BAI was 0.133. CONCLUSION: Brain atrophy independently predicts the long term post-operative mortality rate after CEA in a cohort containing mainly symptomatic patients. Future studies are needed to validate the results in prospective settings and in asymptomatic patients.

Evaluation of a wrist-worn photoplethysmography monitor for heart rate variability estimation in patients recovering from laparoscopic colon resection.

To evaluate the accuracy of heart rate variability (HRV) parameters obtained with a wrist-worn photoplethysmography (PPG) monitor in patients recovering from minimally invasive colon resection to investigate whether PPG has potential in postoperative patient monitoring. 31 patients were monitored for three days or until discharge or reoperation using a wrist-worn PPG monitor (PulseOn, Finland) with a Holter monitor (Faros 360, Bittium Biosignals, Finland) as a reference measurement device. Beat-to-beat intervals (BBI) and HRV information collected by PPG were compared with RR intervals (RRI) and HRV obtained from the ECG reference after removing artefacts and ectopic beats. The beat-to-beat mean error (ME) and mean absolute error (MAE) of good quality heartbeat intervals obtained by wrist PPG were estimated as - 1.34 ms and 10.4 ms respectively. A significant variation in the accuracy of the HRV parameters was found. In the time domain, SDNN (9.11%), TRI (11.4%) and TINN (11.1%) were estimated with low relative MAE, while RMSSD (34.3%), pNN50 (139%) and NN50 (188%) had higher errors. The logarithmic parameters in the frequency domain (VLF Log, LF Log and HF Log) exhibited the lowest relative error, and for non-linear parameters, SD2 (7.5%), DFA α1 (8.25%) and DFA α2 (4.71%) were calculated much more accurately than SD1 (34.3%). The wrist PPG shows some potential for use in a clinical setting. The accuracy of several HRV parameters analyzed post hoc was found sufficient to be used in further studies concerning postoperative recovery of patients undergoing laparoscopic colon resection, although there were large errors in many common HRV parameters such as RMSSD, pNN50 and NN50, rendering them unusable.ClinicalTrials.gov Identifier: NCT04996511, August 9, 2021, retrospectively registered.

Bile-volatile organic compounds in the diagnostics of pancreatic cancer and biliary obstruction: A prospective proof-of-concept study.

Objectives: Detection of volatile organic compounds (VOCs) from bodily fluids with field asymmetric waveform ion mobility spectrometry (FAIMS) and related methods has been studied in various settings. Preliminary results suggest that it is possible to detect prostate, colorectal, ovarian and pancreatic cancer from urine samples. In this study, our primary aim was to differentiate pancreatic cancer from pancreatitis and benign tumours of the pancreas by using bile samples obtained during endoscopic retrograde cholangiopancreatography (ERCP). Secondarily, we aimed to differentiate all pancreatic region malignancies from all other kinds of benign causes of biliary obstruction. Methods: A bile sample was successfully aspirated from 94 patients during ERCP in Tampere University Hospital. Hospital and patient records were prospectively followed up for at least two years after ERCP. Bile samples were analysed using a Lonestar chemical analyser (Owlstone, UK) using an ATLAS sampling system and a split-flow box. Diagnoses and corresponding data from the analyses were matched and divided into two subcategories for comparison. Statistical analysis was performed using linear discriminant analysis, support vector machines, and 5-fold cross-validation. Results: Pancreatic cancers (n=8) were differentiated from benign pancreatic lesions (n=9) with a sensitivity of 100%, specificity of 77.8%, and correct rate of 88%. All pancreatic region cancers (n=19) were differentiated from all other kinds of benign causes of biliary obstruction (n=75) with corresponding values of 21.1%, 94.7%, and 80.7%. The sample size was too small to try to differentiate pancreatic cancers from adjacent cancers. Conclusion: Analysing bile VOCs using FAIMS shows promising capability in detecting pancreatic cancer and other cancers in the pancreatic area.

Identifying chronic rhinosinusitis without nasal polyps by analyzing aspirated nasal air with an electronic nose based on differential mobility spectrometry.

BACKGROUND: The diagnosis of chronic rhinosinusitis (CRS) is a complicated procedure. An electronic nose (eNose) is a novel method that detects disease from gas-phase mixtures, such as human breath. AIMS/OBJECTIVES: To determine whether an eNose based on differential mobility spectrometry (DMS) can detect chronic rhinosinusitis without nasal polyps (CRSsNP) by analyzing aspirated nasal air. MATERIALS AND METHODS: Adult patients with CRSsNP were examined. The control group consisted of patients with septal deviation. Nasal air was aspirated into a collection bag and analyzed with DMS. The DMS data were classified using regularized linear discriminant analysis (LDA) models with 10-fold cross-validation. RESULTS: The accuracy of the DMS to distinguish CRSsNP from patients with septal deviation was 69%. Sensitivity and specificity were 67 and 70%, respectively. Bonferroni-corrected statistical differences were clearly noted. When a subgroup with more severe inflammatory disease was compared to controls, the classification accuracy increased to 82%. CONCLUSIONS: The results of this feasibility study demonstrate that CRSsNP can potentially be differentiated distinguished from patients with similar nasal symptoms by analyzing the aspirated nasal air using DMS. Further research is warranted to evaluate the ability of this novel method in the differential diagnostics of CRS.

Method for the Intraoperative Detection of IDH Mutation in Gliomas with Differential Mobility Spectrometry.

Isocitrate dehydrogenase (IDH) mutation status is an important factor for surgical decision-making: patients with IDH-mutated tumors are more likely to have a good long-term prognosis, and thus favor aggressive resection with more survival benefit to gain. Patients with IDH wild-type tumors have generally poorer prognosis and, therefore, conservative resection to avoid neurological deficit is favored. Current histopathological analysis with frozen sections is unable to identify IDH mutation status intraoperatively, and more advanced methods are therefore needed. We examined a novel method suitable for intraoperative IDH mutation identification that is based on the differential mobility spectrometry (DMS) analysis of the tumor. We prospectively obtained tumor samples from 22 patients, including 11 IDH-mutated and 11 IDH wild-type tumors. The tumors were cut in 88 smaller specimens that were analyzed with DMS. With a linear discriminant analysis (LDA) algorithm, the DMS was able to classify tumor samples with 86% classification accuracy, 86% sensitivity, and 85% specificity. Our results show that DMS is able to differentiate IDH-mutated and IDH wild-type tumors with good accuracy in a setting suitable for intraoperative use, which makes it a promising novel solution for neurosurgical practice.

Forecasting daily emergency department arrivals using high-dimensional multivariate data: a feature selection approach.

BACKGROUND AND OBJECTIVE: Emergency Department (ED) overcrowding is a chronic international issue that is associated with adverse treatment outcomes. Accurate forecasts of future service demand would enable intelligent resource allocation that could alleviate the problem. There has been continued academic interest in ED forecasting but the number of used explanatory variables has been low, limited mainly to calendar and weather variables. In this study we investigate whether predictive accuracy of next day arrivals could be enhanced using high number of potentially relevant explanatory variables and document two feature selection processes that aim to identify which subset of variables is associated with number of next day arrivals. Performance of such predictions over longer horizons is also shown. METHODS: We extracted numbers of total daily arrivals from Tampere University Hospital ED between the time period of June 1, 2015 and June 19, 2019. 158 potential explanatory variables were collected from multiple data sources consisting not only of weather and calendar variables but also an extensive list of local public events, numbers of website visits to two hospital domains, numbers of available hospital beds in 33 local hospitals or health centres and Google trends searches for the ED. We used two feature selection processes: Simulated Annealing (SA) and Floating Search (FS) with Recursive Least Squares (RLS) and Least Mean Squares (LMS). Performance of these approaches was compared against autoregressive integrated moving average (ARIMA), regression with ARIMA errors (ARIMAX) and Random Forest (RF). Mean Absolute Percentage Error (MAPE) was used as the main error metric. RESULTS: Calendar variables, load of secondary care facilities and local public events were dominant in the identified predictive features. RLS-SA and RLS-FA provided slightly better accuracy compared ARIMA. ARIMAX was the most accurate model but the difference between RLS-SA and RLS-FA was not statistically significant. CONCLUSIONS: Our study provides new insight into potential underlying factors associated with number of next day presentations. It also suggests that predictive accuracy of next day arrivals can be increased using high-dimensional feature selection approach when compared to both univariate and nonfiltered high-dimensional approach. Performance over multiple horizons was similar with a gradual decline for longer horizons. However, outperforming ARIMAX remains a challenge when working with daily data. Future work should focus on enhancing the feature selection mechanism, investigating its applicability to other domains and in identifying other potentially relevant explanatory variables.

Radiographically quantified sarcopenia and traditional cardiovascular risk assessment in predicting long-term mortality after endovascular aortic repair.

OBJECTIVE: This study evaluated radiographically quantified sarcopenia and the patient's comorbidity burden based on traditional cardiovascular risk assessment as potential predictors of long-term mortality after endovascular aortic repair (EVAR). METHODS: The study included 480 patients treated with standard EVAR for intact infrarenal abdominal aortic aneurysms. Patient characteristics, comorbidities, aneurysm dimensions, and other preoperative risk factors were collected retrospectively. Preoperative computed tomography was used to measure psoas muscle area (PMA) at the L3 level. Patients were divided into three groups based on American Society of Anesthesiologists (ASA) score and PMA. In the high-risk group, patients had sarcopenia (PMA <8.0 cm2 for males and <5.5 cm2 for females) and an ASA score of 4. In the medium-risk group, patients had either sarcopenia or an ASA score of 4. Patients in the low-risk group had no sarcopenia and the ASA score was less than 4. Risk factors for long-term mortality were determined using multivariable analysis. Kaplan-Meier survival estimates were calculated for all-cause mortality. RESULTS: Patients in the high- and medium-risk groups were older than those in the low-risk group (77 ± 7, 76 ± 6, and 74 ± 8 years, respectively, P < .01). Patients in the high-risk group had higher prevalence of coronary artery disease, pulmonary disease, and chronic kidney disease. There were no differences in 30-day or 90-day mortality between the groups. The independent predictors of long-term mortality were age, ASA score, PMA, chronic kidney disease, and maximum aneurysm sac diameter. The estimated 1-year mortality rates were 5% ± 2% for the low-risk, 5% ± 2% for the medium-risk, and 18% ± 5% for the high-risk group (P < .01). Five-year mortality estimates were 23% ± 4%, 36% ± 3%, and 60% ± 6%, respectively (P < .01). The mean follow-up time was 5.0 ± 2.8 years. CONCLUSIONS: Both ASA and PMA were strong predictors of increased mortality after elective EVAR. The combination of these two can be used as a simple risk stratification tool to identify patients in whom aneurysm repair or the intensive long-term surveillance after EVAR may be unwarranted.