Validation of a Textile-Based Wearable Measuring Electrocardiogram and Breathing Frequency for Sleep Apnea Monitoring.

Sleep apnea (SA) is a prevalent disorder characterized by recurrent events of nocturnal apnea. Polysomnography (PSG) represents the gold standard for SA diagnosis. This laboratory-based procedure is complex and costly, and less cumbersome wearable devices have been proposed for SA detection and monitoring. A novel textile multi-sensor monitoring belt recording electrocardiogram (ECG) and breathing frequency (BF) measured by thorax excursion was developed and tested in a sleep laboratory for validation purposes. The aim of the current study was to evaluate the diagnostic performance of ECG-derived heart rate variability and BF-derived breathing rate variability and their combination for the detection of sleep apnea in a population of patients with a suspicion of SA. Fifty-one patients with a suspicion of SA were recruited in the sleep laboratory of the Cantonal Hospital St. Gallen. Patients were equipped with the monitoring belt and underwent a single overnight laboratory-based PSG. In addition, some patients further tested the monitoring belt at home. The ECG and BF signals from the belt were compared to PSG signals using the Bland-Altman methodology. Heart rate and breathing rate variability analyses were performed. Features derived from these analyses were used to build a support vector machine (SVM) classifier for the prediction of SA severity. Model performance was assessed using receiver operating characteristics (ROC) curves. Patients included 35 males and 16 females with a median age of 49 years (range: 21 to 65) and a median apnea-hypopnea index (AHI) of 33 (IQR: 16 to 58). Belt-derived data provided ECG and BF signals with a low bias and in good agreement with PSG-derived signals. The combined ECG and BF signals improved the classification accuracy for SA (area under the ROC curve: 0.98; sensitivity and specificity greater than 90%) compared to single parameter classification based on either ECG or BF alone. This novel wearable device combining ECG and BF provided accurate signals in good agreement with the gold standard PSG. Due to its unobtrusive nature, it is potentially interesting for multi-night assessments and home-based patient follow-up.

Effect of the Covid-19 pandemic on hospitalizations for non-Covid-19-pneumonia and exacerbations of chronic obstructive pulmonary diseases in Switzerland: comparison of national data between 2020/2021 and 2015-2019.

BACKGROUND: Protective measures applied during the Covid-19 pandemic had a marked impact on the incidence of pneumonia. However, systematic data are lacking for hospitalizations for pneumonia and acute exacerbations of chronic obstructive lung diseases (AECOPD) not caused by SARS-CoV-2 in Switzerland. We aimed to compare the incidences of hospitalization for these entities between 2020/2021 and prepandemic years. METHODS: This retrospective study examined all nationwide hospitalizations for non-Covid-19-pneumonia and AECOPD listed as primary diagnoses based on ICD-10 codes between 2015 and 2021 in a publicly available hospitalization database of the Swiss Federal Statistical Office. Hospitalizations for acute coronary syndrome (ACS) and stroke were used as controls. Changes of monthly incidences of hospitalizations, length of stay (LOS) and mortality were compared between 2020/2021 and the average of 2015-2019. RESULTS: The incidences of hospitalizations for AECOPD and for pneumonia showed seasonal variations from 2015 to 2019 followed by significant and almost identical decreases in 2020/2021 (incidence rate ratio [IRR] 0.59, 95% CI: 0.45-0.77, p < 0.001, and IRR: 0.62, 95% CI: 0.52-0.74, p < 0.001, respectively). Hospital-mortality was slightly higher in 2020/2021 for AECOPD (2015-2019: 3.8%; 2020/2021: 4.2%, odds ratio [OR] 1.24, 95% CI: 1.07-1.44, p = 0.004) and for pneumonia (2015-2019: 4.5%, 2020/2021: 4.6%, odds ratio [OR] 1.17, 95% CI: 1.07-1.28, p < 0.001). Median LOS slightly decreased for AECOPD (2015-2019: 8 [IQR: 5-14] days; 2020/2021: 7 [IQR: 4-13] days, Wilcoxon test: p < 0.001) but slightly increased for pneumonia (2015-2019: 7 [IQR: 4-11] days; 2020/2021: 7 [IQR: 4-13] days, Wilcoxon test: p < 0.001). Throughout 2020/2021, there were no significant fluctuations observed in the incidences of ACS and stroke. (IRR: 0.98, 95% CI: 0.83-1.16, p = 0.810, IRR: 0.96, 95% CI: 0.81-1.14, p = 0.636, respectively). CONCLUSION: The first two years of the Covid-19 pandemic showed a marked decrease in incidences in AECOPD and non-Covid-19 pneumonia hospitalizations in Switzerland. It is likely that this effect is associated with the society-based, at first vigorous, social distancing measures.

Tracking Real-World Physical Activity in Chronic Obstructive Pulmonary Disease Over One Year: Results from a Monocentric, Prospective, Observational Cohort Study.

Introduction: Lung function constraints and comorbidities such as coronary heart disease, sarcopenia, and mood disorders make chronic obstructive pulmonary disease (COPD) patients avoid physical activity (PA). However, PA represents an important pillar of COPD management and is explicitly recommended by professional associations to enhance physical functioning and positively modulate disease progression. Methods: In this monocentric, prospective, observational feasibility study, it was our primary objective to investigate the association between PA and the evolution of the COPD assessment test (CAT) and the occurrence of acute exacerbations of COPD (AECOPD), respectively. To this end, we equipped 42 COPD patients with an activity tracking wearable and telemonitored their daily PA levels over one year using a dedicated web-based interface. Patients additionally provided weekly CAT scores using the same telehealth platform and came in for 3 study visits to assess functional parameters and biochemical markers related to nutrition and inflammation. Results: A principal study finding was that PA was inversely associated with CAT score (drop of 0.21 points associated with an increase of 1000 daily steps, p = 0.004), and that the 50% of patients with higher PA levels showed less CAT score progression over time (0.42 points per year) than the 50% of patients with lower PA levels (3.26 points per year) (p < 0.001). In addition, higher PA levels were significantly associated with a lower likelihood of experiencing a moderate-to-severe AECOPD (31% risk reduction associated with an increase of 1000 daily steps, p = 0.0097). Discussion: Our study demonstrates the relevance of PA for key COPD outcome metrics in a real-world setting and underpins the importance of PA for COPD self-management in everyday life. Our study paves the way for future intervention trials to prospectively identify medically relevant PA thresholds and establish training recommendations for different patient subgroups.

Quantification of breathing irregularity for the diagnosis of dysfunctional breathing using proportional tidal volume variation: a cross-sectional, retrospective real-world study.

OBJECTIVES: To develop a statistical approach that provides a quantitative index measuring the magnitude of the irregularity of the breathing response to exercise for the diagnosis of dysfunctional breathing. DESIGN: Cross-sectional, retrospective, real-world study. SETTING: Single-centre study. PARTICIPANTS: A population of 209 patients investigated with cardiopulmonary exercise testing in our institution for unexplained or disproportionate exertional dyspnoea between January and July 2022. PRIMARY AND SECONDARY OUTCOME MEASURES: A novel statistical approach providing a quantitative index-proportional tidal volume variation (PTVV)-was developed to measure the magnitude of the irregularity of the breathing response to exercise. RESULTS: PTVV provided a reliable statistical readout for the objective assessment of DB with a prediction accuracy of 78% (95% CI: 72 to 83%). The prevalence of DB in the investigated population was high with more than half of the patients affected by moderate-to-severe DB. CONCLUSIONS: PTVV can easily be implemented in the clinical routine. Our study suggests a possible further simplification for the diagnosis of DB with two objective criteria including PTVV and one single criterion for hyperventilation.

Impact of the 2022 pulmonary hypertension definition on haemodynamic classification and mortality in patients with aortic stenosis undergoing valve replacement.

Aims: With the 2022 pulmonary hypertension (PH) definition, the mean pulmonary artery pressure (mPAP) threshold for any PH was lowered from ≥25 to >20 mmHg, and the pulmonary vascular resistance (PVR) value to differentiate between isolated post-capillary PH (IpcPH) and combined pre- and post-capillary PH (CpcPH) was reduced from >3 Wood units (WU) to >2 WU. We assessed the impact of this change in the PH definition in aortic stenosis (AS) patients undergoing aortic valve replacement (AVR). Methods and results: Severe AS patients (n = 503) undergoing pre-AVR cardiac heart catheterization were classified according to both the 2015 and 2022 definitions. The post-AVR mortality [median follow-up 1348 (interquartile range 948-1885) days] was assessed. According to the 2015 definition, 219 (44% of the entire population) patients had PH: 63 (29%) CpcPH, 125 (57%) IpcPH, and 31 (14%) pre-capillary PH. According to the 2022 definition, 321 (+47%) patients were diagnosed with PH, and 156 patients (31%) were re-classified: 26 patients from no PH to IpcPH, 38 from no PH to pre-capillary PH, 38 from no PH to unclassified PH, 4 from pre-capillary PH to unclassified PH, and 50 from IpcPH to CpcPH (CpcPH: +79%). With both definitions, only the CpcPH patients displayed increased mortality (hazard ratios ≈ 4). Among the PH-defining haemodynamic components, PVR was the strongest predictor of death. Conclusion: In severe AS, the application of the 2022 PH definition results in a substantially higher number of patients with any PH as well as CpcPH. With either definition, CpcPH patients have a significantly increased post-AVR mortality.

Electronic Nicotine-Delivery Systems for Smoking Cessation.

BACKGROUND: Electronic nicotine-delivery systems - also called e-cigarettes - are used by some tobacco smokers to assist with quitting. Evidence regarding the efficacy and safety of these systems is needed. METHODS: In this open-label, controlled trial, we randomly assigned adults who were smoking at least five tobacco cigarettes per day and who wanted to set a quit date to an intervention group, which received free e-cigarettes and e-liquids, standard-of-care smoking-cessation counseling, and optional (not free) nicotine-replacement therapy, or to a control group, which received standard counseling and a voucher, which they could use for any purpose, including nicotine-replacement therapy. The primary outcome was biochemically validated, continuous abstinence from smoking at 6 months. Secondary outcomes included participant-reported abstinence from tobacco and from any nicotine (including smoking, e-cigarettes, and nicotine-replacement therapy) at 6 months, respiratory symptoms, and serious adverse events. RESULTS: A total of 1246 participants underwent randomization; 622 participants were assigned to the intervention group, and 624 to the control group. The percentage of participants with validated continuous abstinence from tobacco smoking was 28.9% in the intervention group and 16.3% in the control group (relative risk, 1.77; 95% confidence interval, 1.43 to 2.20). The percentage of participants who abstained from smoking in the 7 days before the 6-month visit was 59.6% in the intervention group and 38.5% in the control group, but the percentage who abstained from any nicotine use was 20.1% in the intervention group and 33.7% in the control group. Serious adverse events occurred in 25 participants (4.0%) in the intervention group and in 31 (5.0%) in the control group; adverse events occurred in 272 participants (43.7%) and 229 participants (36.7%), respectively. CONCLUSIONS: The addition of e-cigarettes to standard smoking-cessation counseling resulted in greater abstinence from tobacco use among smokers than smoking-cessation counseling alone. (Funded by the Swiss National Science Foundation and others; ESTxENDS ClinicalTrials.gov number, NCT03589989.).

Assessment of functional diversities in patients with Asthma, COPD, Asthma-COPD overlap, and Cystic Fibrosis (CF).

The objectives of the present study were to evaluate the discriminating power of spirometric and plethysmographic lung function parameters to differenciate the diagnosis of asthma, ACO, COPD, and to define functional characteristics for more precise classification of obstructive lung diseases. From the databases of 4 centers, a total of 756 lung function tests (194 healthy subjects, 175 with asthma, 71 with ACO, 78 with COPD and 238 with CF) were collected, and gradients among combinations of target parameters from spirometry (forced expiratory volume one second: FEV1; FEV1/forced vital capacity: FEV1/FVC; forced expiratory flow between 25-75% FVC: FEF25-75), and plethysmography (effective, resistive airway resistance: sReff; aerodynamic work of breathing at rest: sWOB), separately for in- and expiration (sReffIN, sReffEX, sWOBin, sWOBex) as well as static lung volumes (total lung capacity: TLC; functional residual capacity: FRCpleth; residual volume: RV), the control of breathing (mouth occlusion pressure: P0.1; mean inspiratory flow: VT/TI; the inspiratory to total time ratio: TI/Ttot) and the inspiratory impedance (Zinpleth = P0.1/VT/TI) were explored. Linear discriminant analyses (LDA) were applied to identify discriminant functions and classification rules using recursive partitioning decision trees. LDA showed a high classification accuracy (sensitivity and specificity > 90%) for healthy subjects, COPD and CF. The accuracy dropped for asthma (~70%) and even more for ACO (~60%). The decision tree revealed that P0.1, sRtot, and VT/TI differentiate most between healthy and asthma (68.9%), COPD (82.1%), and CF (60.6%). Moreover, using sWOBex and Zinpleth ACO can be discriminated from asthma and COPD (60%). Thus, the functional complexity of obstructive lung diseases can be understood, if specific spirometric and plethysmographic parameters are used. Moreover, the newly described parameters of airway dynamics and the central control of breathing including Zinpleth may well serve as promising functional marker in the field of precision medicine.

Non-pharmaceutical interventions to optimize cancer immunotherapy.

The traditional picture of cancer patients as weak individuals requiring maximum rest and protection is beginning to dissolve. Too much focus on the medical side and one's own vulnerability and mortality might be counterproductive and not doing justice to the complexity of human nature. Unlike cytotoxic and lympho-depleting treatments, immune-engaging therapies strengthen the immune system and are typically less harmful for patients. Thus, cancer patients receiving checkpoint inhibitors are not viewed as being vulnerable per se, at least not in immunological and physical terms. This perspective article advocates a holistic approach to cancer immunotherapy, with an empowered patient in the center, focusing on personal resources and receiving domain-specific support from healthcare professionals. It summarizes recent evidence on non-pharmaceutical interventions to enhance the efficacy of immune checkpoint blockade and improve quality of life. These interventions target behavioral factors such as diet, physical activity, stress management, circadian timing of checkpoint inhibitor infusion, and waiving unnecessary co-medication curtailing immunotherapy efficacy. Non-pharmaceutical interventions are universally accessible, broadly applicable, instantly actionable, scalable, and economically sustainable, creating value for all stakeholders involved. Most importantly, this holistic framework re-emphasizes the patient as a whole and harnesses the full potential of anticancer immunity and checkpoint blockade, potentially leading to survival benefits. Digital therapeutics are proposed to accompany the patients on their mission toward change in lifestyle-related behaviors for creating optimal conditions for treatment efficacy and personal growth.

Gender-specific disease trajectories prior to the onset of COPD allow individualized screening and early intervention.

BACKGROUND: Nation-wide hospitalization databases include diagnostic information at the level of an entire population over an extended period of time. Comorbidity network and early disease development can be unveiled. Chronic obstructive pulmonary disease (COPD) is an underdiagnosed condition for which it is crucial to identify early disease indicators. The identification of gender-specific conditions preceding the onset of COPD may reveal disease progression patterns allowing for early diagnosis and intervention. The objective of the study was to investigate the antecedent hospitalization history of patients newly diagnosed with COPD and to retrace a gender-specific trajectory of coded entities prior to the onset of COPD. MATERIAL AND METHODS: A population-wide hospitalization database including information about all hospitalizations in Switzerland between 2002 and 2018 was used. COPD cases were extracted from the database and comorbidities occurring prior to the onset of COPD identified. Comorbidities significantly over-represented in COPD compared with a 1:1, age- and sex-matched control population were identified and their longitudinal evolution was analyzed. RESULTS: Between 2002 and 2018, 697,714 hospitalizations with coded COPD were recorded in Switzerland. Sixty-two diagnoses were significantly over-represented before onset of COPD. These preceding comorbidities included both well-established conditions and novel links to COPD. Early pre-conditions included nicotine and alcohol abuse, obesity and cardiovascular diseases. Later comorbidities included atrial fibrillation, diseases of the genitourinary system and pneumonia. Atherosclerotic heart diseases were more prevalent in males, whereas hypothyroidism, varicose and intestinal disorders were more frequent in females. Disease trajectories were validated using an independent data set. CONCLUSIONS: Gender-specific disease trajectories highlight early indicators and pathogenetic links between COPD and antecedent diseases and could allow for early detection and intervention.

Smartphone-based cough monitoring as a near real-time digital pneumonia biomarker.

Background: Cough represents a cardinal symptom of acute respiratory tract infections. Generally associated with disease activity, cough holds biomarker potential and might be harnessed for prognosis and personalised treatment decisions. Here, we tested the suitability of cough as a digital biomarker for disease activity in coronavirus disease 2019 (COVID-19) and other lower respiratory tract infections. Methods: We conducted a single-centre, exploratory, observational cohort study on automated cough detection in patients hospitalised for COVID-19 (n=32) and non-COVID-19 pneumonia (n=14) between April and November 2020 at the Cantonal Hospital St Gallen, Switzerland. Cough detection was achieved using smartphone-based audio recordings coupled to an ensemble of convolutional neural networks. Cough levels were correlated to established markers of inflammation and oxygenation. Measurements and main results: Cough frequency was highest upon hospital admission and declined steadily with recovery. There was a characteristic pattern of daily cough fluctuations, with little activity during the night and two coughing peaks during the day. Hourly cough counts were strongly correlated with clinical markers of disease activity and laboratory markers of inflammation, suggesting cough as a surrogate of disease in acute respiratory tract infections. No apparent differences in cough evolution were observed between COVID-19 and non-COVID-19 pneumonia. Conclusions: Automated, quantitative, smartphone-based detection of cough is feasible in hospitalised patients and correlates with disease activity in lower respiratory tract infections. Our approach allows for near real-time telemonitoring of individuals in aerosol isolation. Larger trials are warranted to decipher the use of cough as a digital biomarker for prognosis and tailored treatment in lower respiratory tract infections.

Compartmentalization of the host microbiome: how tumor microbiota shapes checkpoint immunotherapy outcome and offers therapeutic prospects.

The host microbiome is polymorphic, compartmentalized, and composed of distinctive tissue microbiomes. While research in the field of cancer immunotherapy has provided an improved understanding of the interaction with the gastrointestinal microbiome, the significance of the tumor-associated microbiome has only recently been grasped. This article provides a state-of-the-art review about the tumor-associated microbiome and sheds light on how local tumor microbiota shapes anticancer immunity and influences checkpoint immunotherapy outcome. The direct route of interaction between cancer cells, immune cells, and microbiota in the tumor microenvironment is emphasized and advocates a focus on the tumor-associated microbiome in addition to the spatially separated gut compartment. Since the mechanisms underlying checkpoint immunotherapy modulation by tumor-associated microbiota remain largely elusive, future research should dissect the pathways involved and outline strategies to therapeutically modulate microbes and their products within the tumor microenvironment. A more detailed knowledge about the mechanisms governing the composition and functional quality of the tumor microbiome will improve cancer immunotherapy and advance precision medicine for solid tumors.

Identification of smoking cessation phenotypes as a basis for individualized counseling: An explorative real-world cohort study.

INTRODUCTION: The rate of relapse in smokers attempting to quit is generally high. In order to maximize the chances of success, it is of interest to better understand the dynamic of lapse and relapse during smoking cessation. We hypothesized that specific behavioral patterns in tobacco consumption could predict the probability of quitting success and could open the possibility for a more targeted approach. The aim of the current study was to characterize clusters of quitting trajectories among participants involved in a smoking cessation program. METHODS: In a retrospective real-world cohort study, data from 843 consecutive participants between March 2012 and December 2014 were collected. Data consisted of baseline information on demographics, smoking history and dependence level, as well as longitudinal data about tobacco consumption. The correlations among time series were characterized using principal coordinates analysis. Clusters were identified using k-means clustering and the average profile associated with each cluster was computed. The association between the participant's baseline characteristics and clusters of tobacco consumption was assessed. RESULTS: Four distinct clusters of transition phenotypes were identified based on tobacco consumption during the cessation phase: the long-term quitters (30%), the persistent smokers/reducers (44%), the short-term returners (16%) and the repeated try and failers (10%). Significant between-cluster differences were found in terms of baseline characteristics and smoking behavior during follow-up. CONCLUSIONS: Meaningful clusters of quitting trajectories could be identified. Such specific behavioral patterns were useful for the application of personalized assistance needed to achieve successful and long-term cessation.

Functional Predictors Discriminating Asthma-COPD Overlap (ACO) from Chronic Obstructive Pulmonary Disease (COPD).

Background: A significant proportion of patients with obstructive lung disease have clinical and functional features of both asthma and chronic obstructive pulmonary disease (COPD), referred to as the asthma-COPD overlap (ACO). The distinction of these phenotypes, however, is not yet well-established due to the lack of defining clinical and/or functional criteria. The aim of our investigations was to assess the discriminating power of various lung function parameters on the assessment of ACO. Methods: From databases of 4 pulmonary centers, a total of 540 patients (231 males, 309 females), including 372 patients with asthma, 77 patients with ACO and 91 patients with COPD, were retrospectively collected, and gradients among combinations of explanatory variables of spirometric (FEV1, FEV1/FVC, FEF25-75), plethysmographic (sReff, sGeff, the aerodynamic work of breathing at rest; sWOB), static lung volumes, including trapped gases and measurements of the carbon monoxide transfer (DLCO, KCO) were explored using multiple factor analysis (MFA). The discriminating power of lung function parameters with respect to ACO was assessed using linear discriminant analysis (LDA). Results: LDA revealed that parameters of airway dynamics (sWOB, sReff, sGeff) combined with parameters of static lung volumes such as functional residual capacity (FRCpleth) and trapped gas at FRC (VTG FRC) are valuable and potentially important tools discriminating between asthma, ACO and COPD. Moreover, sWOB significantly contributes to the diagnosis of obstructive airway diseases, independent from the state of pulmonary hyperinflation, whilst the diffusion capacity for carbon monoxide (DLCO) significantly differentiates between the 3 diagnostic classes. Conclusion: The complexity of COPD with its components of interaction and their heterogeneity, especially in discrimination from ACO, may well be differentiated if patients are explored by a whole set of target parameters evaluating, interactionally, flow limitation, airway dynamics, pulmonary hyperinflation, small airways dysfunction and gas exchange disturbances assessing specific functional deficits.

In-hospital survival paradox in patients with sleep apnea-A nation-wide nested case-control study.

BACKGROUND: Sleep apnea (SA) is a prevalent disorder characterized by recurrent events of nocturnal apnea originating from obstructive and/or central mechanisms. SA disrupts normal sleep and can lead to a series of complications when left untreated. SA results in intermittent hypoxia which has an impact on the cardio- and cerebrovascular system. Hospitalized patients with SA typically have a greater burden of comorbidity, a longer length of hospital stay, but may show an improvement of in-hospital mortality compared to patients without diagnosed SA. The reason for this survival benefit is controversial and we aimed to clarify this protective effect in the light of predictive factors including SA-associated comorbidities using a nation-wide hospitalization database. METHODS AND FINDINGS: Data were extracted from a nation-wide hospitalization database provided by the Swiss Federal Office for Statistics. Hospitalized patients with a SA co-diagnosis were extracted from the database together with a 1:1-matched control population without SA. Overall, 212'581 patients with SA were hospitalized in Switzerland between 2002 and 2018. Compared to the controls, SA cases had a longer median length of hospital stay (7 days; 95% CI: 3 to 15 vs. 4 days; 95% CI: 2 to 10) (p < 0.001) and a higher median number of comorbidities (8 comorbidities; IQR: 5 to 11 vs. 3 comorbidities; IQR: 1 to 6) (p < 0.001). The risk of in-hospital mortality was lower in the SA cases compared to the controls (OR: 0.73; 95% CI: 0.7 to 0.76; p < 0.001). SA was associated with a survival benefit in hospitalizations related to 28 of 47 conditions with the highest rate of in-hospital death. Sixty-three comorbidities were significantly over-represented in SA cases among which obesity, hypertension and anatomic nasal deviations were associated with a significant decrease of in-hospital mortality. CONCLUSIONS: Compared to matched controls, SA was associated with significant and relevant inpatient survival benefit in a number of most deadly conditions. Within SA-patients, associated comorbidities mostly correlated with a poorer prognosis, whereas obesity and hypertension were associated with an improved in-hospital mortality.

Text mining-based measurement of precision of polysomnographic reports as basis for intervention.

BACKGROUND: Text mining can be applied to automate knowledge extraction from unstructured data included in medical reports and generate quality indicators applicable for medical documentation. The primary objective of this study was to apply text mining methodology for the analysis of polysomnographic medical reports in order to quantify sources of variation - here the diagnostic precision vs. the inter-rater variability - in the work-up of sleep-disordered breathing. The secondary objective was to assess the impact of a text block standardization on the diagnostic precision of polysomnography reports in an independent test set. RESULTS: Polysomnography reports of 243 laboratory-based overnight sleep investigations scored by 9 trained sleep specialists of the Sleep Center St. Gallen were analyzed using a text-mining methodology. Patterns in the usage of discriminating terms allowed for the characterization of type and severity of disease and inter-rater homogeneity. The variation introduced by the inter-rater (technician/physician) heterogeneity was found to be twice as high compared to the variation introduced by effective diagnostic information. A simple text block standardization could significantly reduce the inter-rater variability by 44%, enhance the predictive value and ultimately improve the diagnostic accuracy of polysomnography reports. CONCLUSIONS: Text mining was successfully used to assess and optimize the quality, as well as the precision and homogeneity of medical reporting of diagnostic procedures - here exemplified with sleep studies. Text mining methodology could lay the ground for objective and systematic qualitative assessment of medical reports.

No evidence of harmful effects of steroids in severe exacerbations of COPD associated with influenza.

PURPOSE: COPD has large impact on patient morbidity and mortality worldwide. Acute exacerbations (AECOPD) are mostly triggered by respiratory infections including influenza. While corticosteroids are strongly recommended in AECOPD, they are potentially harmful during influenza. We aimed to evaluate if steroid treatment for AECOPD due to influenza may worsen outcomes. METHODS: A retrospective analysis of a Swiss nation-wide hospitalization database was conducted identifying all AECOPD hospitalisations between 2012 and 2017. In separate analyses, outcomes concerning length-of-stay (LOS), in-hospital mortality, rehospitalisation rate, empyema and aspergillosis were compared between AECOPD during and outside influenza season; AECOPD with and without laboratory-confirmed influenza; and AECOPD plus pneumonia with and without laboratory-confirmed influenza. RESULTS: Patients hospitalized for AECOPD during influenza season showed shorter LOS (11.3 vs. 11.6 day, p < 0.001) but higher rehospitalisation rates (33 vs 31%, p < 0.001) compared to those hospitalized outside influenza season. Patients with confirmed influenza infection had lower in-hospital mortality (3.3 vs. 5.5%, p = 0.010) and rehospitalisation rates (29 vs. 37%, p < 0.001) than those without confirmed influenza. CONCLUSION: Using different indicators for influenza as the likely cause of AECOPD, we found no consistent evidence of worse outcomes of AECOPD due to influenza for hospitalized patients. Assuming that most of these patients received corticosteroids, as it is accepted standard of care in Switzerland, this study gives no evidence to change the current practice of using corticosteroids for hospitalized AECOPD independent of the influenza status.

OMIP 077: Definition of all principal human leukocyte populations using a broadly applicable 14-color panel.

This Optimized Multicolor Immunofluorescence Panel was designed to identify and quantify all principal leukocyte populations in human blood using a minimum number of markers. We achieved this goal using a carefully selected combination of 14 surface markers compatible with standard flow cytometric instruments and accessible to a particularly large research community. Optimized for use in whole blood, this panel allows polymorphonuclear cell identification, supports live cell recovery, and is well-suited for absolute cell counting applications in the original in vivo volume. Panel performance and the separation of populations are high, and virtually no cells remain undefined after gating. Besides the identification of neutrophils, eosinophils, basophils, T cells, natural killer cells, B cells, plasma cells, monocytes, myeloid dendritic cells and plasmacytoid dendritic cells, this panel also covers progenitor cells and may therefore be attractive for stem cell researchers. Envisioned applications of this panel include immune monitoring within clinical trials, initial discovery to inform subset-targeted panels, and clinical diagnostics. In summary, this panel offers a broadly applicable platform for immune cell identification, quantification and characterization in human samples, particularly whole blood.