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ObjectivesThe Modern Innovative Solutions to Improve Outcomes in Asthma, Breathlessness and Chronic Obstructive Pulmonary Disease (COPD) (MABC) service aimed to enhance disease management for chronic respiratory conditions through specialist multidisciplinary clinics, predominantly in the community. This study assesses the outcomes of these clinics.DesignThis study used a prospective, longitudinal, participatory action research approach.SettingThe study was conducted in primary care practices across Hampshire, UK.ParticipantsAdults aged 16 years and above with poorly controlled asthma or COPD, as well as those with undifferentiated breathlessness not under specialist care, were included.InterventionsParticipants received care through the multidisciplinary, specialist-led MABC clinics.Primary and secondary outcome measuresPrimary outcomes included disease activity, quality of life and healthcare utilisation. Secondary outcomes encompassed clinic attendance, diagnostic changes, patient activation, participant and healthcare professional experiences and cost-effectiveness.ResultsA total of 441 participants from 11 general practitioner practices were recruited. Ninety-six per cent of participants would recommend MABC clinics. MABC assessments led to diagnosis changes for 64 (17%) participants with asthma and COPD and treatment adjustments for 252 participants (57%). Exacerbations decreased significantly from 236 to 30 after attending the clinics (p<0.005), with a mean reduction of 0.53 exacerbation events per participant. Reductions were also seen in unscheduled and out-of-hours primary care attendance, emergency department visits and hospital admissions (all p<0.005). Cost savings from reduced exacerbations and healthcare utilisation offset increased medication costs and clinic expenses.ConclusionsSpecialist-supported multidisciplinary teams in MABC clinics improved diagnosis accuracy and adherence to guidelines. High patient satisfaction, disease control improvements and reduced exacerbations resulted in decreased unscheduled healthcare use and cost savings.Trial registration numberNCT03096509.

IntroductionThe prognosis of malignant pleural mesothelioma (MPM) is poor, with a median survival of 8–12 months. The ability to predict prognosis in MPM would help clinicians to make informed decisions regarding treatment and identify appropriate research opportunities for patients. The aims of this study were to examine associations between clinical and pathological information gathered during routine care, and prognosis of patients with MPM, and to develop a 6-month mortality risk prediction model.MethodsA retrospective cohort study of patients diagnosed with MPM at Queen Alexandra Hospital, Portsmouth, UK between December 2009 and September 2013. Multivariate analysis was performed on routinely available histological, clinical and laboratory data to assess the association between different factors and 6-month survival, with significant associations used to create a model to predict the risk of death within 6 months of diagnosis with MPM.Results100 patients were included in the analysis. Variables significantly associated with patient survival in multivariate analysis were age (HR 1.31, 95% CI 1.09 to 1.56), smoking status (current smoker HR 3.42, 95% CI 1.11 to 4.20), chest pain (HR 2.14, 95% CI 1.23 to 3.72), weight loss (HR 2.13, 95% CI 1.18 to 3.72), platelet count (HR 1.05, 95% CI 1.00 to 1.10), urea (HR 2.73, 95% CI 1.31 to 5.69) and adjusted calcium (HR 1.47, 95% CI 1.10 to 1.94). The resulting risk model had a c-statistic value of 0.76. A Hosmer-Lemeshow test confirmed good calibration of the model against the original dataset.ConclusionRisk of death at 6 months in patients with a confirmed diagnosis of MPM can be predicted using variables readily available in clinical practice. The risk prediction model we have developed may be used to influence treatment decisions in patients with MPM. Further validation of the model requires evaluation of its performance on a separate dataset.

Tobacco smoking is the primary cause of chronic obstructive pulmonary disease (COPD) globally. Capnography data was collected twice daily for up to 6 months from 147 COPD participants across multiple studies using TidalSense’s N-Tidal device. Waveform features from the alpha angle region of the capnogram showed strong association with pack year history, indicating that capnography can quantify a dose-response relationship between smoking exposure and airway remodelling. This non-linear association reached an inflection around 25 pack years, potentially indicating a ‘tipping point’ beyond which the likelihood of retaining normal lung function significantly diminishes. This provides valuable mechanistic insights and could help estimate disease risk and support early preventative interventions. Trial registration ClinicalTrials.gov NCT02814253 (registered on 27 June 2016), ClinicalTrials.gov NCT03615365 (registered on 3 August 2018), ClinicalTrials.gov NCT04939558 (registered on 25 June 2021).

Background Although currently most widely used in mechanical ventilation and cardiopulmonary resuscitation, features of the carbon dioxide (CO 2 ) waveform produced through capnometry have been shown to correlate with V/Q mismatch, dead space volume, type of breathing pattern, and small airway obstruction. This study applied feature engineering and machine learning techniques to capnography data collected by the N-Tidal™ device across four clinical studies to build a classifier that could distinguish CO 2 recordings (capnograms) of patients with COPD from those without COPD. Methods Capnography data from four longitudinal observational studies (CBRS, GBRS, CBRS2 and ABRS) was analysed from 295 patients, generating a total of 88,186 capnograms. CO 2 sensor data was processed using TidalSense’s regulated cloud platform, performing real-time geometric analysis on CO 2 waveforms to generate 82 physiologic features per capnogram. These features were used to train machine learning classifiers to discriminate COPD from ‘non-COPD’ (a group that included healthy participants and those with other cardiorespiratory conditions); model performance was validated on independent test sets. Results The best machine learning model (XGBoost) performance provided a class-balanced AUROC of 0.985 ± 0.013, positive predictive value (PPV) of 0.914 ± 0.039 and sensitivity of 0.915 ± 0.066 for a diagnosis of COPD. The waveform features that are most important for driving classification are related to the alpha angle and expiratory plateau regions. These features correlated with spirometry readings, supporting their proposed properties as markers of COPD. Conclusion The N-Tidal™ device can be used to accurately diagnose COPD in near-real-time, lending support to future use in a clinical setting. Trial registration: Please see NCT03615365, NCT02814253, NCT04504838 and NCT03356288.

In an increasingly comorbid population, there are significant challenges to diagnosing the cause of breathlessness, and once diagnosed, considerable difficulty in detecting deterioration early enough to provide effective intervention. The burden of the breathless patient on the health care economy is substantial, with asthma, chronic heart failure, and pneumonia affecting over 6 million people in the United Kingdom alone. Furthermore, these patients often have more than one contributory factor to their breathlessness symptoms, with conditions such as dysfunctional breathing pattern disorders-an under-recognized component. Current methods of diagnosing and monitoring breathless conditions can be extensive and difficult to perform. As a consequence, home monitoring is poorly complied with. In contrast, capnography (the measurement of tidal breath carbon dioxide) is performed during normal breathing. There is a need for a simple, easy-to-use, personal device that can aid in the diagnosis and monitoring of respiratory and cardiac causes of breathlessness. The aim of this study was to explore the use of a new, handheld capnometer (called the N-Tidal C) in different conditions that cause breathlessness. We will study whether the tidal breath carbon dioxide (TBCO ) waveform, as measured by the N-Tidal C, has different characteristics in a range of respiratory and cardiac conditions. We will perform a longitudinal, observational study of the TBCO waveform (capnogram) as measured by the N-Tidal C capnometer. Participants with a confirmed diagnosis of asthma, breathing pattern disorders, chronic heart failure, motor neurone disease, pneumonia, as well as volunteers with no history of lung disease will be asked to provide twice daily, 75-second TBCO collection via the N-Tidal C device for 6 months duration. The collated capnograms will be correlated with the underlying diagnosis and disease state (stable or exacerbation) to determine if there are different TBCO characteristics that can distinguish different respiratory and cardiac causes of breathlessness. This study's recruitment is ongoing. It is anticipated that the results will be available in late 2018. The General Breathing Record Study will provide an evaluation of the use of capnography as a diagnostic and home-monitoring tool for various diseases. RR1-10.2196/9767.

Respiratory rate (RR) is the most sensitive physiological observation to predict clinical deterioration on hospital wards, and poor clinical monitoring has been highlighted as a primary contributor to avoidable mortality. Patients in intensive care have their RR monitored continuously, but this equipment is rarely available on general hospital wards.BACKGROUNDRespiratory rate (RR) is the most sensitive physiological observation to predict clinical deterioration on hospital wards, and poor clinical monitoring has been highlighted as a primary contributor to avoidable mortality. Patients in intensive care have their RR monitored continuously, but this equipment is rarely available on general hospital wards.The primary objective is to assess the accuracy of the RespiraSense device in comparison with other methods currently used in clinical practice. The secondary objective is to assess the accuracy of the RespiraSense device in participants in different positions and when reading aloud.OBJECTIVEThe primary objective is to assess the accuracy of the RespiraSense device in comparison with other methods currently used in clinical practice. The secondary objective is to assess the accuracy of the RespiraSense device in participants in different positions and when reading aloud.A single-center, prospective observational study will investigate the agreement of the RespiraSense device as compared with other device measurements (capnography, electrocardiogram) and the current standard measurement of RR (manual counting by a trained health care professional). The different methods will be employed concurrently on the same participant as part of a single study visit.METHODSA single-center, prospective observational study will investigate the agreement of the RespiraSense device as compared with other device measurements (capnography, electrocardiogram) and the current standard measurement of RR (manual counting by a trained health care professional). The different methods will be employed concurrently on the same participant as part of a single study visit.Recruitment to this study has not yet started as funding decisions are still pending. Therefore, results are not available at this stage. It is anticipated that the data required could be collected within 2 months of first recruitment to the study and data analysis completed within 6 months of the study start date.RESULTSRecruitment to this study has not yet started as funding decisions are still pending. Therefore, results are not available at this stage. It is anticipated that the data required could be collected within 2 months of first recruitment to the study and data analysis completed within 6 months of the study start date.The Evaluation of Agreement of Breathing Rates Measured by a Novel Device, Manual Counting, and Other Techniques Used in Clinical Practice (VENTILATE) study will provide further validation of the use of the RespiraSense device in subjects with abnormal respiratory rates.CONCLUSIONSThe Evaluation of Agreement of Breathing Rates Measured by a Novel Device, Manual Counting, and Other Techniques Used in Clinical Practice (VENTILATE) study will provide further validation of the use of the RespiraSense device in subjects with abnormal respiratory rates.PRR1-10.2196/15437.INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)PRR1-10.2196/15437.