Soft sensor for viable cell counting by measuring dynamic oxygen uptake rate.

Regulatory authorities in biopharmaceutical industry emphasize process design by process understanding but applicable tools that are easy to implement are still missing. Soft sensors are a promising tool for the implementation of the Quality by Design (QbD) approach and Process Analytical Technology (PAT). In particular, the correlation between viable cell counting and oxygen consumption was investigated, but problems remained: Either the process had to be modified for excluding CO2 in pH control, or complex kLa models had to be set up for specific processes. In this work, a non-invasive soft sensor for simplified on-line cell counting based on dynamic oxygen uptake rate was developed with no need of special equipment. The dynamic oxygen uptake rates were determined by automated and periodic interruptions of gas supply in DASGIP® bioreactor systems, realized by a programmed Visual Basic script in the DASware® control software. With off-line cell counting, the two parameters were correlated based on linear regression and led to a robust model with a correlation coefficient of 0.92. Avoidance of oxygen starvation was achieved by gas flow reactivation at a certain minimum dissolved oxygen concentration. The soft sensor model was established in the exponential growth phase of a Chinese Hamster Ovary fed-batch process. Control studies showed no impact on cell growth by the discontinuous gas supply. This soft sensor is the first to be presented that does not require any specialized additional equipment as the methodology relies solely on the direct measurement of oxygen consumed by the cells in the bioreactor.

Prognostic value of EndoPredict test in patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative primary breast cancer screened for the randomized, double-blind, phase III UNIRAD trial.

BACKGROUND: The purpose of this study was to evaluate the prognostic value of the multigene EndoPredict test in prospectively collected data of patients screened for the randomized, double-blind, phase III UNIRAD trial, which evaluated the addition of everolimus to adjuvant endocrine therapy in high-risk, hormone receptor-positive, human epidermal growth factor receptor 2 (HER2)-negative early breast cancer. PATIENTS AND METHODS: Patients were classified into low or high risk according to the EPclin score, consisting of a 12-gene molecular score combined with tumor size and nodal status. Association of the EPclin score with disease-free survival (DFS) and distant metastasis-free survival (DMFS) was evaluated using Kaplan-Meier estimates. The independent prognostic added value of EPclin score was tested in a multivariate Cox model after adjusting on tumor characteristics. RESULTS: EndoPredict test results were available for 768 patients: 663 patients classified as EPclin high risk (EPCH) and 105 patients as EPclin low risk (EPCL). Median follow-up was 70 months (range 1-172 months). For the 429 EPCH randomized patients, there was no significant difference in DFS between treatment arms. The 60-month relapse rate for patients in the EPCL and EPCH groups was 0% and 7%, respectively. Hazard ratio (HR) supposing continuous EPclin score was 1.87 [95% confidence interval (CI) 1.4-2.5, P < 0.0001]. This prognostic effect remained significant when assessed in a Cox model adjusting on tumor size, number of positive nodes and tumor grade (HR 1.52, 95% CI 1.09-2.13, P = 0.0141). The 60-month DMFS for patients in the EPCL and EPCH groups was 100% and 94%, respectively (adjusted HR 8.10, 95% CI 1.1-59.1, P < 0.0001). CONCLUSIONS: The results confirm the value of EPclin score as an independent prognostic parameter in node-positive, hormone receptor-positive, HER2-negative early breast cancer patients receiving standard adjuvant treatment. EPclin score can be used to identify patients at higher risk of recurrence who may warrant additional systemic treatments.

Chemotherapy is not needed when complete evacuation of gestational choriocarcinoma leads to hCG normalization.

BACKGROUND: The standard treatment for gestational choriocarcinoma is chemotherapy. OBJECTIVE: To describe the risk of recurrence with expectant management of gestational choriocarcinoma that has reached a normal human chorionic gonadotropin level after tumor removal without adjuvant chemotherapy. METHODS: A retrospective multicenter international cohort study was conducted from 1981 to 2017 involving 11 gestational trophoblastic disease reference centers with patient's follow-up extended until 2023. Clinical and biological data of included patients were extracted from each center's database. The inclusion criteria were i) histological diagnosis of gestational choriocarcinoma in any kind of placental tissue retrieved, ii) spontaneous normalization of human chorionic gonadotropin level following choriocarcinoma retrieval, iii) patient did not receive any oncological treatment for the choriocarcinoma, iv) and at least 6 months of follow-up after the first human chorionic gonadotropin level normalization. RESULTS: Among 80 patients with retrieved gestational choriocarcinoma and whose human chorionic gonadotropin level normalized without any other oncological therapy, none had a recurrence of choriocarcinoma after a median follow-up of 50 months. The median interval between choriocarcinoma excision and human chorionic gonadotropin level normalization was 48 days. The International Federation of Gynecology and Obstetrics/World Health Organization risk score was ≤6 in 93.7% of the cases. CONCLUSIONS: This multicenter international study reports that selected patients with gestational choriocarcinoma managed in gestational trophoblastic disease reference centers did not experience any relapse when the initial tumor evacuation is followed by human chorionic gonadotropin level normalization without any additional treatment. Expectant management may be a safe approach for highly selected patients.

Being a "Good Parent" to a NICU Infant With a Major Congenital Anomaly.

BACKGROUND: In the United States, up to one-third of infants with a congenital anomaly require neonatal intensive care unit (NICU) hospitalization. Parents of these infants may have different decision-making priorities, which may be influenced by the timing of the infant's diagnosis. PURPOSE: (1) To compare the ranked importance of decision-making beliefs for parents of infants who received a prenatal versus postnatal congenital diagnosis and (2) explore how parents describe their decision-making beliefs. METHODS: A cross-sectional, sequential mixed-methods pilot design was applied to collect quantitative data using the Good Parent Ranking Exercise and further explore parents' decision-making beliefs through qualitative interviews. Maximum difference scaling/hierarchical Bayes estimation and content analysis were used to analyze the quantitative and qualitative data, respectively. RESULTS: Forty mothers completed the Good Parent Ranking Exercise and 20 mothers completed qualitative interviews. Four of the top 5 ranked parenting beliefs were shared by mothers in the prenatal and postnatal groups. Mothers in the postnatal group ranked "focusing on my child's quality of life" higher. Qualitative interviews revealed that previously identified decision-making beliefs were consistent in this NICU parent population, with 1 additional belief identified. Mixed-methods analysis revealed high concordance between the prenatal and postnatal groups. IMPLICATIONS FOR PRACTICE: NICU nurses need to know that decision-making beliefs for parents who receive a prenatal versus postnatal congenital diagnosis, while largely similar, may have differences. IMPLICATIONS FOR RESEARCH: Future research should explore decision-making beliefs in demographically diverse parent groups (ie, fathers, partnered vs nonpartnered couples) and effective strategies for promoting NICU parents' decision-making beliefs.

A straightforward method for determination of the sevoflurane metabolite hexafluoroisopropanol in urinary occupational medical samples by headspace-gas chromatography mass spectrometry.

Biological monitoring of the unmodified sevoflurane and its metabolite hexafluoroisopropanol (HFIP) in urine samples was proposed to determine the individual exposure levels of the medical staff. In this study, a method for simultaneous determination of both compounds in urine using static headspace-gas chromatography-mass spectrometry (HS-GC-MS) was developed. The method is linear over a broad concentration range from 1 to 1000 µg/L (r2 > 0.999) and shows high precision. Limits of quantification (LOQ) are 0.6 µg/L for sevoflurane and 3 µg/L for HFIP, representing an excellent sensitivity without the necessity of analyte enrichment. The method was successfully applied in a German pilot-study to monitor both compounds in samples from medical personnel working in operating theatres. Urinary concentrations of HFIP ranged between < LOQ and 145 µg/L, while sevoflurane was below the LOD in all samples.

Cannabis use frequency and pain interference among people with HIV.

Cannabis is often used by people with HIV (PWH) for pain, yet study results are inconsistent regarding whether and how it affects pain. This study examines whether greater cannabis use frequency is associated with lower pain interference and whether cannabis use modifies the association of pain severity and pain interference among 134 PWH with substance dependence or a lifetime history of injection drug use. Multi-variable linear regression models examined the association between past 30-day cannabis use frequency and pain interference. Additional models evaluated whether cannabis use modified the association between pain severity and pain interference. Cannabis use frequency was not significantly associated with pain interference. However, in a model with interaction between cannabis use frequency and pain severity, greater cannabis use frequency attenuated the strength of the association between pain severity and pain interference (p = 0.049). The adjusted mean difference (AMD) in pain interference was +1.13, + 0.81, and +0.05 points for each 1-point increase in pain severity for those with no cannabis use, 15 days of use, and daily use, respectively. These findings suggest that attenuating the impact of pain severity on pain-related functional impairment is a potential mechanism for a beneficial role of cannabis for PWH.

Leptomeningeal disease as a presenting feature of gestational trophoblastic neoplasia: A review and recommendations for management.

OBJECTIVES: Gestational Trophoblastic Neoplasia (GTN) is a rare group of malignant placental-related tumours requiring systemic anti-cancer treatment. Leptomeningeal disease (LMD) related to GTN is not well reported with no consensus in optimal treatment. We offer recommendations for management of these patients. METHODS: We discuss five patients with GTN who presented with features of LMD and were diagnosed with gadolinium-enhanced MRI brain, all of whom received low dose induction etoposide-cisplatin (EP) followed by either EP-etoposide, methotrexate (CNS) and actinomycin-D (EMA) or EMA(CNS)-cyclophosphamide and vincristine (CO). RESULTS: Four out of the five patients additionally received intrathecal methotrexate. Four patients had complete hCG response to first line multi-agent chemotherapy, one patient required second line paclitaxel, cisplatin alternating with paclitaxel, etoposide (TP/TE), where paclitaxel was substituted with nab-paclitaxel due to anaphylaxis, followed by hysterectomy. One of the four initial complete hCG responders relapsed in the lung requiring further systemic treatment with subsequent lobectomy. Patient reported outcomes indicate persistent neurological symptoms are mild and do not affect functionality and quality of life. CONCLUSION: With a follow-up range of 2-6 years, all five patients remain cured demonstrating excellent survival outcomes with the avoidance of whole-brain radiotherapy in all cases.

The importance of cultural tailoring of communicators and media outlets in an influenza vaccination awareness campaign: a digital randomized trial.

The COVID-19 pandemic has exposed the vulnerability of ethnic minorities again. Health inequity within ethnic minorities has been explained by factors such as higher prevalence of underlying disease, restricted access to care, and lower vaccination rates. In this study, we investigated the effect of cultural tailoring of communicators and media outlets, respectively, on vaccine willingness in an influenza vaccination campaign in the Netherlands. A total of 1226 participants were recruited from two culturally non-tailored media outlets (Dutch newspaper and Facebook), and one media outlet tailored to a large community in the Netherlands with Indian ancestry. The participants from all three media outlets were randomly exposed to a vaccination awareness video delivered by a physician with an Indian or Dutch background, followed by an online survey. Cultural tailoring compared to cultural non-tailoring of communicators showed no difference in improvement of vaccine willingness (13.9% vs. 20.7% increment, respectively, p = 0.083). However, the media outlet tailored to the community with Indian ancestry, resulted in a higher improvement of vaccine willingness compared to non-tailored media outlets (46.7% vs. 14.7% increment, respectively, p < 0.001, unadjusted OR = 5.096). These results suggest that cultural tailoring of media outlets may be critical to effectively reach out to ethnic minorities to help optimize vaccination rates and improve general health.

Accuracy of mobile 6-lead electrocardiogram device for assessment of QT interval: a prospective validation study.

INTRODUCTION: Ambulatory assessment of the heart rate-corrected QT interval (QTc) can be of diagnostic value, for example in patients on QTc-prolonging medication. Repeating sequential 12-lead electrocardiograms (ECGs) to monitor the QTc is cumbersome, but mobile ECG (mECG) devices can potentially solve this problem. As the accuracy of single-lead mECG devices is reportedly variable, a multilead mECG device may be more accurate. METHODS: This prospective dual-centre study included outpatients visiting our cardiology clinics for any indication. Participants underwent an mECG recording using a smartphone-enabled 6­lead mECG device immediately before or immediately after a conventional 12-lead ECG recording. Multiple QTc values in both recordings were manually measured in leads I and II using the tangent method and subsequently compared. RESULTS: In total, 234 subjects were included (mean ± standard deviation (SD) age: 57 ± 17 years; 58% males), of whom 133 (57%) had cardiac disease. QTc measurement in any lead was impossible due to artefacts in 16 mECGs (7%) and no 12-lead ECGs. Mean (± SD) QTc in lead II on the mECG and 12-lead ECG was 401 ± 30 and 406 ± 31 ms, respectively. Mean (± SD) absolute difference in QTc values between both modalities was 12 ± 9 ms (r = 0.856; p < 0.001). In 55% of the subjects, the absolute difference between QTc values was < 10 ms. CONCLUSION: A 6-lead mECG allows for QTc assessment with good accuracy and can be used safely in ambulatory QTc monitoring. This may improve patient satisfaction and reduce healthcare costs.

Results of the c-TRAK TN trial: a clinical trial utilising ctDNA mutation tracking to detect molecular residual disease and trigger intervention in patients with moderate- and high-risk early-stage triple-negative breast cancer.

BACKGROUND: Post-treatment detection of circulating tumour DNA (ctDNA) in early-stage triple-negative breast cancer (TNBC) patients predicts high risk of relapse. c-TRAK TN assessed the utility of prospective ctDNA surveillance in TNBC and the activity of pembrolizumab in patients with ctDNA detected [ctDNA positive (ctDNA+)]. PATIENTS AND METHODS: c-TRAK TN, a multicentre phase II trial, with integrated prospective ctDNA surveillance by digital PCR, enrolled patients with early-stage TNBC and residual disease following neoadjuvant chemotherapy, or stage II/III with adjuvant chemotherapy. ctDNA surveillance comprised three-monthly blood sampling to 12 months (18 months if samples were missed due to coronavirus disease), and ctDNA+ patients were randomised 2 : 1 to intervention : observation. ctDNA results were blinded unless patients were allocated to intervention, when staging scans were done and those free of recurrence were offered pembrolizumab. A protocol amendment (16 September 2020) closed the observation group; all subsequent ctDNA+ patients were allocated to intervention. Co-primary endpoints were (i) ctDNA detection rate and (ii) sustained ctDNA clearance rate on pembrolizumab (NCT03145961). RESULTS: Two hundred and eight patients registered between 30 January 2018 and 06 December 2019, 185 had tumour sequenced, 171 (92.4%) had trackable mutations, and 161 entered ctDNA surveillance. Rate of ctDNA detection by 12 months was 27.3% (44/161, 95% confidence interval 20.6% to 34.9%). Seven patients relapsed without prior ctDNA detection. Forty-five patients entered the therapeutic component (intervention n = 31; observation n = 14; one observation patient was re-allocated to intervention following protocol amendment). Of patients allocated to intervention, 72% (23/32) had metastases on staging at the time of ctDNA+, and 4 patients declined pembrolizumab. Of the five patients who commenced pembrolizumab, none achieved sustained ctDNA clearance. CONCLUSIONS: c-TRAK TN is the first prospective study to assess whether ctDNA assays have clinical utility in guiding therapy in TNBC. Patients had a high rate of metastatic disease on ctDNA detection. Findings have implications for future trial design, emphasising the importance of commencing ctDNA testing early, with more sensitive and/or frequent ctDNA testing regimes.

Electrocardiogram-based mortality prediction in patients with COVID-19 using machine learning.

BACKGROUND AND PURPOSE: The electrocardiogram (ECG) is frequently obtained in the work-up of COVID-19 patients. So far, no study has evaluated whether ECG-based machine learning models have added value to predict in-hospital mortality specifically in COVID-19 patients. METHODS: Using data from the CAPACITY-COVID registry, we studied 882 patients admitted with COVID-19 across seven hospitals in the Netherlands. Raw format 12-lead ECGs recorded within 72 h of admission were studied. With data from five hospitals (n = 634), three models were developed: (a) a logistic regression baseline model using age and sex, (b) a least absolute shrinkage and selection operator (LASSO) model using age, sex and human annotated ECG features, and (c) a pre-trained deep neural network (DNN) using age, sex and the raw ECG waveforms. Data from two hospitals (n = 248) was used for external validation. RESULTS: Performances for models a, b and c were comparable with an area under the receiver operating curve of 0.73 (95% confidence interval [CI] 0.65-0.79), 0.76 (95% CI 0.68-0.82) and 0.77 (95% CI 0.70-0.83) respectively. Predictors of mortality in the LASSO model were age, low QRS voltage, ST depression, premature atrial complexes, sex, increased ventricular rate, and right bundle branch block. CONCLUSION: This study shows that the ECG-based prediction models could be helpful for the initial risk stratification of patients diagnosed with COVID-19, and that several ECG abnormalities are associated with in-hospital all-cause mortality of COVID-19 patients. Moreover, this proof-of-principle study shows that the use of pre-trained DNNs for ECG analysis does not underperform compared with time-consuming manual annotation of ECG features.

A new benchmark of soft X-ray transition energies of Ne , CO 2 , and SF 6 : paving a pathway towards ppm accuracy.

Abstract: A key requirement for the correct interpretation of high-resolution X-ray spectra is that transition energies are known with high accuracy and precision. We investigate the K-shell features of Ne , CO 2 , and SF 6 gases, by measuring their photo ion-yield spectra at the BESSY II synchrotron facility simultaneously with the 1s-np fluorescence emission of He-like ions produced in the Polar-X EBIT. Accurate ab initio calculations of transitions in these ions provide the basis of the calibration. While the CO 2 result agrees well with previous measurements, the SF 6 spectrum appears shifted by ∼ 0.5 eV, about twice the uncertainty of the earlier results. Our result for Ne shows a large departure from earlier results, but may suffer from larger systematic effects than our other measurements. The molecular spectra agree well with our results of time-dependent density functional theory. We find that the statistical uncertainty allows calibrations in the desired range of 1-10 meV, however, systematic contributions still limit the uncertainty to ∼ 40-100 meV, mainly due to the temporal stability of the monochromator energy scale. Combining our absolute calibration technique with a relative energy calibration technique such as photoelectron energy spectroscopy will be necessary to realize its full potential of achieving uncertainties as low as 1-10 meV.

Current state of artificial intelligence-based algorithms for hospital admission prediction in patients with heart failure: a scoping review.

Aims: Patients with congestive heart failure (HF) are prone to clinical deterioration leading to hospital admissions, burdening both patients and the healthcare system. Predicting hospital admission in this patient group could enable timely intervention, with subsequent reduction of these admissions. To date, hospital admission prediction remains challenging. Increasing amounts of acquired data and development of artificial intelligence (AI) technology allow for the creation of reliable hospital prediction algorithms for HF patients. This scoping review describes the current literature on strategies and performance of AI-based algorithms for prediction of hospital admission in patients with HF. Methods and results: PubMed, EMBASE, and the Web of Science were used to search for articles using machine learning (ML) and deep learning methods to predict hospitalization in patients with HF. After eligibility screening, 23 articles were included. Sixteen articles predicted 30-day hospital (re-)admission resulting in an area under the curve (AUC) ranging from 0.61 to 0.79. Six studies predicted hospital admission over longer time periods ranging from 6 months to 3 years, with AUC's ranging from 0.65 to 0.78. One study prospectively evaluated performance of a disposable sensory patch at home after hospitalization which resulted in an AUC of 0.89 for unplanned hospital admission prediction. Conclusion: AI has the potential to enable prediction of hospital admission in HF patients. Improvement of data management, adding new data sources such as telemonitoring data and ML models and prospective and external validation of current models must be performed before clinical applicability is possible.

Effect of an interactive, educational app about venous thromboembolism and anticoagulation on patient satisfaction: A randomized controlled trial.

BACKGROUND: Adequate patient education is essential for patients to engage in shared decision-making when deciding to stop or continue anticoagulation after 3 months for venous thromboembolism (VTE). Our objectives were to evaluate the effect of an interactive, educational app on patients' level of satisfaction with information, perceived level of knowledge, decisional conflict and extent of shared decision-making when deciding on treatment duration of VTE. MATERIALS AND METHODS: This randomized controlled trial in 1 academic and 3 general Dutch hospitals included adult patients diagnosed with VTE without malignancy or prolonged anticoagulation for other indications. Patients were randomized in 1:1 ratio to receive the app (intervention group) in addition to hospital-specific standard of care. The app, created for this study, contains information on VTE and anticoagulation on an interactive timeline. In the week preceding the consultation when treatment duration is decided, patients were provided with daily videos using push notifications. Outcomes were assessed through self-reported questionnaires at baseline, 1-2 days before and 1 day after consultation. Data were analyzed using t-tests and linear mixed models for repeated measurements. RESULTS: Data of 56 patients were analyzed (mean age 57 ± 13; 27% female). On a numeric rating scale from 0 to 10, patients who received the app were 0.9 points (95%CI 0.0-1.7; p 0.04) more satisfied with the provided information. Patients who received the app experienced significantly less decisional conflict. No differences in other outcomes were observed. CONCLUSIONS: An educational app about VTE and anticoagulation increases patients' satisfaction and reduces decisional conflict when deciding on treatment duration of VTE. This study was registered in the Netherlands Trial Register (NL7037).

Deep Learning-Based Data-Point Precise R-Peak Detection in Single-Lead Electrocardiograms.

Low-cost wearables with capability to record electrocardiograms (ECG) are becoming increasingly available. These wearables typically acquire single-lead ECGs that are mainly used for screening of cardiac arrhythmias such as atrial fibrillation. Most arrhythmias are characteruzed by changes in the RR-interval, hence automatic methods to diagnose arrythmia may utilize R-peak detection. Existing R-peak detection methods are fairly accurate but have limited precision. To enable data-point precise detection of R-peaks, we propose a method that uses a fully convolutional dilated neural network. The network is trained and evaluated with manually annotated R-peaks in a heterogeneous set of ECGs that contain a wide range of cardiac rhythms and acquisition noise. 700 randomly chosen ECGs from the PhysioNet/CinC challenge 2017 were used for training (n=500), validation (n=100) and testing (n=100). The network achieves a precision of 0.910, recall of 0.926, and an F1-score of 0.918 on the test set. Our data-point precise R-peak detector may be important step towards fully automatic cardiac arrhythmia detection.Clinical relevance- This method enables data-point precise detection of R-peaks that provides a basis for detection and characterization of arrhythmias.

Employing a mobile health decision aid to improve decision-making for patients with advanced prostate cancer and their decision partners/proxies: the CHAMPION randomized controlled trial study design.

BACKGROUND: Metastatic prostate cancer remains a lethal malignancy that warrants novel supportive interventions for patients and their decision partners and proxies. Decision aids have been applied primarily to patients with localized disease, with minimal inclusion of patients with advanced prostate cancer and their decision partners. The use of a community patient navigator (CPN) has been shown to have a positive supportive role in health care, particularly with individuals from minority populations. Research is needed to evaluate decision support interventions tailored to the needs of advanced prostate cancer patients and their decision partners in diverse populations. METHODS: Guided by Janis and Mann's Conflict Model of Decision Making, the Cancer Health Aid to Manage Preferences and Improve Outcomes through Navigation (CHAMPION) is a randomized controlled trial to assess the feasibility and acceptability of a mobile health (mHealth), CPN-administered decision support intervention designed to facilitate communication between patients, their decision partners, and the healthcare team. Adult prostate cancer patients and their decision partners at three mid-Atlantic hospitals in the USA were randomized to receive enhanced usual care or the decision intervention. The CHAMPION intervention includes a theory-based decision-making process tutorial, immediate and health-related quality of life graphical summaries over time (using mHealth), values clarification via a balance sheet procedure with the CPN support during difficult decisions, and facilitated discussions with providers to enhance informed, shared decision-making. DISCUSSION: The CHAMPION intervention is designed to leverage dynamic resources, such as CPN teams, mHealth technology, and theory-based information, to support decision-making for advanced prostate cancer patients and their decision partners. This intervention is intended to engage decision partners in addition to patients and represents a novel, sustainable, and scalable way to build on individual and community strengths. Patients from minority populations, in particular, may face unique challenges during clinical communication. CHAMPION emphasizes the inclusion of decision partners and CPNs as facilitators to help address these barriers to care. Thus, the CHAMPION intervention has the potential to positively impact patient and decision partner well-being by reducing decisional conflict and decision regret related to complex, treatment-based decisions, and to reduce cancer health disparities. Trial registration ClinicalTrials.gov NCT03327103 . Registered on 31 October 2017-retrospectively registered. World Health Organization Trial Registration Data Set included in Supplementary Materials.

The accuracy of heartbeat detection using photoplethysmography technology in cardiac patients.

INTRODUCTION: Photoplethysmography (PPG) in wearable sensors potentially plays an important role in accessible heart rhythm monitoring. We investigated the accuracy of a state-of-the-art bracelet (Corsano 287) for heartbeat detection in cardiac patients and evaluated the efficacy of a signal qualifier in identifying medically useful signals. METHODS: Patients from an outpatient cardiology clinic underwent a simultaneous resting ECG and PPG recording, which we compared to determine accuracy of the PPG sensor for detecting heartbeats within 100 and 50 ms of the ECG-detected heart beats and correlation and Limits of Agreement for heartrate (HR) and RR-intervals. We defined subgroups for skin type, hair density, age, BMI and gender and applied a previously described signal qualifier. RESULTS: In 180 patients 7914 ECG-, and 7880 (99%) PPG-heartbeats were recorded. The PPG-accuracy within 100 ms was 94.6% (95% CI 94.1-95.1) and 89.2% (95% CI 88.5-89.9) within 50 ms. Correlation was high for HR (R = 0.991 (95% CI 0.988-0.993), n = 180) and RR-intervals (R = 0.891 (95% CI 0.886-0.895), n = 7880). The 95% Limits of Agreement (LoA) were -3.89 to 3.77 (mean bias 0.06) beats per minute for HR and -173 to 171 (mean bias -1) for RR-intervals. Results were comparable across all subgroups. The signal qualifier led to a higher accuracy in a 100 ms range (98.2% (95% CI 97.9-98.5)) (n = 143). CONCLUSION: We showed that the Corsano 287 Bracelet with PPG-technology can determine HR and RR-intervals with high accuracy in cardiovascular at-risk patient population among different subgroups, especially with a signal quality indicator.

An interrupted time series analysis of the lockdown policies in India: a national-level analysis of COVID-19 incidence.

India implemented a national mandatory lockdown policy (Lockdown 1.0) on 24 March 2020 in response to Coronavirus Disease 2019 (COVID-19). The policy was revised in three subsequent stages (Lockdown 2.0-4.0 between 15 April to 18 May 2020), and restrictions were lifted (Unlockdown 1.0) on 1 June 2020. This study evaluated the effect of lockdown policy on the COVID-19 incidence rate at the national level to inform policy response for this and future pandemics. We conducted an interrupted time series analysis with a segmented regression model using publicly available data on daily reported new COVID-19 cases between 2 March 2020 and 1 September 2020. National-level data from Google Community Mobility Reports during this timeframe were also used in model development and robustness checks. Results showed an 8% [95% confidence interval (CI) = 6-9%] reduction in the change in incidence rate per day after Lockdown 1.0 compared to prior to the Lockdown order, with an additional reduction of 3% (95% CI = 2-3%) after Lockdown 4.0, suggesting an 11% (95% CI = 9-12%) reduction in the change in COVID-19 incidence after Lockdown 4.0 compared to the period before Lockdown 1.0. Uptake of the lockdown policy is indicated by decreased mobility and attenuation of the increasing incidence of COVID-19. The increasing rate of incident case reports in India was attenuated after the lockdown policy was implemented compared to before, and this reduction was maintained after the restrictions were eased, suggesting that the policy helped to 'flatten the curve' and buy additional time for pandemic preparedness, response and recovery.

Bridging the age gap in breast cancer: impact of omission of breast cancer surgery in older women with oestrogen receptor-positive early breast cancer on quality-of-life outcomes.

BACKGROUND: Primary endocrine therapy may be an alternative treatment for less fit women with oestrogen receptor (ER)-positive breast cancer. This study compared quality-of-life (QoL) outcomes in older women treated with surgery or primary endocrine therapy. METHODS: This was a multicentre, prospective, observational cohort study of surgery or primary endocrine therapy in women aged over 70 years with operable breast cancer. QoL was assessed using European Organisation for Research and Treatment of cancer QoL questionnaires QLQ-C30, -BR23, and -ELD14, and the EuroQol Five Dimensions 5L score at baseline, 6 weeks, and 6, 12, 18, and 24 months. Propensity score matching was used to adjust for baseline variation in health, fitness, and tumour stage. RESULTS: The study recruited 3416 women (median age 77 (range 69-102) years) from 56 breast units. Of these, 2979 (87.2 per cent) had ER-positive breast cancer; 2354 women had surgery and 500 received primary endocrine therapy (125 were excluded from analysis due to inadequate data or non-standard therapy). Median follow-up was 52 months. The primary endocrine therapy group was older and less fit. Baseline QoL differed between the groups; the mean(s.d.) QLQ-C30 global health status score was 66.2(21.1) in patients who received primary endocrine therapy versus 77.1(17.8) among those who had surgery plus endocrine therapy. In the unmatched analysis, changes in QoL between 6 weeks and baseline were noted in several domains, but by 24 months most scores had returned to baseline levels. In the matched analysis, major surgery (mastectomy or axillary clearance) had a more pronounced adverse impact than primary endocrine therapy in several domains. CONCLUSION: Adverse effects on QoL are seen in the first few months after surgery, but by 24 months these have largely resolved. Women considering surgery should be informed of these effects.

Bridging the age gap in breast cancer: cluster randomized trial of two decision support interventions for older women with operable breast cancer on quality of life, survival, decision quality, and treatment choices.

BACKGROUND: Rates of surgery and adjuvant therapy for breast cancer vary widely between breast units. This may contribute to differences in survival. This cluster RCT evaluated the impact of decision support interventions (DESIs) for older women with breast cancer, to ascertain whether DESIs influenced quality of life, survival, decision quality, and treatment choice. METHODS: A multicentre cluster RCT compared the use of two DESIs against usual care in treatment decision-making in older women (aged at least ≥70 years) with breast cancer. Each DESI comprised an online algorithm, booklet, and brief decision aid to inform choices between surgery plus adjuvant endocrine therapy versus primary endocrine therapy, and adjuvant chemotherapy versus no chemotherapy. The primary outcome was quality of life. Secondary outcomes included decision quality measures, survival, and treatment choice. RESULTS: A total of 46 breast units were randomized (21 intervention, 25 usual care), recruiting 1339 women (670 intervention, 669 usual care). There was no significant difference in global quality of life at 6 months after the baseline assessment on intention-to-treat analysis (difference -0.20, 95 per cent confidence interval (C.I.) -2.69 to 2.29; P = 0.900). In women offered a choice of primary endocrine therapy versus surgery plus endocrine therapy, knowledge about treatments was greater in the intervention arm (94 versus 74 per cent; P = 0.003). Treatment choice was altered, with a primary endocrine therapy rate among women with oestrogen receptor-positive disease of 21.0 per cent in the intervention versus 15.4 per cent in usual-care sites (difference 5.5 (95 per cent C.I. 1.1 to 10.0) per cent; P = 0.029). The chemotherapy rate was 10.3 per cent at intervention versus 14.8 per cent at usual-care sites (difference -4.5 (C.I. -8.0 to 0) per cent; P = 0.013). Survival was similar in both arms. CONCLUSION: The use of DESIs in older women increases knowledge of breast cancer treatment options, facilitates shared decision-making, and alters treatment selection. Trial registration numbers: EudraCT 2015-004220-61 (https://eudract.ema.europa.eu/), ISRCTN46099296 (http://www.controlled-trials.com).