Sex-specific differences in physiological parameters related to SARS-CoV-2 infections among a national cohort (COVI-GAPP study).

Considering sex as a biological variable in modern digital health solutions, we investigated sex-specific differences in the trajectory of four physiological parameters across a COVID-19 infection. A wearable medical device measured breathing rate, heart rate, heart rate variability, and wrist skin temperature in 1163 participants (mean age = 44.1 years, standard deviation [SD] = 5.6; 667 [57%] females). Participants reported daily symptoms and confounders in a complementary app. A machine learning algorithm retrospectively ingested daily biophysical parameters to detect COVID-19 infections. COVID-19 serology samples were collected from all participants at baseline and follow-up. We analysed potential sex-specific differences in physiology and antibody titres using multilevel modelling and t-tests. Over 1.5 million hours of physiological data were recorded. During the symptomatic period of infection, men demonstrated larger increases in skin temperature, breathing rate, and heart rate as well as larger decreases in heart rate variability than women. The COVID-19 infection detection algorithm performed similarly well for men and women. Our study belongs to the first research to provide evidence for differential physiological responses to COVID-19 between females and males, highlighting the potential of wearable technology to inform future precision medicine approaches.

Patient Factors in the Dose Selection of Oral Sumatriptan for Acute Migraine: A Post Hoc Analysis of Two Randomized Controlled Studies.

INTRODUCTION: Patients are seeking greater involvement in their healthcare. It therefore may be beneficial to provide guidance on initial oral sumatriptan dose selection for the treatment of acute migraine in nontraditional settings, such as telehealth and other remote forms of medical care. We sought to determine whether clinical or demographic factors are predictive of oral sumatriptan dose preference. METHODS: This was a post hoc analysis of two clinical studies designed to determine preference for 25, 50, or 100 mg oral sumatriptan. Patients were aged 18-65 years with at least a 1 year history of migraine and experienced, on average, between one and six severe or moderately severe migraine attacks per month, with or without aura. Predictive factors were demographic measures, medical history, and migraine characteristics. Possibly predictive factors were identified using three analyses: classification and regression tree analysis, marginal significance (P < 0.1) within a full-model logistic regression, and/or selection within a forward-selection procedure in a logistic regression. A reduced model containing the variables identified in the preliminary analyses was developed. Due to differences in study design, data were not combined. RESULTS: A dose preference was expressed by 167 patients in Study 1 and 222 patients in Study 2. Gender and medical history of urologic and/or psychological conditions in Study 1 and duration of migraine history, height, and medical history of endocrine or neurologic disease and headache severity in Study 2 were identified as possibly predictive. The predictive model showed low positive predictive value (PPV; 23.8%) and low sensitivity (21.7%) for Study 1. For Study 2, the model showed moderate PPV (60.0%) but low sensitivity (10.9%). CONCLUSIONS: No clinical or demographic characteristics alone or in combination were consistently or strongly associated with preference for oral sumatriptan dose level. TRIAL REGISTRATION: The studies on which this paper is based were conducted before trial registration indexes were introduced.

How Well do Polygenic Risk Scores Identify Men at High Risk for Prostate Cancer? Systematic Review and Meta-Analysis.

OBJECTIVES: Genome-wide association studies have revealed over 200 genetic susceptibility loci for prostate cancer (PCa). By combining them, polygenic risk scores (PRS) can be generated to predict risk of PCa. We summarize the published evidence and conduct meta-analyses of PRS as a predictor of PCa risk in Caucasian men. PATIENTS AND METHODS: Data were extracted from 59 studies, with 16 studies including 17 separate analyses used in the main meta-analysis with a total of 20,786 cases and 69,106 controls identified through a systematic search of ten databases. Random effects meta-analysis was used to obtain pooled estimates of area under the receiver-operating characteristic curve (AUC). Meta-regression was used to assess the impact of number of single-nucleotide polymorphisms (SNPs) incorporated in PRS on AUC. Heterogeneity is expressed as I2 scores. Publication bias was evaluated using funnel plots and Egger tests. RESULTS: The ability of PRS to identify men with PCa was modest (pooled AUC 0.63, 95% CI 0.62-0.64) with moderate consistency (I2 64%). Combining PRS with clinical variables increased the pooled AUC to 0.74 (0.68-0.81). Meta-regression showed only negligible increase in AUC for adding incremental SNPs. Despite moderate heterogeneity, publication bias was not evident. CONCLUSION: Typically, PRS accuracy is comparable to PSA or family history with a pooled AUC value 0.63 indicating mediocre performance for PRS alone.

Investigation of the use of a sensor bracelet for the presymptomatic detection of changes in physiological parameters related to COVID-19: an interim analysis of a prospective cohort study (COVI-GAPP).

OBJECTIVES: We investigated machinelearningbased identification of presymptomatic COVID-19 and detection of infection-related changes in physiology using a wearable device. DESIGN: Interim analysis of a prospective cohort study. SETTING, PARTICIPANTS AND INTERVENTIONS: Participants from a national cohort study in Liechtenstein were included. Nightly they wore the Ava-bracelet that measured respiratory rate (RR), heart rate (HR), HR variability (HRV), wrist-skin temperature (WST) and skin perfusion. SARS-CoV-2 infection was diagnosed by molecular and/or serological assays. RESULTS: A total of 1.5 million hours of physiological data were recorded from 1163 participants (mean age 44±5.5 years). COVID-19 was confirmed in 127 participants of which, 66 (52%) had worn their device from baseline to symptom onset (SO) and were included in this analysis. Multi-level modelling revealed significant changes in five (RR, HR, HRV, HRV ratio and WST) device-measured physiological parameters during the incubation, presymptomatic, symptomatic and recovery periods of COVID-19 compared with baseline. The training set represented an 8-day long instance extracted from day 10 to day 2 before SO. The training set consisted of 40 days measurements from 66 participants. Based on a random split, the test set included 30% of participants and 70% were selected for the training set. The developed long short-term memory (LSTM) based recurrent neural network (RNN) algorithm had a recall (sensitivity) of 0.73 in the training set and 0.68 in the testing set when detecting COVID-19 up to 2 days prior to SO. CONCLUSION: Wearable sensor technology can enable COVID-19 detection during the presymptomatic period. Our proposed RNN algorithm identified 68% of COVID-19 positive participants 2 days prior to SO and will be further trained and validated in a randomised, single-blinded, two-period, two-sequence crossover trial. Trial registration number ISRCTN51255782; Pre-results.

The performance of wearable sensors in the detection of SARS-CoV-2 infection: a systematic review.

Containing the COVID-19 pandemic requires rapidly identifying infected individuals. Subtle changes in physiological parameters (such as heart rate, respiratory rate, and skin temperature), discernible by wearable devices, could act as early digital biomarkers of infections. Our primary objective was to assess the performance of statistical and algorithmic models using data from wearable devices to detect deviations compatible with a SARS-CoV-2 infection. We searched MEDLINE, Embase, Web of Science, the Cochrane Central Register of Controlled Trials (known as CENTRAL), International Clinical Trials Registry Platform, and ClinicalTrials.gov on July 27, 2021 for publications, preprints, and study protocols describing the use of wearable devices to identify a SARS-CoV-2 infection. Of 3196 records identified and screened, 12 articles and 12 study protocols were analysed. Most included articles had a moderate risk of bias, as per the National Institute of Health Quality Assessment Tool for Observational and Cross-Sectional Studies. The accuracy of algorithmic models to detect SARS-CoV-2 infection varied greatly (area under the curve 0·52-0·92). An algorithm's ability to detect presymptomatic infection varied greatly (from 20% to 88% of cases), from 14 days to 1 day before symptom onset. Increased heart rate was most frequently associated with SARS-CoV-2 infection, along with increased skin temperature and respiratory rate. All 12 protocols described prospective studies that had yet to be completed or to publish their results, including two randomised controlled trials. The evidence surrounding wearable devices in the early detection of SARS-CoV-2 infection is still in an early stage, with a limited overall number of studies identified. However, these studies show promise for the early detection of SARS-CoV-2 infection. Large prospective, and preferably controlled, studies recruiting and retaining larger and more diverse populations are needed to provide further evidence.

A prospective, randomized, single-blinded, crossover trial to investigate the effect of a wearable device in addition to a daily symptom diary for the Remote Early Detection of SARS-CoV-2 infections (COVID-RED): a structured summary of a study protocol for a randomized controlled trial.

OBJECTIVES: It is currently thought that most-but not all-individuals infected with SARS-CoV-2 develop symptoms, but the infectious period starts on average 2 days before the first overt symptoms appear. It is estimated that pre- and asymptomatic individuals are responsible for more than half of all transmissions. By detecting infected individuals before they have overt symptoms, wearable devices could potentially and significantly reduce the proportion of transmissions by pre-symptomatic individuals. Using laboratory-confirmed SARS-CoV-2 infections (detected via serology tests [to determine if there are antibodies against the SARS-CoV-2 in the blood] or SARS-CoV-2 infection tests such as polymerase chain reaction [PCR] or antigen tests) as the gold standard, we will determine the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the following two algorithms to detect first time SARS-CoV-2 infection including early or asymptomatic infection: • The algorithm using Ava bracelet data when coupled with self-reported Daily Symptom Diary data (Wearable + Symptom Data Algo; experimental condition) • The algorithm using self-reported Daily Symptom Diary data alone (Symptom Only Algo; control condition) In addition, we will determine which of the two algorithms has superior performance characteristics for detecting SARS-CoV-2 infection including early or asymptomatic infection as confirmed by SARS-CoV-2 virus testing. TRIAL DESIGN: The trial is a randomized, single-blinded, two-period, two-sequence crossover trial. The study will start with an initial learning phase (maximum of 3 months), followed by period 1 (3 months) and period 2 (3 months). Subjects entering the study at the end of the recruitment period may directly start with period 1 and will not be part of the learning phase. Each subject will undergo the experimental condition (the Wearable + Symptom Data Algo) in either period 1 or period 2 and the control condition (Symptom Only Algo) in the other period. The order will be randomly assigned, resulting in subjects being allocated 1:1 to either sequence 1 (experimental condition first) or sequence 2 (control condition first). Based on demographics, medical history and/or profession, each subject will be stratified at baseline into a high-risk and normal-risk group within each sequence. PARTICIPANTS: The trial will be conducted in the Netherlands. A target of 20,000 subjects will be enrolled. Based on demographics, medical history and/or profession, each subject will be stratified at baseline into a high-risk and normal-risk group within each sequence. This results in approximately 6500 normal-risk individuals and 3500 high-risk individuals per sequence. Subjects will be recruited from previously studied cohorts as well as via public campaigns and social media. All data for this study will be collected remotely through the Ava COVID-RED app, the Ava bracelet, surveys in the COVID-RED web portal and self-sampling serology and PCR kits. More information on the study can be found in www.covid-red.eu . During recruitment, subjects will be invited to visit the COVID-RED web portal. After successfully completing the enrolment questionnaire, meeting eligibility criteria and indicating interest in joining the study, subjects will receive the subject information sheet and informed consent form. Subjects can enrol in COVID-RED if they comply with the following inclusion and exclusion criteria: Inclusion criteria: • Resident of the Netherlands • At least 18 years old • Informed consent provided (electronic) • Willing to adhere to the study procedures described in the protocol • Must have a smartphone that runs at least Android 8.0 or iOS 13.0 operating systems and is active for the duration of the study (in the case of a change of mobile number, the study team should be notified) • Be able to read, understand and write Dutch Exclusion criteria: • Previous positive SARS-CoV-2 test result (confirmed either through PCR/antigen or antibody tests; self-reported) • Current suspected (e.g. waiting for test result) COVID-19 infection or symptoms of a COVID-19 infection (self-reported) • Participating in any other COVID-19 clinical drug, vaccine or medical device trial (self-reported) • Electronic implanted device (such as a pacemaker; self-reported) • Pregnant at the time of informed consent (self-reported) • Suffering from cholinergic urticaria (per the Ava bracelet's user manual; self-reported) • Staff involved in the management or conduct of this study INTERVENTION AND COMPARATOR: All subjects will be instructed to complete the Daily Symptom Diary in the Ava COVID-RED app daily, wear their Ava bracelet each night and synchronize it with the app each day for the entire period of study participation. Provided with wearable sensor and/or self-reported symptom data within the last 24 h, the Ava COVID-RED app's underlying algorithms will provide subjects with a real-time indicator of their overall health and well-being. Subjects will see one of three messages, notifying them that no seeming deviations in symptoms and/or physiological parameters have been detected; some changes in symptoms and/or physiological parameters have been detected and they should self-isolate; or alerting them that deviations in their symptoms and/or physiological parameters could be suggestive of a potential COVID-19 infection and to seek additional testing. We will assess the intraperson performance of the algorithms in the experimental condition (Wearable + Symptom Data Algo) and control conditions (Symptom Only Algo). Note that both algorithms will also instruct to seek testing when any SARS-CoV-2 symptoms are reported in line with those defined by the Dutch national institute for public health and the environment 'Rijksinstituut voor Volksgezondheid en Milieu' (RIVM) guidelines. MAIN OUTCOMES: The trial will evaluate the use and performance of the Ava COVID-RED app and Ava bracelet, which uses sensors to measure breathing rate, pulse rate, skin temperature and heart rate variability for the purpose of early and asymptomatic detection and monitoring of SARS-CoV-2 in general and high-risk populations. Using laboratory-confirmed SARS-CoV-2 infections (detected via serology tests, PCR tests and/or antigen tests) as the gold standard, we will determine the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for each of the following two algorithms to detect first-time SARS-CoV-2 infection including early or asymptomatic infection: the algorithm using Ava bracelet data when coupled with the self-reported Daily Symptom Diary data and the algorithm using self-reported Daily Symptom Diary data alone. In addition, we will determine which of the two algorithms has superior performance characteristics for detecting SARS-CoV-2 infection including early or asymptomatic infection as confirmed by SARS-CoV-2 virus testing. The protocol contains an additional twenty secondary and exploratory objectives which address, among others, infection incidence rates, health resource utilization, symptoms reported by SARS-CoV-2-infected participants and the rate of breakthrough and asymptomatic SARS-CoV-2 infections among individuals vaccinated against COVID-19. PCR or antigen testing will occur when the subject receives a notification from the algorithm to seek additional testing. Subjects will be advised to get tested via the national testing programme and report the testing result in the Ava COVID-RED app and a survey. If they cannot obtain a test via the national testing programme, they will receive a nasal swab self-sampling kit at home, and the sample will be tested by PCR in a trial-affiliated laboratory. In addition, all subjects will be asked to take a capillary blood sample at home at baseline (between month 0 and 3.5 months after the start of subject recruitment), at the end of the learning phase (month 3; note that this sampling moment is skipped if a subject entered the study at the end of the recruitment period), period 1 (month 6) and period 2 (month 9). These samples will be used for SARS-CoV-2-specific antibody testing in a trial-affiliated laboratory, differentiating between antibodies resulting from a natural infection and antibodies resulting from COVID-19 vaccination (as vaccination will gradually be rolled out during the trial period). Baseline samples will only be analysed if the sample collected at the end of the learning phase is positive, or if the subject entered the study at the end of the recruitment period, and samples collected at the end of period 1 will only be analysed if the sample collected at the end of period 2 is positive. When subjects obtain a positive PCR/antigen or serology test result during the study, they will continue to be in the study but will be moved into a so-called COVID-positive mode in the Ava COVID-RED app. This means that they will no longer receive recommendations from the algorithms but can still contribute and track symptom and bracelet data. The primary analysis of the main objective will be executed using the data collected in period 2 (months 6 through 9). Within this period, serology tests (before and after period 2) and PCR/antigen tests (taken based on recommendations by the algorithms) will be used to determine if a subject was infected with SARS-CoV-2 or not. Within this same time period, it will be determined if the algorithms gave any recommendations for testing. The agreement between these quantities will be used to evaluate the performance of the algorithms and how these compare between the study conditions. RANDOMIZATION: All eligible subjects will be randomized using a stratified block randomization approach with an allocation ratio of 1:1 to one of two sequences (experimental condition followed by control condition or control condition followed by experimentalcondition). Based on demographics, medical history and/or profession, each subject will be stratified at baseline into a high-risk and normal-risk group within each sequence, resulting in approximately equal numbers of high-risk and normal-risk individuals between the sequences. BLINDING (MASKING): In this study, subjects will be blinded to the study condition and randomization sequence. Relevant study staff and the device manufacturer will be aware of the assigned sequence. The subject will wear the Ava bracelet and complete the Daily Symptom Diary in the Ava COVID-RED app for the full duration of the study, and they will not know if the feedback they receive about their potential infection status will only be based on the data they entered in the Daily Symptom Diary within the Ava COVID-RED app or based on both the data from the Daily Symptom Diary and the Ava bracelet. NUMBERS TO BE RANDOMIZED (SAMPLE SIZE): A total of 20,000 subjects will be recruited and randomized 1:1 to either sequence 1 (experimental condition followed by control condition) or sequence 2 (control condition followed by experimental condition), taking into account their risk level. This results in approximately 6500 normal-risk and 3500 high-risk individuals per sequence. TRIAL STATUS: Protocol version: 3.0, dated May 3, 2021. Start of recruitment: February 19, 2021. End of recruitment: June 3, 2021. End of follow-up (estimated): November 2021 TRIAL REGISTRATION: The Netherlands Trial Register on the 18th of February, 2021 with number NL9320 ( https://www.trialregister.nl/trial/9320 ) FULL PROTOCOL: The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this letter serves as a summary of the key elements of the full protocol.

Cost-Effectiveness of Lower Extremity Nerve Decompression Surgery in the Prevention of Ulcers and Amputations: A Markov Analysis.

BACKGROUND: The costs and health effects associated with lower extremity complications in diabetes mellitus are an increasing burden to society. In selected patients, lower extremity nerve decompression is able to reduce symptoms of neuropathy and the concomitant risks of diabetic foot ulcers and amputations. To estimate the health and economic effects of this type of surgery, the cost-effectiveness of this intervention compared to current nonsurgical care was studied. METHODS: To estimate the incremental cost-effectiveness of lower extremity nerve decompression over a 10-year period, a Markov model was developed to simulate the onset and progression of diabetic foot disease in patients with diabetes and neuropathy who underwent lower extremity nerve decompression surgery, compared to a group undergoing current nonsurgical care. Mean survival time, health-related quality of life, presence or risk of lower extremity complications, and in-hospital costs were the outcome measures assessed. Data from the Rotterdam Diabetic Foot Study were used as current care, complemented with information from international studies on the epidemiology of diabetic foot disease, resource use, and costs, to feed the model. RESULTS: Lower extremity nerve decompression surgery resulted in improved life expectancy (88,369.5 life-years versus 86,513.6 life-years), gain of quality-adjusted life-years (67,652.5 versus 64,082.3), and reduced incidence of foot complications compared to current care (490 versus 1087). The incremental cost-effectiveness analysis was -€59,279.6 per quality-adjusted life-year gained, which is below the Dutch critical threshold of less than €80,000 per quality-adjusted life-year. CONCLUSIONS: Decompression surgery of lower extremity nerves improves survival, reduces diabetic foot complications, and is cost saving and cost-effective compared with current care, suggesting considerable socioeconomic benefit for society.

A prospective, randomized, single-blinded, crossover trial to investigate the effect of a wearable device in addition to a daily symptom diary for the remote early detection of SARS-CoV-2 infections (COVID-RED): a structured summary of a study protocol for a randomized controlled trial.

OBJECTIVES: It is currently thought that most-but not all-individuals infected with SARS-CoV-2 develop symptoms, but that the infectious period starts on average two days before the first overt symptoms appear. It is estimated that pre- and asymptomatic individuals are responsible for more than half of all transmissions. By detecting infected individuals before they have overt symptoms, wearable devices could potentially and significantly reduce the proportion of transmissions by pre-symptomatic individuals. Using laboratory-confirmed SARS-CoV-2 infections (detected via serology tests [to determine if there are antibodies against the SARS-CoV-2 in the blood] or SARS-CoV-2 infection tests such as polymerase chain reaction [PCR] or antigen tests) as the gold standard, we will determine the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the following two algorithms to detect first time SARS-CoV-2 infection including early or asymptomatic infection: the algorithm using Ava bracelet data when coupled with self-reported Daily Symptom Diary data (Wearable + Symptom Data Algo; experimental condition) the algorithm using self-reported Daily Symptom Diary data alone (Symptom Only Algo; control condition) In addition, we will determine which of the two algorithms has superior performance characteristics for detecting SARS-CoV-2 infection including early or asymptomatic infection as confirmed by SARS-CoV-2 virus testing. TRIAL DESIGN: The trial is a randomized, single-blinded, two-period, two-sequence crossover trial. All subjects will participate in an initial Learning Phase (varying from 2 weeks to 3 months depending on enrolment date), followed by two contiguous 3-month test phases, Period 1 and Period 2. Each subject will undergo the experimental condition (the Wearable + Symptom Data Algo) in one of these periods and the control condition (Symptom Only Algo) in the other period. The order will be randomly assigned, resulting in subjects being allocated 1:1 to either Sequence 1 (experimental condition first) or Sequence 2 (control condition first). Based on demographics, medical history and/or profession, each subject will be stratified at baseline into a high-risk and normal-risk group within each sequence. PARTICIPANTS: The trial will be conducted in the Netherlands. A target of 20,000 subjects will be enrolled. Based on demographics, medical history and/or profession, each subject will be stratified at baseline into a high-risk and normal-risk group within each sequence. This results in approximately 6,500 normal-risk individuals and 3,500 high-risk individuals per sequence. Subjects will be recruited from previously studied cohorts as well as via public campaigns and social media. All data for this study will be collected remotely through the Ava COVID-RED app, the Ava bracelet, surveys in the COVID-RED web portal, and self-sampling serology and PCR kits. During recruitment, subjects will be invited to visit the COVID-RED web portal ( www.covid-red.eu ). After successfully completing the enrolment questionnaire, meeting eligibility criteria and indicating interest in joining the study, subjects will receive the subject information sheet and informed consent form. Subjects can enrol in COVID-RED if they comply with the following inclusion and exclusion criteria. INCLUSION CRITERIA: Resident of the Netherlands At least 18 years old Informed consent provided (electronic) Willing to adhere to the study procedures described in the protocol Must have a smartphone that runs at least Android 8.0 or iOS 13.0 operating systems and is active for the duration of the study (in the case of a change of mobile number, study team should be notified) Be able to read, understand and write Dutch Exclusion criteria: Previous positive SARS-CoV-2 test result (confirmed either through PCR/antigen or antibody tests; self-reported) Previously received a vaccine developed specifically for COVID-19 or in possession of an appointment for vaccination in the near future (self-reported) Current suspected (e.g., waiting for test result) COVID-19 infection or symptoms of a COVID-19 infection (self-reported) Participating in any other COVID-19 clinical drug, vaccine, or medical device trial (self-reported) Electronic implanted device (such as a pacemaker; self-reported) Pregnant at time of informed consent (self-reported) Suffering from cholinergic urticaria (per the Ava bracelet's User Manual; self-reported) Staff involved in the management or conduct of this study INTERVENTION AND COMPARATOR: All subjects will be instructed to complete the Daily Symptom Diary in the Ava COVID-RED app daily, wear their Ava bracelet each night and synchronise it with the app each day for the entire period of study participation. Provided with wearable sensor and/or self-reported symptom data within the last 24 hours, the Ava COVID-RED app's underlying algorithms will provide subjects with a real-time indicator of their overall health and well-being. Subjects will see one of three messages, notifying them that: no seeming deviations in symptoms and/or physiological parameters have been detected; some changes in symptoms and/or physiological parameters have been detected and they should self-isolate; or alerting them that deviations in their symptoms and/or physiological parameters could be suggestive of a potential COVID-19 infection and to seek additional testing. We will assess intraperson performance of the algorithms in the experimental condition (Wearable + Symptom Data Algo) and control conditions (Symptom Only Algo). MAIN OUTCOMES: The trial will evaluate the use and performance of the Ava COVID-RED app and Ava bracelet, which uses sensors to measure breathing rate, pulse rate, skin temperature, and heart rate variability for the purpose of early and asymptomatic detection and monitoring of SARS-CoV-2 in general and high-risk populations. Using laboratory-confirmed SARS-CoV-2 infections (detected via serology tests, PCR tests and/or antigen tests) as the gold standard, we will determine the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for each of the following two algorithms to detect first-time SARS-CoV-2 infection including early or asymptomatic infection: the algorithm using Ava Bracelet data when coupled with the self-reported Daily Symptom Diary data, and the algorithm using self-reported Daily Symptom Diary data alone. In addition, we will determine which of the two algorithms has superior performance characteristics for detecting SARS-CoV-2 infection including early or asymptomatic infection as confirmed by SARS-CoV-2 virus testing. The protocol contains an additional seventeen secondary outcomes which address infection incidence rates, health resource utilization, symptoms reported by SARS-CoV-2 infected participants, and the rate of breakthrough and asymptomatic SARS-CoV-2 infections among individuals vaccinated against COVID-19. PCR or antigen testing will occur when the subject receives a notification from the algorithm to seek additional testing. Subjects will be advised to get tested via the national testing programme, and report the testing result in the Ava COVID-RED app and a survey. If they cannot obtain a test via the national testing programme, they will receive a nasal swab self-sampling kit at home, and the sample will be tested by PCR in a trial-affiliated laboratory. In addition, all subjects will be asked to take a capillary blood sample at home at baseline (Month 0), and at the end of the Learning Phase (Month 3), Period 1 (Month 6) and Period 2 (Month 9). These samples will be used for SARS-CoV-2-specific antibody testing in a trial-affiliated laboratory, differentiating between antibodies resulting from a natural infection and antibodies resulting from COVID-19 vaccination (as vaccination will gradually be rolled out during the trial period). Baseline samples will only be analysed if the sample collected at the end of the Learning Phase is positive, and samples collected at the end of Period 1 will only be analysed if the sample collected at the end of Period 2 is positive. When subjects obtain a positive PCR/antigen or serology test result during the study, they will continue to be in the study but will be moved into a so-called "COVID-positive" mode in the Ava COVID-RED app. This means that they will no longer receive recommendations from the algorithms but can still contribute and track symptom and bracelet data. The primary analysis of the main objective will be executed using data collected in Period 2 (Month 6 through 9). Within this period, serology tests (before and after Period 2) and PCR/antigen tests (taken based on recommendations by the algorithms) will be used to determine if a subject was infected with SARS-CoV-2 or not. Within this same time period, it will be determined if the algorithms gave any recommendations for testing. The agreement between these quantities will be used to evaluate the performance of the algorithms and how these compare between the study conditions. RANDOMISATION: All eligible subjects will be randomized using a stratified block randomization approach with an allocation ratio of 1:1 to one of two sequences (experimental condition followed by control condition or control condition followed by experimental condition). Based on demographics, medical history and/or profession, each subject will be stratified at baseline into a high-risk and normal-risk group within each sequence, resulting in equal numbers of high-risk and normal-risk individuals between the sequences. BLINDING (MASKING): In this study, subjects will be blinded as to study condition and randomization sequence. Relevant study staff and the device manufacturer will be aware of the assigned sequence. The subject will wear the Ava bracelet and complete the Daily Symptom Diary in the Ava COVID-RED appfor the full duration of the study, and they will not know if the feedback they receive about their potential infection status will only be based on data they entered in the Daily Symptom Diary within the Ava COVID-RED app or based on both the data from the Daily Symptom Diary and the Ava bracelet. NUMBERS TO BE RANDOMISED (SAMPLE SIZE): 20,000 subjects will be recruited and randomized 1:1 to either Sequence 1 (experimental condition followed by control condition) or Sequence 2 (control condition followed by experimental condition), taking into account their risk level. This results in approximately 6,500 normal-risk and 3,500 high-risk individuals per sequence. TRIAL STATUS: Protocol version: 1.2, dated January 22nd, 2021 Start of recruitment: February 22nd, 2021 End of recruitment (estimated): April 2021 End of follow-up (estimated): December 2021 TRIAL REGISTRATION: The trial has been registered at the Netherlands Trial Register on the 18th of February, 2021 with number NL9320 ( https://www.trialregister.nl/trial/9320 ) FULL PROTOCOL: The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.

Validation of cardiovascular outcomes and risk factors in the Clinical Practice Research Datalink in the United Kingdom.

PURPOSE: Strategies to identify and validate acute myocardial infarction (AMI) and stroke in primary-care electronic records may impact effect measures, but to an unknown extent. Additionally, the validity of cardiovascular risk factors that could act as confounders in studies on those endpoints has not been thoroughly assessed in the United Kingdom Clinical Practice Research Datalink's (CPRD's) GOLD database. We explored the validity of algorithms to identify cardiovascular outcomes and risk factors and evaluated different outcome-identification strategies using these algorithms for estimation of adjusted incidence rate ratios (IRRs). METHODS: First, we identified AMI, stroke, smoking, obesity, and menopausal status in a cohort treated for overactive bladder by applying computerized algorithms to primary care medical records (2004-2012). We validated these cardiovascular outcomes and risk factors with physician questionnaires (gold standard for this analysis). Second, we estimated IRRs for AMI and stroke using algorithm-identified and questionnaire-confirmed cases, comparing these with IRRs from cases identified through linkage with hospitalization/mortality data (best estimate). RESULTS: For AMI, the algorithm's positive predictive value (PPV) was >90%. Initial algorithms for stroke performed less well because of inclusion of codes for prevalent stroke; algorithm refinement increased PPV to 80% but decreased sensitivity by 20%. Algorithms for smoking and obesity were considered valid. IRRs based on questionnaire-confirmed cases only were closer to IRRs estimated from hospitalization/mortality data than IRRs from algorithm-identified cases. CONCLUSIONS: AMI, stroke, smoking, obesity, and postmenopausal status can be accurately identified in CPRD. Physician questionnaire-validated AMI and stroke cases yield IRRs closest to the best estimate.

Author Correction: Introducing PIONEER: a project to harness big data in prostate cancer research.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Introducing PIONEER: a project to harness big data in prostate cancer research.

Prostate Cancer Diagnosis and Treatment Enhancement Through the Power of Big Data in Europe (PIONEER) is a European network of excellence for big data in prostate cancer, consisting of 32 private and public stakeholders from 9 countries across Europe. Launched by the Innovative Medicines Initiative 2 and part of the Big Data for Better Outcomes Programme (BD4BO), the overarching goal of PIONEER is to provide high-quality evidence on prostate cancer management by unlocking the potential of big data. The project has identified critical evidence gaps in prostate cancer care, via a detailed prioritization exercise including all key stakeholders. By standardizing and integrating existing high-quality and multidisciplinary data sources from patients with prostate cancer across different stages of the disease, the resulting big data will be assembled into a single innovative data platform for research. Based on a unique set of methodologies, PIONEER aims to advance the field of prostate cancer care with a particular focus on improving prostate-cancer-related outcomes, health system efficiency by streamlining patient management, and the quality of health and social care delivered to all men with prostate cancer and their families worldwide.

The Association of Tacrolimus Formulation Switching with Trough Concentration Variability: A Retrospective Cohort Study of Tacrolimus Use Post-Kidney Transplantation Based on National Drug Code (NDC) Numbers.

INTRODUCTION: It was hypothesized that patients experiencing at least one tacrolimus formulation switch may require more frequent therapeutic drug monitoring, subsequent dose adjustments, and a potential for untoward clinical outcomes than patients who remain on a single formulation. METHODS: Eligible patients were adult kidney transplant recipients with stable renal function at month 3 post-transplant and no evidence of acute rejection, receiving an oral, tacrolimus-based regimen. Patients were categorized into two groups (fixed or variable formulation) using the US National Drug Code (NDC) on the basis of tacrolimus formulation usage over the 12-month period. RESULTS: A total of 305 patients were enrolled from four US transplant centers; 44 (14.4%) received multiple formulations and 261 (85.6%) received a single formulation. Mean number of tacrolimus dose adjustments and mean cumulative milligram dose change were not statistically different between the two groups. Mean trough-to-dose ratio, frequency of trough level measurements, and mean number of excursions above 120% or below 80% of the patient's mean trough concentration were significantly higher in the variable compared to the fixed formulation group. CONCLUSION: A variable tacrolimus formulation regimen was associated with a higher frequency of trough level measurements and a greater number of excursions in trough levels compared with continuing on a fixed formulation regimen of tacrolimus in this retrospective chart review study. FUNDING: Astellas Pharma Global Development, Inc. Plain language summary available for this article.

Cardiovascular safety of mirabegron: analysis of an integrated clinical trial database of patients with overactive bladder syndrome.

Mirabegron is a ß3-adrenoreceptor agonist used for the treatment of overactive bladder syndrome. We evaluated the cardiovascular (CV) safety of mirabegron using pooled data from 13 studies. The analysis included 13,396 patients who received ≥1 dose of mirabegron (25 mg/50 mg) or comparator antimuscarinics (solifenacin 2.5 mg/5 mg/10 mg or tolterodine extended release 4 mg) as monotherapies, or placebo. We focused on changes in blood pressure and CV adverse events. Baseline CV risk factors had an imbalanced effect on subsequent CV adverse events. The frequency of these adverse events was comparable for overactive bladder treatments (0.4%-1.5%) and placebo (0.9%). Changes from baseline in blood pressure were similar for the overactive bladder treatments and placebo, and did not confer increased risk of CV adverse events. Multivariate analyses demonstrated that baseline CV risk factors (history of arrhythmia, history of coronary artery disease, and history of stroke/transient ischemic attack) were significantly associated with subsequent CV adverse events in the trials, whereas overactive bladder therapies were not. In conclusion, using an analytical approach to carefully control for CV characteristics of patients in these trials demonstrated no evidence of increased CV risk for mirabegron or antimuscarinics over placebo in the treatment of overactive bladder syndrome.

Healthcare utilization and costs with fixed-source versus variable-source tacrolimus in patients receiving a kidney transplant.

AIMS: Switching drug manufacturers in transplant patients may require an increased intensity of therapeutic monitoring, leading to additional healthcare visits, associated laboratory tests, and perhaps hospitalizations. As real-world studies examining the interchangeability of tacrolimus from different manufacturers are limited, the purpose of this study was to examine the healthcare resource utilization (HRU) and economic impact of tacrolimus-switching in kidney transplantation. MATERIALS AND METHODS: This cross-sectional, retrospective study examined HRU and healthcare costs (HCCs) among patients with a kidney transplant who were prescribed tacrolimus from fixed-source (FS) vs variable-source (VS) manufacturers using claims data from the large US health plan Humana from October 1, 2012, to December 31, 2013. RESULTS: Overall, 1,024 patients were identified (FS: n = 674, 66%; VS: n = 350, 34%). The number of therapeutic drug monitoring (TDM) events for the VS group was 13% greater than for the FS group after controlling for demographics, comorbidity score, and number of medications (incidence rate ratio = 1.13, p = .033). Adjusted total HCCs were 9% lower for VS (US$28,054 vs US$30,823, p = .045). In the unadjusted analysis, VS had greater emergency department (ED) utilization (45% vs 35%, p < .002). In the VS group, the mean (standard deviation [SD]) number of days from manufacturer switch to first outpatient visit was 23.8 (33.6), and the number of days (SD) to first TDM event was 43.6 (56.2). LIMITATIONS: Study limitations include the lack of availability of many transplant-specific variables within the Humana database, potential errors/omissions in claims coding, and restriction of cross-sectional data examination to a 1-year period. CONCLUSIONS: VS patients had greater TDM and lower total HCCs. Further research is warranted to understand the drivers of ED use among the VS group, and to determine factors associated with delayed TDM after regimen modification. Opportunities may exist to improve the quality of care for patients receiving immunosuppressant treatment with tacrolimus.

Variation in Cardiovascular Risk Related to Individual Antimuscarinic Drugs Used to Treat Overactive Bladder: A UK Cohort Study.

BACKGROUND: Blocking muscarinic receptors could have an effect on cardiac function, especially among elderly patients with overactive bladder (OAB). STUDY OBJECTIVE: To investigate the risk of cardiovascular (CV) events in users of antimuscarinic drugs to treat OAB. DESIGN, SETTING, AND PARTICIPANTS: Cohort study of new users of darifenacin, fesoterodine, oxybutynin, solifenacin, tolterodine, or trospium, 18 years or older, in the United Kingdom's Clinical Practice Research Datalink (CPRD), 2004-2012. OUTCOME MEASUREMENTS AND MAIN RESULTS: Using tolterodine as the reference, we estimated propensity-score-stratified incidence rate ratios (IRRs) for acute myocardial infarction, stroke, CV mortality, major adverse cardiac events (MACE, a combined end point of the previous three), and all-cause death for individual antimuscarinic drugs. The study cohort included 119,912 new users of OAB drugs. The mean age at cohort entry was 62 years, 70% were female, and the mean follow-up was 3.3 years. The adjusted IRR for MACE and current use of oxybutynin compared with current use of tolterodine was 1.14 (95% confidence interval [CI] 1.01-1.30). In contrast, the IRR was 0.65 (CI 0.56-0.76) for current use of solifenacin compared with tolterodine. In this study, performed with health care data, the distribution of risk factors was relatively similar across users of different OAB drugs and, although our analyses controlled for a range of measured potential confounders, residual confounding cannot be ruled out. CONCLUSIONS: In an observational comparative study of users of medications to treat OAB conducted in routine clinical practice, the risk for CV side effects was increased in users of oxybutynin and decreased in users of solifenacin compared with users of tolterodine.

Validation of Cancer Cases Using Primary Care, Cancer Registry, and Hospitalization Data in the United Kingdom.

BACKGROUND: In the United Kingdom, hospital or cancer registry data can be linked to electronic medical records for a subset of general practices and years. METHODS: We used Clinical Practice Research Datalink data (2004-2012) from patients treated for overactive bladder. We electronically identified provisional cases of 10 common cancers in General Practitioner Online Database data and validated them by medical profile review. In practices with linkage to Hospital Episodes Statistics and National Cancer Data Repository (2004-2010), we validated provisional cancer cases against these data sources. This linkage also let us identify additional cancer diagnoses in individuals without cancer diagnosis records in the General Practitioner Online Database. RESULTS: Among 50,840 patients, 1,486 provisional cancer cases were identified in the General Practitioner Online Database for 2004-2012. Medical profile review confirmed 93% of 661 cases in nonlinked practices (range, 100% of non-Hodgkin lymphomas and uterine cancer to 77% of skin melanomas) and 96% of 825 cases in linked practices (100% of kidney and uterine cancers to 92% of melanomas). In the subset of linked practices, for 2004-2010, 720 cases were confirmed, of which 68% were identifiable in the General Practitioner Online Database (range, 90% of breast to 36% of kidney cancers). CONCLUSIONS: Most cases of cancer identified electronically in the General Practitioner Online Database were confirmed. A substantial proportion of cases, especially of cancer types not typically managed by general practitioners, would be missed without Hospital Episodes Statistics and National Cancer Data Repository data (and are likely missed in nonlinked practices). See video abstract at, http://links.lww.com/EDE/B315. REGISTRATION (BEFORE STUDY CONDUCT): European Union electronic Register of Post-Authorisation Studies (EU PAS Registry) number EUPAS5529, http://www.encepp.eu/encepp/viewResource.htm?id=11107.

Comparison of cardiovascular events among treatments for overactive bladder: a Danish nationwide cohort study.

PURPOSE: The purpose of this study is to explore the cardiovascular safety of antimuscarinic drugs to treat overactive bladder (OAB) in Denmark. METHODS: This was a cohort study using data recorded in Danish registries from patients newly exposed to darifenacin, fesoterodine, oxybutynin, solifenacin, tolterodine, or trospium in 2004-2012. We estimated crude and standardized incidence rates (IRs) for acute myocardial infarction (AMI); stroke; cardiovascular mortality; major adverse cardiac events (MACE, a combined endpoint of the previous three outcomes); and all-cause death for the individual and combined drugs. We also estimated crude, standardized, and propensity score-stratified incidence rate ratios (IRRs) comparing individual antimuscarinic drugs to tolterodine as the reference. RESULTS: Among 72,917 new users of OAB drugs (mean age, 66 years; 60% women), the standardized IR (95% confidence interval) per 1000 person-years for current use of any OAB drug was 2.7 (2.5-2.9) for AMI, 1.3 (1.2-1.5) for stroke, 7.8 (7.5-8.1) for MACE, 4.8 (4.5-5.0) for cardiovascular mortality, and 15.2 (14.8-15.6) for all-cause mortality. Propensity score-stratified IRRs for current use (reference, tolterodine) were close to the null for all drugs and endpoints. CONCLUSIONS: We did not identify differences in the risk of cardiovascular events or mortality among users of individual antimuscarinic OAB drugs.

Epidemiological features of invasive mold infections among solid organ transplant recipients: PATH Alliance® registry analysis.

Epidemiological characteristics of 333 proven and probable invasive mould infections (IMIs) among solid organ transplant recipients (SOTRs) identified between 2004 and 2008 from the Prospective Antifungal Therapy Alliance (PATH) registry are presented. Liver transplant recipients (LTRs) had the lowest median time to IMIs (109 days; interquartile range [IQR] 24-611 days), the highest rate of disseminated disease (n/N = 18/33; 55%), and highest mortality (n/N = 21/33; 64%). Lung transplant recipients had highest median time to IMIs (486 days; IQR 117-1358 days) and lowest mortality (n/N = 31/184; 17%). Complete or partial response at week 12 in patients with invasive aspergillosis (IA) was 67% (n/N = 189/281), and 41% (n/N = 9/22) in mucormycosis patients. In the composite outcome of death or no response to therapy, LTRs had the worst outcome. Higher suspicion of mold infection and institution of appropriate antifungal prophylactic strategies are warranted, especially in high risk LTRs.