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

It is time to define an organizational model for the prevention and management of infections along the surgical pathway : a worldwide cross-sectional survey

Background The objectives of the study were to investigate the organizational characteristics of acute care facilities worldwide in preventing and managing infections in surgery; assess participants' perception regarding infection prevention and control (IPC) measures, antibiotic prescribing practices, and source control; describe awareness about the global burden of antimicrobial resistance (AMR) and IPC measures; and determine the role of the Coronavirus Disease 2019 pandemic on said awareness. Methods A cross-sectional web-based survey was conducted contacting 1432 health care workers (HCWs) belonging to a mailing list provided by the Global Alliance for Infections in Surgery. The self-administered questionnaire was developed by a multidisciplinary team. The survey was open from May 22, 2021, and June 22, 2021. Three reminders were sent, after 7, 14, and 21 days. Results Three hundred four respondents from 72 countries returned a questionnaire, with an overall response rate of 21.2%. Respectively, 90.4% and 68.8% of participants stated their hospital had a multidisciplinary IPC team or a multidisciplinary antimicrobial stewardship team. Local protocols for antimicrobial therapy of surgical infections and protocols for surgical antibiotic prophylaxis were present in 76.6% and 90.8% of hospitals, respectively. In 23.4% and 24.0% of hospitals no surveillance systems for surgical site infections and no monitoring systems of used antimicrobials were implemented. Patient and family involvement in IPC management was considered to be slightly or not important in their hospital by the majority of respondents (65.1%). Awareness of the global burden of AMR among HCWs was considered very important or important by 54.6% of participants. The COVID-19 pandemic was considered by 80.3% of respondents as a very important or important factor in raising HCWs awareness of the IPC programs in their hospital. Based on the survey results, the authors developed 15 statements for several questions regarding the prevention and management of infections in surgery. The statements may be the starting point for designing future evidence-based recommendations. Conclusion Adequacy of prevention and management of infections in acute care facilities depends on HCWs behaviours and on the organizational characteristics of acute health care facilities to support best practices and promote behavioural change. Patient involvement in the implementation of IPC is still little considered. A debate on how operationalising a fundamental change to IPC, from being solely the HCWs responsibility to one that involves a collaborative relationship between HCWs and patients, should be opened.Peer reviewe

It is time to define an organizational model for the prevention and management of infections along the surgical pathway: a worldwide cross-sectional survey

Background The objectives of the study were to investigate the organizational characteristics of acute care facilities worldwide in preventing and managing infections in surgery; assess participants' perception regarding infection prevention and control (IPC) measures, antibiotic prescribing practices, and source control; describe awareness about the global burden of antimicrobial resistance (AMR) and IPC measures; and determine the role of the Coronavirus Disease 2019 pandemic on said awareness. Methods A cross-sectional web-based survey was conducted contacting 1432 health care workers (HCWs) belonging to a mailing list provided by the Global Alliance for Infections in Surgery. The self-administered questionnaire was developed by a multidisciplinary team. The survey was open from May 22, 2021, and June 22, 2021. Three reminders were sent, after 7, 14, and 21 days. Results Three hundred four respondents from 72 countries returned a questionnaire, with an overall response rate of 21.2%. Respectively, 90.4% and 68.8% of participants stated their hospital had a multidisciplinary IPC team or a multidisciplinary antimicrobial stewardship team. Local protocols for antimicrobial therapy of surgical infections and protocols for surgical antibiotic prophylaxis were present in 76.6% and 90.8% of hospitals, respectively. In 23.4% and 24.0% of hospitals no surveillance systems for surgical site infections and no monitoring systems of used antimicrobials were implemented. Patient and family involvement in IPC management was considered to be slightly or not important in their hospital by the majority of respondents (65.1%). Awareness of the global burden of AMR among HCWs was considered very important or important by 54.6% of participants. The COVID-19 pandemic was considered by 80.3% of respondents as a very important or important factor in raising HCWs awareness of the IPC programs in their hospital. Based on the survey results, the authors developed 15 statements for several questions regarding the prevention and management of infections in surgery. The statements may be the starting point for designing future evidence-based recommendations. Conclusion Adequacy of prevention and management of infections in acute care facilities depends on HCWs behaviours and on the organizational characteristics of acute health care facilities to support best practices and promote behavioural change. Patient involvement in the implementation of IPC is still little considered. A debate on how operationalising a fundamental change to IPC, from being solely the HCWs responsibility to one that involves a collaborative relationship between HCWs and patients, should be opened

Ten golden rules for optimal antibiotic use in hospital settings: the WARNING call to action

Antibiotics are recognized widely for their benefits when used appropriately. However, they are often used inappropriately despite the importance of responsible use within good clinical practice. Effective antibiotic treatment is an essential component of universal healthcare, and it is a global responsibility to ensure appropriate use. Currently, pharmaceutical companies have little incentive to develop new antibiotics due to scientific, regulatory, and financial barriers, further emphasizing the importance of appropriate antibiotic use. To address this issue, the Global Alliance for Infections in Surgery established an international multidisciplinary task force of 295 experts from 115 countries with different backgrounds. The task force developed a position statement called WARNING (Worldwide Antimicrobial Resistance National/International Network Group) aimed at raising awareness of antimicrobial resistance and improving antibiotic prescribing practices worldwide. The statement outlined is 10 axioms, or “golden rules,” for the appropriate use of antibiotics that all healthcare workers should consistently adhere in clinical practice

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

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

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

Identifying biomarkers of differential chemotherapy response in TNBC patient-derived xenografts with a CTD/WGCNA approach

Summary: Although systemic chemotherapy remains the standard of care for TNBC, even combination chemotherapy is often ineffective. The identification of biomarkers for differential chemotherapy response would allow for the selection of responsive patients, thus maximizing efficacy and minimizing toxicities. Here, we leverage TNBC PDXs to identify biomarkers of response. To demonstrate their ability to function as a preclinical cohort, PDXs were characterized using DNA sequencing, transcriptomics, and proteomics to show consistency with clinical samples. We then developed a network-based approach (CTD/WGCNA) to identify biomarkers of response to carboplatin (MSI1, TMSB15A, ARHGDIB, GGT1, SV2A, SEC14L2, SERPINI1, ADAMTS20, DGKQ) and docetaxel (c, MAGED4, CERS1, ST8SIA2, KIF24, PARPBP). CTD/WGCNA multigene biomarkers are predictive in PDX datasets (RNAseq and Affymetrix) for both taxane- (docetaxel or paclitaxel) and platinum-based (carboplatin or cisplatin) response, thereby demonstrating cross-expression platform and cross-drug class robustness. These biomarkers were also predictive in clinical datasets, thus demonstrating translational potential