A method for intelligent allocation of diagnostic testing by leveraging data from commercial wearable devices: a case study on COVID-19.

Mass surveillance testing can help control outbreaks of infectious diseases such as COVID-19. However, diagnostic test shortages are prevalent globally and continue to occur in the US with the onset of new COVID-19 variants and emerging diseases like monkeypox, demonstrating an unprecedented need for improving our current methods for mass surveillance testing. By targeting surveillance testing toward individuals who are most likely to be infected and, thus, increasing the testing positivity rate (i.e., percent positive in the surveillance group), fewer tests are needed to capture the same number of positive cases. Here, we developed an Intelligent Testing Allocation (ITA) method by leveraging data from the CovIdentify study (6765 participants) and the MyPHD study (8580 participants), including smartwatch data from 1265 individuals of whom 126 tested positive for COVID-19. Our rigorous model and parameter search uncovered the optimal time periods and aggregate metrics for monitoring continuous digital biomarkers to increase the positivity rate of COVID-19 diagnostic testing. We found that resting heart rate (RHR) features distinguished between COVID-19-positive and -negative cases earlier in the course of the infection than steps features, as early as 10 and 5 days prior to the diagnostic test, respectively. We also found that including steps features increased the area under the receiver operating characteristic curve (AUC-ROC) by 7-11% when compared with RHR features alone, while including RHR features improved the AUC of the ITA model's precision-recall curve (AUC-PR) by 38-50% when compared with steps features alone. The best AUC-ROC (0.73 ± 0.14 and 0.77 on the cross-validated training set and independent test set, respectively) and AUC-PR (0.55 ± 0.21 and 0.24) were achieved by using data from a single device type (Fitbit) with high-resolution (minute-level) data. Finally, we show that ITA generates up to a 6.5-fold increase in the positivity rate in the cross-validated training set and up to a 4.5-fold increase in the positivity rate in the independent test set, including both symptomatic and asymptomatic (up to 27%) individuals. Our findings suggest that, if deployed on a large scale and without needing self-reported symptoms, the ITA method could improve the allocation of diagnostic testing resources and reduce the burden of test shortages.

A Method for Intelligent Allocation of Diagnostic Testing by Leveraging Data from Commercial Wearable Devices: A Case Study on COVID-19.

Mass surveillance testing can help control outbreaks of infectious diseases such as COVID-19. However, diagnostic test shortages are prevalent globally and continue to occur in the US with the onset of new COVID-19 variants, demonstrating an unprecedented need for improving our current methods for mass surveillance testing. By targeting surveillance testing towards individuals who are most likely to be infected and, thus, increasing testing positivity rate (i.e., percent positive in the surveillance group), fewer tests are needed to capture the same number of positive cases. Here, we developed an Intelligent Testing Allocation (ITA) method by leveraging data from the CovIdentify study (6,765 participants) and the MyPHD study (8,580 participants), including smartwatch data from 1,265 individuals of whom 126 tested positive for COVID-19. Our rigorous model and parameter search uncovered the optimal time periods and aggregate metrics for monitoring continuous digital biomarkers to increase the positivity rate of COVID-19 diagnostic testing. We found that resting heart rate features distinguished between COVID-19 positive and negative cases earlier in the course of the infection than steps features, as early as ten and five days prior to the diagnostic test, respectively. We also found that including steps features increased the area under the receiver operating characteristic curve (AUC-ROC) by 7-11% when compared with RHR features alone, while including RHR features improved the AUC of the ITA model's precision-recall curve (AUC-PR) by 38-50% when compared with steps features alone. The best AUC-ROC (0.73 ± 0.14 and 0.77 on the cross-validated training set and independent test set, respectively) and AUC-PR (0.55 ± 0.21 and 0.24) were achieved by using data from a single device type (Fitbit) with high-resolution (minute-level) data. Finally, we show that ITA generates up to a 6.5-fold increase in the positivity rate in the cross-validated training set and up to a 3-fold increase in the positivity rate in the independent test set, including both symptomatic and asymptomatic (up to 27%) individuals. Our findings suggest that, if deployed on a large scale and without needing self-reported symptoms, the ITA method could improve allocation of diagnostic testing resources and reduce the burden of test shortages.

Myasthenic crisis-induced Takotsubo cardiomyopathy in an elderly man: A case report of an underestimated but deadly combination.

BACKGROUND: Patients with myasthenia gravis (MG) are at a higher risk of developing Takotsubo cardiomyopathy (TTC), particularly during a myasthenic crisis. Myasthenic crisis-associated TTC occurs predominantly in women. In this case report, we present a man with metastasized prostate carcinoma who developed TTC after new-onset MG. CASE SUMMARY: An 81-year-old man with non-insulin dependent diabetes mellitus and metastasized prostate carcinoma presented with dyspnea. During primary assessment examination at the emergency department, there was evident blepharoptosis of his right eye. His electrocardiograms were suggestive of an acute anterior wall myocardial infarction, for which he underwent emergency coronary angiography. No obstructive coronary artery disease was found. During the coronary angiography, the patient developed respiratory failure and was admitted to the Intensive Care Unit for non-invasive respiratory support. The following day, diagnostic neostigmine test revealed a myasthenic crisis. Bedside echocardiography revealed left ventricular apical ballooning with a typical appearance of TTC. Despite the potentially reversible character of both MG and TTC, the patient and family requested an end of support in the Intensive Care Unit due to age and chronic malignancy with reduced quality of life in recent months after non-chemo-responding prostate carcinoma. The patient died soon after treatment withdrawal. CONCLUSION: Elderly men should be carefully evaluated for TTC when new-onset MG is diagnosed.

Oncolytic Virotherapy Blockade by Microglia and Macrophages Requires STAT1/3.

The first oncolytic virotherapy employing HSV-1 (oHSV-1) was approved recently by the FDA to treat cancer, but further improvements in efficacy are needed to eradicate challenging refractory tumors, such as glioblastomas (GBM). Microglia/macrophages comprising approximately 40% of a GBM tumor may limit virotherapeutic efficacy. Here, we show these cells suppress oHSV-1 growth in gliomas by internalizing the virus through phagocytosis. Internalized virus remained capable of expressing reporter genes while viral replication was blocked. Macrophage/microglia formed a nonpermissive OV barrier, preventing dissemination of oHSV-1 in the glioma mass. The deficiency in viral replication in microglial cells was associated with silencing of particular viral genes. Phosphorylation of STAT1/3 was determined to be responsible for suppressing oHSV-1 replication in macrophages/microglia. Treatment with the oxindole/imidazole derivative C16 rescued oHSV-1 replication in microglia/macrophages by inhibiting STAT1/3 activity. In the U87 xenograft model of GBM, C16 treatment overcame the microglia/macrophage barrier, thereby facilitating tumor regression without causing a spread of the virus to normal organs. Collectively, our results suggest a strategy to relieve a STAT1/3-dependent therapeutic barrier and enhance oHSV-1 oncolytic activity in GBM.Significance: These findings suggest a strategy to enhance the therapeutic efficacy of oncolytic virotherapy in glioblastoma. Cancer Res; 78(3); 718-30. ©2017 AACR.

Tumour-specific triple-regulated oncolytic herpes virus to target glioma.

Oncolytic herpes simplex virus type 1 (oHSV-1) therapy is an emerging treatment modality that selectively destroys cancer. Here we report use of a glioma specific HSV-1 amplicon virus (SU4-124 HSV-1) to selectively target tumour cells. To achieve transcriptional regulation of the SU4-124 HSV-1 virus, the promoter for the essential HSV-1 gene ICP4 was replaced with a tumour specific survivin promoter. Translational regulation was achieved by incorporating 5 copies of microRNA 124 target sequences into the 3'UTR of the ICP4 gene. Additionally, a 5'UTR of rat fibroblast growth factor -2 was added in front of the viral ICP4 gene open reading frame. Our results confirmed enhanced expression of survivin and eIF4E in different glioma cells and increased micro-RNA124 expression in normal human and mouse brain tissue. SU4-124 HSV-1 had an increased ICP4 expression and virus replication in different glioma cells compared to normal neuronal cells. SU4-124 HSV-1 exerted a strong antitumour effect against a panel of glioma cell lines. Intracranial injection of SU4-124 HSV-1 did not reveal any sign of toxicity on day 15 after the injection. Moreover, a significantly enhanced antitumour effect with the intratumourally injected SU4-124 HSV-1 virus was demonstrated in mice bearing human glioma U87 tumours, whereas viral DNA was almost undetectable in normal organs. Our study indicates that incorporation of multiple cancer-specific regulators in an HSV-1 system significantly enhances both cancer specificity and oncolytic activity.