Comparing the efficacy of tocilizumab with corticosteroid therapy in treating COVID-19 patients: a systematic review and meta-analysis.

PURPOSE: Tocilizumab has shown equivocal outcomes in reducing mortality in COVID-19. The corticosteroids appear to be an affordable alternative to tocilizumab. This study aims to estimate the efficacy of tocilizumab and the corticosteroids particularly dexamethasone and methylprednisolone and to identify possible determinants of their efficacy. METHODS: Five electronic databases were searched for studies involving tocilizumab, dexamethasone, and methylprednisolone in treating COVID-19. We included case-control and randomized or partially randomized trials. Meta-regression for patient baseline characteristics, co-medications, and tocilizumab dose regimens was performed to identify contributing factors to drug efficacy. RESULTS: Thirteen randomized controlled trials (RCTs) and twenty-four case-control studies were included in our meta-analysis involving 18,702 patients. Meta-analysis among the RCTs showed that a summary estimate favoring mortality reduction (OR 0.71, 95%CI 0.55 - 0.92) contributed mainly by tocilizumab and dexamethasone. Among case-control studies, meta-analysis showed mortality reduction (OR 0.52, 95%CI 0.36 - 0.75) contributed by tocilizumab and tocilizumab-methylprednisolone combination. Methylprednisolone alone did not reduce mortality except for one study involving high dose pulse therapy. Meta-analysis also found that all three drugs did not significantly reduce mechanical ventilation (OR 0.72, 95%CI 0.32 - 1.60). CONCLUSION: Tocilizumab and dexamethasone emerge as viable options in reducing mortality in severe COVID-19 patients. A tocilizumab-corticosteroid combination strategy may improve therapeutic outcome in cases where single therapy fails.

A non-printed integrated-circuit textile for wireless theranostics.

While the printed circuit board (PCB) has been widely considered as the building block of integrated electronics, the world is switching to pursue new ways of merging integrated electronic circuits with textiles to create flexible and wearable devices. Herein, as an alternative for PCB, we described a non-printed integrated-circuit textile (NIT) for biomedical and theranostic application via a weaving method. All the devices are built as fibers or interlaced nodes and woven into a deformable textile integrated circuit. Built on an electrochemical gating principle, the fiber-woven-type transistors exhibit superior bending or stretching robustness, and were woven as a textile logical computing module to distinguish different emergencies. A fiber-type sweat sensor was woven with strain and light sensors fibers for simultaneously monitoring body health and the environment. With a photo-rechargeable energy textile based on a detailed power consumption analysis, the woven circuit textile is completely self-powered and capable of both wireless biomedical monitoring and early warning. The NIT could be used as a 24/7 private AI "nurse" for routine healthcare, diabetes monitoring, or emergencies such as hypoglycemia, metabolic alkalosis, and even COVID-19 patient care, a potential future on-body AI hardware and possibly a forerunner to fabric-like computers.