The COVID-19 pandemic has strained testing capabilities worldwide. There is an urgent need to find economical and scalable ways to test more people. We present Tapestry, a novel quantitative nonadaptive pooling scheme to test many samples using only a few tests. The underlying molecular diagnostic test is any real-time RT-PCR diagnostic panel approved for the detection of the SARS-CoV-2 virus. In cases where most samples are negative for the virus, Tapestry accurately identifies the status of each individual sample with a single round of testing in fewer tests than simple two-round pooling. We also present a companion Android application BYOM Smart Testing which guides users through the pipetting steps required to perform the combinatorial pooling. The results of the pooled tests can be fed into the application to recover the status and estimated viral load for each individual sample. NOTE: This protocol has been validated with in vitro experiments that used synthetic RNA and DNA fragments and additionally, its expected behavior has been confirmed using computer simulations. Validation with clinical samples is ongoing. We are looking for clinical collaborators with access to patient samples. Please contact the corresponding author if you wish to validate this protocol on clinical samples.

Objectives: Determine the variation in outcomes and respiratory mechanics between the subjects who are intubated earlier versus later in their coronavirus disease 2019 course. Design: Retrospective cohort study. Setting: Northwestern Memorial Hospital ICUs. Patients: All patients intubated for coronavirus disease 2019 between March 2020 and June 2020. Interventions: Patients were stratified by time to intubation: 30 subjects were intubated 4–24 hours after presentation and 24 subjects were intubated 5–10 days after presentation. Baseline characteristics, hospitalization, ventilator mechanics, and outcomes were extracted and analyzed. Ten clinically available CT scans were manually reviewed to identify evidence of pulmonary vascular thrombosis and intussusceptive angiogenesis. Measurements and Main Results: Median time from symptom onset to intubation was significantly different between the early and late intubation cohorts, with the latter being intubated later in the course of their illness (7.9 vs 11.8 d; p = 0.04). The early intubation cohort had a lower mortality rate than the late intubation cohort (6% vs 30%, p < 0.001) without significantly different respiratory mechanics at the time of intubation. The late intubation cohort was noted to have higher dead space ratio (0.40 vs 0.52; p = 0.03). On review of CT scans, the late intubation cohort also had more dilated peripheral segments on imaging (two segments vs five segments). Conclusions: The question as to whether delaying intubation is beneficial or harmful for patients with coronavirus disease 2019-induced hypoxemic respiratory failure has yet to be answered. As our approaches to coronavirus disease 2019 continue to evolve, the decision of timing of intubation remains paramount. Although noninvasive ventilation may allow for delaying intubation, it is possible that there are downstream effects of delayed intubation that should be considered, including the potential for pulmonary vascular thrombosis and intussusceptive angiogenesis with delayed intubation.

We propose 'Tapestry', a novel approach to pooled testing with application to COVID-19 testing with quantitative Reverse Transcription Polymerase Chain Reaction (RT-PCR) that can result in shorter testing time and conservation of reagents and testing kits. Tapestry combines ideas from compressed sensing and combinatorial group testing with a novel noise model for RT-PCR used for generation of synthetic data. Unlike Boolean group testing algorithms, the input is a quantitative readout from each test and the output is a list of viral loads for each sample relative to the pool with the highest viral load. While other pooling techniques require a second confirmatory assay, Tapestry obtains individual sample-level results in a single round of testing, at clinically acceptable false positive or false negative rates. We also propose designs for pooling matrices that facilitate good prediction of the infected samples while remaining practically viable. When testing n samples out of which k n are infected, our method needs only O(k log n) tests when using random binary pooling matrices, with high probability. However, we also use deterministic binary pooling matrices based on combinatorial design ideas of Kirkman Triple Systems to balance between good reconstruction properties and matrix sparsity for ease of pooling. A lower bound on the number of tests with these matrices for satisfying a sufficient condition for guaranteed recovery is k √ n. In practice, we have observed the need for fewer tests with such matrices than with random pooling matrices. This makes Tapestry capable of very large savings at low prevalence rates, while simultaneously remaining viable even at prevalence rates as high as 9.5%. Empirically we find that single-round Tapestry pooling improves over two-round Dorfman pooling by almost a factor of 2 in the number of tests required. We describe how to combine combinatorial group testing and compressed sensing algorithmic ideas together to create a new kind of algorithm that is very effective in deconvoluting pooled tests. We validate Tapestry in simulations and wet lab experiments with oligomers in quantitative RT-PCR assays. An accompanying Android application Byom Smart Testing makes the Tapestry protocol straightforward to implement in testing centres, and is made available for free download. Lastly, we describe use-case scenarios for deployment.

The results of this study do not support adding an ambulatory, continuous ropivacaine infusion to a single-injection ropivacaine TAP block for hernia surgery. However, the present investigation was underpowered, and further study is warranted.

Backgroud COVID-19 has led to a reduction in operating efficiency. We aim to identify these inefficiencies and possible solutions as we begin to pursue a move to planned surgical care. Methods All trauma and orthopaedic emergency surgery were analysed for May 2019 and May 2020. Timing data was collated to look at the following: anaesthetic preparation time, anaesthetic time, surgical preparation time, surgical time, transfer to recovery time and turnaround time. Data for 2019 was collected retrospectively and data for 2020 was collected prospectively. Results A total of 222 patients underwent emergency orthopaedic surgery in May 2019 and 161 in May 2020. A statistically significant increase in all timings was demonstrated in 2020 apart from anaesthetic time which demonstrated a significant decrease. A subgroup analysis for hip fractures demonstrated a similar result. No increase in surgical time was observed in hand and wrist surgery or for debridement and washouts. Although the decrease in anaesthetic time is difficult to explain, this could be attributed to a reduction in combined anaesthetic techniques and possibly the effect of fear. The other increases in time demonstrated can largely be attributed to the PPE required for aerosol generating procedures and other measures taken to reduce spread of the virus. These procedures currently form a large amount of the orthopaedic case load. Conclusion COVID-19 has led to significant reductions in operating room efficiency. This will have significant impact on waiting times. Increasing frequency of regional anaesthesia concurrently with non-aerosol generating surgeries may improve efficiency.