Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

“Dichotomies in Silk: Shrinking and Stretching”

Shibori processes can be used to generate highly-textured surface designs for the production of pure silk garments that permanently retain their form and elasticity. Fabric is first shaped using a variety of traditional stitch-resist shibori techniques on greige goods (untreated fabric) of Japanese Gunma silk, a special fabric with highly over-spun silk filaments. Next, fabric is scoured, causing it to shrink – an effect of the high-twist yarns. In unprotected areas, the textile is permanently pleated, whereas the remaining stitch-resisted and protected areas of the fabric become permanently textured. Texture can further be enhanced 0through shibori dyeing. A major consideration in designing garments using the method described above is the fact that the scouring process leads to a sixty percent reduction in the total surface area of the textile. Therefore, it is necessary to calculate how and where this reduction will occur before scouring in order to ensure that the multiple textures and specific design features (i.e. cuffs, collars and waistline), appear at the appropriate and designated positions within the final piece. This technique, unlike that of traditional garment design, involves multiple textures within a continuous piece -- no seams exist between the pleated and stitch-resisted areas. Collectively, the elasticity inherent in the final pieces, coupled with their seamless nature, results in extraordinary fluidity and new possibilities in design

Loop Order Analysis of Weft-Knitted Textiles

In this paper, we describe algorithms that perform loop order analysis of weft-knitted textiles, which build upon the foundational TopoKnit topological data structure and associated query functions. During knitting, loops of yarn may be overlayed on top of each other and then stitched together with another piece of yarn. Loop order analysis aims to determine the front-to-back ordering of these overlapping loops, given a stitch pattern that defines the knitted fabric. Loop order information is crucial for the simulation of electrical current, water, force, and heat flow within functional fabrics. The new algorithms are based on the assumption that stitch instructions are executed row-by-row and for each row the instructions can be executed in any temporal order. To make our algorithms knitting-machine-independent, loop order analysis utilizes precedence rules that capture the order that stitch commands are executed when a row of yarn loops are being knitted by a two-bed flat weft knitting machine. Basing the algorithms on precedence rules allows them to be modified to adapt to the analysis of fabrics manufactured on a variety of knitting machines that may execute stitch commands in different temporal orders. Additionally, we have developed visualization methods for displaying the loop order information within the context of a TopoKnit yarn topology graph

Loop Order Analysis of Weft-Knitted Textiles

In this paper, we describe algorithms that perform loop order analysis of weft-knitted textiles, which build upon the foundational TopoKnit topological data structure and associated query functions. During knitting, loops of yarn may be overlayed on top of each other and then stitched together with another piece of yarn. Loop order analysis aims to determine the front-to-back ordering of these overlapping loops, given a stitch pattern that defines the knitted fabric. Loop order information is crucial for the simulation of electrical current, water, force, and heat flow within functional fabrics. The new algorithms are based on the assumption that stitch instructions are executed row-by-row and for each row the instructions can be executed in any temporal order. To make our algorithms knitting-machine-independent, loop order analysis utilizes precedence rules that capture the order that stitch commands are executed when a row of yarn loops are being knitted by a two-bed flat weft knitting machine. Basing the algorithms on precedence rules allows them to be modified to adapt to the analysis of fabrics manufactured on a variety of knitting machines that may execute stitch commands in different temporal orders. Additionally, we have developed visualization methods for displaying the loop order information within the context of a TopoKnit yarn topology graph

MXene Composite and Coaxial Fibers with High Stretchability and Conductivity for Wearable Strain Sensing Textiles

The integration of nanomaterials with high conductivity into stretchable polymer fibers can achieve novel functionalities such as sensing physical deformations. With a metallic conductivity that exceeds other solution-processed nanomaterials, 2D titanium carbide MXene is an attractive material to produce conducting and stretchable fibers. Here, a scalable wet-spinning technique is used to produce Ti3C2Tx MXene/polyurethane (PU) composite fibers that show both conductivity and high stretchability. The conductivity at a very low percolation threshold of ≈1 wt% is demonstrated, which is lower than the previously reported values for MXene-based polymer composites. When used as a strain sensor, the MXene/PU composite fibers show a high gauge factor of ≈12900 (≈238 at 50% strain) and a large sensing strain of ≈152%. The cyclic strain sensing performance is further improved by producing fibers with MXene/PU sheath and pure PU core using a coaxial wet-spinning process. Using a commercial-scale knitting machine, MXene/PU fibers are knitted into a one-piece elbow sleeve, which can track various movements of the wearer's elbow. This study establishes fundamental insights into the behavior of MXene in elastomeric composites and presents strategies to achieve MXene-based fibers and textiles with strain sensing properties suitable for applications in health, sports, and entertainment

Self-Folding Textiles through Manipulation of Knit Stitch Architecture

This research presents a preliminary study on finding predictable methods of controlling the self-folding behaviors of weft knit textiles for use in the development of smart textiles and garment devices, such as those with shape memory, auxetic behavior or transformation abilities. In this work, Shima Seiki SDS-One Apex computer-aided knitting technology, Shima Seiki industrial knitting machines, and the study of paper origami tessellation patterns were used as tools to understand and predict the self-folding abilities of weft knit textiles. A wide range of self-folding weft knit structures was produced, and relationships between the angles and ratios of the knit and purl stitch types were determined. Mechanical testing was used as a means to characterize differences produced by stitch patterns, and to further understand the relationships between angles and folding abilities. By defining a formulaic method for predicting the nature of the folds that occur due to stitch architecture patterns, we can better design self-folding fabrics for smart textile applications