Can syndromic surveillance help forecast winter hospital bed pressures in England?

BACKGROUND: Health care planners need to predict demand for hospital beds to avoid deterioration in health care. Seasonal demand can be affected by respiratory illnesses which in England are monitored using syndromic surveillance systems. Therefore, we investigated the relationship between syndromic data and daily emergency hospital admissions. METHODS: We compared the timing of peaks in syndromic respiratory indicators and emergency hospital admissions, between 2013 and 2018. Furthermore, we created forecasts for daily admissions and investigated their accuracy when real-time syndromic data were included. RESULTS: We found that syndromic indicators were sensitive to changes in the timing of peaks in seasonal disease, especially influenza. However, each year, peak demand for hospital beds occurred on either 29th or 30th December, irrespective of the timing of syndromic peaks. Most forecast models using syndromic indicators explained over 70% of the seasonal variation in admissions (adjusted R square value). Forecast errors were reduced when syndromic data were included. For example, peak admissions for December 2014 and 2017 were underestimated when syndromic data were not used in models. CONCLUSION: Due to the lack of variability in the timing of the highest seasonal peak in hospital admissions, syndromic surveillance data do not provide additional early warning of timing. However, during atypical seasons syndromic data did improve the accuracy of forecast intensity

Evaluation of a pixelated large format CMOS sensor for x-ray microbeam radiotherapy

PURPOSE: Current techniques and procedures for dosimetry in microbeams typically rely on radiochromic film or small volume ionization chambers for validation and quality assurance in 2D and 1D, respectively. Whilst well characterized for clinical and preclinical radiotherapy, these methods are noninstantaneous and do not provide real time profile information. The objective of this work is to determine the suitability of the newly developed vM1212 detector, a pixelated CMOS (complementary metal-oxide-semiconductor) imaging sensor, for in situ and in vivo verification of x-ray microbeams.METHODS: Experiments were carried out on the vM1212 detector using a 220 kVp small animal radiation research platform (SARRP) at the Helmholtz Centre Munich. A 3 x 3 cm2 square piece of EBT3 film was placed on top of a marked nonfibrous card overlaying the sensitive silicon of the sensor. One centimeter of water equivalent bolus material was placed on top of the film for build-up. The response of the detector was compared to an Epson Expression 10000XL flatbed scanner using FilmQA Pro with triple channel dosimetry. This was also compared to a separate exposure using 450 µm of silicon as a surrogate for the detector and a Zeiss Axio Imager 2 microscope using an optical microscopy method of dosimetry. Microbeam collimator slits with range of nominal widths of 25, 50, 75, and 100 µm were used to compare beam profiles and determine sensitivity of the detector and both film measurements to different microbeams.RESULTS: The detector was able to measure peak and valley profiles in real-time, a significant reduction from the 24 hr self-development required by the EBT3 film. Observed full width at half maximum (FWHM) values were larger than the nominal slit widths, ranging from 130 to 190 µm due to divergence. Agreement between the methods was found for peak-to-valley dose ratio (PVDR), peak to peak separation and FWHM, but a difference in relative intensity of the microbeams was observed between the detectors.CONCLUSIONS: The investigation demonstrated that pixelated CMOS sensors could be applied to microbeam radiotherapy for real-time dosimetry in the future, however the relatively large pixel pitch of the vM1212 detector limit the immediate application of the results.</p

Optimization of a 65 nm CMOS imaging process for monolithic CMOS sensors for high energy physics

The long term goal of the CERN Experimental Physics Department R&D on monolithic sensors is the development of sub-100nm CMOS sensors for high energy physics. The first technology selected is the TPSCo 65nm CMOS imaging technology. A first submission MLR1 included several small test chips with sensor and circuit prototypes and transistor test structures. One of the main questions to be addressed was how to optimize the sensor in the presence of significant in-pixel circuitry. In this paper this optimization is described as well as the experimental results from the MLR1 run confirming its effectiveness. A second submission investigating wafer-scale stitching has just been completed. This work has been carried out in strong synergy with the ITS3 upgrade of the ALICE experiment

Optimization of a 65 nm CMOS imaging process for monolithic CMOS sensors for high energy physics

The long term goal of the CERN Experimental Physics Department R&D on monolithic sensors is the development of sub-100nm CMOS sensors for high energy physics. The first technology selected is the TPSCo 65nm CMOS imaging technology. A first submission MLR1 included several small test chips with sensor and circuit prototypes and transistor test structures. One of the main questions to be addressed was how to optimize the sensor in the presence of significant in-pixel circuitry. In this paper this optimization is described as well as the experimental results from the MLR1 run confirming its effectiveness. A second submission investigating wafer-scale stitching has just been completed. This work has been carried out in strong synergy with the ITS3 upgrade of the ALICE experiment

Effectiveness of a national quality improvement programme to improve survival after emergency abdominal surgery (EPOCH): a stepped-wedge cluster-randomised trial

BACKGROUND: Emergency abdominal surgery is associated with poor patient outcomes. We studied the effectiveness of a national quality improvement (QI) programme to implement a care pathway to improve survival for these patients. METHODS: We did a stepped-wedge cluster-randomised trial of patients aged 40 years or older undergoing emergency open major abdominal surgery. Eligible UK National Health Service (NHS) hospitals (those that had an emergency general surgical service, a substantial volume of emergency abdominal surgery cases, and contributed data to the National Emergency Laparotomy Audit) were organised into 15 geographical clusters and commenced the QI programme in a random order, based on a computer-generated random sequence, over an 85-week period with one geographical cluster commencing the intervention every 5 weeks from the second to the 16th time period. Patients were masked to the study group, but it was not possible to mask hospital staff or investigators. The primary outcome measure was mortality within 90 days of surgery. Analyses were done on an intention-to-treat basis. This study is registered with the ISRCTN registry, number ISRCTN80682973. FINDINGS: Treatment took place between March 3, 2014, and Oct 19, 2015. 22 754 patients were assessed for elegibility. Of 15 873 eligible patients from 93 NHS hospitals, primary outcome data were analysed for 8482 patients in the usual care group and 7374 in the QI group. Eight patients in the usual care group and nine patients in the QI group were not included in the analysis because of missing primary outcome data. The primary outcome of 90-day mortality occurred in 1210 (16%) patients in the QI group compared with 1393 (16%) patients in the usual care group (HR 1·11, 0·96-1·28). INTERPRETATION: No survival benefit was observed from this QI programme to implement a care pathway for patients undergoing emergency abdominal surgery. Future QI programmes should ensure that teams have both the time and resources needed to improve patient care. FUNDING: National Institute for Health Research Health Services and Delivery Research Programme

DECAL:a reconfigurable monolithic active pixel sensor for tracking and calorimetry in a 180 nm image sensor process

In this paper, we describe DECAL, a prototype Monolithic Active Pixel Sensor (MAPS) device designed to demonstrate the feasibility of both digital calorimetry and reconfigurability in ASICs for particle physics. The goal of this architecture is to help reduce the development and manufacturing costs of detectors for future colliders by developing a chip that can operate both as a digital silicon calorimeter and a tracking chip. The prototype sensor consists of a matrix of 64 &times; 64 55 &mu;m pixels, and provides a readout at 40 MHz of the number of particles which have struck the matrix in the preceding 25 ns. It can be configured to report this as a total sum across the sensor (equivalent to the pad of an analogue calorimeter) or the sum per column (equivalent to a traditional strip detector). The design and operation of the sensor are described, and the results of chip characterisation are reported and compared to simulations