Analyzing historical and future acute neurosurgical demand using an AI-enabled predictive dashboard

Characterizing acute service demand is critical for neurosurgery and other emergency-dominant specialties in order to dynamically distribute resources and ensure timely access to treatment. This is especially important in the post-Covid 19 pandemic period, when healthcare centers are grappling with a record backlog of pending surgical procedures and rising acute referral numbers. Healthcare dashboards are well-placed to analyze this data, making key information about service and clinical outcomes available to staff in an easy-to-understand format. However, they typically provide insights based on inference rather than prediction, limiting their operational utility. We retrospectively analyzed and prospectively forecasted acute neurosurgical referrals, based on 10,033 referrals made to a large volume tertiary neurosciences center in London, U.K., from the start of the Covid-19 pandemic lockdown period until October 2021 through the use of a novel AI-enabled predictive dashboard. As anticipated, weekly referral volumes significantly increased during this period, largely owing to an increase in spinal referrals (p < 0.05). Applying validated time-series forecasting methods, we found that referrals were projected to increase beyond this time-point, with Prophet demonstrating the best test and computational performance. Using a mixed-methods approach, we determined that a dashboard approach was usable, feasible, and acceptable among key stakeholders

Prevalence of hemoglobin variants in a diabetic population at high risk of hemoglobinopathies and optimization of HbA1c monitoring by incorporating HPLC in the laboratory workup

Background: In Tunisia, diabetes mellitus and hemoglobinopathies are major public health problems. Glycated hemoglobin (HbA1c) is  recommended for long-term monitoring of diabetes mellitus, but the presence of hemoglobin variants may interfere with HbA1c measurement. The aim was to determine the prevalence of hemoglobin variants in Tunisian diabetics and optimize the monitoring of diabetics using HbA1c.Methods: The study enrolled 9,792 Tunisian diabetic patients. HbA1c was measured by cation-exchange highpressure liquid chromatography (HPLC). All the chromatograms were analyzed for the presence of Hbvariants.Results: We identified 228 cases (2.33%) of Hb variants with D-10 HPLC (Bio-Rad): 191 with HbA/S trait, 27 with HbA/C trait, and 10 hemoglobin variants with the mention ‘Variant-Window’ on the chromatograms and subsequently identified as HbA/S on Variant I HPLC (Bio-Rad). Thus, the prevalence of HbS was 2.05%. We did not find any homozygous variant. All HbA1c results were reported to the treating physician.Conclusions: To evaluate glycated hemoglobin in populations with a high prevalence of hemoglobinopathies, we should use the HPLC method, which is easy, economical, and reliable. Based on an algorithm, hemoglobinvariants visualized on HPLC should be reported to the physician to improve the management of patients.Keywords: hemoglobinopathies; HbA1c; HPLC; diabetes mellitus; prevalence; Tunisi

Defining hypoxaemia from pulse oximeter measurements of oxygen saturation in well children at low altitude in Bangladesh: an observational study

BACKGROUND: WHO defines hypoxaemia, a low peripheral arterial oxyhaemoglobin saturation (SpO2), as <90%. Although hypoxaemia is an important risk factor for mortality of children with respiratory infections, the optimal SpO2 threshold for defining hypoxaemia is uncertain in low-income and middle-income countries (LMICs). We derived a SpO2 threshold for hypoxaemia from well children in Bangladesh residing at low altitude. METHODS: We prospectively enrolled well, children aged 3-35 months participating in a pneumococcal vaccine evaluation in Sylhet district, Bangladesh between June and August 2017. Trained health workers conducting community surveillance measured the SpO2 of children using a Masimo Rad-5 pulse oximeter with a wrap sensor. We used standard summary statistics to evaluate the SpO2 distribution, including whether the distribution differed by age or sex. We considered the 2.5th, 5th and 10th percentiles of SpO2 as possible lower thresholds for hypoxaemia. RESULTS: Our primary analytical sample included 1470 children (mean age 18.6±9.5 months). Median SpO2 was 98% (IQR 96%-99%), and the 2.5th, 5th and 10th percentile SpO2 was 91%, 92% and 94%. No child had a SpO2 <90%. Children 3-11 months had a lower median SpO2 (97%) than 12-23 months (98%) and 24-35 months (98%) (p=0.039). The SpO2 distribution did not differ by sex (p=0.959). CONCLUSION: A SpO2 threshold for hypoxaemia derived from the 2.5th, 5th or 10th percentile of well children is higher than <90%. If a higher threshold than <90% is adopted into LMIC care algorithms then decision-making using SpO2 must also consider the child's clinical status to minimise misclassification of well children as hypoxaemic. Younger children in lower altitude LMICs may require a different threshold for hypoxaemia than older children. Evaluating the mortality risk of sick children using higher SpO2 thresholds for hypoxaemia is a key next step

State-of-the-Art Duolingo Features and Applications

Duolingo is a rapidly growing on-line platform for language learning. In this paper learning theories that are embodied in its design are analyzed and certain shortcomings are identified. In the past two years, Duolingo has expanded its platform with the addition of new applications and features. State-of-the-art updates are reviewed in order to uncover whether they address limitations of Duolingo’s original design or provide enhancements to the learning platform

Observation and Interpretation of Microstructurally Induced Fluctuations of Back-Surface Signals and Ultrasonic Attenuation in Titanium Alloys

During ultrasonic inspection for flaws in engineering materials, it is important to understand the interactions between the inspecting beam and the microstructure in which flaws are embedded. It has been found that in certain materials such interactions can have dramatic effects on the characteristics of the beam as it propagates to and from a flaw and consequently can have deleterious effects on both flaw characterization and the probability of detection. It is well known that, the microstructure can backscatter energy, creating noise which can mask small flaws. In addition, a flaw signal can be attenuated by the removal of energy from the beam by absorption and scattering. Considerable progress has been made towards developing a theoretical understanding of these phenomena. For example, backscattered grain noise has been successfully modeled by Han and Thompson [1] for duplex microstructures that commonly occur in Ti-17 and Ti-6A1-4V alloys used in the rotating components of aircraft engines. In addition, attenuation has been modeled for randomly oriented, equiaxed, cubic microstructures [2], for textured, equiaxed, cubic, stainless-steel [3], and also for elongated textured microstructures [4]

Network Archaeology: Uncovering Ancient Networks from Present-day Interactions

Often questions arise about old or extinct networks. What proteins interacted in a long-extinct ancestor species of yeast? Who were the central players in the Last.fm social network 3 years ago? Our ability to answer such questions has been limited by the unavailability of past versions of networks. To overcome these limitations, we propose several algorithms for reconstructing a network's history of growth given only the network as it exists today and a generative model by which the network is believed to have evolved. Our likelihood-based method finds a probable previous state of the network by reversing the forward growth model. This approach retains node identities so that the history of individual nodes can be tracked. We apply these algorithms to uncover older, non-extant biological and social networks believed to have grown via several models, including duplication-mutation with complementarity, forest fire, and preferential attachment. Through experiments on both synthetic and real-world data, we find that our algorithms can estimate node arrival times, identify anchor nodes from which new nodes copy links, and can reveal significant features of networks that have long since disappeared.Comment: 16 pages, 10 figure

Are 'Village Doctors' in Bangladesh a curse or a blessing?

<p>Abstract</p> <p>Background</p> <p>Bangladesh is one of the health workforce crisis countries in the world. In the face of an acute shortage of trained professionals, ensuring healthcare for a population of 150 million remains a major challenge for the nation. To understand the issues related to shortage of health workforce and healthcare provision, this paper investigates the role of various healthcare providers in provision of health services in Chakaria, a remote rural area in Bangladesh.</p> <p>Methods</p> <p>Data were collected through a survey carried out during February 2007 among 1,000 randomly selected households from 8 unions of Chakaria <it>Upazila</it>. Information on health-seeking behaviour was collected from 1 randomly chosen member of a household from those who fell sick during 14 days preceding the survey.</p> <p>Results</p> <p>Around 44% of the villagers suffered from an illness during 14 days preceding the survey and of them 47% sought treatment for their ailment. 65% patients consulted Village Doctors and for 67% patients Village Doctors were the first line of care. Consultation with MBBS doctors was low at 14%. Given the morbidity level observed during the survey it was calculated that 250 physicians would be needed in Chakaria if the patients were to be attended by a qualified physician.</p> <p>Conclusions</p> <p>With the current shortage of physicians and level of production in the country it was asserted that it is very unlikely for Bangladesh to have adequate number of physicians in the near future. Thus, making use of existing healthcare providers, such as Village Doctors, could be considered a realistic option in dealing with the prevailing crisis.</p

Cosmogenic neutron production at the Sudbury Neutrino Observatory

Neutrons produced in nuclear interactions initiated by cosmic-ray muons present an irreducible background to many rare-event searches, even in detectors located deep underground. Models for the production of these neutrons have been tested against previous experimental data, but the extrapolation to deeper sites is not well understood. Here we report results from an analysis of cosmogenically produced neutrons at the Sudbury Neutrino Observatory. A specific set of observables are presented, which can be used to benchmark the validity of geant4 physics models. In addition, the cosmogenic neutron yield, in units of 10-4 cm2/(g·μ), is measured to be 7.28±0.09(stat)-1.12+1.59(syst) in pure heavy water and 7.30±0.07(stat)-1.02+1.40(syst) in NaCl-loaded heavy water. These results provide unique insights into this potential background source for experiments at SNOLAB