An algorithm to identify patients aged 0-3 with rare genetic disorders

BACKGROUND

With over 7000 Mendelian disorders, identifying children with a specific rare genetic disorder diagnosis through structured electronic medical record data is challenging given incompleteness of records, inaccurate medical diagnosis coding, as well as heterogeneity in clinical symptoms and procedures for specific disorders. We sought to develop a digital phenotyping algorithm (PheIndex) using electronic medical records to identify children aged 0-3 diagnosed with genetic disorders or who present with illness with an increased risk for genetic disorders.

RESULTS

Through expert opinion, we established 13 criteria for the algorithm and derived a score and a classification. The performance of each criterion and the classification were validated by chart review. PheIndex identified 1,088 children out of 93,154 live births who may be at an increased risk for genetic disorders. Chart review demonstrated that the algorithm achieved 90% sensitivity, 97% specificity, and 94% accuracy.

CONCLUSIONS

The PheIndex algorithm can help identify when a rare genetic disorder may be present, alerting providers to consider ordering a diagnostic genetic test and/or referring a patient to a medical geneticist.

First Measurement of η Meson Production in Neutrino Interactions on Argon with MicroBooNE

We present a measurement of η production from neutrino interactions on argon with the MicroBooNE detector. The modeling of resonant neutrino interactions on argon is a critical aspect of the neutrino oscillation physics program being carried out by the DUNE and Short Baseline Neutrino programs. η production in neutrino interactions provides a powerful new probe of resonant interactions, complementary to pion channels, and is particularly suited to the study of higher-order resonances beyond the Δ(1232). We measure a flux-integrated cross section for neutrino-induced η production on argon of 3.22±0.84(stat)±0.86(syst) 10^{-41}  cm^{2}/nucleon. By demonstrating the successful reconstruction of the two photons resulting from η production, this analysis enables a novel calibration technique for electromagnetic showers in GeV accelerator neutrino experiments.

Search for Heavy Neutral Leptons in Electron-Positron and Neutral-Pion Final States with the MicroBooNE Detector

We present the first search for heavy neutral leptons (HNLs) decaying into νe^{+}e^{-} or νπ^{0} final states in a liquid-argon time projection chamber using data collected with the MicroBooNE detector. The data were recorded synchronously with the NuMI neutrino beam from Fermilab's main injector corresponding to a total exposure of 7.01×10^{20} protons on target. We set upper limits at the 90% confidence level on the mixing parameter |U_{μ4}|^{2} in the mass ranges 10≤m_{HNL}≤150  MeV for the νe^{+}e^{-} channel and 150≤m_{HNL}≤245  MeV for the νπ^{0} channel, assuming |U_{e4}|^{2}=|U_{τ4}|^{2}=0. These limits represent the most stringent constraints in the mass range 35 Collapse

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Affiliation(s)

P Abratenko Tufts University, Medford, Massachusetts 02155, USA
O Alterkait Tufts University, Medford, Massachusetts 02155, USA
D Andrade Aldana Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
L Arellano The University of Manchester, Manchester M13 9PL, United Kingdom
J Asaadi University of Texas, Arlington, Texas 76019, USA
A Ashkenazi Tel Aviv University, Tel Aviv, Israel, 69978
S Balasubramanian Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
B Baller Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
G Barr University of Oxford, Oxford OX1 3RH, United Kingdom
D Barrow University of Oxford, Oxford OX1 3RH, United Kingdom
J Barrow Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA Tel Aviv University, Tel Aviv, Israel, 69978
V Basque Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
O Benevides Rodrigues Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
S Berkman Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA Michigan State University, East Lansing, Michigan 48824, USA
A Bhanderi The University of Manchester, Manchester M13 9PL, United Kingdom
A Bhat University of Chicago, Chicago, Illinois 60637, USA
M Bhattacharya Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
M Bishai Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
A Blake Lancaster University, Lancaster LA1 4YW, United Kingdom
B Bogart University of Michigan, Ann Arbor, Michigan 48109, USA
T Bolton Kansas State University (KSU), Manhattan, Kansas 66506, USA
J Y Book Harvard University, Cambridge, Massachusetts 02138, USA
M B Brunetti University of Warwick, Coventry CV4 7AL, United Kingdom
L Camilleri Columbia University, New York, New York 10027, USA
Y Cao The University of Manchester, Manchester M13 9PL, United Kingdom
D Caratelli University of California, Santa Barbara, California 93106, USA
F Cavanna Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
G Cerati Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
A Chappell University of Warwick, Coventry CV4 7AL, United Kingdom
Y Chen SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
J M Conrad Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
M Convery SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
L Cooper-Troendle University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
J I Crespo-Anadón Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
R Cross University of Warwick, Coventry CV4 7AL, United Kingdom
M Del Tutto Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
S R Dennis University of Cambridge, Cambridge CB3 0HE, United Kingdom
P Detje University of Cambridge, Cambridge CB3 0HE, United Kingdom
A Devitt Lancaster University, Lancaster LA1 4YW, United Kingdom
R Diurba Universität Bern, Bern CH-3012, Switzerland
Z Djurcic Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
R Dorrill Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
K Duffy University of Oxford, Oxford OX1 3RH, United Kingdom
S Dytman University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
B Eberly University of Southern Maine, Portland, Maine 04104, USA
P Englezos Rutgers University, Piscataway, New Jersey 08854, USA
A Ereditato University of Chicago, Chicago, Illinois 60637, USA Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
J J Evans The University of Manchester, Manchester M13 9PL, United Kingdom
R Fine Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
O G Finnerud The University of Manchester, Manchester M13 9PL, United Kingdom
W Foreman Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
B T Fleming University of Chicago, Chicago, Illinois 60637, USA
D Franco University of Chicago, Chicago, Illinois 60637, USA
A P Furmanski University of Minnesota, Minneapolis, Minnesota 55455, USA
F Gao University of California, Santa Barbara, California 93106, USA
D Garcia-Gamez Universidad de Granada, Granada E-18071, Spain
S Gardiner Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
G Ge Columbia University, New York, New York 10027, USA
S Gollapinni Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
E Gramellini The University of Manchester, Manchester M13 9PL, United Kingdom
P Green University of Oxford, Oxford OX1 3RH, United Kingdom
H Greenlee Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
L Gu Lancaster University, Lancaster LA1 4YW, United Kingdom
W Gu Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
R Guenette The University of Manchester, Manchester M13 9PL, United Kingdom
P Guzowski The University of Manchester, Manchester M13 9PL, United Kingdom
L Hagaman University of Chicago, Chicago, Illinois 60637, USA
O Hen Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
C Hilgenberg University of Minnesota, Minneapolis, Minnesota 55455, USA
G A Horton-Smith Kansas State University (KSU), Manhattan, Kansas 66506, USA
Z Imani Tufts University, Medford, Massachusetts 02155, USA
B Irwin University of Minnesota, Minneapolis, Minnesota 55455, USA
M Ismail University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
C James Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
X Ji Nankai University, Nankai District, Tianjin 300071, China
J H Jo Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
R A Johnson University of Cincinnati, Cincinnati, Ohio 45221, USA
Y-J Jwa Columbia University, New York, New York 10027, USA
D Kalra Columbia University, New York, New York 10027, USA
N Kamp Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
G Karagiorgi Columbia University, New York, New York 10027, USA
W Ketchum Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
M Kirby Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
T Kobilarcik Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
I Kreslo Universität Bern, Bern CH-3012, Switzerland
M B Leibovitch University of California, Santa Barbara, California 93106, USA
I Lepetic Rutgers University, Piscataway, New Jersey 08854, USA
J-Y Li University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
K Li Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
Y Li Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
K Lin Rutgers University, Piscataway, New Jersey 08854, USA
B R Littlejohn Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
H Liu Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
W C Louis Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
X Luo University of California, Santa Barbara, California 93106, USA
C Mariani Center for Neutrino Physics, Virginia Tech, Blacksburg, Viriginia 24061, USA
D Marsden The University of Manchester, Manchester M13 9PL, United Kingdom
J Marshall University of Warwick, Coventry CV4 7AL, United Kingdom
N Martinez Kansas State University (KSU), Manhattan, Kansas 66506, USA
D A Martinez Caicedo South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
S Martynenko Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
A Mastbaum Rutgers University, Piscataway, New Jersey 08854, USA
I Mawby University of Warwick, Coventry CV4 7AL, United Kingdom
N McConkey University College London, London WC1E 6BT, United Kingdom
V Meddage Kansas State University (KSU), Manhattan, Kansas 66506, USA
J Micallef Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA Tufts University, Medford, Massachusetts 02155, USA
K Miller University of Chicago, Chicago, Illinois 60637, USA
A Mogan Colorado State University, Fort Collins, Colorado 80523, USA
T Mohayai Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA Indiana University, Bloomington, Indiana 47405, USA
M Mooney Colorado State University, Fort Collins, Colorado 80523, USA
A F Moor University of Cambridge, Cambridge CB3 0HE, United Kingdom
C D Moore Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
L Mora Lepin The University of Manchester, Manchester M13 9PL, United Kingdom
M M Moudgalya The University of Manchester, Manchester M13 9PL, United Kingdom
S Mulleriababu Universität Bern, Bern CH-3012, Switzerland
D Naples University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
A Navrer-Agasson The University of Manchester, Manchester M13 9PL, United Kingdom
N Nayak Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
M Nebot-Guinot University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
J Nowak Lancaster University, Lancaster LA1 4YW, United Kingdom
N Oza Columbia University, New York, New York 10027, USA
O Palamara Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
N Pallat University of Minnesota, Minneapolis, Minnesota 55455, USA
V Paolone University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
A Papadopoulou Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
V Papavassiliou New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
H B Parkinson University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
S F Pate New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
N Patel Lancaster University, Lancaster LA1 4YW, United Kingdom
Z Pavlovic Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
E Piasetzky Tel Aviv University, Tel Aviv, Israel, 69978
I Pophale Lancaster University, Lancaster LA1 4YW, United Kingdom
X Qian Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
J L Raaf Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
V Radeka Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
A Rafique Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
M Reggiani-Guzzo University of Edinburgh, Edinburgh EH9 3FD, United Kingdom The University of Manchester, Manchester M13 9PL, United Kingdom
L Ren New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
L Rochester SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
J Rodriguez Rondon South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
M Rosenberg Tufts University, Medford, Massachusetts 02155, USA
M Ross-Lonergan Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
C Rudolf von Rohr Universität Bern, Bern CH-3012, Switzerland
I Safa Columbia University, New York, New York 10027, USA
G Scanavini Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
D W Schmitz University of Chicago, Chicago, Illinois 60637, USA
A Schukraft Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
W Seligman Columbia University, New York, New York 10027, USA
M H Shaevitz Columbia University, New York, New York 10027, USA
R Sharankova Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
J Shi University of Cambridge, Cambridge CB3 0HE, United Kingdom
E L Snider Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
M Soderberg Syracuse University, Syracuse, New York 13244, USA
S Söldner-Rembold The University of Manchester, Manchester M13 9PL, United Kingdom
J Spitz University of Michigan, Ann Arbor, Michigan 48109, USA
M Stancari Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
J St John Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
T Strauss Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
A M Szelc University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
W Tang University of Tennessee, Knoxville, Tennessee 37996, USA
N Taniuchi University of Cambridge, Cambridge CB3 0HE, United Kingdom
K Terao SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
C Thorpe Lancaster University, Lancaster LA1 4YW, United Kingdom The University of Manchester, Manchester M13 9PL, United Kingdom
D Torbunov Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
D Totani University of California, Santa Barbara, California 93106, USA
M Toups Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
Y-T Tsai SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
J Tyler Kansas State University (KSU), Manhattan, Kansas 66506, USA
M A Uchida University of Cambridge, Cambridge CB3 0HE, United Kingdom
T Usher SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
B Viren Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
M Weber Universität Bern, Bern CH-3012, Switzerland
H Wei Louisiana State University, Baton Rouge, Louisiana 70803, USA
A J White University of Chicago, Chicago, Illinois 60637, USA
S Wolbers Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
T Wongjirad Tufts University, Medford, Massachusetts 02155, USA
M Wospakrik Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
K Wresilo University of Cambridge, Cambridge CB3 0HE, United Kingdom
W Wu University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
E Yandel University of California, Santa Barbara, California 93106, USA
T Yang Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
L E Yates Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
H W Yu Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
G P Zeller Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
J Zennamo Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
C Zhang Brookhaven National Laboratory (BNL), Upton, New York 11973, USA

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Effects of empagliflozin on progression of chronic kidney disease: a prespecified secondary analysis from the empa-kidney trial

BACKGROUND

Sodium-glucose co-transporter-2 (SGLT2) inhibitors reduce progression of chronic kidney disease and the risk of cardiovascular morbidity and mortality in a wide range of patients. However, their effects on kidney disease progression in some patients with chronic kidney disease are unclear because few clinical kidney outcomes occurred among such patients in the completed trials. In particular, some guidelines stratify their level of recommendation about who should be treated with SGLT2 inhibitors based on diabetes status and albuminuria. We aimed to assess the effects of empagliflozin on progression of chronic kidney disease both overall and among specific types of participants in the EMPA-KIDNEY trial.

METHODS

EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA), and included individuals aged 18 years or older with an estimated glomerular filtration rate (eGFR) of 20 to less than 45 mL/min per 1·73 m2, or with an eGFR of 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher. We explored the effects of 10 mg oral empagliflozin once daily versus placebo on the annualised rate of change in estimated glomerular filtration rate (eGFR slope), a tertiary outcome. We studied the acute slope (from randomisation to 2 months) and chronic slope (from 2 months onwards) separately, using shared parameter models to estimate the latter. Analyses were done in all randomly assigned participants by intention to treat. EMPA-KIDNEY is registered at ClinicalTrials.gov, NCT03594110.

FINDINGS

Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and then followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroups of eGFR included 2282 (34·5%) participants with an eGFR of less than 30 mL/min per 1·73 m2, 2928 (44·3%) with an eGFR of 30 to less than 45 mL/min per 1·73 m2, and 1399 (21·2%) with an eGFR 45 mL/min per 1·73 m2 or higher. Prespecified subgroups of uACR included 1328 (20·1%) with a uACR of less than 30 mg/g, 1864 (28·2%) with a uACR of 30 to 300 mg/g, and 3417 (51·7%) with a uACR of more than 300 mg/g. Overall, allocation to empagliflozin caused an acute 2·12 mL/min per 1·73 m2 (95% CI 1·83-2·41) reduction in eGFR, equivalent to a 6% (5-6) dip in the first 2 months. After this, it halved the chronic slope from -2·75 to -1·37 mL/min per 1·73 m2 per year (relative difference 50%, 95% CI 42-58). The absolute and relative benefits of empagliflozin on the magnitude of the chronic slope varied significantly depending on diabetes status and baseline levels of eGFR and uACR. In particular, the absolute difference in chronic slopes was lower in patients with lower baseline uACR, but because this group progressed more slowly than those with higher uACR, this translated to a larger relative difference in chronic slopes in this group (86% [36-136] reduction in the chronic slope among those with baseline uACR <30 mg/g compared with a 29% [19-38] reduction for those with baseline uACR ≥2000 mg/g; ptrend<0·0001).

INTERPRETATION

Empagliflozin slowed the rate of progression of chronic kidney disease among all types of participant in the EMPA-KIDNEY trial, including those with little albuminuria. Albuminuria alone should not be used to determine whether to treat with an SGLT2 inhibitor.

FUNDING

Boehringer Ingelheim and Eli Lilly.

Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

BACKGROUND

The EMPA-KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population.

METHODS

EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110.

FINDINGS

Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62-0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16-1·59), representing a 50% (42-58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all >0·1).

INTERPRETATION

In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease.

FUNDING

Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council.

Hyperon Polarization along the Beam Direction Relative to the Second and Third Harmonic Event Planes in Isobar Collisions at sqrt[s_{NN}]=200 GeV

The polarization of Λ and Λ[over ¯] hyperons along the beam direction has been measured relative to the second and third harmonic event planes in isobar Ru+Ru and Zr+Zr collisions at sqrt[s_{NN}]=200  GeV. This is the first experimental evidence of the hyperon polarization by the triangular flow originating from the initial density fluctuations. The amplitudes of the sine modulation for the second and third harmonic results are comparable in magnitude, increase from central to peripheral collisions, and show a mild p_{T} dependence. The azimuthal angle dependence of the polarization follows the vorticity pattern expected due to elliptic and triangular anisotropic flow, and qualitatively disagrees with most hydrodynamic model calculations based on thermal vorticity and shear induced contributions. The model results based on one of existing implementations of the shear contribution lead to a correct azimuthal angle dependence, but predict centrality and p_{T} dependence that still disagree with experimental measurements. Thus, our results provide stringent constraints on the thermal vorticity and shear-induced contributions to hyperon polarization. Comparison to previous measurements at RHIC and the LHC for the second-order harmonic results shows little dependence on the collision system size and collision energy.

First Double-Differential Measurement of Kinematic Imbalance in Neutrino Interactions with the MicroBooNE Detector

We report the first measurement of flux-integrated double-differential quasielasticlike neutrino-argon cross sections, which have been made using the Booster Neutrino Beam and the MicroBooNE detector at Fermi National Accelerator Laboratory. The data are presented as a function of kinematic imbalance variables which are sensitive to nuclear ground-state distributions and hadronic reinteraction processes. We find that the measured cross sections in different phase-space regions are sensitive to different nuclear effects. Therefore, they enable the impact of specific nuclear effects on the neutrino-nucleus interaction to be isolated more completely than was possible using previous single-differential cross section measurements. Our results provide precision data to help test and improve neutrino-nucleus interaction models. They further support ongoing neutrino-oscillation studies by establishing phase-space regions where precise reaction modeling has already been achieved.

First Measurement of Quasielastic Λ Baryon Production in Muon Antineutrino Interactions in the MicroBooNE Detector

We present the first measurement of the cross section of Cabibbo-suppressed Λ baryon production, using data collected with the MicroBooNE detector when exposed to the neutrinos from the main injector beam at the Fermi National Accelerator Laboratory. The data analyzed correspond to 2.2×10^{20} protons on target running in neutrino mode, and 4.9×10^{20} protons on target running in anti-neutrino mode. An automated selection is combined with hand scanning, with the former identifying five candidate Λ production events when the signal was unblinded, consistent with the GENIE prediction of 5.3±1.1 events. Several scanners were employed, selecting between three and five events, compared with a prediction from a blinded Monte Carlo simulation study of 3.7±1.0 events. Restricting the phase space to only include Λ baryons that decay above MicroBooNE's detection thresholds, we obtain a flux averaged cross section of 2.0_{-1.7}^{+2.2}×10^{-40}  cm^{2}/Ar, where statistical and systematic uncertainties are combined.

Does active participation via integrated questions in large lectures matter?

This paper investigates whether the intensity of participation in large lecture quizzes in a tertiary education context, facilitated and monitored by an online platform, is associated with better examination performance. The platform mirrors lecture slides onto student devices and uses integrated "clicker" style questions within the lecture to quiz students on concepts learned. Using regression, we find that the intensity of quiz participation is positively related to students' performance. Student study perceptions, based on study and career plans, moderate the results. These findings are relevant to educators, especially in a post-COVID-19 learning environment, where the online quiz function could be used to foster participation.

A structured, telephone-delivered intervention to reduce methamphetamine use: study protocol for a parallel-group randomised controlled trial

BACKGROUND

Australia has one of the highest rates of methamphetamine (MA) use in the world; however, uptake of in-person psychological treatment remains extremely low due to numerous individual (e.g. stigma, shame) and structural (e.g. service accessibility, geographical location) barriers to accessing care. Telephone-delivered interventions are ideally placed to overcome many of the known barriers to treatment access and delivery. This randomised controlled trial (RCT) will examine the efficacy of a standalone, structured telephone-delivered intervention to reduce MA problem severity and related harms.

METHODS

This study is a double-blind, parallel-group RCT. We will recruit 196 ± 8 individuals with mild to moderate MA use disorder from across Australia. After eligibility and baseline assessments, participants will be randomly allocated to receive either the Ready2Change-Methamphetamine (R2C-M) intervention (n = 98 ± 4; four to six telephone-delivered intervention sessions, R2C-M workbooks and MA information booklet) or control (n = 98 ± 4; four to six ≤5-min telephone check-ins and MA information booklet including information on accessing further support). Telephone follow-up assessments will occur at 6 weeks and 3, 6 and 12 months post-randomisation. The primary outcome is change in MA problem severity (Drug Use Disorders Identification Test, DUDIT) at 3 months post-randomisation. Secondary outcomes are as follows: MA problem severity (DUDIT) at 6 and 12 months post-randomisation, amount of methamphetamine used, methamphetamine use days, methamphetamine use disorder criteria met, cravings, psychological functioning, psychotic-like experiences, quality of life and other drug use days (at some or all timepoints of 6 weeks and 3, 6 and 12 months post-randomisation). Mixed-methods program evaluation will be performed and cost-effectiveness will be examined.

DISCUSSION

This study will be the first RCT internationally to assess the efficacy of a telephone-delivered intervention for MA use disorder and related harms. The proposed intervention is expected to provide an effective, low-cost, scalable treatment for individuals otherwise unlikely to seek care, preventing future harms and reducing health service and community costs.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04713124 . Pre-registered on 19 January 2021.

Social work in alcohol and other drug service navigation: supporting social complexity in dual diagnosis

Purpose

Many people with dual diagnosis present with social complexity that impedes service access. The role of social work support in such service navigation is poorly understood. This study aims to characterise client presentations to an Australian telephone-based social work alcohol and other drug (AOD) service navigation and linkage program, with consideration of presentation complexity compared between those clients who present with or without self-reported mental health (MH) concerns and a history of MH diagnoses, to identify differences in baseline characteristics, and linkage outcomes.

Design/methodology/approach

A retrospective audit was conducted of routinely collected clinical information from a six-month period, selected to capture the social and health challenges experienced during the mid-pandemic period (mid-2021) in Victoria, Australia, during which a number of lockdowns resulted in a reliance on telephone-based services. The audit focused on client and presentation characteristics, and compared clients with and without a history of co-occurring MH and AOD concerns.

Findings

It was found that three in four people accessing an Australian telephone-based AOD service navigation and linkage program presented with dual diagnosis. Individuals with dual diagnosis required more support from the service compared to those without a co-occurring MH disorder; but overall, were just as likely to achieve a successful linkage to services, when offered holistic, long-term social work support.

Originality/value

This study focused on the role of social workers in this service navigation program in supporting individuals with complexity. It also highlights the challenges in operationalising social complexity factors alongside clinical MH and AOD diagnoses, and points to the need for further research to guide future service development for this vulnerable client group.

First Constraints on Light Sterile Neutrino Oscillations from Combined Appearance and Disappearance Searches with the MicroBooNE Detector

We present a search for eV-scale sterile neutrino oscillations in the MicroBooNE liquid argon detector, simultaneously considering all possible appearance and disappearance effects within the 3+1 active-to-sterile neutrino oscillation framework. We analyze the neutrino candidate events for the recent measurements of charged-current ν_{e} and ν_{μ} interactions in the MicroBooNE detector, using data corresponding to an exposure of 6.37×10^{20} protons on target from the Fermilab booster neutrino beam. We observe no evidence of light sterile neutrino oscillations and derive exclusion contours at the 95% confidence level in the plane of the mass-squared splitting Δm_{41}^{2} and the sterile neutrino mixing angles θ_{μe} and θ_{ee}, excluding part of the parameter space allowed by experimental anomalies. Cancellation of ν_{e} appearance and ν_{e} disappearance effects due to the full 3+1 treatment of the analysis leads to a degeneracy when determining the oscillation parameters, which is discussed in this Letter and will be addressed by future analyses.

Effectiveness of a Stand-alone Telephone-Delivered Intervention for Reducing Problem Alcohol Use: A Randomized Clinical Trial

Importance

Despite the magnitude of alcohol use problems globally, treatment uptake remains low. Telephone-delivered interventions have potential to overcome many structural and individual barriers to help seeking, yet their effectiveness as a stand-alone treatment for problem alcohol use has not been established.

Objective

To examine the effectiveness of the Ready2Change telephone-delivered intervention in reducing alcohol problem severity up to 3 months among a general population sample.

Design, Setting, and Participants

This double-blind, randomized clinical trial recruited participants with an Alcohol Use Disorders Identification Test (AUDIT) score of greater than 6 (for female participants) and 7 (for male participants) from across Australia during the period of May 25, 2018, to October 2, 2019. Telephone assessments occurred at baseline and 3 months after baseline (84.9% retention). Data collection was finalized September 2020.

Interventions

The telephone-based cognitive and behavioral intervention comprised 4 to 6 telephone sessions with a psychologist. The active control condition comprised four 5-minute telephone check-ins from a researcher and alcohol and stress management pamphlets.

Main Outcomes and Measures

The primary outcome was change in alcohol problem severity, measured with the AUDIT total score. Drinking patterns were measured with the Timeline Followback (TLFB) instrument.

Results

This study included a total of 344 participants (mean [SD] age, 39.9 [11.4] years; range, 18-73 years; 177 male participants [51.5%]); 173 participants (50.3%) composed the intervention group, and 171 participants (49.7%) composed the active control group. Less than one-third of participants (101 [29.4%]) had previously sought alcohol treatment, despite a high mean (SD) baseline AUDIT score of 21.5 (6.3) and 218 (63.4%) scoring in the probable dependence range. For the primary intention-to-treat analyses, there was a significant decrease in AUDIT total score from baseline to 3 months in both groups (intervention group decrease, 8.22; 95% CI, 7.11-9.32; P < .001; control group decrease, 7.13; 95% CI, 6.10-8.17; P < .001), but change over time was not different between groups (difference, 1.08; 95% CI, -0.43 to 2.59; P = .16). In secondary analyses, the intervention group showed a significantly greater reduction in the AUDIT hazardous use domain relative to the control group at 3 months (difference, 0.58; 95% CI, 0.02-1.14; P = .04). A greater reduction in AUDIT total score was observed for the intervention group relative to the control group when adjusting for exposure to 2 or more sessions (difference, 3.40; 95% CI, 0.36-6.44; P = .03) but not 1 or more sessions (per-protocol analysis).

Conclusions and Relevance

Based on the primary outcome, AUDIT total score, this randomized clinical trial did not find superior effectiveness of this telephone-based cognitive and behavioral intervention compared with active control. However, the intervention was effective in reducing hazardous alcohol use and reduced alcohol problem severity when 2 or more sessions were delivered. Trial outcomes demonstrate the potential benefits of this highly scalable and accessible model of alcohol treatment.

Trial Registration

ANZCTR Identifier: ACTRN12618000828224.

Consumer-grade wearables identify changes in multiple physiological systems during COVID-19 disease progression

Consumer-grade wearables are needed to track disease, especially in the ongoing pandemic, as they can monitor patients in real time. We show that decomposing heart rate from low-cost wearable technologies into signals from different systems can give a multidimensional description of physiological changes due to COVID-19 infection. We find that the separate physiological features of basal heart rate, heart rate response to physical activity, circadian variation in heart rate, and autocorrelation of heart rate are significantly altered and can classify symptomatic versus healthy periods. Increased heart rate and autocorrelation begin at symptom onset, while the heart rate response to activity increases soon after symptom onset and increases more in individuals exhibiting cough. Symptom onset is associated with a blunting of circadian variation in heart rate, as measured by the uncertainty in the phase estimate. This work establishes an innovative data analytic approach to monitor disease progression remotely using consumer-grade wearables.

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We separate wearable heart rate into cardiopulmonary, circadian, and other signals

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Parameters from different physiological systems enable disease tracking

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Individual signals change in distinct ways around COVID-19 symptom onset

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Together, the parameter changes can distinguish healthy from infection periods

Inpatient Administration of Alpha-1-Adrenergic Receptor Blocking Agents Reduces Mortality in Male COVID-19 Patients

Apha-1-adrenergic receptor antagonists (α₁-blockers) can suppress pro-inflammatory cytokines, thereby potentially improving outcomes among patients with COVID-19. Accordingly, we evaluated the association between α₁-blocker exposure (before or during hospitalization) and COVID-19 in-hospital mortality. We identified 2,627 men aged 45 or older who were admitted to Mount Sinai hospitals with COVID-19 between February 24 and May 31, 2020, in New York. Men exposed to α₁-blockers (N = 436) were older (median age 73 vs. 64 years, P < 0.001) and more likely to have comorbidities than unexposed men (N = 2,191). Overall, 777 (29.6%) patients died in hospital, and 1,850 (70.4%) were discharged. Notably, we found that α₁-blocker exposure was independently associated with improved in-hospital mortality in a multivariable logistic analysis (OR 0.699; 95% CI, 0.498-0.982; P = 0.039) after adjusting for patient demographics, comorbidities, and baseline vitals and labs. The protective effect of α₁-blockers was stronger among patients with documented inpatient exposure to α₁-blockers (OR 0.624; 95% CI 0.431-0.903; P = 0.012). Finally, age-stratified analyses suggested variable benefit from inpatient α₁-blocker across age groups: Age 45-65 OR 0.483, 95% CI 0.216-1.081 (P = 0.077); Age 55-75 OR 0.535, 95% CI 0.323-0.885 (P = 0.015); Age 65-89 OR 0.727, 95% CI 0.484-1.092 (P = 0.124). Taken together, clinical trials to assess the therapeutic value of α₁-blockers for COVID-19 complications are warranted.

Evolution of the repression mechanisms in circadian clocks

BACKGROUND

Circadian (daily) timekeeping is essential to the survival of many organisms. An integral part of all circadian timekeeping systems is negative feedback between an activator and repressor. However, the role of this feedback varies widely between lower and higher organisms.

RESULTS

Here, we study repression mechanisms in the cyanobacterial and eukaryotic clocks through mathematical modeling and systems analysis. We find a common mathematical model that describes the mechanism by which organisms generate rhythms; however, transcription's role in this has diverged. In cyanobacteria, protein sequestration and phosphorylation generate and regulate rhythms while transcription regulation keeps proteins in proper stoichiometric balance. Based on recent experimental work, we propose a repressor phospholock mechanism that models the negative feedback through transcription in clocks of higher organisms. Interestingly, this model, when coupled with activator phosphorylation, allows for oscillations over a wide range of protein stoichiometries, thereby reconciling the negative feedback mechanism in Neurospora with that in mammals and cyanobacteria.

CONCLUSIONS

Taken together, these results paint a picture of how circadian timekeeping may have evolved.

Distinct Circadian Assessments From Wearable Data Reveal Social Distancing Promoted Internal Desynchrony Between Circadian Markers

Mobile measures of human circadian rhythms (CR) are needed in the age of chronotherapy. Two wearable measures of CR have recently been validated: one that uses heart rate to extract circadian rhythms that originate in the sinoatrial node of the heart, and another that uses activity to predict the laboratory gold standard and central circadian pacemaker marker, dim light melatonin onset (DLMO). We first find that the heart rate markers of normal real-world individuals align with laboratory DLMO measurements when we account for heart rate phase error. Next, we expand upon previous work that has examined sleep patterns or chronotypes during the COVID-19 lockdown by studying the effects of social distancing on circadian rhythms. In particular, using data collected from the Social Rhythms app, a mobile application where individuals upload their wearable data and receive reports on their circadian rhythms, we compared the two circadian phase estimates before and after social distancing. Interestingly, we found that the lockdown had different effects on the two ambulatory measurements. Before the lockdown, the two measures aligned, as predicted by laboratory data. After the lockdown, when circadian timekeeping signals were blunted, these measures diverged in 70% of subjects (with circadian rhythms in heart rate, or CRHR, becoming delayed). Thus, while either approach can measure circadian rhythms, both are needed to understand internal desynchrony. We also argue that interventions may be needed in future lockdowns to better align separate circadian rhythms in the body.

Inferring causality in biological oscillators

MOTIVATION

Fundamental to biological study is identifying regulatory interactions. The recent surge in time-series data collection in biology provides a unique opportunity to infer regulations computationally. However, when components oscillate, model-free inference methods, while easily implemented, struggle to distinguish periodic synchrony and causality. Alternatively, model-based methods test the reproducibility of time series given a specific model but require inefficient simulations and have limited applicability.

RESULTS

We develop an inference method based on a general model of molecular, neuronal and ecological oscillatory systems that merges the advantages of both model-based and model-free methods, namely accuracy, broad applicability and usability. Our method successfully infers the positive and negative regulations within various oscillatory networks, e.g. the repressilator and a network of cofactors at the pS2 promoter, outperforming popular inference methods.

AVAILABILITY AND IMPLEMENTATION

We provide a computational package, ION (Inferring Oscillatory Networks), that users can easily apply to noisy, oscillatory time series to uncover the mechanisms by which diverse systems generate oscillations. Accompanying MATLAB code under a BSD-style license and examples are available at https://github.com/Mathbiomed/ION. Additionally, the code is available under a CC-BY 4.0 License at https://doi.org/10.6084/m9.figshare.16431408.v1.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A method for characterizing daily physiology from widely used wearables

Millions of wearable-device users record their heart rate (HR) and activity. We introduce a statistical method to extract and track six key physiological parameters from these data, including an underlying circadian rhythm in HR (CRHR), the direct effects of activity, and the effects of meals, posture, and stress through hormones like cortisol. We test our method on over 130,000 days of real-world data from medical interns on rotating shifts, showing that CRHR dynamics are distinct from those of sleep-wake or physical activity patterns and vary greatly among individuals. Our method also estimates a personalized phase-response curve of CRHR to activity for each individual, representing a passive and personalized determination of how human circadian timekeeping continually changes due to real-world stimuli. We implement our method in the "Social Rhythms" iPhone and Android app, which anonymously collects data from wearable-device users and provides analysis based on our method.

Ready2Change: Preliminary effectiveness of a telephone-delivered intervention program for alcohol, methamphetamine and cannabis use problems

INTRODUCTION

Telehealth has considerable potential to overcome many of the barriers to accessing care for substance use problems, thereby increasing the opportunity for earlier intervention. The Ready2Change program is a multiple-session outbound telephone-delivered cognitive and behavioural intervention for mild-to-moderate substance use disorders, embedded within a long-established 24/7 alcohol and drug helpline. We sought to analyse routinely collected program data in a preliminary study to examine the effectiveness of Ready2Change in reducing substance use problem severity and psychological distress.

METHODS

A retrospective analysis of program data from December 2013 to June 2018 was performed. Analysed cases were 249 clients living in Victoria, Australia with alcohol (n = 191), methamphetamine (n = 40) or cannabis (n = 18) as their primary drug of concern. A within-subjects design was used to examine pre- and post-intervention substance use problem severity and psychological distress.

RESULTS

For alcohol cases, there was a statistically significant decrease in alcohol problem severity [AUDIT, mean difference = -12.7, 95% confidence interval (CI) -14.0, -11.5]. Statistically significant reductions in drug problem severity (DUDIT) were observed for methamphetamine (mean difference = -17.3, 95% CI -20.9, -13.7) and cannabis (mean difference = -15.9, 95% CI -22.3, -9.6) cases. All groups showed reductions in problem severity for other substances used (P < 0.05) and psychological distress (P < 0.001).

DISCUSSION AND CONCLUSIONS

Results suggest Ready2Change benefits clients with alcohol, methamphetamine and cannabis use problems, with the potential to improve treatment access for health inequity groups including those living in remote areas. These findings warrant further investigation into the effectiveness of this program.

Monitoring beliefs and physiological measures in students at risk for COVID-19 using wearable sensors and smartphone technology: Protocol for a mobile health study

BACKGROUND

The COVID-19 pandemic has impacted lives significantly and greatly affected an already vulnerable population, college students, in relation to mental health and public safety. Social distancing and isolation have brought about challenges to student's mental health. Mobile health apps and wearable sensors may help to monitor students at risk for COVID-19 and support their mental well-being.

OBJECTIVE

Through the use of a wearable sensor and smartphone-based survey completion, this study aimed to monitor students at risk for COVID-19.

METHODS

We conducted a prospective study of students, undergraduate and graduate, at a public university in the Midwest. Students were instructed to download the Fitbit, Social Rhythms, and Roadmap 2.0 apps onto their personal mobile devices (Android or iOS). Subjects consented to provide up to 10 saliva samples during the study period. Surveys were administered through the Roadmap 2.0 app at five timepoints - at baseline, 1-month later, 2-months later, 3-months later, and at study completion. The surveys gathered information regarding demographics, COVID-19 diagnoses and symptoms, and mental health resilience, with the aim of documenting the impact of COVID-19 on the college student population.

RESULTS

This study enrolled 2,158 college students between September 2020 and January 2021. Subjects are currently being followed on-study for one academic year. Data collection and analysis are ongoing.

CONCLUSIONS

This study examined student health and well-being during the COVID-19 pandemic. It also assessed the feasibility of wearable sensor use and survey completion in a college student population, which may inform the role of our mobile health tools on student health and well-being. Finally, using wearable sensor data, biospecimen collection, and self-reported COVID-19 diagnosis, our results may provide key data towards the development of a model for the early prediction and detection of COVID-19.

CLINICALTRIAL

ClinicalTrials.gov NCT04766788.

Magnetic resonance imaging analysis of human skull diploic venous anatomy

Background:

The skull diploic venous space (DVS) represents a potential route for cerebrospinal fluid (CSF) diversion and absorption in the treatment of hydrocephalus. The goal of this study was to carry out a detailed characterization of the drainage pattern of the DVS of the skull using high-resolution MRI, especially the diploic veins draining to the lacunae laterales (LLs) since the LLs constitute an important channel for the CSF to access the superior sagittal sinus and subsequently the systemic circulation. The objective was to identify those skull regions optimally suited for an intraosseous CSF diversion system.

Methods:

High-resolution, T1-weighted MRI scans from 20 adult and 16 pediatric subjects were selected for analysis. Skulls were divided into four regions, that is, frontal, parietal, temporal, and occipital. On each scan, a trained observer counted all diploic veins in every skull region. Each diploic vein was also followed to determine its final drainage pathway (i.e., dural venous sinus, dural vein, LL, or indeterminate).

Results:

In the adult age group, the frontal and occipital skull regions showed the highest number of diploic veins. However, the highest number of draining diploic veins connecting to the lacunae lateralis was found in the frontal and parietal skull region, just anterior and just posterior to the coronal suture. In the pediatric age group, the parietal skull region, just posterior to the coronal suture, showed the highest overall number of diploic veins and also the highest number of draining diploic veins connecting to the LL.

Conclusion:

This study suggested that diploic venous density across the skull varies with age, with more parietal diploic veins in the pediatric age range, and more occipital and frontal diploic veins in adults. If the DVS is ultimately used for CSF diversion, our anatomical data point to optimal sites for the insertion of specially designed intraosseous infusion devices for the treatment of hydrocephalus. Likely the optimal sites for CSF diversion would be the parietal region just posterior to the coronal suture in children, and in adults, frontal and/or parietal just anterior or just posterior to the coronal suture.

Monitoring Health Care Workers at Risk for COVID-19 Using Wearable Sensors and Smartphone Technology: Protocol for an Observational mHealth Study

BACKGROUND

Health care workers (HCWs) have been working on the front lines of the COVID-19 pandemic with high risks of viral exposure, infection, and transmission. Standard COVID-19 testing is insufficient to protect HCWs from these risks and prevent the spread of disease. Continuous monitoring of physiological data with wearable sensors, self-monitoring of symptoms, and asymptomatic COVID-19 testing may aid in the early detection of COVID-19 in HCWs and may help reduce further transmission among HCWs, patients, and families.

OBJECTIVE

By using wearable sensors, smartphone-based symptom logging, and biospecimens, this project aims to assist HCWs in self-monitoring COVID-19.

METHODS

We conducted a prospective, longitudinal study of HCWs at a single institution. The study duration was 1 year, wherein participants were instructed on the continuous use of two wearable sensors (Fitbit Charge 3 smartwatch and TempTraq temperature patches) for up to 30 days. Participants consented to provide biospecimens (ie, nasal swabs, saliva swabs, and blood) for up to 1 year from study entry. Using a smartphone app called Roadmap 2.0, participants entered a daily mood score, submitted daily COVID-19 symptoms, and completed demographic and health-related quality of life surveys at study entry and 30 days later. Semistructured qualitative interviews were also conducted at the end of the 30-day period, following completion of daily mood and symptoms reporting as well as continuous wearable sensor use.

RESULTS

A total of 226 HCWs were enrolled between April 28 and December 7, 2020. The last participant completed the 30-day study procedures on January 16, 2021. Data collection will continue through January 2023, and data analyses are ongoing.

CONCLUSIONS

Using wearable sensors, smartphone-based symptom logging and survey completion, and biospecimen collections, this study will potentially provide data on the prevalence of COVID-19 infection among HCWs at a single institution. The study will also assess the feasibility of leveraging wearable sensors and self-monitoring of symptoms in an HCW population.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04756869; https://clinicaltrials.gov/ct2/show/NCT04756869.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/29562.

Symptomatic malunion after midshaft clavicle fracture in an adolescent patient: a case report of surgical deformity correction using a 3D printed model

A 14-year-old boy underwent surgery for symptomatic malunion of the clavicle. This complication, which is uncommon in adults and adolescents, occurred after a displaced midshaft clavicle fracture that had been treated conservatively. Surgery may be considered if functional impairment, pain, weakness, fatigability and neurological symptoms persist in the presence of significant clavicular deformity. Our case was unusual because the patient had a symptomatic malunion and lost range of movement of his shoulder despite a minor degree of clavicular shortening. We adopted an approach used in lower limb deformity correction but not described for the clavicle in which corrective osteotomy was planned and practised using a three-dimensional printed model of the malunited clavicle. A three-dimensional printed model of the mirror image of the opposite clavicle served as a template of normal. Three-dimensional models were printed from the computed tomography data. The patient's symptoms resolved and he recovered full range of movement and shoulder function following the corrective osteotomy.

Real-time, personalized medicine through wearable sensors and dynamic predictive modeling: a new paradigm for clinical medicine

Accurately predicting the onset and course of a disease in an individual is a major unmet challenge in medicine due to the complex and dynamic nature of disease progression. Continuous data from wearable technologies and biomarker data with a fine time resolution provide a unique opportunity to learn more about disease evolution and to usher in a new era of personalized and real-time medicine. Herein, we propose the potential of real-time, continuously measured physiological data as a noninvasive biomarker approach for detecting disease transitions, using allogeneic hematopoietic stem cell transplant (HCT) patient care as an example. Additionally, we review a recent computational technique, the landscape dynamic network biomarker method, that uses biomarker data to identify transition states in disease progression and explore how to use it with both biomarker and physiological data for earlier detection of graft-versus-host disease specifically. Throughout, we argue that increased collaboration across multiple fields is essential to realizing the full potential of wearable and biomarker data in a new paradigm of personalized and real-time medicine.

Persistent influence of obliquity on ice age terminations since the Middle Pleistocene transition

Radiometric dating of glacial terminations over the past 640,000 years suggests pacing by Earth's climatic precession, with each glacial-interglacial period spanning four or five cycles of ~20,000 years. However, the lack of firm age estimates for older Pleistocene terminations confounds attempts to test the persistence of precession forcing. We combine an Italian speleothem record anchored by a uranium-lead chronology with North Atlantic ocean data to show that the first two deglaciations of the so-called 100,000-year world are separated by two obliquity cycles, with each termination starting at the same high phase of obliquity, but at opposing phases of precession. An assessment of 11 radiometrically dated terminations spanning the past million years suggests that obliquity exerted a persistent influence on not only their initiation but also their duration.

A structured telephone-delivered intervention to reduce problem alcohol use (Ready2Change): study protocol for a parallel group randomised controlled trial

Background

Current population surveys suggest around 20% of Australians meet diagnostic criteria for an alcohol use disorder. However, only a minority seek professional help due to individual and structural barriers, such as low health literacy, stigma, geography, service operating hours and wait lists. Telephone-delivered interventions are readily accessible and ideally placed to overcome these barriers. We will conduct a randomised controlled trial (RCT) to examine the efficacy of a standalone, structured telephone-delivered intervention to reduce alcohol consumption, problem severity and related psychological distress among individuals with problem alcohol use.

Methods/design

This is a single site, parallel group, two-arm superiority RCT. We will recruit 344 participants from across Australia with problem alcohol use. After completing a baseline assessment, participants will be randomly allocated to receive either the Ready2Change (R2C) intervention (n = 172, four to six sessions of structured telephone-delivered intervention, R2C self-help resource, guidelines for alcohol consumption and stress management pamphlets) or the control condition (n = 172, four phone check-ins < 5 min, guidelines for alcohol consumption and stress management pamphlets). Telephone follow-up assessments will occur at 4–6 weeks, 3 months, 6 months and 12 months post-baseline. The primary outcome is the Alcohol Use Disorders Identification Test (AUDIT) score administered at 3 months post-baseline. Secondary outcomes include change in AUDIT score (6 and 12 months post-baseline), change in number of past-month heavy drinking days, psychological distress, health and wellbeing, quality of life, client treatment evaluation and cost effectiveness.

Discussion

This study will be one of the first RCTs conducted internationally to examine the impact of a standalone, structured telephone-delivered intervention to address problem alcohol use and associated psychological morbidity. The proposed intervention is expected to contribute to the health and wellbeing of individuals who are otherwise unlikely to seek treatment through mainstream service models, to reduce the burden on specialist services and primary care providers and to provide an accessible and proportionate response, with resulting cost savings for the health system and broader community.

Trial registration

Australian New Zealand Clinical Trials Registry, ACTRN12618000828224. Pre-registered on 16 May 2018.

Electronic supplementary material

The online version of this article (10.1186/s13063-019-3462-9) contains supplementary material, which is available to authorized users.

Multimessenger observations of a flaring blazar coincident with high-energy neutrino IceCube-170922A

Previous detections of individual astrophysical sources of neutrinos are limited to the Sun and the supernova 1987A, whereas the origins of the diffuse flux of high-energy cosmic neutrinos remain unidentified. On 22 September 2017, we detected a high-energy neutrino, IceCube-170922A, with an energy of ~290 tera–electron volts. Its arrival direction was consistent with the location of a known γ-ray blazar, TXS 0506+056, observed to be in a flaring state. An extensive multiwavelength campaign followed, ranging from radio frequencies to γ-rays. These observations characterize the variability and energetics of the blazar and include the detection of TXS 0506+056 in very-high-energy γ-rays. This observation of a neutrino in spatial coincidence with a γ-ray–emitting blazar during an active phase suggests that blazars may be a source of high-energy neutrinos.

Intraosseous infusion into the skull: potential application for the management of hydrocephalus

OBJECT

Hydrocephalus results from abnormal cerebrospinal fluid (CSF) volumes or flow patterns. The absorption of CSF is determined largely by pressures within veins and venous sinuses in the head and adjacent to the spine. Most surgical solutions for hydrocephalus involve diversion of excess CSF into alternative absorption sites, and most of these solutions are still suboptimal. The focus of this work has been to recreate more normal CSF absorption into the dural venous sinuses without having to directly access the superior sagittal sinus (SSS).

METHODS

Intraosseous skull infusion for the purpose of accessing the SSS and the systemic venous system was tested by experimental skull infusions of tracer fluids into living large animals (14 adult pigs). Compared with control injections into an ear vein, infusions into the skull through specially designed infusion devices had similar systemic absorption characteristics. This suggested that intraosseous skull infusion in a living large animal was successful in gaining access to the SSS and systemic venous system.

CONCLUSIONS

This study constitutes the first demonstration of the success of intraosseous skull infusion in gaining rapid access to the systemic venous system and it thus opens the possibility of using this strategy for diversion of CSF back into the intracranial venous system for the treatment of hydrocephalus.

A relative reduction in mid-follicular LH concentrations during GnRH agonist IVF/ICSI cycles leads to lower live birth rates

BACKGROUND

The effect of early- and mid-follicular LH concentrations on the ovarian response and pregnancy outcomes was evaluated in women receiving pituitary down-regulation with a GnRH agonist and ovarian stimulation with recombinant FSH (rFSH) during IVF/ICSI treatment.

METHODS

Blood samples were collected prospectively from 701 cycles (560 patients) of assisted reproduction and analysed retrospectively. On the basis of LH concentrations on stimulation day 7/8, the patients were divided into two groups: LH<1.2 IU/l (n=179) and LH>or=1.2 IU/l (n=522). Cycle outcomes were also compared on the basis of a ratio of mid- to early-follicular LH concentrations (<or=0.5, n=210; >0.5, n=491).

RESULTS

Patients with low LH concentrations were found to have a significant reduction in the late-follicular estradiol concentrations (P<0.001), the number of oocytes retrieved (P<0.01) and the number of usable embryos (P<0.01), and they required significantly more rFSH (430 IU difference, P<0.01). These differences did not translate into a significant change in live birth rates. Conversely, a ratio of <or=0.5 mid- to early-follicular LH concentrations (a reduction of >or=50%) was associated with a significant reduction in live birth rates per embryo transfer and per cycle started (27.3 versus 19.0%, P<0.05 and 22.2 versus 15.8%, P<0.05, respectively).

CONCLUSIONS

Low mid-follicular levels of LH have a significant impact on ovarian response but not on live birth rates. A fall in LH level of >or=50% from the early- to mid-follicular phase resulted in a lower live birth rate.