Measurement of the ^{140}Ce(n,γ) Cross Section at n_TOF and Its Astrophysical Implications for the Chemical Evolution of the Universe

^{140}Ce(n,γ) is a key reaction for slow neutron-capture (s-process) nucleosynthesis due to being a bottleneck in the reaction flow. For this reason, it was measured with high accuracy (uncertainty ≈5%) at the n_TOF facility, with an unprecedented combination of a high purity sample and low neutron-sensitivity detectors. The measured Maxwellian averaged cross section is up to 40% higher than previously accepted values. Stellar model calculations indicate a reduction around 20% of the s-process contribution to the Galactic cerium abundance and smaller sizeable differences for most of the heavier elements. No variations are found in the nucleosynthesis from massive stars.

Is Quadriceps-Strengthening Exercises (QSE) in Medial-Compartment Knee Osteoarthritis with Neutral and Varus Malalignment a Paradox? - A Risk-Appraisal of Strength-Training on Disease Progression

Introduction

The present inquiry seeks to investigate whether the current regimens of QSEs (Quadriceps-Strengthening Exercises) aggravate the disease while mitigating symptoms.

Materials and methods

A comparative study was conducted on 32 patients with medial compartment osteoarthritis of knees. While the neutral group of 16 patients was constituted of those with an anatomical-lateral-femoro-tibial-angle (aFTA) 176-180º, varus group comprised an equal number of patients with an aFTA >180º. A home-based 12-week strength-training program involving weekly visits to hospital for supervised sessions was administered. The outcome measures were visual-analog-scale (VAS), medial patello-femoral joint tenderness (MPFJT), time-up-and-go-test (TUGT), stair-climb test, step test, WOMAC, IKDC scores, aFTA, hip-knee-ankle (HKA) angle, lateral-tibio-femoral-joint-separation (LTFJS), and horizontal-distance-from-centre-of-knee-to-Mikulicz-line.

Results

There was a significant increase in quadriceps strength (p<0.01) in both groups. Values for neutral group with VAS score (p=0.01), MPFJT (p=0.01), TUGT (p=0.01), timing of the stair climb test (p=0.01), WOMAC (p<0.01), and IKDC (p=0.03) were better compared to varus group with VAS score (p=0.13), MPFJT (p=0.03), TUGT (p=0.90), timing of stair climb test (p=0.68), WOMAC (p<0.02), and IKDC (p=0.05). Varus group also showed an increase in aFTA and LTFJS in 12 patients, increase in HKA in 11, and increase in horizontal distance from the centre of knee to the Mikulicz line in 7 patients.

Conclusion

The present study brings to the fore the paradoxical role played by QSEs in management of medial knee OA. While there is a radiological progression of the disease in both neutral and varus mal-aligned knees more so in the latter than the former.

Tests of Light-Lepton Universality in Angular Asymmetries of B^{0}→D^{*-}ℓν Decays

We present the first comprehensive tests of the universality of the light leptons in the angular distributions of semileptonic B^{0}-meson decays to charged spin-1 charmed mesons. We measure five angular-asymmetry observables as functions of the decay recoil that are sensitive to lepton-universality-violating contributions. We use events where one neutral B is fully reconstructed in ϒ(4S)→BB[over ¯] decays in data corresponding to 189  fb^{-1} integrated luminosity from electron-positron collisions collected with the Belle II detector. We find no significant deviation from the standard model expectations.

Measurement of CP Violation in B^{0}→K_{S}^{0}π^{0} Decays at Belle II

We report a measurement of the CP-violating parameters C and S in B^{0}→K_{S}^{0}π^{0} decays at Belle II using a sample of 387×10^{6}  BB[over ¯] events recorded in e^{+}e^{-} collisions at a center-of-mass energy corresponding to the ϒ(4S) resonance. These parameters are determined by fitting the proper decay-time distribution of a sample of 415 signal events. We obtain C=-0.04_{-0.15}^{+0.14}±0.05 and S=0.75_{-0.23}^{+0.20}±0.04, where the first uncertainties are statistical and the second are systematic.

AMR Sign - An Arthroscopic S-shaped Fold Signifying Adequate Medial Meniscus Repair

Introduction

The preferred management of medial meniscus tears has notably moved from meniscectomies towards repair. With a higher volume of meniscal repairs being done all across the world with every passing day, the lack of an objective and definitive sign suggesting the adequacy of its repair is daunting. The purpose of our study was to introduce a unique and novel arthroscopic sign formed after adequate repair of the medial meniscus, the AMR (Adequacy of Medial meniscus Repair) sign. We hypothesised that it is not only the objective end point for repair, but can also form the indicator for excellent clinical, functional, and radiological outcome even in the long term.

Materials and methods

This was a multicentric, prospective study initiated by the corresponding author, and the findings validated subsequently by the other authors. Overall, it included 804 patients of isolated medial meniscus tear operated with arthroscopic all-inside technique between January 2014 and December 2017. Patients were segregated into three groups based on whether an S-shaped curve in the free, inner edge of the medial meniscus sign was formed post-repair, lost after further tightening, or not formed upon subjective completion of repair. All the patients were followed-up and evaluated based of medial joint line tenderness, McMurray's test for medial meniscus, IKDC score, WOMET score, and radiologically using an MRI at the terminal follow-up.

Results

The mean terminal follow-up was 42.34±4.54 months. There was significant (p<0.01) improvement in all patients at the terminal follow-up post-surgery, irrespective of the group. The group in which AMR sign was formed and maintained showed a significantly better functional outcome on terminal follow-up as well as lower failure rates compared to the other two groups.

Conclusion

AMR sign is an S-shaped fold at the inner, free edge of medial meniscus, formed after an adequate repair of isolated medial meniscus tear, as viewed on arthroscopy. It is an objective sign denoting regained integrity of the collagen architecture of the medial meniscus following repair. It is also a reliable indicator of excellent long term functional, clinical, and radiological outcome and also lower failure rates in patients after arthroscopic medial meniscus repair.

Search for the Lepton Flavor Violating Decays B^{+}→K^{+}τ^{±}ℓ^{∓} (ℓ=e, μ) at Belle

We present a search for the lepton flavor violating decays B^{+}→K^{+}τ^{±}ℓ^{∓}, with ℓ=(e,μ), using the full data sample of 772×10^{6}  BB[over ¯] pairs recorded by the Belle detector at the KEKB asymmetric-energy e^{+}e^{-} collider. We use events in which one B meson is fully reconstructed in a hadronic decay mode. We find no evidence for B^{±}→K^{±}τℓ decays and set upper limits on their branching fractions at the 90% confidence level in the (1-3)×10^{-5} range. The obtained limits are the world's best results.

End-of-life solar photovoltaic panel waste management in India: forecasting and environmental impact assessment

Presently, India is in the stage of installation of solar photovoltaic panels and no focus is being given towards the impending problem of handling solar waste. The absence of adequate regulations, guidelines and operational infrastructure for photovoltaic waste in the country may lead to waste being inappropriately landfilled or incinerated in a manner that may be detrimental to human health and the environment. Business as usual projection estimates 6.64 million tonnes and 5.48 million tonnes of waste generation due to the early and regular losses using the Weibull distribution function, respectively by 2040 in India. The current study also systematically investigates various policies and legislation developments on the end-of-life of photovoltaic modules in various regions of the world, to identify gaps for further assessment. Using life cycle assessment methodology, this paper compares the environmental impacts of landfilling end-of-life crystalline silicon panels with avoided burden approach due to the recycling of materials. It has been demonstrated that solar photovoltaic recycling and reusing the recovered materials will result in impact reduction in the forthcoming production phase by as high as 70%. Further, the outcomes of carbon footprint, single score indicator with the application of Intergovernmental Panel on Climate Change also predicts lower values for avoided burden approach due to recycling (15,393.96 kgCO2 eq) in comparison to landfill approach (19,844.054 kg CO2 eq). The outcomes of this study aim to illuminate the importance of the sustainable management of photovoltaic panels at end-of-life.

First Measurement of the B^{+}→π^{+}π^{0}π^{0} Branching Fraction and CP Asymmetry

We study B^{+}→π^{+}π^{0}π^{0} using 711  fb^{-1} of data collected at the ϒ(4S) resonance with the Belle detector at the KEKB asymmetric-energy e^{+}e^{-} collider. We measure an inclusive branching fraction of (19.0±1.5±1.4)×10^{-6} and an inclusive CP asymmetry of (9.2±6.8±0.7)%, where the first uncertainties are statistical and the second are systematic, and a B^{+}→ρ(770)^{+}π^{0} branching fraction of (11.2±1.1±0.9_{-1.6}^{+0.8})×10^{-6}, where the third uncertainty is due to possible interference with B^{+}→ρ(1450)^{+}π^{0}. We present the first observation of a structure around 1  GeV/c^{2} in the π^{0}π^{0} mass spectrum, with a significance of 6.4σ, and measure a branching fraction to be (6.9±0.9±0.6)×10^{-6}. We also report a measurement of local CP asymmetry in this structure.

Use of topic modeling to assess research trends in the journal Gynecologic Oncology

STUDY OBJECTIVE

There is scant research identifying thematic trends within medical research. This work may provide insight into how a given field values certain topics. We assessed the feasibility of using a machine learning approach to determine the most common research themes published in Gynecologic Oncology over a thirty-year period and to subsequently evaluate how interest in these topics changed over time.

METHODS

We retrieved the abstracts of all original research published in Gynecologic Oncology from 1990 to 2020 using PubMed. Abstract text was processed through a natural language processing algorithm and clustered into topical themes using latent Dirichlet allocation (LDA) prior to manual labeling. Topics were investigated for temporal trends.

RESULTS

We retrieved 12,586 original research articles, of which 11,217 were evaluable for subsequent analysis. Twenty-three research topics were selected at the completion of topic modeling. The topics of basic science genetics, epidemiologic methods, and chemotherapy experienced the greatest increase over the time period, while postoperative outcomes, reproductive age cancer management, and cervical dysplasia experienced the greatest decline. Interest in basic science research remained relatively constant. Topics were additionally reviewed for words indicative of either surgical or medical therapy. Both surgical and medical topics saw increasing interest, with surgical topics experiencing a greater increase and representing a higher proportion of published topics.

CONCLUSIONS

Topic modeling, a type of unsupervised machine learning, was successfully used to identify trends in research themes. The application of this technique provided insight into how the field of gynecologic oncology values the components of its scope of practice and therefore how it may choose to allocate grant funding, disseminate research, and participate in the public discourse.

First Observation of Λπ^{+} and Λπ^{-} Signals near the K[over ¯]N(I=1) Mass Threshold in Λ_{c}^{+}→Λπ^{+}π^{+}π^{-} Decay

Using the data sample of 980  fb^{-1} collected with the Belle detector operating at the KEKB asymmetric-energy e^{+}e^{-} collider, we present the results of an investigation of the Λπ^{+} and Λπ^{-} invariant mass distributions looking for substructure in the decay Λ_{c}^{+}→Λπ^{+}π^{+}π^{-}. We find a significant signal in each mass distribution. When interpreted as resonances, we find for the Λπ^{+} (Λπ^{-}) combination a mass of 1434.3±0.6(stat)±0.9(syst)  MeV/c^{2} [1438.5±0.9(stat)±2.5(syst)  MeV/c^{2}], an intrinsic width of 11.5±2.8(stat)±5.3(syst)  MeV/c^{2} [33.0±7.5(stat)±23.6(syst)  MeV/c^{2}] with a significance of 7.5σ (6.2σ). As these two signals are very close to the K[over ¯]N threshold, we also investigate the possibility of a K[over ¯]N cusp, and find that we cannot discriminate between these two interpretations due to the limited size of the data sample.

Evidence of a New Excited Charmed Baryon Decaying to Σ_{c}(2455)^{0,++}π^{±}

We present the study of B[over ¯]^{0}→Σ_{c}(2455)^{0,++}π^{±}p[over ¯] decays based on 772×10^{6}  BB[over ¯] events collected with the Belle detector at the KEKB asymmetric-energy e^{+}e^{-} collider. The Σ_{c}(2455)^{0,++} candidates are reconstructed via their decay to Λ_{c}^{+}π^{∓} and Λ_{c}^{+} decays to pK^{-}π^{+}, pK_{S}^{0}, and Λπ^{+} final states. The corresponding branching fractions are measured to be B(B[over ¯]^{0}→Σ_{c}(2455)^{0}π^{+}p[over ¯])=(1.09±0.06±0.07)×10^{-4} and B(B[over ¯]^{0}→Σ_{c}(2455)^{++}π^{-}p[over ¯])=(1.84±0.11±0.12)×10^{-4}, which are consistent with the world average values with improved precision. A new structure is found in the M_{Σ_{c}(2455)^{0,++}π^{±}} spectrum with a significance of 4.2σ including systematic uncertainty. The structure is possibly an excited Λ_{c}^{+} and is tentatively named Λ_{c}(2910)^{+}. Its mass and width are measured to be (2913.8±5.6±3.8)  MeV/c^{2} and (51.8±20.0±18.8)  MeV, respectively. The products of branching fractions for the Λ_{c}(2910)^{+} are measured to be B(B[over ¯]^{0}→Λ_{c}(2910)^{+}p[over ¯])×B(Λ_{c}(2910)^{+}→Σ_{c}(2455)^{0}π^{+})=(9.5±3.6±1.6)×10^{-6} and B(B[over ¯]^{0}→Λ_{c}(2910)^{+}p[over ¯])×B(Λ_{c}(2910)^{+}→Σ_{c}(2455)^{++}π^{-})=(1.24±0.35±0.10)×10^{-5}. Here, the first and second uncertainties are statistical and systematic, respectively.

Vacuum rhexis - A novel capsulorhexis technique for white cataracts

Capsulorhexis in white intumescent cataract is often associated with extension leading to radial tears or biradial extension "Argentinian flag sign" and associated complications. We describe a novel technique of managing this situation. Vacuum rhexis is performed with a 24 G bent cannula attached to a 10-ml syringe. The flap is lifted and then caught using 24 G cannula. The suction is manually controlled by the surgeon, and the rhexis is completed using circumferential movement. The chamber stability is well maintained as there is no leakage, and the bent tip gives excellent fulcrum for movement. The advantage of this technique is that a single port is used for maintaining the chamber stability and it needs no special surgical instruments. Vacuum rhexis is a novel surgical technique used for performing successful continuous curvilinear capsulorhexis (CCC) of adequate size in white and intumescent cataracts, with a consistent and predictable outcome.

Risk of selection bias assessment in the NINDS rt-PA stroke study

OBJECTIVES

The NINDS rt-PA Stroke Study is frequently cited in support of alteplase for acute ischemic stroke within 3 h of symptom onset. Multiple post-hoc reanalyses of this trial have been published to adjust for a baseline imbalance in stroke severity. We performed a risk of selection bias assessment and reanalyzed trial data to determine if the etiology of this baseline imbalance was more likely due to random chance or randomization errors.

METHODS

A risk of selection bias assessment was conducted using signaling questions from the Cochrane Risk of Bias 2 (ROB 2) tool. Four sensitivity analyses were conducted on the trial data based on the randomization process: assessment of imbalances in allocation in unique strata; adherence to a pre-specified restriction on randomization between time strata at each randomization center; assessment of differences in baseline computed tomography (CT) results in unique strata; and comparison of baseline characteristics between allocation groups within each time strata. A multivariable logistic regression model was used to compare reported treatment effects with revised treatment effects after adjustment of baseline imbalances identified in the sensitivity analyses.

RESULTS

Based on criteria from the ROB 2 tool, the risk of bias arising from the randomization process was high. Sensitivity analyses found 11 of 16 unique strata deviated from the expected 1:1 allocation ratio. Three randomization centers violated an apriori rule regarding a maximum difference in allocation between the time strata. Three unique strata had imbalances in baseline CT results that prognostically favored alteplase. Four imbalances in baseline characteristics were identified in the 91-180-min time stratum that all prognostically favored alteplase and were consistent with a larger alteplase treatment effect size compared to the 0-90-min time stratum. After adjustments for baseline imbalances, all reported treatment effects were reduced. Three out of seven originally positive reported results were revised to non-significant.

CONCLUSION

This risk of selection bias assessment revealed a high risk of selection bias in the NINDS rt-PA Stroke Study. Sensitivity analyses conducted based on the randomization process supported this assessment. Baseline imbalances in the trial were more likely due to randomization errors than random chance. Adjusted analyses accounting for baseline imbalances revealed a reduction in reported treatment effects supporting the presence of selection bias in the trial. Treatment decisions and guideline recommendations based on the original treatment effect reported in the NINDS rt-PA Stroke Study should be done cautiously.

Methodological survey of missing outcome data in an alteplase for ischemic stroke meta-analysis

OBJECTIVE

Recent national guidelines recommend alteplase treatment for ischemic stroke within 4.5 h of symptom-onset based on meta-analyses of randomized controlled clinical trials (RCT). A detailed description of missing outcome data (MOD) due to participant loss to follow-up has never been published. The objective of this study was to perform a methodlogical survey on missing outcome data in an alteplase for ischemic stroke meta-analysis.

MATERIALS AND METHODS

A methodological survey was performed on a chosen meta-analysis of alteplase for ischemic stroke RCTs that most closely aligns with recent national guideline recommendations. Data were collected to assess the number of participants lost to follow-up; differential lost to follow-up between allocation groups; baseline characteristics of those lost to follow-up; and the imputation methods used by individual trials and the chosen meta-analysis. The number of participants lost to follow-up was compared with the fragility index; and repeated for individually positive RCTs in the meta-analysis.

RESULTS

The methodological survey revealed a substantial degree of missing information regarding MOD in the chosen meta-analysis and in individual RCTs. Single imputation was exclusively used in all RCTs and in the meta-analysis. The number of participants lost to follow-up was greater than the fragility index in the chosen meta-analysis and individually positive component RCTs suggesting that MOD may impact the direction of the reported effect or effect size.

CONCLUSION

This methodological survey of an alteplase for ischemic stroke meta-analysis revealed MOD may be an important source of unrecognized bias. This survey highlights the need for sensitivity analyses using more robust methods of imputation.

NeuroBlu: a natural language processing (NLP) electronic health record (EHR) data analytic tool to generate real-world evidence in mental healthcare

Introduction

EHRs contain a rich source of real-world data that can support evidence generation to better understand mental disorders and improve treatment outcomes. However, EHR datasets are complex and include unstructured free text data that are time consuming to manually review and analyse. We present NeuroBlu, a secure, cloud-based analytic tool that includes bespoke NLP software to enable users to analyse large volumes of EHR data to generate real-world evidence in mental healthcare.

Objectives

(i) To assemble a large mental health EHR dataset in a secure, cloud-based environment.

(ii) To apply NLP software to extract data on clinical features as part of the Mental State Examination (MSE).

(iii) To analyse the distribution of NLP-derived MSE features by psychiatric diagnosis.

Methods

EHR data from 25 U.S. mental healthcare providers were de-identified and transformed into a common data model. NLP models were developed to extract 241 MSE features using a deep learning, long short-term memory (LSTM) approach. The NeuroBlu tool (https://www.neuroblu.ai/) was used to analyse the associations of MSE features in 543,849 patients.

Results

The figure below illustrates the percentage of patients in each diagnostic category with at least one recorded MSE feature.

Conclusions

Delusions and hallucinations were more likely to be recorded in people with schizophrenia and schizoaffective disorder, and cognitive features were more likely to be recorded in people with dementia. However, mood symptoms were frequently recorded across all diagnoses illustrating their importance as a transdiagnostic clinical feature. NLP-derived clinical information could enhance the potential of EHR data to generate real-world evidence in mental healthcare.

Disclosure

This study was funded in full by Holmusk.

Feasibility and Prediction of Adverse Events in a Postoperative Monitoring Program of Patient-Reported Outcomes and a Wearable Device Among Gynecologic Oncology Patients

PURPOSE

The objective of this study was to test the feasibility of implementing a postoperative monitoring program for women with gynecologic cancers composed of patient-reported outcomes (PROs) and a wearable activity monitor.

METHODS

We prospectively enrolled patients undergoing gynecologic cancer surgery to this single-arm study. Enrolled patients completed PROs (Patient-Reported Outcomes Measurement Information System physical function, sleep disturbance, anxiety, fatigue, and pain intensity) at baseline and one-week intervals for 4 weeks. They also wore a wearable accelerometer device that measured steps, heart rate, and intensity of physical activity. The primary outcome was feasibility. The secondary outcome was prediction of unscheduled contacts with the health care system on a given postoperative day.

RESULTS

We enrolled 34 women. Three patients were unevaluable. The mean age was 58 years. The mean body mass index was 31 kg/m²; 17 patients were White (54.8%), 12 patients were Black (38.7%), and two patients (6.5%) were Asian. The overall wear time was 83.8%, and patients responded to 80.4% of the PRO instruments. Twenty-two patients (71%) had an unscheduled contact with the health care system postoperatively (median 1.5, 0.0-8.0). The day of an unscheduled health care utilization event was predicted with acceptable discrimination (area under the receiver operating characteristic curve 0.75; 95% CI, 0.67 to 0.81). PROs of fatigue and physical function were most predictive followed by wearable device outputs of lightly active minutes and average daily heart rate.

CONCLUSION

Implementation of a postoperative monitoring program of patient-reported outcomes and a wearable device was feasible. The specific day of an unscheduled contact with the health care system was predicted with acceptable discrimination.

Measurement of Two-Particle Correlations of Hadrons in e^{+}e^{-} Collisions at Belle

The measurement of two-particle angular correlation functions in high-multiplicity e^{+}e^{-} collisions at sqrt[s]=10.52  GeV is reported. In this study, the 89.5  fb^{-1} of hadronic e^{+}e^{-} annihilation data collected by the Belle detector at KEKB are used. Two-particle angular correlation functions are measured in the full relative azimuthal angle (Δϕ) and three units of pseudorapidity (Δη), defined by either the electron beam axis or the event-shape thrust axis, and are studied as a function of charged-particle multiplicity. The measurement in the thrust axis analysis, with mostly outgoing quark pairs determining the reference axis, is sensitive to the region of additional soft gluon emissions. No significant anisotropic collective behavior is observed with either coordinate analyses. Near-side jet correlations appear to be absent in the thrust axis analysis. The measurements are compared to predictions from various event generators and are expected to provide new constraints to the phenomenological models in the low-energy regime.

Search for a Light Higgs Boson in Single-Photon Decays of ϒ(1S) Using ϒ(2S)→π^{+}π^{-}ϒ(1S) Tagging Method

We search for a light Higgs boson (A^{0}) decaying into a τ^{+}τ^{-} or μ^{+}μ^{-} pair in the radiative decays of ϒ(1S). The production of ϒ(1S) mesons is tagged by ϒ(2S)→π^{+}π^{-}ϒ(1S) transitions, using 158×10^{6} ϒ(2S) events accumulated with the Belle detector at the KEKB asymmetric energy electron-positron collider. No significant A^{0} signals in the mass range from the τ^{+}τ^{-} or μ^{+}μ^{-} threshold to 9.2  GeV/c^{2} are observed. We set the upper limits at 90% credibility level (C.L.) on the product branching fractions for ϒ(1S)→γA^{0} and A^{0}→τ^{+}τ^{-} varying from 3.8×10^{-6} to 1.5×10^{-4}. Our results represent an approximately twofold improvement on the current world best upper limits for the ϒ(1S)→γA^{0}(→τ^{+}τ^{-}) production. For A^{0}→μ^{+}μ^{-}, the upper limits on the product branching fractions for ϒ(1S)→γA^{0} and A^{0}→μ^{+}μ^{-} are at the same level as the world average limits, and vary from 3.1×10^{-7} to 1.6×10^{-5}. The upper limits at 90% credibility level on the Yukawa coupling f_{ϒ(1S)} and mixing angle sinθ_{A^{0}} are also given.

First 80Se(n,γ) cross section measurement with high resolution in the full stellar energy range 1 eV - 100 keV and its astrophysical implications for the s-process

Most elements heavier than iron have been generated in the stellar media by means of neutron capture reactions, approximately half are produced by the slow neutron capture or s-process. Radiative neutron capture cross section measurements are of fundamental importance for the study of this mechanism. In this contribution we present a brief summary on the measurement and results for the 80Se(n,γ) cross-section. The experiment was carried out at CERN n_TOF EAR1 via the time of flight (ToF) technique, using four C6D6 scintillation detectors with very fast response. More than a hundred new resonances have been analyzed for the first time with a high accuracy. The MACS obtained at kT = 8 keV is 36% smaller than the recommended value in KADo-NiS. Some of the astrophysical implications of this result are elucidated in this contribution.

Abstract TP119: Celecoxib In Aneurysmal Subarachnoid Hemorrhage: A Single Center Experience

Introduction: Inflammation may play a central role in delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage (aSAH). Prostaglandins are inflammatory mediators that are elevated in aSAH and are synthesized by cyclooxygenase-2 (Cox-2). Celecoxib is a selective Cox-2 inhibitor with anti-inflammatory effects and good central nervous system penetration. In a mouse model of SAH, Cox-2 gene expression was found to be up-regulated in brain endothelial cells and celecoxib was found to limit Cox-2 up-regulation. We sought to evaluate the safety of celecoxib in patients with aSAH for future clinical studies.

Methods: We used a matched case-control study to evaluate safety of celecoxib in aSAH patients. Our prospectively collected aSAH database (N=230) was retrospectively reviewed from 1/2010 - 2/2020. Celecoxib cases (N=13) and controls (N=217) were matched by closest Euclidean distance based on age and Glasgow Coma Scale (Figure 1). Each case was matched with 4 controls to maximize power based on closest Euclidean distance. Baseline characteristics for cases and controls were compared using a t-test or signed rank test for pairs. Categorical variables were compared using McNemar’s test for discordant pairs. A p value ≤.05 was considered significant for all univariate testing. Results are listed in Table 1.

Discussion: No adverse events were associated with celecoxib use. At our center, celecoxib was primarily used in high grade aSAH for fever or headache. Maximum and mean temperature are statistically higher in the celecoxib group, consistent with the treatment indication. There were no differences in vasospasm prevalence, although our analysis is limited by sample size. Given the favorable safety profile, ease of drug availability, and plausible mechanism of therapeutic effect, celecoxib warrants further study in aSAH.

Measurement of Differential Branching Fractions of Inclusive B→X_{u}ℓ^{+}ν_{ℓ} Decays

The first measurements of differential branching fractions of inclusive semileptonic B→X_{u}ℓ^{+}ν_{ℓ} decays are performed using the full Belle data set of 711  fb^{-1} of integrated luminosity at the ϒ(4S) resonance and for ℓ=e, μ. With the availability of these measurements, new avenues for future shape-function model-independent determinations of the Cabibbo-Kobayashi-Maskawa matrix element |V_{ub}| can be pursued to gain new insights in the existing tension with respect to exclusive determinations. The differential branching fractions are reported as a function of the lepton energy, the four-momentum-transfer squared, light-cone momenta, the hadronic mass, and the hadronic mass squared. They are obtained by subtracting the backgrounds from semileptonic B→X_{c}ℓ^{+}ν_{ℓ} decays and other processes, and corrected for resolution and acceptance effects.

Measurements of the Branching Fractions of the Semileptonic Decays Ξ_{c}^{0}→Ξ^{-}ℓ^{+}ν_{ℓ} and the Asymmetry Parameter of Ξ_{c}^{0}→Ξ^{-}π^{+}

Using data samples of 89.5 and 711  fb^{-1} recorded at energies of sqrt[s]=10.52 and 10.58 GeV, respectively, with the Belle detector at the KEKB e^{+}e^{-} collider, we report measurements of branching fractions of semileptonic decays Ξ_{c}^{0}→Ξ^{-}ℓ^{+}ν_{ℓ} (ℓ=e or μ) and the CP-asymmetry parameter of Ξ_{c}^{0}→Ξ^{-}π^{+} decay. The branching fractions are measured to be B(Ξ_{c}^{0}→Ξ^{-}e^{+}ν_{e})=(1.31±0.04±0.07±0.38)% and B(Ξ_{c}^{0}→Ξ^{-}μ^{+}ν_{μ})=(1.27±0.06±0.10±0.37)%, and the decay parameter α_{Ξπ} is measured to be 0.63±0.03±0.01 with much improved precision compared with the current world average. The corresponding ratio B(Ξ_{c}^{0}→Ξ^{-}e^{+}ν_{e})/B(Ξ_{c}^{0}→Ξ^{-}μ^{+}ν_{μ}) is 1.03±0.05±0.07, which is consistent with the expectation of lepton flavor universality. The first measured asymmetry parameter A_{CP}=(α_{Ξ^{-}π^{+}}+α_{Ξ[over ¯]^{+}π^{-}})/(α_{Ξ^{-}π^{+}}-α_{Ξ[over ¯]^{+}π^{-}})=0.024±0.052±0.014 is found to be consistent with zero. The first and the second uncertainties above are statistical and systematic, respectively, while the third ones arise due to the uncertainty of the Ξ_{c}^{0}→Ξ^{-}π^{+} branching fraction.

Machine learning models improve prediction of large vessel occlusion and mechanical thrombectomy candidacy in acute ischemic stroke

BACKGROUND AND PURPOSE

Early identification of large vessel occlusions (LVO) and timely recanalization are paramount to improved clinical outcomes in acute ischemic stroke. A stroke assessment that maximizes sensitivity and specificity for LVOs is needed to identify these cases and not overburden the health system with unnecessary transfers. Machine learning techniques are being used for predictive modeling in many aspects of stroke care and may have potential in predicting LVO presence and mechanical thrombectomy (MT) candidacy.

METHODS

Ischemic stroke patients treated at Loyola University Medical Center from July 2018 to June 2019 (N = 286) were included. Thirty-five clinical and demographic variables were analyzed using machine learning algorithms, including logistic regression, extreme gradient boosting, random forest (RF), and decision trees to build models predictive of LVO presence and MT candidacy by area of the curve (AUC) analysis. The best performing model was compared with prior stroke scales.

RESULTS

When using all 35 variables, RF best predicted LVO presence (AUC = 0.907 ± 0.856-0.957) while logistic regression best predicted MT candidacy (AUC = 0.930 ± 0.886-0.974). When compact models were evaluated, a 10-feature RF model best predicted LVO (AUC = 0.841 ± 0.778-0.904) and an 8-feature RF model best predicted MT candidacy (AUC = 0.862 ± 0.782-0.942). The compact RF models had sensitivity, specificity, negative predictive value and positive predictive value of 0.81, 0.87, 0.92, 0.72 for LVO and 0.87, 0.97, 0.97, 0.86 for MT, respectively. The 10-feature RF model was superior at predicting LVO to all previous stroke scales (AUC 0.944 vs 0.759-0.878) and the 8-feature RF model was superior at predicting MT (AUC 0.970 vs 0.746-0.834).

CONCLUSION

Random forest machine learning models utilizing clinical and demographic variables predicts LVO presence and MT candidacy with a high degree of accuracy in an ischemic stroke cohort. Further validation of this strategy for triage of stroke patients requires prospective and external validation.

Prediction of 30-Day Readmission After Stroke Using Machine Learning and Natural Language Processing

Background and Purpose: This study aims to determine whether machine learning (ML) and natural language processing (NLP) from electronic health records (EHR) improve the prediction of 30-day readmission after stroke.

Methods: Among index stroke admissions between 2011 and 2016 at an academic medical center, we abstracted discrete data from the EHR on demographics, risk factors, medications, hospital complications, and discharge destination and unstructured textual data from clinician notes. Readmission was defined as any unplanned hospital admission within 30 days of discharge. We developed models to predict two separate outcomes, as follows: (1) 30-day all-cause readmission and (2) 30-day stroke readmission. We compared the performance of logistic regression with advanced ML algorithms. We used several NLP methods to generate additional features from unstructured textual reports. We evaluated the performance of prediction models using a five-fold validation and tested the best model in a held-out test dataset. Areas under the curve (AUCs) were used to compare discrimination of each model.

Results: In a held-out test dataset, advanced ML methods along with NLP features out performed logistic regression for all-cause readmission (AUC, 0.64 vs. 0.58; p < 0.001) and stroke readmission prediction (AUC, 0.62 vs. 0.52; p < 0.001).

Conclusion: NLP-enhanced machine learning models potentially advance our ability to predict readmission after stroke. However, further improvement is necessary before being implemented in clinical practice given the weak discrimination.

Test of Lepton-Flavor Universality in B→K^{*}ℓ^{+}ℓ^{-} Decays at Belle

We present a measurement of R_{K^{*}}, the branching fraction ratio B(B→K^{*}μ^{+}μ^{-})/B(B→K^{*}e^{+}e^{-}), for both charged and neutral B mesons. The ratio for the charged case R_{K^{*+}} is the first measurement ever performed. In addition, we report absolute branching fractions for the individual modes in bins of the squared dilepton invariant mass q^{2}. The analysis is based on a data sample of 711  fb^{-1}, containing 772×10^{6}  BB[over ¯] events, recorded at the ϒ(4S) resonance with the Belle detector at the KEKB asymmetric-energy e^{+}e^{-} collider. The obtained results are consistent with standard model expectations.

Evidence for X(3872)→J/ψπ^{+}π^{-} Produced in Single-Tag Two-Photon Interactions

We report the first evidence for X(3872) production in two-photon interactions by tagging either the electron or the positron in the final state, exploring the highly virtual photon region. The search is performed in e^{+}e^{-}→e^{+}e^{-}J/ψπ^{+}π^{-}, using 825  fb^{-1} of data collected by the Belle detector operated at the KEKB e^{+}e^{-} collider. We observe three X(3872) candidates, where the expected background is 0.11±0.10 events, with a significance of 3.2σ. We obtain an estimated value for Γ[over ˜]_{γγ}B(X(3872)→J/ψπ^{+}π^{-}) assuming the Q^{2} dependence predicted by a cc[over ¯] meson model, where -Q^{2} is the invariant mass squared of the virtual photon. No X(3915)→J/ψπ^{+}π^{-} candidates are found.

Abstract P506: Machine Learning Models Improve Prediction of Large Vessel Occlusion and Mechanical Thrombectomy Candidacy in Acute Ischemic Stroke

Background and Purpose: Early identification of large vessel occlusions (LVO) and timely recanalization are paramount in improved clinical outcomes in acute ischemic stroke. Multiple simple stroke scales have good sensitivity, but compromise specificity for predicting LVO. No scale has been shown to predict mechanical thrombectomy (MT) candidacy. Machine learning techniques are being used for predictive modeling in many aspects of stroke care and may have potential in predicting LVO presence and MT candidacy.

Methods: 287 acute ischemic stroke patients from July 2018 to July 2019 at Loyola University Medical Center were included. 36 clinical and demographic variables were analyzed using machine learning and statistical algorithms, including logistic regression, extreme gradient boosting, random forest, and decision trees to build models predictive of LVO and MT. The best performing model was compared with prior stroke scales.

Results: Random forest based model resulted in the highest classification performance to predict both LVO and MT outcomes with an area under the curve (AUC) of 0.90±0.07 and 0.94±0.04, respectively. When the predictors were reduced to 7, random forest maintained a high AUC for predicting LVO (0.89). When reduced to 10 predictors, the random forest model predicted MT with an AUC = 0.93. Random forest models had excellent sensitivity and specificity of 0.86 and 0.89 for LVO and 0.89 and 0.95 for MT, respectively. The negative predictive value was 0.94 for LVO and 0.98 for MT while the positive predictive value was 0.77 for LVO and 0.79 for MT. With equal sensitivity, the random forest model was favorable to all previous stroke scales.

Conclusion: Machine learning utilizing clinical and demographic variables predicts LVO and patient candidacy for MT with a high degree of accuracy. Further validation of this strategy for triage of stroke patients requires prospective and external validation.

Abstract MP32: Machine Learning Models Identify Predictors of Poor Outcome in Patients Undergoing Mechanical Thrombectomy for Acute Ischemic Stroke

Introduction: Predicting outcome after mechanical thrombectomy (MT) for ischemic stroke due to LVO can inform prognosis and guide early management. Prior studies report heterogeneity in risk factors for poor outcome. Machine learning may identify patterns of poor outcome from diverse variables that are difficult to discern with conventional statistical methods.

Methods: Using a retrospective database of 233 stroke patients (2015-20) who had MT for LVO, we created machine learning predictive models with clinical and imaging variables for the following 4 outcomes: decompressive craniectomy, discharge mRS ≥4, development of post-stroke cerebral edema with mass effect, and in-hospital mortality. We compared 10 learner models: AdaBoost, Tree, Random Forest, Neural Network, CN2 Rule Induction, Logistic Regression, Naïve Bayes, kNN, Stochastic Gradient Descent, and Support Vector Machine. Variables were ranked by 5 scoring methods: information gain, information gain ratio, gini decrease, chi-square, ReliefF, and fast correlation-based filter. A prediction model was created using the top 5 variables to maximize the area under the receiver operating characteristic curve and classification accuracy. Models were 5-fold cross validated. Analyses were conducted via Stata and Orange Data Mining.

Results: Prediction model sets of 5 variables were generated for the 4 outcomes of interest. Infarction volume was most important for predicting decompressive craniectomy, discharge mRS ≥4, and in-hospital mortality. Cerebral edema was important for decompressive craniectomy, discharge mRS ≥4, and in-hospital mortality. Initial NIHSS was important for decompressive craniectomy, discharge mRS ≥4, and in-hospital mortality. Contrast staining on post-procedural CT was important for cerebral edema (χ 2 11.9) and in-hospital mortality (χ 2 21.8). Patient age was important for discharge mRS ≥4 and decompressive craniectomy.

Conclusion: We identified prediction models consistent with established prognostic variables. Post-MT contrast staining is a novel and important predictor of poor outcome, which merits further research. In conclusion, machine learning can be used to create accurate prediction models for outcome after MT for ischemic stroke with LVO.

Simultaneous LeFort III and LeFort I Osteotomies in Craniometaphyseal Dysplasia

Craniometaphyseal dysplasia (CMD) is a rare genetic disease affecting bone metabolism with sclerosis of craniofacial bones. Orthognathic surgery has rarely been described in this patient population due to the bony thickness, making osteotomies challenging. We present a 19-year-old male with CMD with malocclusion, severe midface hypoplasia, and obstructive sleep apnea. With the aid virtual planning, we safely performed a combined LeFort III/I midface advancement to correct a negative overjet to improve occlusal balance, decrease scleral show, and diminish daytime sleepiness.

Improved Visual Localization via Graph Filtering

Vision-based localization is the problem of inferring the pose of the camera given a single image. One commonly used approach relies on image retrieval where the query input is compared against a database of localized support examples and its pose is inferred with the help of the retrieved items. This assumes that images taken from the same places consist of the same landmarks and thus would have similar feature representations. These representations can learn to be robust to different variations in capture conditions like time of the day or weather. In this work, we introduce a framework which aims at enhancing the performance of such retrieval-based localization methods. It consists in taking into account additional information available, such as GPS coordinates or temporal proximity in the acquisition of the images. More precisely, our method consists in constructing a graph based on this additional information that is later used to improve reliability of the retrieval process by filtering the feature representations of support and/or query images. We show that the proposed method is able to significantly improve the localization accuracy on two large scale datasets, as well as the mean average precision in classical image retrieval scenarios.

Lung Protective Ventilation in Brain-Injured Patients: Low Tidal Volumes or Airway Pressure Release Ventilation?

The optimal mode of mechanical ventilation for lung protection is unknown in brain-injured patients as this population is excluded from large studies of lung protective mechanical ventilation. Survey results suggest that low tidal volume (LTV) ventilation is the favored mode likely due to the success of LTV in other patient populations. Airway pressure release ventilation (APRV) is an alternative mode of mechanical ventilation that may offer several benefits over LTV in this patient population. APRV is an inverse-ratio, pressure-controlled mode of mechanical ventilation that utilizes a higher mean airway pressure compared with LTV. This narrative review compares both modes of mechanical ventilation and their consequences in brain-injured patients. Fears that APRV may raise intracranial pressure by virtue of a higher mean airway pressure are not substantiated by the available evidence. Primarily by virtue of spontaneous breathing, APRV often results in improvement in systemic hemodynamics and thereby improvement in cerebral perfusion pressure. Compared with LTV, sedation requirements are lessened by APRV allowing for more accurate neuromonitoring. APRV also uses an open loop system supporting clearance of secretions throughout the respiratory cycle. Additionally, APRV avoids hypercapnic acidosis and oxygen toxicity that may be especially deleterious to the injured brain. Although high-level evidence is lacking that one mode of mechanical ventilation is superior to another in brain-injured patients, several aspects of APRV make it an appealing mode for select brain-injured patients.

Clinical outcomes from out-of-hospital cardiac arrest in low-resource settings - A scoping review

AIM OF THE SCOPING REVIEW

Scientific recommendations on resuscitation are typically formulated from the perspective of an ideal resource environment, with little consideration of applicability in lower-income countries. We aimed to determine clinical outcomes from out-of-hospital cardiac arrest (OHCA) in low-resource countries, to identify shortcomings related to resuscitation in these areas and possible solutions, and to suggest future research priorities.

DATA SOURCES

This scoping review was part of the continuous evidence evaluation process of the International Liaison Committee on Resuscitation (ILCOR), and was performed following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews. We identified low-resource countries as countries with a low- or middle gross national income per capita (World Bank data). We performed a literature search on outcomes after OHCA in these countries, and we extracted data on the outcome. We applied descriptive statistics and conducted a post-hoc correlation analysis of cohort size and ROSC rates.

RESULTS

We defined 24 eligible studies originating from middle-income countries, but none from low-income regions, suggesting a reporting bias. The number of reported patients in these studies ranged from 54 to 3214. Utstein-style reporting was rarely used. Return of spontaneous circulation varied from 0% to 62%. Fifteen studies reported on survival to hospital discharge (between 1.0 and 16.7%) or favourable neurological outcome (between 1.0 and 9.3%). An inverse correlation was found for study cohort size and the rate of return of spontaneous circulation (ρ = -0.48, p = 0.034).

CONCLUSION

Studies of OHCA outcomes in low-resource countries are heterogeneous and may be compromised by reporting bias. Minimum cardiopulmonary resuscitation standards for low-resource settings should be developed collaboratively involving local experts, respecting culture and context while balancing competing health priorities.

Search for Axionlike Particles Produced in e^{+}e^{-} Collisions at Belle II

We present a search for the direct production of a light pseudoscalar a decaying into two photons with the Belle II detector at the SuperKEKB collider. We search for the process e^{+}e^{-}→γa, a→γγ in the mass range 0.2<m_{a}<9.7  GeV/c^{2} using data corresponding to an integrated luminosity of (445±3)  pb^{-1}. Light pseudoscalars interacting predominantly with standard model gauge bosons (so-called axionlike particles or ALPs) are frequently postulated in extensions of the standard model. We find no evidence for ALPs and set 95% confidence level upper limits on the coupling strength g_{aγγ} of ALPs to photons at the level of 10^{-3}  GeV^{-1}. The limits are the most restrictive to date for 0.2<m_{a}<1  GeV/c^{2}.

Natural language processing with machine learning to predict outcomes after ovarian cancer surgery

OBJECTIVE

To determine if natural language processing (NLP) with machine learning of unstructured full text documents (a preoperative CT scan) improves the ability to predict postoperative complication and hospital readmission among women with ovarian cancer undergoing surgery when compared with discrete data predictors alone.

METHODS

Medical records from two institutions were queried to identify women with ovarian cancer and available preoperative CT scan reports who underwent debulking surgery. Machine learning methods using both discrete data predictors (age, comorbidities, preoperative laboratory values) and natural language processing of full text reports (preoperative CT scans) were used to predict postoperative complication and hospital readmission within 30 days of surgery. Discrimination was measured using the area under the receiver operating characteristic curve (AUC).

RESULTS

We identified 291 women who underwent debulking surgery for ovarian cancer. Mean age was 59, mean preoperative CA125 value was 610 U/ml and albumin was 3.9 g/dl. There were 25 patients (8.6%) who were readmitted and 45 patients (15.5%) who developed postoperative complications within 30 days. Using discrete features alone, we were able to predict postoperative readmission with an AUC of 0.56 (0.54-0.58, 95% CI); this improved to 0.70 (0.68-0.73, 95% CI) (p < 0.001) with the addition of NLP of preoperative CT scans.

CONCLUSIONS

Natural language processing with machine learning improved the ability to predict postoperative complication and hospital readmission among women with ovarian cancer undergoing surgery.

The Atherogenic Index of Plasma is Independently Associated with Symptomatic Carotid Artery Stenosis

INTRODUCTION

Small, dense low-density lipoprotein (sdLDL) is strongly associated with symptomatic carotid artery stenosis, but is not routinely evaluated in ischemic stroke patients. A method using the logarithmic transformation of the ratio of the plasma concentration of triglycerides (TGY) to HDL-cholesterol (HDL-C)[(Log[TGY/HDL-C])] has been described as a surrogate marker for sdLDL termed the atherogenic index of plasma (AIP).

OBJECTIVE

To determine if the AIP is independently associated with symptomatic carotid artery stenosis.

METHODS

We conducted a single center case-controlled study using a sample of ischemic stroke patients and compared risk factors of patients with and without symptomatic carotid artery stenosis. A multivariate logistic regression model was used to determine if the AIP divided into four quartiles was independently associated with symptomatic carotid artery stenosis. This model was compared to three other lipid models. Associations between non-lipid variables and the AIP were also identified.

RESULTS

31 cases of ischemic stroke due to symptomatic carotid artery stenosis and 236 controls of ischemic stroke not due to carotid artery stenosis were identified. Of the four lipid models assessed, only the model including the AIP (model 4) was found to be significantly associated with symptomatic carotid artery stenosis. The odd's ratio (OR) for quartile 3 was 3.82 (95% CI 1.03-14.17) and the OR for quartile 4 was 4.13 (95% CI 1.09-15.54) using quartile 1 as a reference. Metabolic syndrome was the only variable associated with the AIP (OR 5.06 95% CI 2.6-9.7).

CONCLUSION

At our single center, the AIP was the only lipid parameter independently associated with symptomatic carotid artery stenosis; and metabolic syndrome was independently associated with the AIP. The AIP may serve as a useful surrogate of sdLDL in patients with symptomatic carotid artery stenosis.