bluuebunny/crossref_metadata_2025_split huggingface dataset:
A global review of penalties for abortion-related offences in 182 countries
Authors: Ambast Sanhita , Atay Hazal , Lavelanet Antonella 
Published: March 2023

Public health research and human rights bodies have demonstrated the risks involved with criminalising abortion services and noted a need for full decriminalisation. Despite this, abortions are criminalised in some circumstances in almost all countries in the world today. This paper uses data from the Global Abortion Policies Database (GAPD) to analyse what criminal penalties exist for those who are seeking, providing and assisting in abortions in 182 countries.This paper uses data on abortion-related penalties available on the GAPD as of October 2022. It includes which actors are penalised, whether specific penalties exist for negligence, non-consensual abortions, whether any secondary additional considerations/judicial discretion exist in sentencing and the legal sources for these penalties.134 countries penalise abortion-seekers, 181 countries penalise abortion-providers and 159 countries penalise persons assisting in abortions. The maximum penalty is between 0 and 5 years of imprisonment in a majority of countries; however, it can be much higher in other countries. Some countries further prescribe fines, and professional sanctions for providers and those who assist. 34 countries restrict the dissemination of information about abortion.The range of possible penalties across countries and associated aggravating and mitigating factors for imposing these penalties support arguments for the decriminalisation of abortion on the grounds of arbitrariness. Abortions are also predominantly regulated through the criminal law, which may compound the stigma associated with seeking, assisting with and/or providing abortions when it is criminalised.There has been no comprehensive study of penalties for abortion at a global level. This article describes what specific penalties abortion seekers and providers face, what factors may increase or decrease these penalties, and the legal sources for these penalties. The findings provide additional evidence of the arbitrariness and potential for stigma associated with the criminalisation of abortion and strengthen the case for decriminalisation.
Hospital quality reporting in the pandemic era: to what extent did hospitals’ COVID-19 census burdens impact 30-day mortality among non-COVID Medicare beneficiaries?
Authors: Pollock Benjamin D , Dowdy Sean C 
Published: March 2023

ObjectivesHighly visible hospital quality reporting stakeholders in the USA such as the US News & World Report (USNWR) and the Centers for Medicare & Medicaid Services (CMS) play an important health systems role via their transparent public reporting of hospital outcomes and performance. However, during the pandemic, many such quality measurement stakeholders and pay-for-performance programmes in the USA and Europe have eschewed the traditional risk adjustment paradigm, instead choosing to pre-emptively exclude months or years of pandemic era performance data due largely to hospitals’ perceived COVID-19 burdens. These data exclusions may lead patients to draw misleading conclusions about where to seek care, while also masking genuine improvements or deteriorations in hospital quality that may have occurred during the pandemic. Here, we assessed to what extent hospitals’ COVID-19 burdens (proportion of hospitalised patients with COVID-19) were associated with their non-COVID 30-day mortality rates from March through November 2020 to inform whether inclusion of pandemic-era data may still be appropriate.DesignThis was a retrospective cohort study using the 100% CMS Inpatient Standard Analytic File and Master Beneficiary Summary File to include all US Medicare inpatient encounters with admission dates from 1 April 2020 through 30 November 2020, excluding COVID-19 encounters. Using linear regression, we modelled the association between hospitals’ COVID-19 proportions and observed/expected (O/E) ratios, testing whether the relationship was non-linear. We calculated alternative hospital O/E ratios after selective pandemic data exclusions mirroring the USNWR data exclusion methodology.Setting and participantsWe analysed 4 182 226 consecutive Medicare inpatient encounters from across 2601 US hospitals.ResultsThe association between hospital COVID-19 proportion and non-COVID O/E 30-day mortality was statistically significant (p<0.0001), but weakly correlated (r2=0.06). The median (IQR) pairwise relative difference in hospital O/E ratios comparing the alternative analysis with the original analysis was +3.7% (−2.5%, +6.7%), with 1908/2571 (74.2%) of hospitals having relative differences within ±10%.ConclusionsFor non-COVID patient outcomes such as mortality, evidence-based inclusion of pandemic-era data is methodologically plausible and must be explored rather than exclusion of months or years of relevant patient outcomes data.
Pharmacy dispensing of abortion pills in Ghana: experiences of pharmacy workers and users
Authors: Otsin Mercy Nana Akua , Black Kirsten , Hooker Leesa , Taft Angela J 
Published: March 2023

BackgroundSelf-managed medical abortions are generally safe; however, pharmacy provision of abortion pills is against the Ghanaian abortion law. Nevertheless, evidence shows increasing numbers of women use it. An understanding of the influence of the law on pharmacies dispensing abortifacients and women who needed hospital care after using these pills is lacking. This study aimed to address this gap.MethodsWe conducted 26 interviews with eight pharmacy workers and 18 women who sought hospital care after using abortion pills. Study participants were recruited from private pharmacies and hospitals within the Ashanti Region of Ghana between June 2017 and March 2018. We employed phenomenology in analysing the data.ResultsResults show that criminalising medical abortion care from pharmacies does not stop abortions but rather drives it to be provided without oversight. It also denied pharmacy workers formal training in medical abortion care, resulting in situations where they failed to provide correct dosage information, used their discretion in determining the price of abortifacients and to whom they would dispense the pills. For women, it contributed to limited interaction with providers and an inability to insist on their rights even in instances where the pills were sold at exorbitant prices.ConclusionsDue to the increasing numbers of Ghanaian women using medical abortion pills from pharmacies, although it is illegal, the ideal would be for medical abortion pills to be made legally available through pharmacies. Given that this may not occur in the short term, an immediate solution would be to upskill pharmacy workers.
Development and validation of machine learning-based model for mortality prediction in patients with acute basilar artery occlusion receiving endovascular treatment: multicentric cohort analysis
Authors: Liu Chang , Huang Jiacheng , Kong Weilin , Chen Liyuan , Song Jiaxing , Yang Jie , Li Fengli , Zi Wenjie 
Published: March 2023

BackgroundPredicting mortality in stroke patients using information available before endovascular treatment (EVT) is an essential component for supporting clinical decision-making. Although the mortality rate of acute basilar artery occlusion (ABAO) after EVT has reached 40%, few studies have focused on predicting mortality in these individuals. Thus, we aimed to develop and validate a machine learning-based mortality prediction tool based on preoperative information for ABAO patients receiving EVT.MethodsThe derivation cohort comprised patients from southern provinces of China in the BASILAR registry. The model (POSITIVE: Predicting mOrtality of baSilar artery occlusion patIents Treated wIth EVT) was trained and optimized using a fivefold cross-validation method in which hyperparameters were selected and fine-tuned. This model was retrospectively tested in patients from the northern provinces of China from the BASILAR registry. A prospective test of POSITIVE was performed on consecutive patients from two hospitals between January 2020 and June 2022.ResultsExtreme gradient boosting was employed to construct the POSITIVE model, which achieved the best predictive performance among the eight machine learning algorithms and showed excellent discrimination (area under the curve (AUC) 0.83, 95% confidence interval (95% CI) 0.80 to 0.87) and calibration (Hosmer-Lemeshow test, P>0.05) in the development cohort. AUC yielded by the POSITIVE model for the retrospective test was 0.79 (95% CI 0.71 to 0.85), higher than that obtained by traditional models. Prospective comparisons showed that the POSITIVE model achieved the highest AUC (0.82, 95% CI 0.74 to 0.90) among all prediction models.ConclusionWe developed a machine learning algorithm and retrospective and prospective testing with multicentric cohorts, which exhibited a solid predictive performance and may act as a convenient reference to guide decision-making for ABAO patients. The POSITIVE model is presented online for user-friendly access.
Predictors of perioperative respiratory adverse events among children with upper respiratory tract infection undergoing pediatric ambulatory ilioinguinal surgery: a prospective observational research
Authors: Jarraya Anouar , Kammoun Manel , Ammar Saloua , Feki Wiem , Kolsi Kamel 
Published: March 2023

ObjectivesAnesthesia for children with an upper respiratory tract infection (URI) has an increased risk of perioperative respiratory adverse events (PRAEs) that may be predicted according to the COLDS score. The aims of this study were to evaluate the validity of the COLDS score in children undergoing ilioinguinal ambulatory surgery with mild to moderate URI and to investigate new predictors of PRAEs.MethodsThis was a prospective observational study including children aged 1–5 years with mild to moderate symptoms of URI who were proposed for ambulatory ilioinguinal surgery. The anesthesia protocol was standardized. Patients were divided into two groups according to the incidence of PRAEs. Multivariate logistic regression was performed to assess predictors for PRAEs.ResultsIn this observational study, 216 children were included. The incidence of PRAEs was 21%. Predictors of PRAEs were respiratory comorbidities (adjusted OR (aOR)=6.3, 95% CI 1.19 to 33.2; p=0.003), patients postponed before 15 days (aOR=4.3, 95% CI 0.83 to 22.4; p=0.029), passive smoking (aOR=5.31, 95% CI 2.07 to 13.6; p=0.001), and COLDS score of >10 (aOR=3.7, 95% CI 0.2 to 53.4; p=0.036).ConclusionsEven in ambulatory surgery, the COLDS score was effective in predicting the risks of PRAEs. Passive smoking and previous comorbidities were the main predictors of PRAEs in our population. It seems that children with severe URI should be postponed to receive surgery for more than 15 days.
Creation of wormholes during the cosmological bounce
Authors: Pavlović Petar , Sossich Marko 
Published: March 2023

AbstractIn this work we demonstrate that wormholes can in principle be naturally created during the cosmological bounce without the need for the exotic matter or any kind of additional modifications of the gravitational sector, apart from the one enabling the cosmological bounce. This result is general and does not depend on the details of the modifications of gravitational equations needed to support the bounce. To study the possible existence of wormholes around the cosmological bounce we introduce general modifications of Einstein’s field equations need to support the bouncing solutions. In this regime we show that it is possible to construct a cosmological wormhole solution supported by matter, radiation and vacuum energy, satisfying the Weak Energy Condition (WEC), which asymptotically approaches the Friedmann–Lemaître–Robertson–Walker (FLRW) metric. However, at a specific cosmological time, which depends on the parameters of the bouncing cosmological model, the WEC describing the matter needed to support such wormholes is spontaneously violated. This means that such wormholes could potentially exist in large numbers during some period around the bounce, significantly changing the causal structure of space-time, and then vanish afterwards.
Gorenstein Projective Coresolutions and Co-Tate Homology Functors
Authors: Liu Zhongkui , Wang Li 
Published: March 2023

For a local commutative Gorenstein ring [Formula: see text], Enochs et al. in [Gorenstein projective resolvents, Comm. Algebra 44 (2016) 3989–4000] defined a functor [Formula: see text] and showed that this functor can be computed by taking a totally acyclic complex arising from a projective coresolution of the first component or a totally acyclic complex arising from a projective resolution of the second component. In order to define the functor [Formula: see text] over general rings, we introduce the right Gorenstein projective dimension of an [Formula: see text]-module [Formula: see text], [Formula: see text], via Gorenstein projective coresolutions, and give some equivalent characterizations for the finiteness of [Formula: see text]. Then over a general ring [Formula: see text] we define a co-Tate homology group [Formula: see text] for [Formula: see text]-modules [Formula: see text] and [Formula: see text] with [Formula: see text] and [Formula: see text], and prove that [Formula: see text] can be computed by complete projective coresolutions of the first variable or by complete projective resolutions of the second variable.
Convolution Neural Network Algorithm for Shockable Arrhythmia Classification Within a Digitally Connected Automated External Defibrillator
Authors: Shen Christine P. , Freed Benjamin C. , Walter David P. , Perry James C. , Barakat Amr F. , Elashery Ahmad Ramy A. , Shah Kevin S. , Kutty Shelby , McGillion Michael , Ng Fu Siong , Khedraki Rola , Nayak Keshav R. , Rogers John D. , Bhavnani Sanjeev P. 
Published: March 2023

Background
Diagnosis of shockable rhythms leading to defibrillation remains integral to improving out‐of‐hospital cardiac arrest outcomes. New machine learning techniques have emerged to diagnose arrhythmias on ECGs. In out‐of‐hospital cardiac arrest, an algorithm within an automated external defibrillator is the major determinant to deliver defibrillation. This study developed and validated the performance of a convolution neural network (CNN) to diagnose shockable arrhythmias within a novel, miniaturized automated external defibrillator.

Methods and Results
There were 26 464 single‐lead ECGs that comprised the study data set. ECGs of 7‐s duration were retrospectively adjudicated by 3 physician readers (N=18 total readers). After exclusions (N=1582), ECGs were divided into training (N=23 156), validation (N=721), and test data sets (N=1005). CNN performance to diagnose shockable and nonshockable rhythms was reported with area under the receiver operating characteristic curve analysis, F1, and sensitivity and specificity calculations. The duration for the CNN to output was reported with the algorithm running within the automated external defibrillator. Internal and external validation analyses included CNN performance among arrhythmias, often mistaken for shockable rhythms, and performance among ECGs modified with noise to mimic artifacts. The CNN algorithm achieved an area under the receiver operating characteristic curve of 0.995 (95% CI, 0.990–1.0), sensitivity of 98%, and specificity of 100% to diagnose shockable rhythms. The F1 scores were 0.990 and 0.995 for shockable and nonshockable rhythms, respectively. After input of a 7‐s ECG, the CNN generated an output in 383±29 ms (total time of 7.383 s). The CNN outperformed adjudicators in classifying atrial arrhythmias as nonshockable (specificity of 99.3%–98.1%) and was robust against noise artifacts (area under the receiver operating characteristic curve range, 0.871–0.999).

Conclusions
We demonstrate high diagnostic performance of a CNN algorithm for shockable and nonshockable rhythm arrhythmia classifications within a digitally connected automated external defibrillator.

Registration

URL:
https://clinicaltrials.gov/ct2/show/NCT03662802
; Unique identifier: NCT03662802
Cardiovascular Risk Prediction in Men and Women Aged Under 50 Years Using Routine Care Data
Authors: van Os Hendrikus J. A. , Kanning Jos P. , Bonten Tobias N. , Rakers Margot M. , Putter Hein , Numans Mattijs E. , Ruigrok Ynte M. , Groenwold Rolf H. H. , Wermer Marieke J. H. 
Published: March 2023

Background
Prediction models for risk of cardiovascular events generally do not include young adults, and cardiovascular risk factors differ between women and men. Therefore, this study aimed to develop prediction models for first‐ever cardiovascular event risk in men and women aged 30 to 49 years.

Methods and Results
We included patients aged 30 to 49 years without cardiovascular disease from a Dutch routine care database. Outcome was defined as first‐ever cardiovascular event. Our reference models were sex‐specific Cox proportional hazards models based on traditional cardiovascular predictors, which we compared with models using 2 predictor subsets with the 20 or 50 most important predictors based on the Cox elastic net model regularization coefficients. We assessed the C‐index and calibration curve slopes at 10 years of follow‐up. We stratified our analyses based on 30‐ to 39‐year and 40‐ to 49‐year age groups at baseline. We included 542 141 patients (mean age 39.7, 51% women). During follow‐up, 10 767 cardiovascular events occurred. Discrimination of reference models including traditional cardiovascular predictors was moderate (women: C‐index, 0.648 [95% CI, 0.645–0.652]; men: C‐index, 0.661 [95%CI, 0.658–0.664]). In women and men, the Cox proportional hazard models including 50 most important predictors resulted in an increase in C‐index (0.030 and 0.012, respectively), and a net correct reclassification of 3.7% of the events in women and 1.2% in men compared with the reference model.

Conclusions
Sex‐specific electronic health record‐derived prediction models for first‐ever cardiovascular events in the general population aged <50 years have moderate discriminatory performance. Data‐driven predictor selection leads to identification of nontraditional cardiovascular predictors, which modestly increase performance of models.
Thiamine for the Treatment of Cardiac Arrest–Induced Neurological Injury: A Randomized, Blinded, Placebo‐Controlled Experimental Study
Authors: Vammen Lauge , Johannsen Cecilie Munch , Baltsen Cecilie Dahl , Nørholt Casper , Eggertsen Mark , Mortensen Signe , Vormfenne Lasse , Povlsen Amalie , Donnino Michael W. , Løfgren Bo , Andersen Lars W. , Granfeldt Asger 
Published: March 2023

Background
Thiamine supplementation has demonstrated protective effects in a mouse model of cardiac arrest. The aim of this study was to investigate the neuroprotective effects of thiamine in a clinically relevant large animal cardiac arrest model. The hypothesis was that thiamine reduces neurological injury evaluated by neuron‐specific enolase levels.

Methods and Results
Pigs underwent myocardial infarction and subsequently 9 minutes of untreated cardiac arrest. Twenty minutes after successful resuscitation, the pigs were randomized to treatment with either thiamine or placebo. All pigs underwent 40 hours of intensive care and were awakened for assessment of functional neurological outcome up until 9 days after cardiac arrest.

Nine pigs were included in both groups, with 8 in each group surviving the entire intensive care phase. Mean area under the curve for neuron‐specific enolase was similar between groups, with 81.5 μg/L per hour (SD, 20.4) in the thiamine group and 80.5 μg/L per hour (SD, 18.3) in the placebo group, with an absolute difference of 1.0 (95% CI, −57.8 to 59.8;
P
=0.97). Likewise, there were no absolute difference in neurological deficit score at the end of the protocol (2 [95% CI, −38 to 42];
P
=0.93). There was no absolute mean group difference in lactate during the intensive care period (1.1 mmol/L [95% CI, −0.5 to 2.7];
P
=0.16).

Conclusions
In this randomized, blinded, placebo‐controlled trial using a pig cardiac arrest model with myocardial infarction and long intensive care and observation for 9 days, thiamine showed no effect in changes to functional neurological outcome or serum levels of neuron‐specific enolase. Thiamine treatment had no effect on lactate levels after successful resuscitation.
Body Mechanics, Optimality, and Sensory Feedback in the Human Control of Complex Objects
Authors: Razavian Reza Sharif , Sadeghi Mohsen , Bazzi Salah , Nayeem Rashida , Sternad Dagmar 
Published: March 2023

AbstractHumans are adept at a wide variety of motor skills, including the handling of complex objects and using tools. Advances to understand the control of voluntary goal-directed movements have focused on simple behaviors such as reaching, uncoupled to any additional object dynamics. Under these simplified conditions, basic elements of motor control, such as the roles of body mechanics, objective functions, and sensory feedback, have been characterized. However, these elements have mostly been examined in isolation, and the interactions between these elements have received less attention. This study examined a task with internal dynamics, inspired by the daily skill of transporting a cup of coffee, with additional expected or unexpected perturbations to probe the structure of the controller. Using optimal feedback control (OFC) as the basis, it proved necessary to endow the model of the body with mechanical impedance to generate the kinematic features observed in the human experimental data. The addition of mechanical impedance revealed that simulated movements were no longer sensitively dependent on the objective function, a highly debated cornerstone of optimal control. Further, feedforward replay of the control inputs was similarly successful in coping with perturbations as when feedback, or sensory information, was included. These findings suggest that when the control model incorporates a representation of the mechanical properties of the limb, that is, embodies its dynamics, the specific objective function and sensory feedback become less critical, and complex interactions with dynamic objects can be successfully managed.
Strong Allee Effect Synaptic Plasticity Rule in an Unsupervised Learning Environment
Authors: Kwessi Eddy 
Published: March 2023

Abstract
Synaptic plasticity, or the ability of a brain to change one or more of its functions or structures at the synaptic level, has generated and is still generating a lot of interest from the scientific community especially from neuroscientists. These interests went into high gear after empirical evidence was collected that challenged the established paradigm that human brain structures and functions are set from childhood and only modest changes were expected beyond. Early synaptic plasticity rules or laws to that regard include the basic Hebbian rule that proposed a mechanism for strengthening or weakening of synapses (weights) during learning and memory. This rule, however, did not account for the fact that weights must have bounded growth over time. Thereafter, many other rules that possess other desirable properties were proposed to complement the basic Hebbian rule. In particular, a desirable property in a synaptic plasticity rule is that the ambient system must account for inhibition, which is often achieved if the rule used allows for a lower bound in synaptic weights. To that regard, in this letter, we propose such a synaptic plasticity rule that is inspired by the Allee effect, a phenomenon often observed in population dynamics. We show that properties such as synaptic normalization, competition between weights, decorrelation potential, and dynamic stability are satisfied. We show that in fact, an Allee effect in synaptic plasticity can be construed as an absence of plasticity.