Comparison of No-Test Telehealth and In-Person Medication Abortion.

Importance: In the US, access to medication abortion using history-based (no-test) eligibility assessment, including through telehealth and mailing of mifepristone, has grown rapidly. Additional evidence on the effectiveness and safety of these models is needed. Objective: To evaluate whether medication abortion with no-test eligibility assessment and mailing of medications is as effective as in-person care with ultrasonography and safe overall. Design, Setting, and Participants: Prospective, observational study with noninferiority analysis. Sites included 4 abortion-providing organizations in Colorado, Illinois, Maryland, Minnesota, Virginia, and Washington from May 2021 to March 2023. Eligible patients were seeking medication abortion up to and including 70 days' gestation, spoke English or Spanish, and were aged 15 years or older. Exposure: Study groups reflected the model of care selected by the patient and clinicians and included: (1) no-test (telehealth) eligibility assessment and mailing of medications (no-test + mail) (n = 228); (2) no-test eligibility assessment and pickup of medications (no-test + pickup) (n = 119); or (3) in-person with ultrasonography (n = 238). Main Outcomes and Measures: Effectiveness, defined as a complete abortion without the need for repeating the mifepristone and misoprostol regimen or a follow-up procedure, and safety, defined as an abortion-related serious adverse event, including overnight hospital admission, surgery, or blood transfusion. Outcomes were derived from patient surveys and medical records. Primary analysis focused on the comparison of the no-test + mail group with the in-person with ultrasonography group. Results: The mean age of the participants (N = 585) was 27.3 years; most identified as non-Hispanic White (48.6%) or non-Hispanic Black (28.1%). Median (IQR) gestational duration was 45 days (39-53) and comparable between study groups (P = .30). Outcome data were available for 91.8% of participants. Overall effectiveness was 94.4% (95% CI, 90.7%-99.2%) in the no-test + mail group and 93.3% (95% CI, 88.3%-98.2%) in the in-person with ultrasonography group in adjusted models (adjusted risk difference, 1.2 [95% CI, -4.1 to 6.4]), meeting the prespecified 5% noninferiority margin. Serious adverse events included overnight hospitalization (n = 4), blood transfusion (n = 2), and emergency surgery (n = 1) and were reported by 1.1% (95% CI, 0.4%-2.4%) of participants, with 3 in the no-test + mail group, 3 in the in-person with ultrasonography group, and none in the no-test + pickup group. Conclusions and Relevance: This prospective, observational study found that medication abortion obtained following no-test telehealth screening and mailing of medications was associated with similar rates of complete abortion compared with in-person care with ultrasonography and met prespecified criteria for noninferiority, with a low prevalence of adverse events.

Feasibility of exergaming for upper extremity rehabilitation in people with multiple sclerosis: prospective clinical trial.

BACKGROUND: Exergaming has been suggested as a rehabilitation method since it is more motivational for people with multiple sclerosis (MS, pwMS). However, the major disadvantage of this method is the lack of specific scenarios designed for pwMS. OBJECTIVES: This study aims to assess the feasibility of exergaming, which was developed for pwMS. METHODS: This unblinded prospective clinical trial was performed in the outpatient MS Clinic of Dokuz Eylül University Hospital. Exergaming scenarios were developed in collaboration with medical personnel consisting of physiotherapists and doctors, and computer engineers. A total of 30 participants who had definite MS diagnoses were included. The exergaming scenarios were implemented using the Microsoft Kinect. A physiotherapist applied custom-made exergames for one session. All the participants were assessed immediately after the session. The User Satisfaction Evaluation Questionnaire was used to assess the user's satisfaction with the system and exergaming. RESULTS: The mean age was 41.5, the mean Expanded Disability Status Scale was 4.5 (range between 0 and 7), and the mean disease duration was 10.0 years. Twenty patients were relapsing-remitting, and 10 were secondary-progressive. The mean scores of the User Satisfaction Evaluation Questionnaire were 4.33 (SD = 0.84) for helpfulness for rehabilitation, 1.63 (SD = 1.1) for not disturbing, 4.50 (SD = 1.07) for understandability, 4.0 (SD = 0.91) for easiness to control, and 4.33 (SD = 0.84) for enjoyability. CONCLUSION: These results showed that our custom-made exergaming scenario could be feasible in upper extremity rehabilitation in MS. More research is needed to investigate its effectiveness in the rehabilitation of upper limbs.

An Empirical Bayes Approach to Shrinkage Estimation on the Manifold of Symmetric Positive-Definite Matrices.

The James-Stein estimator is an estimator of the multivariate normal mean and dominates the maximum likelihood estimator (MLE) under squared error loss. The original work inspired great interest in developing shrinkage estimators for a variety of problems. Nonetheless, research on shrinkage estimation for manifold-valued data is scarce. In this article, we propose shrinkage estimators for the parameters of the Log-Normal distribution defined on the manifold of N × N symmetric positive-definite matrices. For this manifold, we choose the Log-Euclidean metric as its Riemannian metric since it is easy to compute and has been widely used in a variety of applications. By using the Log-Euclidean distance in the loss function, we derive a shrinkage estimator in an analytic form and show that it is asymptotically optimal within a large class of estimators that includes the MLE, which is the sample Fréchet mean of the data. We demonstrate the performance of the proposed shrinkage estimator via several simulated data experiments. Additionally, we apply the shrinkage estimator to perform statistical inference in both diffusion and functional magnetic resonance imaging problems.

Failure of the Law to Grant Access to Legal Abortion in Chile.

Introduction: In 2017, Chile decriminalized abortion on three grounds: (i) if the pregnant person's life is at risk, (ii) fetal nonviability, and (iii) rape or incest. This multicase study explores the experiences of pregnant people legally entitled to but denied access to legal abortion in Chile. Methods: Through a snowball sampling approach, we recruited adult Chilean residents who sought, were eligible for, and were denied a legal abortion after September 2017. We conducted semistructured interviews with participants to explore their experiences in seeking and being denied legal abortions. We recorded and transcribed the interviews, then coded and analyzed the transcriptions to identify common themes. Results: We identified four women who met the eligibility criteria. The interviews revealed five common themes in their experiences: (i) disparate levels of social support in accessing abortion, (ii) abundant access barriers, (iii) forced pregnancy, (iv) abortion stigma, and (v) a failure of the law to provide access to abortion. Discussion and Health Equity Implications: Although the 2017 law expanded legal access to abortion in Chile, significant barriers remain. Compounded with social stigma, and the socioeconomic disparities in abortion access, pregnant people continue to face insurmountable obstacles in obtaining legal abortions, even when their lives are at risk and the pregnancy is not viable. The state must prioritize equity of access to legal abortions. Future studies should continue to explore the challenges people face accessing legal abortion care to inform strategies to ensure people are able to obtain the quality care that they are legally entitled to.

Cognition as a parameter in monitoring the effect of multiple sclerosis relapse treatment: A prospective controlled study.

BACKGROUND: Cognitive evaluation was considered to be very important in the relapse period, on the basis of the presence of isolated cognitive attacks and the necessity of monitoring the patient both physically and cognitively. MATERIALS AND METHODS: People with MS (pwMS) who were hospitalized during relapse were included in the study. All MS patients were evaluated by the neurologist with Expanded Disability Status Scale (EDSS), The 9 Hole Peg Test (9HPT) and the Timed 25-Foot Walk Test (T25-FWT). Additionally, all participants were examined cognitively with the Turkish version of the Brief International Cognitive Assessment for MS (BICAMS) battery. Also, schedules were indicated as during relapse before the treatment (pre-treatment) and the first month after relapse (1-month follow-up). RESULTS: A total of 140 MS patients (mean age; 34.98±10.09, mean disease duration; 6.05±5.29 years) and 86 healthy controls (mean age; 36.94±10.83) were included to the present study. The mean EDSS scores in pre-treatment in MS patients was 2.74±1.14 and decreased significantly in the 1-month follow-up (1.74±1.24; p<0.001). The mean SDMT score was lower by 8.76 points in MS patients than in HCs) in pre-treatment and 7.66 points in 1-month follow-up (p<0.001). The mean SDMT scores of all participants increased with measurement time gradually (p<0.001). CONCLUSION: In this study, it was detected which cognitive domains were affected after relapse treatment and cognitive changes in pwMS during relapse and remission periods compared to the healthy controls. All three BICAMS test scores significantly increased in one-month follow-up than the pre-treatment period. The results showed that CVLT-II and BVMT-R scores improved more in pwMS than in HCs, and also SDMT scores of pwMS showed a trend of increase, but was not a significant improvement.

Perspectives on Alternative Models of Medication Abortion Provision Among Abortion Patients in the United States.

OBJECTIVE: Restrictions on the availability of medication abortion are a barrier to accessing early abortion. People seeking medication abortion may be interested in obtaining the medications through alternative models. The purpose of this study was to explore patient perspectives on obtaining abortion medications in advance of pregnancy or over the counter (OTC). STUDY DESIGN: Between October 2017 and August 2018, we conducted 30 in-depth interviews with abortion patients who indicated support for alternative models. We recruited patients from 10 abortion clinics in states with a range of policy environments. We analyzed interviews using inductive and deductive iterative techniques. RESULTS: Participants identified logistical benefits of these alternative models, including eliminating travel to a clinic and multiple appointments, and increased privacy around decision-making. Participants were interested in advance provision for its convenience and the sense of preparedness that would come with having the pills available at home, yet some had concerns about the pills being found or stolen. Privacy was the key factor considered for OTC access, including both the privacy benefits of avoiding a clinic and the concern of having one's privacy compromised within the community if purchasing the medications in public. CONCLUSIONS: People who have previously had a medication abortion are interested in alternative methods of provision for reasons concerning convenience, privacy, and avoiding burdens related to hostile policy environments, such as long travel distances to clinics and multiple appointments. Concerns around these models were primarily safety concerns for young people. Further research is needed to evaluate the safety, effectiveness, acceptability, and feasibility of these alternative models of providing medication abortion.

Horospherical Decision Boundaries for Large Margin Classification in Hyperbolic Space.

Hyperbolic spaces have been quite popular in the recent past for representing hierarchically organized data. Further, several classification algorithms for data in these spaces have been proposed in the literature. These algorithms mainly use either hyperplanes or geodesics for decision boundaries in a large margin classifiers setting leading to a non-convex optimization problem. In this paper, we propose a novel large margin classifier based on horospherical decision boundaries that leads to a geodesically convex optimization problem that can be optimized using any Riemannian gradient descent technique guaranteeing a globally optimal solution. We present several experiments depicting the competitive performance of our classifier in comparison to SOTA.

Geometric Deep Learning for Unsupervised Registration of Diffusion Magnetic Resonance Images.

Deep learning based models for registration predict a transformation directly from moving and fixed image appearances. These models have revolutionized the field of medical image registration, achieving accuracy on-par with classical registration methods at a fraction of the computation time. Unfortunately, most deep learning based registration methods have focused on scalar imaging modalities such as T1/T2 MRI and CT, with less attention given to more complex modalities such as diffusion MRI. In this paper, to the best of our knowledge, we present the first end-to-end geometric deep learning based model for the non-rigid registration of fiber orientation distribution fields (fODF) derived from diffusion MRI (dMRI). Our method can be trained in a fully-unsupervised fashion using only input fODF image pairs, i.e. without ground truth deformation fields. Our model introduces several novel differentiable layers for local Jacobian estimation and reorientation that can be seamlessly integrated into the recently introduced manifold-valued convolutional network in literature. The results of this work are accurate deformable registration algorithms for dMRI data that can execute in the order of seconds, as opposed to dozens of minutes to hours consumed by their classical counterparts.

"No Big Deal": A Qualitative Study of Pharmacists' Perspectives on Dispensing Mifepristone for Medication Abortion.

INTRODUCTION: Until December 2021, the United States Food and Drug Administration impeded abortion access by restricting pharmacists from dispensing mifepristone, one of two drugs used in medication abortion. This study aimed to explore pharmacists' perspectives on dispensing mifepristone. METHODS: We conducted semistructured interviews with pharmacists before and after participating in a pilot project where mifepristone was dispensed from their pharmacies. We thematically coded all interview transcripts, then summarized emergent themes related to pharmacists' support, comfort, experiences, and concerns around dispensing mifepristone. RESULTS: Between May 2018 and July 2020, we interviewed 29 pharmacists (22 at baseline and 15 at follow-up, with 8 completing both interviews) from 5 pharmacies. At both baseline and follow-up, interviewees strongly supported pharmacists dispensing mifepristone, feeling it would improve quality of care by providing more convenient medication abortion access and streamlined service delivery and take advantage of pharmacists' expertise and availability. All pharmacists interviewed at follow-up reported dispensing mifepristone except two who were willing but did not have the opportunity. Pharmacists experienced few challenges dispensing mifepristone. Their main concern was perceived discomfort that other pharmacists and pharmacy staff may experience, particularly in conservative areas or small pharmacies where pharmacists' refusal to dispense mifepristone could impede abortion access. CONCLUSIONS: Most pharmacists supported dispensing mifepristone and were comfortable doing so after education on mifepristone and medication abortion. They dispensed mifepristone without difficulty, in a similar process as dispensing other medications. With the recent removal of U.S. Food and Drug Administration restrictions prohibiting it, our findings support the feasibility of pharmacists dispensing mifepristone.

Nested Hyperbolic Spaces for Dimensionality Reduction and Hyperbolic NN Design.

Hyperbolic neural networks have been popular in the recent past due to their ability to represent hierarchical data sets effectively and efficiently. The challenge in developing these networks lies in the nonlinearity of the embedding space namely, the Hyperbolic space. Hyperbolic space is a homogeneous Riemannian manifold of the Lorentz group which is a semi-Riemannian manifold, i.e. a manifold equipped with an indefinite metric. Most existing methods (with some exceptions) use local linearization to define a variety of operations paralleling those used in traditional deep neural networks in Euclidean spaces. In this paper, we present a novel fully hyperbolic neural network which uses the concept of projections (embeddings) followed by an intrinsic aggregation and a nonlinearity all within the hyperbolic space. The novelty here lies in the projection which is designed to project data on to a lower-dimensional embedded hyperbolic space and hence leads to a nested hyperbolic space representation independently useful for dimensionality reduction. The main theoretical contribution is that the proposed embedding is proved to be isometric and equivariant under the Lorentz transformations, which are the natural isometric transformations in hyperbolic spaces. This projection is computationally efficient since it can be expressed by simple linear operations, and, due to the aforementioned equivariance property, it allows for weight sharing. The nested hyperbolic space representation is the core component of our network and therefore, we first compare this representation - independent of the network - with other dimensionality reduction methods such as tangent PCA, principal geodesic analysis (PGA) and HoroPCA. Based on this equivariant embedding, we develop a novel fully hyperbolic graph convolutional neural network architecture to learn the parameters of the projection. Finally, we present experiments demonstrating comparative performance of our network on several publicly available data sets.

Nested Grassmannians for Dimensionality Reduction with Applications.

In the recent past, nested structures in Riemannian manifolds has been studied in the context of dimensionality reduction as an alternative to the popular principal geodesic analysis (PGA) technique, for example, the principal nested spheres. In this paper, we propose a novel framework for constructing a nested sequence of homogeneous Riemannian manifolds. Common examples of homogeneous Riemannian manifolds include the n-sphere, the Stiefel manifold, the Grassmann manifold and many others. In particular, we focus on applying the proposed framework to the Grassmann manifold, giving rise to the nested Grassmannians (NG). An important application in which Grassmann manifolds are encountered is planar shape analysis. Specifically, each planar (2D) shape can be represented as a point in the complex projective space which is a complex Grassmann manifold. Some salient features of our framework are: (i) it explicitly exploits the geometry of the homogeneous Riemannian manifolds and (ii) the nested lower-dimensional submanifolds need not be geodesic. With the proposed NG structure, we develop algorithms for the supervised and unsupervised dimensionality reduction problems respectively. The proposed algorithms are compared with PGA via simulation studies and real data experiments and are shown to achieve a higher ratio of expressed variance compared to PGA.

VolterraNet: A Higher Order Convolutional Network With Group Equivariance for Homogeneous Manifolds.

Convolutional neural networks have been highly successful in image-based learning tasks due to their translation equivariance property. Recent work has generalized the traditional convolutional layer of a convolutional neural network to non-euclidean spaces and shown group equivariance of the generalized convolution operation. In this paper, we present a novel higher order Volterra convolutional neural network (VolterraNet) for data defined as samples of functions on Riemannian homogeneous spaces. Analagous to the result for traditional convolutions, we prove that the Volterra functional convolutions are equivariant to the action of the isometry group admitted by the Riemannian homogeneous spaces, and under some restrictions, any non-linear equivariant function can be expressed as our homogeneous space Volterra convolution, generalizing the non-linear shift equivariant characterization of Volterra expansions in euclidean space. We also prove that second order functional convolution operations can be represented as cascaded convolutions which leads to an efficient implementation. Beyond this, we also propose a dilated VolterraNet model. These advances lead to large parameter reductions relative to baseline non-euclidean CNNs. To demonstrate the efficacy of the VolterraNet performance, we present several real data experiments involving classification tasks on spherical-MNIST, atomic energy, Shrec17 data sets, and group testing on diffusion MRI data. Performance comparisons to the state-of-the-art are also presented.

ManifoldNet: A Deep Neural Network for Manifold-Valued Data With Applications.

Geometric deep learning is a relatively nascent field that has attracted significant attention in the past few years. This is partly due to the availability of data acquired from non-euclidean domains or features extracted from euclidean-space data that reside on smooth manifolds. For instance, pose data commonly encountered in computer vision reside in Lie groups, while covariance matrices that are ubiquitous in many fields and diffusion tensors encountered in medical imaging domain reside on the manifold of symmetric positive definite matrices. Much of this data is naturally represented as a grid of manifold-valued data. In this paper we present a novel theoretical framework for developing deep neural networks to cope with these grids of manifold-valued data inputs. We also present a novel architecture to realize this theory and call it the ManifoldNet. Analogous to vector spaces where convolutions are equivalent to computing weighted sums, manifold-valued data 'convolutions' can be defined using the weighted Fréchet Mean ([Formula: see text]). (This requires endowing the manifold with a Riemannian structure if it did not already come with one.) The hidden layers of ManifoldNet compute [Formula: see text]s of their inputs, where the weights are to be learnt. This means the data remain manifold-valued as they propagate through the hidden layers. To reduce computational complexity, we present a provably convergent recursive algorithm for computing the [Formula: see text]. Further, we prove that on non-constant sectional curvature manifolds, each [Formula: see text] layer is a contraction mapping and provide constructive evidence for its non-collapsibility when stacked in layers. This captures the two fundamental properties of deep network layers. Analogous to the equivariance of convolution in euclidean space to translations, we prove that the [Formula: see text] is equivariant to the action of the group of isometries admitted by the Riemannian manifold on which the data reside. To showcase the performance of ManifoldNet, we present several experiments using both computer vision and medical imaging data sets.

Pharmacists' knowledge, perspectives, and experiences with mifepristone dispensing for medication abortion.

BACKGROUND: The U.S. Food and Drug Administration (FDA) restricts dispensing of mifepristone for medication abortion to certified health care providers at clinical facilities, thus prohibiting pharmacist dispensing. Allowing mifepristone dispensing by pharmacists could improve access to medication abortion. OBJECTIVE: To assess the feasibility of pharmacists dispensing mifepristone to patients who have undergone evaluation for eligibility and counseling for medication abortion by a clinician. METHODS: Before providing a study training on medication abortion, we administered baseline surveys to pharmacists who participated in a multisite mifepristone-dispensing intervention. The survey assessed medication abortion knowledge-using a 15-item score-and perceptions about the benefits and challenges of the model. We administered follow-up surveys in the study's final month that also assessed the pharmacists' satisfaction and experiences with mifepristone dispensing. To investigate the association of the study intervention with the pharmacists' knowledge, perceptions, and experiences dispensing mifepristone, we conducted multivariable linear regression analyses using generalized estimating equation models, accounting for clustering by individual. RESULTS: Among the 72 pharmacists invited from 6 pharmacies, 47 (65%) completed the baseline surveys, and 56 (78%) received training. At the study's end (mean 18 months later), 43 of the 56 pharmacists who received training (77%) completed the follow-up surveys. At follow-up, 36 (83%) respondents were very or somewhat satisfied with mifepristone dispensing, and 24 (56%) reported experiencing no challenges dispensing mifepristone. Four (6%) of the 72 pharmacists invited objected to participating in mifepristone dispensing. In regression analyses, average knowledge scores, perceived ease of implementation, and level of support for the pharmacist-dispensing model were higher at follow-up (P < 0.001). CONCLUSION: Most pharmacists were willing to be trained, dispensed mifepristone with few challenges when given the opportunity, were satisfied with the model, and had higher knowledge levels at follow-up. Our findings support removal of FDA's restriction on pharmacist dispensing of mifepristone.

The outcome of a national MS-Covid-19 study: What the Turkish MS cohort reveals?

BACKGROUND: The pandemic of the new type of corona virus infection 2019 [Covid-19] also affect people with Multiple Sclerosis (pwMS). Currently, the accumulating information on the effects of the infection regarding the demographic and clinical characteristics of the disease, as well as outcomes within different DMTs¸ enable us to have better practices on the management of the Covid-19 infection in pwMS. OBJECTIVE: To investigate the incidence of coronavirus disease 2019 (Covid-19) and to reveal the relationship between the demographic-clinical and therapeutic features and the outcome of Covid-19 infection in a multi-center national cohort of pwMS. METHODS: The Turkish Neurological Society-MS Study Group in association with the Italian MuSC-19 Study Group initiated this study. A web-based electronic Case Report Form (eCRF) of Study-MuSC-19 were used to collect the data. The demographic data and MS histories of the patients were obtained from the file tracking forms of the relevant clinics. RESULTS: 309 MS patients with confirmed Covid-19 infection were included in this study. Two hundred nineteen (219) were females (70.9%). The mean age was 36.9, ranging from 18 to 66, 194 of them (62.8%) were under 40. The clinical phenotype was relapsing-remitting in 277 (89.6%) and progressive in 32 (10.4%). Disease duration ranged from 0.2 years to 31.4 years. The median EDSS was 1.5, ranging from 0 to 8.5. The EDSS score was<= 1 in 134 (43%) of the patients. 91.6% of the patients were on a DMT, Fingolimod was the most frequently used drug (22.0%), followed by Interferon (20.1%). The comorbidity rate is 11.7%. We were not able to detect any significant association of DMTs with Covid-19 severity. CONCLUSION: The Turkish MS-Covid-19 cohort had confirmed that pwMS are not at risk of having a more severe COVID-19 outcome irrespective of the DMT that they are treated. In addition, due to being a younger population with less comorbidities most had a mild disease further highlight that the only associated risk factors for having a moderate to severe COVID-19 course are similar with the general population such as having comorbid conditions and being older.

Medication Abortion With Pharmacist Dispensing of Mifepristone.

OBJECTIVE: To estimate effectiveness and acceptability of medication abortion with mifepristone dispensed by pharmacists. METHODS: We conducted a prospective cohort study at eight clinical sites and pharmacies in California and Washington State from July 2018 to March 2020. Pharmacists at participating pharmacies underwent a 1-hour training on medication abortion. We approached patients who had already been evaluated, counseled, and consented for medication abortion per standard of care. Patients interested in study participation gave consent, and the clinician electronically sent a prescription to the pharmacy for mifepristone 200 mg orally, followed 24-48 hours later by misoprostol 800 micrograms buccally. Participants were sent web-based surveys about their experience and outcomes on days 2 and 14 after enrollment and had routine follow-up with study sites. We extracted demographic and clinical data, including abortion outcome and adverse events, from medical records. We performed multivariable logistic regression to assess the association of pharmacy experience and other covariates with satisfaction. RESULTS: We enrolled 266 participants and obtained clinical outcome information for 262 (98.5%), of whom two reported not taking either medication. Of the 260 participants with abortion outcome information, 252 (96.9%) and 237 (91.2%) completed day 2 and 14 surveys, respectively. Complete medication abortion (primary outcome) occurred for 243 participants (93.5%, 95% CI 89.7-96.1%). Four participants (1.5%, 95% CI 0.4-3.9%) had an adverse event, none of which was serious or related to pharmacist dispensing. In the day 2 survey, 91.3% (95% CI 87.1-94.4%) of participants reported satisfaction with the pharmacy experience. In the day 14 survey, 84.4% (95% CI 79.1-88.8%) reported satisfaction with the medication abortion experience. Those reporting being very satisfied with the pharmacy experience had higher odds of reporting overall satisfaction with medication abortion (adjusted odds ratio 2.96, 95% CI 1.38-6.32). CONCLUSION: Pharmacist dispensing of mifepristone for medication abortion is effective and acceptable to patients, with a low prevalence of adverse events. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, NCT03320057.

Intrinsic Grassmann Averages for Online Linear, Robust and Nonlinear Subspace Learning.

Principal component analysis (PCA) and Kernel principal component analysis (KPCA) are fundamental methods in machine learning for dimensionality reduction. The former is a technique for finding this approximation in finite dimensions and the latter is often in an infinite dimensional reproducing Kernel Hilbert-space (RKHS). In this paper, we present a geometric framework for computing the principal linear subspaces in both (finite and infinite) situations as well as for the robust PCA case, that amounts to computing the intrinsic average on the space of all subspaces: the Grassmann manifold. Points on this manifold are defined as the subspaces spanned by K-tuples of observations. The intrinsic Grassmann average of these subspaces are shown to coincide with the principal components of the observations when they are drawn from a Gaussian distribution. We show similar results in the RKHS case and provide an efficient algorithm for computing the projection onto the this average subspace. The result is a method akin to KPCA which is substantially faster. Further, we present a novel online version of the KPCA using our geometric framework. Competitive performance of all our algorithms are demonstrated on a variety of real and synthetic data sets.

Chilean Medical and Midwifery Faculty's Views on Conscientious Objection for Abortion Services.

CONTEXT: In 2017, Chile reformed its abortion law to allow the procedure under limited circumstances. Exploring the views of Chilean medical and midwifery faculty regarding abortion and the use of conscientious objection (CO) at the time of reform can inform how these topics are being taught to the country's future health care providers. METHODS: Between March and September 2017, 30 medical and midwifery school faculty from universities in Santiago, Chile were interviewed; 20 of the faculty taught at secular universities and 10 taught at religiously affiliated universities. Faculty perspectives on CO and abortion, the scope of CO, and teaching about CO and abortion were analyzed using a grounded theory approach. RESULTS: Most faculty at secular and religiously affiliated universities supported the rights of clinicians to refuse to provide abortion care. Secular-university faculty generally thought that CO should be limited to specific providers and rejected the idea of institutional CO, whereas religious-university faculty strongly supported the use of CO by a broad range of providers and at the institutional level. Only secular-university faculty endorsed the idea that CO should be regulated so that it does not hinder access to abortion care. CONCLUSIONS: The broader support for CO in abortion among religious-university faculty raises concerns about whether students are being taught their ethical responsibility to put the needs of their patients above their own. Future research should monitor whether Chile's CO regulations and practices are guaranteeing people's access to abortion care.

RESUMEN Contexto: En 2017, Chile reformó su ley de aborto para permitir el procedimiento bajo circunstancias limitadas. Explorar las opiniones del personal académico de medicina y partería en relación con el aborto y el uso de la objeción de conciencia (OC) en el momento de la reforma, puede informar sobre los temas que están siendo enseñados a los futuros prestadores de servicios de salud del país. Métodos: Entre marzo y septiembre de 2017, fueron entrevistados 30 miembros del personal académico de las facultades de medicina y partería de universidades en Santiago, Chile. Veinte de ellos enseñaban en universidades laicas y diez en universidades con afiliación religiosa. Se analizaron las perspectivas del personal académico sobre la OC y el aborto, el alcance de la OC, y la enseñanza sobre OC y aborto, mediante el uso de un enfoque de teoría fundamentada. Resultados: La mayoría del personal académico de las universidades laicas y de las de afiliación religiosa apoyó el derecho del personal clínico a rehusarse a proveer servicios de aborto. En general, el personal académico de las universidades laicas pensó que la OC debería limitarse a proveedores de servicios específicos y rechazó la idea de una OC institucional, mientras que el personal académico de las universidades con afiliación religiosa apoyó decididamente el uso de la OC por un amplio conjunto de proveedores y a nivel institucional. Solamente el personal académico de las universidades laicas avaló la idea de que la OC debería ser regulada de tal forma que no obstaculizara el acceso a los servicios de aborto. Conclusions: El amplio apoyo a la OC en relación con el aborto en el personal académico de las universidades con afiliación religiosa genera preocupaciones sobre si se está enseñando a los estudiantes sobre su responsabilidad ética de poner las necesidades de sus pacientes por encima de las propias. Futuras investigaciones deben monitorear si las reglamentaciones y prácticas en materia de OC en Chile están garantizando el acceso de las personas a los servicios de aborto.

RÉSUMÉ Contexte: En 2017, le Chili a réformé sa législation de l'avortement, autorisant l'intervention dans des circonstances limitées. Létude de l'opinion du corps professoral des facultés de médecine et des écoles de sages-femmes concernant l'avortement et le recours à l'objection de conscience (OC) au moment de la réforme peut éclairer la manière dont ces sujets sont enseignés aux futurs prestataires de soins de santé du pays. Méthodes: Entre mars et septembre 2017, 30 professeurs et enseignants de facultés et écoles de médecine et de sages-femmes à Santiago (Chili) ont été interviewés; 20 enseignaient dans des universités laïques et 10, dans des universités de confession religieuse. Leurs points de vue sur l'OC et l'avortement, la portée de l'OC et l'enseignement relatif à l'OC et à l'avortement ont été analysés selon l'approche de la théorie ancrée. Résultats: Pour la plupart, le corps professoral des universités laïques et de confession religieuse reconnaissait le droit des cliniciens à refuser la prestation de soins d'avortement. Les professeurs d'universités laïques estimaient généralement que l'OC devrait être limitée à certains prestataires spécifiques et rejetaient la notion de l'OC institutionnelle, alors que ceux des facultés et écoles de confession religieuse soutenaient fermement le recours à l'OC par un large éventail de prestataires et au niveau institutionnel. Seul le corps professoral laïc souscrivait à l'idée que l'OC doit être réglementée de manière à ne pas entraver l'accès aux soins d'avortement. Conclusions: Le soutien plus large de l'OC à l'avortement parmi le corps professoral d'universités de confession religieuse soulève des questions quant à savoir si les étudiants sont sensibilisés à leur responsabilité éthique de faire passer les besoins de leurs patientes avant les leurs. La recherche future devra surveiller si la réglementation et la pratique de l'OC au Chili garantissent l'accès aux soins d'avortement.

"Obviously there is a conflict between confidentiality and what you are required to do by law": Chilean university faculty and student perspectives on reporting unlawful abortions.

BACKGROUND AND OBJECTIVES: While Chile recently decriminalized abortion in cases of rape, lethal fetal anomaly, and to save a woman's life, most abortions are still criminalized. We assessed medical and midwifery school faculty and students' views on punishing and reporting people involved in unlawful abortion, and their understanding of their obligation to protect patient confidentiality and to report unlawful abortions. METHODS: We interviewed 30 medical and midwifery school clinician faculty from seven public, private, secular and Catholic-affiliated universities, all located in the metropolitan region of Santiago, Chile. Medical (n = 239) and midwifery (n = 79) students at these same seven universities completed an online survey. We coded faculty interview transcripts, and analyzed codes related to maintaining patient confidentiality and reporting unlawful abortion. We summarized student views related to reporting and imprisoning people involved in unlawful abortion, and used general estimating equation (GEE) models to identify the factors associated with support for criminalization. RESULTS: Faculty and students generally did not support reporting or imprisoning anyone involved in an unlawful abortion and believed that protecting patient information takes precedence over reporting. Yet, faculty described pressures to report in the public sector and several cases where they or their colleagues were involved in reports. Most students somewhat/strongly agreed (78%) that patient information concerning an unlawful abortion should be kept confidential; 35% strongly/somewhat agreed that a clinician involved in an unlawful surgical abortion should be imprisoned, and 18% agreed that the woman involved should be imprisoned, with students from secular universities being significantly less likely to support reporting and punishing people involved in unlawful abortion, than students from Catholic universities. DISCUSSION: There is a need to clarify clinicians' ethical obligations in abortion care, in particular in Catholic universities, so that they can ensure that their patients have access to high quality confidential health care services.