bluuebunny/crossref_metadata_2025_split huggingface dataset:
Empowering Research on Epilepsy Surgery Outcomes
Authors: Dickey Adam S. , Krafty Robert T. , Pedersen Nigel P. 
Published: May 2022

ABSTRACTLow statistical power is a recognized problem in many fields. We performed a systematic review to determine the median statistical power of studies of epilepsy surgery outcomes. We performed a PubMed search for studies reporting epilepsy surgery outcomes for the years 1980-2020, focusing on studies using stereoelectroencephalography (SEEG). We extracted patient count data for comparisons of surgical outcome between two groups, based on a reported prognostic factor. We defined a clinically meaningful difference as the difference in seizure freedom for MRI positive (66.9%) versus negative (45.5%) from the largest study found. Based on 69 studies of surgery outcomes in patients undergoing SEEG, the median sample size was 38 patients, and the median statistical power was 24%. This implies at least a 17% chance a study with a significant result is false, assuming 1:1 pre-test odds. Results from simulation studies suggest that, if a typical SEEG study finds a significant effect, then the median observed effect size will be more than double the true effect size. We conclude that studies of epilepsy surgery outcomes using SEEG are often statistically underpowered, which limits the reproducibility and reliability of the literature. We discuss how statistical power could be improved.SHORT SUMMARYWe performed a systematic review to determine the median statistical power of studies of epilepsy surgery outcomes, focused on stereoelectroencephalography. We extracted patient count data for comparisons of outcomes between two groups. We defined a clinically meaningful difference as the prognostic value of a normal versus abnormal MRI. Based on 69 studies, the median sample size was 38 patients, and the median statistical power was 24%. Underpowered studies will overestimate the size of true effects and are more likely to report false positive results. We discuss how statistical power, and thus reproducibility and reliability of results, can be improved.
Infection prevention and control preparedness among public hospitals and COVID-19 temporary treatment and monitoring facilities in the Philippines
Authors: de Claro Vergil , Bautista Noemi , Torralba Ma. Rosario , Castro Vina Vanessa , Lucero Miguel Angelo , Molleno Lady Jedfeliz , Stan Laurentiu 
Published: May 2022

AbstractObjectivesAn effective response to COVID-19 necessitates rigid compliance of health facilities to infection prevention and control (IPC) protocols to protect HCWs, prevent onward transmission, and mitigate the impact of the outbreak on the health care system. The study aims to assess the compliance of public hospitals and temporary treatment and monitoring facilities (TTMFs) to IPC standards for COVID-19.MethodsA baseline assessment survey was conducted between July 20 to August 18, 2020, from selected facilities in 38 local government units (LGU) across the country utilising a 35-point questionnaire corresponding to a set of standards issued by the Philippine Department of Health.ResultsThe study shows that public hospitals reported sufficient IPC preparedness and compliance compared to TTMFs in the domains of engineering and administrative controls. Both types of facilities reported weak compliance in the use of color-coded bags and in having a central storage for infectious waste. In addition, among TTMFs adherence to proper labelling of waste bins, presence of instructional materials for waste disposal, directional signages for movements of HCWs and patients, availability of an IPC policy, and advocacy materials on proper handwashing, respiratory etiquette, and physical distancing, and PPE use were also low.ConclusionThe COVID-19 pandemic has shown the importance of IPC preparedness among health care facilities to effectively prevent disease transmission and mitigate its impact on the health care system. The findings suggests that periodic monitoring and augmentation of resources are needed to immediately address the compliance gaps. However, systemic improvements and long-term investments are required to sustain IPC practices over time.What is already known?Infection prevention and control measures are effective at protecting patients and health care workers from facility-acquired infections and averting onward transmission of the disease.What are the new findings?Findings from this study highlight the critical gaps in infection prevention and control preparedness among established healthcare settings like hospitals and in repurposed spaces such as temporary facilities for COVID-19 isolation that were primarily set up to manage the surge in cases.What do the new findings imply?It focuses attention on the periodic monitoring of health facilities’ compliance to standard infection prevention and control practices especially during outbreak situations as a basis for identifying immediate resource and technical requirements, and for planning the needed investments in the long term.
Photoacoustic imaging to monitor outcomes during hyperbaric oxygen therapy: Validation in a small cohort and case study in a bilateral chronic ischemic wound
Authors: Mantri Yash , Mishra Aditya , Anderson Caesar A. , Jokerst Jesse V. 
Published: May 2022

AbstractDiseases of the microcirculatory system are well-known risk factors for chronic wound healing. Hyperbaric oxygen therapy (HBO2) is a common therapeutic modality that drives oxygen into hypoxic tissue to promote healing. Ischemia/hypoxia are common confounding variables associated with failure of wound progress and/or relapse, and hence it is important to develop tools that map and measure perfusion and oxygen saturation in the wound bed. Photoacoustic (PA) imaging is an ideal tool to address these concerns. Ten patients undergoing HBO2underwent PA oximetry of the left radial artery and forearm pre- and post-HBO2; this cohort validated the use of PA imaging in HBO2. There was a significant increase in radial artery oxygenation after HBO2(p=0.002) in the validation cohort. PA significantly underestimated arterial oxygenation compared to a pulse oximeter. We also include a case study: a non-diabetic male in his 50s (HB 010) presenting with bilateral ischemic and gangrenous wounds. HB 010 underwent additional scanning of the wound sites both pre- and post-HBO2. HB 010 showed higher perfusion and oxygen saturation on the right foot than the left after HBO2which correlated with independent surgical observations. Imaging assisted with limb salvage treatment options by limiting the initial amputation site to only the toes. Hence, this work shows that PA imaging can measure changes in arterial oxygen saturation due to HBO2; it can also produce 3D maps of tissue oxygenation and evaluate response to therapy during HBO2.Key PointsPhotoacoustic oximetry can measure and map changes in arterial oxygenation due to hyperbaric oxygen therapy. Photoacoustic imaging shows changes in perfusion in a patient presenting with bilateral ischemic and gangrenous wounds and thus informing limb salvage treatment.
ATTCT and ATTCC repeat expansions in the ATXN10 gene affect disease penetrance of spinocerebellar ataxia type 10
Authors: Morato Torres C. Alejandra , Zafar Faria , Tsai Yu-Chih , Vazquez Jocelyn Palafox , Gallagher Michael D. , McLaughlin Ian , Hong Karl , Lai Jill , Lee Joyce , Chirino-Perez Amanda , Romero-Molina Angel Omar , Torres Francisco , Fernandez-Ruiz Juan , Ashizawa Tetsuo , Ziegle Janet , Jiménez Gil Francisco Javier , Schüle Birgitt 
Published: May 2022

AbstractSpinocerebellar ataxia type 10 (SCA10) is an autosomal-dominant disorder caused by an expanded pentanucleotide repeat in the ATXN10 gene. This repeat expansion, when fully penetrant, has a size of 850 to 4500 repeats. It has been shown that the repeat composition can be a modifier of disease, e.g., seizures.Here, we describe a Hispanic kindred in which we identified both pure (ATTCT)n expansions and mixed (ATTCT)n-(ATTCC)n in the same family. We used No-Amp targeted sequencing and optical genome mapping to decipher the composition of these repeat expansions. We found a considerable degree of mosaicism in the repeat expansion. This mosaicism was confirmed in skin fibroblasts from ATXN10 carriers with RNAScope in situ hybridization. All affected family members with the mixed ATXN10 repeat expansion showed typical clinical signs of spinocerebellar ataxia and epilepsy. In contrast, individuals with the pure ATXN10 expansion present with Parkinson’s disease or are unaffected even more than 20 years older than the average age at onset for SCA10.Our findings suggest that the pure (ATTCT)n expansion is non-pathogenic while repeat interruptions, e.g., (ATTCC)n, are necessary to cause SCA10. This mechanism has been recently described for several other repeat expansions, including SCA31 (BEAN1), SCA37 (DAB1), and three loci for benign adult familial myoclonic epilepsy BAFME (SAMD12, TNRC6A, RAPGEF2). Therefore, long-read sequencing and optical genome mapping of the entire genomic structure of repeat expansions is critical for clinical practice, and genetic counseling as variations in the repeat can affect disease penetrance, symptoms, and disease trajectory.
Green space and loneliness: a systematic review with theoretical and methodological guidance for future research
Authors: Astell-Burt Thomas , Hartig Terry , Putra I Gusti Ngurah Edi , Walsan Ramya , Dendup Tashi , Feng Xiaoqi 
Published: May 2022

AbstractUrban greening may help to reduce the population health impacts of loneliness and its concomitants, such as hopelessness and despair. However, the literature lacks both a critical appraisal of extant evidence and a conceptual model to explain how green space would work as a structural intervention. Both are needed to guide decision making and further research. We conducted a systematic review of quantitative studies testing associations between green space and loneliness, searching seven databases. Twenty two studies were identified by 25/01/2022. Most of the studies were conducted in high-income countries and fifteen (68%) had cross-sectional designs. Green space was measured inconsistently using either objective or subjective indicators. Few studies examined specific green space types or qualities. The majority of studies measured general loneliness (e.g. using the UCLA loneliness scale). Different types of loneliness (social, emotional, existential) were not analysed. Of 132 associations, 88 (66.6%) indicated potential protection from green space against loneliness, with 44 (33.3%) reaching statistical significance (p<0.05). We integrated these findings with evidence from qualitative studies to elaborate and extend the existing pathway domain model linking green space and health. These elaborations and extensions acknowledge the following: (a) different types of green space have implications for different types of loneliness; (b) multilevel circumstances influence the likelihood a person will benefit or suffer harm from green space; (c) personal, relational, and collective processes operate within different domains of pathways linking green space with loneliness and its concomitants; (d) loneliness and its concomitants are explicitly positioned as mediators within the broader causal system that links green space with health and wellbeing. This review and model provide guidance for decision making and further epidemiological research on green space and loneliness.
Using set visualization techniques to investigate and explain patterns of missing values in electronic health records
Authors: Ruddle Roy A. , Adnan Muhammad , Hall Marlous 
Published: May 2022

ABSTRACTObjectivesMissing data is the most common data quality issue in electronic health records (EHRs). Checks are typically limited to counting the number of missing values in individual fields, but researchers and organisations need to understand multi-field missing data patterns, and counts or numerical summaries are poorly suited to that. This study shows how set-based visualization enables multi-field missing data patterns to be discovered and investigated.DesignDevelopment and evaluation of interactive set visualization techniques to find patterns of missing data and generate actionable insights.Setting and participantsAnonymised Admitted Patient Care health records for NHS hospitals and independent sector providers in England. The visualization and data mining software was run over 16 million records and 86 fields in the dataset.ResultsThe dataset contained 960 million missing values. Set visualization bar charts showed how those values were distributed across the fields, including several fields that, unexpectedly, were not complete. Set intersection heatmaps revealed unexpected gaps in diagnosis, operation and date fields. Information gain ratio and entropy calculations allowed us to identify the origin of each unexpected pattern, in terms of the values of other fields.ConclusionsOur findings show how set visualization reveals important insights about multi-field missing data patterns in large EHR datasets. The study revealed both rare and widespread data quality issues that were previously unknown to an epidemiologist, and allowed a particular part of a specific hospital to be pinpointed as the origin of rare issues that NHS Digital did not know exist.ARTICLE SUMMARYStrengths and limitations of this studyThis study demonstrates the utility of interactive set visualization techniques for finding and explaining patterns of missing values in electronic health records, irrespective of whether those patterns are common or rare.The techniques were evaluated in a case study with a large (16-million record; 86 field) Admitted Patient Care dataset from NHS hospitals.There was only one data table in the dataset. However, ways to adapt the techniques for longitudinal data and relational databases are described.The evaluation only involved one dataset, but that was from a national organisation that provides many similar datasets each year to researchers and organisations.
Self-Reported SARS-CoV-2 Vaccination is Consistent with Electronic Health Record Data among the COVID-19 Community Research Partnership
Authors: Tjaden Ashley H. , Fete Lida M. , Edelstein Sharon L. , Gibbs Michael , Hinkelman Amy , Runyon Michael , Santos Roberto P. , Weintraub William S. , Yukich Joshua , Uschner Diane ,   the COVID-19 Community Research Partnership Study Group
Published: May 2022

ABSTRACTIntroductionObservational studies of SARS-CoV-2 vaccine effectiveness depend on accurate ascertainment of vaccination receipt, date, and product type. Self-reported vaccine data may be more readily available to and less expensive for researchers than assessing medical records.MethodsWe surveyed adult participants in the COVID-19 Community Research Partnership who had an authenticated EHR (N=41,484) concerning receipt of SARS-CoV-2 vaccination using a daily survey beginning in December 2020 and a supplemental survey in September-October 2021. We compared self-reported information to that available in the EHR for the following data points: vaccine brand, date of first dose, and number of doses. Self-reported data was available immediately following vaccination (in the daily survey) and at a delayed interval (in the supplemental survey).ResultsFor the date of first vaccine dose, self-reported “immediate” recall was within +/- 7 days of the date reported in the “delayed” survey for 87.9% of participants. Among the 19.6% of participants with evidence of vaccination in their EHR, 95% self-reported vaccination in one of the two surveys. Self-reported dates were within +/- 7 days of documented EHR vaccination for 97.6% of the “immediate” surveys and 92.0% of the “delayed” surveys. Self-reported vaccine product details matched those in the EHR for over 98% of participants for both “immediate” and “delayed” surveys.ConclusionsSelf-reported dates and product details for COVID-19 vaccination can be a good surrogate when medical records are unavailable in large observational studies. A secondary confirmation of dates for a subset of participants with EHR data will provide internal validity.
Spatially Constrained Gene Regulation Identifies Key Genetic Contributions of Preeclampsia, Hypertension and Proteinuria
Authors: Boom Genevieve , O’Sullivan Justin M. , Schierding William 
Published: May 2022

AbstractPreeclampsia (PE) is a relatively common but severe pregnancy disorder that is characterized by hypertension (HTN) and either proteinuria (PRO), or other organ damage. There are very limited effective treatments for PE, and it is associated with substantial effects on the health of both the mother and fetus. 25 genetic variants have been associated (p < 1 × 10−6) with PE in the latest genome-wide association studies (GWAS). By overlapping the regulatory impacts of the PE-associated genetic variants with the regulatory impacts of HTN- and PRO-associated genetic variants, we were able to identify shared functional impacts between PE and HTN. We identified significant variation of the mean LOUEF scores for genes targeted by cis- and trans-acting eQTLs, consistent with an enrichment for regulatory interactions with target genes intolerant to loss-of-function mutations. Signaling pathways were enriched within the protein-protein interaction networks (PPINs) that were constructed using proteins encoded by the eQTL targeted genes. Finally, tissue-specific analyses of eQTLs specific to whole blood and arteries detected dysregulation of PE-relevant regulatory pathways. Collectively, these results are consistent with a model in which predisposition to HTN and PRO lays a molecular groundwork toward risk for PE pathogenesis. These findings inform on possible therapeutic targets for future studies.
Is Cancer significant Comorbid Condition in COVID 19 Infected Patients? -A Retrospective Analysis Experienced in a Tertiary Care Center in Eastern India
Authors: Mukherjee Kalyan K , Dam Aniruddha , Chakrabarti Deepa , Jatua Debasish , Sengupta Saubhik , Dutta Rita , Majumdar Suparna , Mandal Shyam Sundar , Basu Biswarup , Bhattacharjee Pratiti , Mukherjee Dattatreya , Sengupta Sankar , Chakrabarti Jayanta 
Published: May 2022

AbstractObjectivesPatients with a history of active malignancy were initially thought to be at a higher risk of having COVID-19, although available data are conflicting due to economic stress, malnutrition, fear of hospitalization or treatment discontinuation. A cohort-based study was undertaken in Indian regional cancer centre to understand cancer-covid link in patients.Study DesignA total of 1565 asymptomatic patients were admitted based on thermal screening and evaluation from the screening form. The COVID 19 has been checked by RT-PCR method and the COVID 19 positive patients were transferred to government allocated COVID 19 hospital. The COVID 19 negative patients were transferred to general ward for further cancer treatment.MethodPost COVID 19 testing, positive patients were transferred to COVID hospital and their outcomes were analyzed and correlated with patient’s age gender and cancer stages.ResultOut of 1565 patients, 54 patients (3.4%) tested positive. Most of the patients are in 45-59 years age group. As female patients admitted were more in number than males, so predominance of disease is higher in female. 3 patients were symptomatic after admission and 2 were severe and were admitted to the ICU with ventilations. 8 patients died in Cancer and one patient died in COVID 19.ConclusionsAs only 3.4% patients tested positive and only one patient out of 54 had died, so cancer is found not to be a comorbid condition towards COVID 19 patients in the Indian population studied.
Artificial intelligence-based opportunistic screening for the detection of arterial hypertension through ECG signals
Authors: Angelaki Eleni , Barmparis Georgios D. , Kochiadakis George , Maragkoudakis Spyros , Savva Eirini , Kampanieris Emmanuel , Kassotakis Spyros , Kalomoirakis Petros , Vardas Panos , Tsironis Giorgos P. , Marketou Maria E. 
Published: May 2022

AbstractBackgroundHypertension is a major risk factor for cardiovascular disease (CVD) which often escapes the diagnosis or should be confirmed by several office visits. The electrocardiogram (ECG) is one of the most widely used diagnostic tools and could be of paramount importance in patients’ initial evaluation.MethodsWe used machine learning (ML) techniques based features derived from the electrocardiogram for detecting hypertension in a population without CVD. We enrolled 1091 subjects who were classified into hypertensive and normotensive group. We trained a random forest (RF), to predict the existence of hypertension in patients based only on a few basic clinical parameters and ECG-derived features. We also calculated Shapley additive explanations (SHAP), a sophisticated feature importance analysis, to interpret each feature’s role in the random forest’s predictions.ResultsOur RF model was able to distinguish hypertensive from normotensive patients with accuracy 84.2 %, specificity 66.7%, sensitivity 91.4%, and area under the receiver-operating curve 0.86. Age, body mass index (BMI), BMI-adjusted Cornell criteria (BMI multiplied by RaVL+SV3), R wave amplitude in aVL, and BMI-modified Sokolow-Lyon voltage (BMI divided by SV1+RV5), were the most important anthropometric and ECG-derived features in terms of the success of our model.ConclusionsOur ML algorithm is effective in the detection of hypertension in patients using ECG-derived and basic anthropometric criteria. Our findings open new horizon in the detection of many undiagnosed hypertensive individuals who have an increased cardiovascular disease risk.
Association of cortical arousals with sleep-disordered breathing events
Authors: Zitting Kirsi-Marja , Lockyer Brandon J , Azarbarzin Ali , Sands Scott A , Wang Wei , Wellman Andrew , Quan Stuart F 
Published: May 2022

ABSTRACTStudy ObjectivesThe American Academy of Sleep Medicine recommends scoring hypopneas in adults when there is a ≥3% oxygen desaturation Or when the event is associated with an arousal. However, there is no rule regarding the duration of the interval between the event termination and the associated arousal. The purpose of this study is to explore the timing between arousals and sleep-disordered breathing (SDB) events.MethodsWe analyzed cortical arousals (>1.6 million) and SDB events (>350,000 apneas and >1.9 million hypopneas) from 11,400 manually scored polysomnography recordings. Only arousals that started within ±30 seconds from the end of SDB events were included. We used the two local minimums on either side of the arousal distribution as the start/end times for the distribution, and to define which arousals are associated with SDB events. Finally, we calculated arousal probability near the end of SDB events.ResultsCortical arousals with start times that fell within the two minimums were considered to be associated with SDB events. Using this definition, we found that 90% of apnea-associated arousals started no earlier than 4 seconds before and no later than 9 seconds after the end of apneas. Similarly, 90% of hypopnea-associated arousals started no earlier than 6 seconds before and no later than 14 seconds after the end of hypopneas, with the peak of the distribution coinciding with event end time. Arousal probability was highest during the first 10 seconds after the end of the event and was higher for longer events.ConclusionsOur results suggest that 90% of SDB-associated arousals start from 6 seconds before to 14 seconds after the end of the respiratory events.