bluuebunny/crossref_metadata_2025_split huggingface dataset:
Outcomes of psychiatric interviews and self-rated symptom scales in people on sick leave for common mental disorders: an observational study
Authors: af Winklerfelt Hammarberg Sandra , Westman Jeanette , Hange Dominique , Finnes Anna , Björkelund Cecilia , Hällgren Jonas , Skoglund Ingmarie , Nager Anna 
Published: June 2022

ObjectivesTo investigate the correspondence between diagnoses on sick leave certificates and diagnoses made in structured psychiatric interviews. Secondary aims were to investigate length of sick leave by diagnoses on sick leave certificates, diagnoses made in structured interviews and symptom severity.DesignObservational study consisting of a secondary analysis of data from a randomised controlled trial and an observational study.SettingThe regions of Stockholm and Västra Götaland, Sweden.Participants480 people on sick leave for common mental disorders.InterventionsParticipants were examined with structured psychiatric interviews and self-rated symptom severity scales.Outcome measures(1) Sick leave certificate diagnoses, (2) diagnoses from the Mini International Neuropsychiatric Interview and the Self-rated Stress-Induced Exhaustion Disorder (SED) Instrument (s-ED), (3) symptom severity (Montgomery-Asberg Depression Rating Scale-self-rating version and the Karolinska Exhaustion Disorder Scale) and (4) number of sick leave days.ResultsThere was little correspondence between diagnoses on sick leave certificates and diagnoses made in structured psychiatric interviews. Many participants on sick leave for SED, anxiety disorder or depression fulfilled criteria for other mental disorders. Most on sick leave for SED (76%) and anxiety disorder (67%) had depression (p=0.041). Length of sick leave did not differ by certificate diagnoses. Participants with SED (s-ED) had longer sick leave than participants without SED (144 vs 84 days; 1.72 (1.37–2.16); p<0.001). More severe symptoms were associated with longer sick leave.ConclusionDiagnoses on sick leave certificates did not reflect the complex and overlapping nature of the diagnoses found in the structured psychiatric interviews. This finding is relevant to the interpretation of information from health data registers, including studies and guidelines based on these data. A result of clinical interest was that more severe symptoms predicted long-term sick leave better than actual diagnoses.
Investigation of the use of a sensor bracelet for the presymptomatic detection of changes in physiological parameters related to COVID-19: an interim analysis of a prospective cohort study (COVI-GAPP)
Authors: Risch Martin , Grossmann Kirsten , Aeschbacher Stefanie , Weideli Ornella C , Kovac Marc , Pereira Fiona , Wohlwend Nadia , Risch Corina , Hillmann Dorothea , Lung Thomas , Renz Harald , Twerenbold Raphael , Rothenbühler Martina , Leibovitz Daniel , Kovacevic Vladimir , Markovic Andjela , Klaver Paul , Brakenhoff Timo B , Franks Billy , Mitratza Marianna , Downward George S , Dowling Ariel , Montes Santiago , Grobbee Diederick E , Cronin Maureen , Conen David , Goodale Brianna M , Risch Lorenz 
Published: June 2022

ObjectivesWe investigated machinelearningbased identification of presymptomatic COVID-19 and detection of infection-related changes in physiology using a wearable device.DesignInterim analysis of a prospective cohort study.Setting, participants and interventionsParticipants from a national cohort study in Liechtenstein were included. Nightly they wore the Ava-bracelet that measured respiratory rate (RR), heart rate (HR), HR variability (HRV), wrist-skin temperature (WST) and skin perfusion. SARS-CoV-2 infection was diagnosed by molecular and/or serological assays.ResultsA total of 1.5 million hours of physiological data were recorded from 1163 participants (mean age 44±5.5 years). COVID-19 was confirmed in 127 participants of which, 66 (52%) had worn their device from baseline to symptom onset (SO) and were included in this analysis. Multi-level modelling revealed significant changes in five (RR, HR, HRV, HRV ratio and WST) device-measured physiological parameters during the incubation, presymptomatic, symptomatic and recovery periods of COVID-19 compared with baseline. The training set represented an 8-day long instance extracted from day 10 to day 2 before SO. The training set consisted of 40 days measurements from 66 participants. Based on a random split, the test set included 30% of participants and 70% were selected for the training set. The developed long short-term memory (LSTM) based recurrent neural network (RNN) algorithm had a recall (sensitivity) of 0.73 in the training set and 0.68 in the testing set when detecting COVID-19 up to 2 days prior to SO.ConclusionWearable sensor technology can enable COVID-19 detection during the presymptomatic period. Our proposed RNN algorithm identified 68% of COVID-19 positive participants 2 days prior to SO and will be further trained and validated in a randomised, single-blinded, two-period, two-sequence crossover trial.Trial registration numberISRCTN51255782; Pre-results.
Multiple air pollutants exposure and leukaemia incidence in Tehran, Iran from 2010 to 2016: a retrospective cohort study
Authors: Khorrami Zahra , Pourkhosravani Mohsen , Eslahi Marzieh , Rezapour Maysam , Akbari Mohammad Esmail , Amini Heresh , Taghavi-Shahri Seyed Mahmood , Künzli Nino , Etemad Koorosh , Khanjani Narges 
Published: June 2022

ObjectiveLeukaemia is one of the most common cancers and may be associated with exposure to environmental carcinogens, especially outdoor air pollutants. The objective of this study was to investigate the association of ambient air pollution and leukaemia in Tehran, Iran.DesignIn this retrospective cohort study, data about the residential district of leukaemia cases diagnosed from 2010 to 2016 were inquired from the Ministry of Health cancer database. Data from a previous study were used to determine long-term average exposure to different air pollutants in 22 districts of Tehran. Latent profile analysis (LPA) was used to classify pollutants in two exposure profiles. The association between air pollutants and leukaemia incidence was analysed by negative binomial regression.SettingTwenty-two districts of Tehran megacity.ParticipantsPatients with leukaemia.Outcome measuresThe outcome variables were incidence rate ratios (IRR) of acute myeloid and lymphoid leukaemia across the districts of Tehran.ResultsThe districts with higher concentrations for all pollutants were near the city centre. The IRR was positive but non-significant for most of the air pollutants. However, annual mean NOx was directly and significantly associated with total leukaemia incidence in the fully adjusted model (IRR (95% CI): 1.03 (1.003 to 1.06) per 10 ppb increase). Based on LPA, districts with a higher multiple air-pollutants profile were also associated with higher leukaemia incidence (IRR (95% CI): 1.003 (0.99 to 1.007) per 1 ppb increase).ConclusionsOur study shows that districts with higher air pollution (nitrogen oxides and multipollutants) have higher incidence rates of leukaemia in Tehran, Iran. This study warrants conducting further research with individual human data and better control of confounding.
Laparoscopic versus open left hemicolectomy for left-sided colon cancer: protocol for a systematic review and meta-analysis
Authors: Du Qiang , Yang Yang , Zhang Jianhao , Liu Xueting , Wang Yong , Yang Lie 
Published: June 2022

IntroductionLaparoscopic colectomy has been widely used clinically due to its minimally invasive advantages, and many studies have also demonstrated its safety and efficacy. However, the efficacy of laparoscopic left hemicolectomy remains unclear due to the differences in pathogenesis and surgical details between left and right colon cancers. Therefore, we plan to conduct a systematic review and meta-analysis to investigate whether laparoscopic techniques can be safely used in left hemicolectomy.Method and analysisThis meta-analysis protocol will be completed and reported according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols guidelines. A systematic search was performed for all articles related to laparoscopic left hemicolectomy in PubMed, Web of Science, Medline, EMBASE and the Cochrane Library from inception to 5 November 2021. Article screening and data extraction were performed independently by two authors and cross-checked after completion. The literature to be included will use corresponding tools for bias risk assessment. Subgroup analyses and sensitivity analyses will be used to explore potential heterogeneity.Ethics and disseminationBecause this systematic review is based on studies with published results and does not involve intervention in patients, no ethical review is required. The results of this study will be published in a peer-reviewed journal.PROSPERO registration numberCRD42022291526.
Dark matter in the CP-violating NMSSM
Authors: Ahmed Waqas , Goodsell Mark , Munir Shoaib 
Published: June 2022

AbstractIn the Next-to-Minimal Supersymmetric Standard Model there is a strong correlation between the mass terms corresponding to the singlet Higgs and the singlino interaction states, both of which are proportional to the parameter$$\kappa $$κ. If this parameter is complex, explicit CP-violation occurs in the Higgs as well as the neutralino sectors of the model at the tree level, unlike in the minimal scenario. A small magnitude of$$\kappa $$κtypically yields a$${{\mathcal {O}}}$$O(10) GeV lightest neutralino with a dominant singlino component. In such a scenario, the phase of$$\kappa $$κ, beside modifying the properties of the five Higgs bosons, can also have a crucial impact on the phenomenology of the neutralino dark matter. In this study we perform a first investigation of this impact on the relic abundance of the dark matter solutions with sub-100 GeV masses, obtained for parameter space configurations of the model that are consistent with a variety of current experimental data.
Investigation of hidden-charm double strange pentaquark candidate $$P_{css}$$ via its mass and strong decays
Authors: Azizi K. , Sarac Y. , Sundu H. 
Published: June 2022

AbstractThis work presents an analysis of a hidden charmed pentaquark candidate state with double strange quark in its quark content. The investigation is performed in two parts, which provide the mass prediction of the considered state and its partial decay widths for the$$P_{css}\rightarrow \Xi ^0 J/\psi $$Pcss→Ξ0J/ψand$$P_{css}\rightarrow \Xi _c^+ D_s^-$$Pcss→Ξc+Ds-channels. For the analyses, two-point and three-point QCD sum rule methods are applied to get the mass and the widths, respectively. The mass for this candidate state is obtained as$$m_{P_{css}}=4600 \pm 155$$mPcss=4600±155 MeV with corresponding current coupling constant$$\lambda _{P_{css}}=(0.81 \pm 0.21)\times 10^{-3}$$λPcss=(0.81±0.21)×10-3 GeV$$^6$$6. These results are used in the analysis of the partial widths of this state for the decays$$P_{css}\rightarrow \Xi ^0 J/\psi $$Pcss→Ξ0J/ψand$$P_{css}\rightarrow \Xi _c^+ D_s^-$$Pcss→Ξc+Ds-. From these decays, the total width is obtained as$$\Gamma = 12.29\pm 2.94 $$Γ=12.29±2.94 MeV. These results may shed light on the future experimental searches in which such types of states are probed and may provide information to discriminate between such possible observations.
Abstract A11: How to adjust comorbidity in mortality outcome in Korean cancer patients using claim-based health care big data
Authors: Lee Sanghee , Cho Hyunsoon 
Published: June 2022

Abstract
Background and Objective: Cancer prognosis is frequently complicated by the presence of comorbid conditions. Prognostic prediction model with less-precise comorbidity risk adjustment would result in biased estimates. This study aimed to illustrate the impact of comorbidity measurements and algorithms for cancer patients using claim-based health care big data.
Method: Data from population-based health claims data, national health insurance database in Korea were used to capture comorbidities in cancer patients. Quan’s ICD-10 was used to identify Charlson and Elixhauser comorbidity. The prevalence of comorbid condition and its impact on mortality were compared according to different claim types (inpatient and outpatient) and ascertainment periods (look-back and window). To improve diagnostic accuracy, Klabunde rule-out algorithm and drug prescriptions were considered, and we assessed how they affect our results. Impact of comorbidity on mortality was assessed by using Cox proportional hazards model adjusting for sex. Prognostic performance to predict short- and long- erm morality was compared using Harrel’s c-statistic.
Result: The most common comorbid conditions were “peptic ulcer disease (PUD),” “chronic pulmonary disease (COPD),” and “mild liver disease (MLD)” in Korean cancer patients. Elixhauser additionally captured 30% of patients with “hypertension” and 3.6% with “depression”; these conditions are not included in Charlson. 90-day versus no window period decreased prevalence of PUD from 27.4 to 19.1 (COPD, 20.2 to 16.3; MLD, 16.4 to 9.5). By shortening the look-back from 3 years to 1 year, prevalence of PUD decreased from 22.9 to 12.9 (COPD, 19.7 to 10.3; MLD, 12.0 to 6.6). In the absence of rule-out algorithm, the prevalence was at most 1.8 times greater in COPD. Within inpatient claim, use of window period had increased HR of MLD (1.9 to 3.7), whereas HR of “myocardial infarction” turned out to be statistically nonsignificant. The C-statistic was 0.71 in 1-year mortality prediction with only inpatient claim. However, better performance was shown with both in- and outpatient claim in predicting 5-year mortality.
Conclusion: Prevalence of comorbidity and its impact on the prognosis prediction vary considerably by comorbidity measurement and algorithm. The higher estimated risk of death in inpatient claim would reflect disease severity. Researchers need to check how patients’ comorbidities are captured by various factors associated with claim-based data, then choose the most adequate algorithm according to patients’ characteristics and study purpose.
Citation Format: Sanghee Lee, Hyunsoon Cho. How to adjust comorbidity in mortality outcome in Korean cancer patients using claim-based health care big data [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr A11.
Abstract A30: Comparing mail-based and Internet population health assessment data: Survey implementation protocol
Authors: Fuemmler Bernard F. , Miller Carrie A. , Wheeler David , Dahman Bassam , Gal Tamas , Kim Sunny , Morris Bonnie , Sheng Yaou , Ginder Gordon 
Published: June 2022

Abstract
Purpose of the Study: Traditionally, population-based health assessments have been conducted through resource intensive approaches such as in-person interviews and mail-based surveys. Newer information technologies have been developed for collecting survey data electronically (i.e., e-cohort approaches), which can be leveraged to recruit participants and collect survey data more efficiently than traditional studies. Funded by a National Cancer Institute P30 Supplement, the purpose of this study overall is to assess health practices and improve cancer prevention and control outreach within our cancer center’s catchment area. The purpose of this report is to describe procedures of this ongoing project collecting survey data through traditional and electronic methods.
Methods: This study will administer a survey using two approaches to population health assessment. The first survey cohort will be obtained via a mail-based survey using traditional probability-based sampling methods. A second cohort will be recruited and assessed through technology-enabled methods. This e-cohort will be contacted using an Internet and mobile phone application adapted from the platform developed by Vibrent Health for the National Institutes of Health All of Us study. In addition to the survey responses, data from wearable devices and health service records data will be collected from participants of the e-cohort.
Results: This protocol report will describe implementation procedures of an epidemiologic research study employing both conventional and novel approaches to survey administration. Upon completion of this study, results will provide metrics for comparing the methodologies, such as response rates and respondent characteristics (e.g., socio-demographics, medical history, and lifestyle behaviors) within and between each approach.
Conclusions: Ultimately, results of this study will aid the development of future epidemiologic research studies by providing practical guidance for public health and survey researchers regarding traditional and electronic survey applications, and perhaps, novel insights from the complementary approach of using both survey research methodologies in tandem.
Citation Format: Bernard F. Fuemmler, Carrie A. Miller, David Wheeler, Bassam Dahman, Tamas Gal, Sunny Kim, Bonnie Morris, Yaou Sheng, Gordon Ginder. Comparing mail-based and Internet population health assessment data: Survey implementation protocol [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr A30.
Abstract A40: Characterization of quantitative gene-expression dimensions in myeloma tumors
Authors: Waller Rosalie G. , Madsen Michael J. , Gardner John , Sborov Douglas , Camp Nicola J. 
Published: June 2022

Abstract
Background: Clinical management and research of multiple myeloma (MM), a cancer of plasma cells, is limited by tumor heterogeneity. A standard approach to deconstruct tumor heterogeneity is to use hierarchical clustering techniques to determine mutually exclusive categorical subtypes. However, categorical subtypes may fail to capture potential important variations that cross tumor subtypes. An alternate approach is to determine orthogonal, quantitative tumor dimensions where each dimension is an independent tumor characteristic. We hypothesize that using a quantitative framework for tumor heterogeneity in MM will uncover biologically relevant components to tumors and may reflect specific molecular liabilities and therapeutic vulnerabilities. Further, these quantitative characteristics may be more homogeneous genetically and useful for germline gene mapping.
Objective: Identify orthogonal, quantitative dimensions in MM tumors using gene expression.
Data: RNA sequencing on treatment-naïve, CD138 sorted tumor cells from 768 individuals. Publicly available from the MM Research Foundation’s Clinical Outcomes on MM Genetic Profiles Assessment (CoMMpass) Interim Analysis 12a. SALMON transcripts per million adjusted expression estimates on 16,870 protein coding genes.
Analyses: Multistage singular value decomposition (SVD) to 1) select representative genes, and 2) characterize the orthogonal, quantitative tumor dimensions. Stage 1: Genes that contribute most to the initial SVD will be selected as representative genes. Stage 2: SVD on selected genes to identify quantitative gene expression tumor dimensions. Each dimension is a linear combination of the representative genes. Future work will associate the quantitative dimensions with demographic, clinical, and genetic (germline and somatic) characteristics, in addition to response to treatment using penalized linear regression modeling.
Conclusions: We present a new approach for the characterization of MM tumors using a more sophisticated quantitative framework that will facilitate more flexibility for subsequent statistical modeling. Improved measures for tumors have the potential to provide increased power for identification of association between tumor characteristics and genetic (germline or somatic) characteristics with ultimate potential for genetic counseling, insights into mechanism, risk stratification, response to treatment, and new candidates for precision therapeutics.
Citation Format: Rosalie G. Waller, Michael J. Madsen, John Gardner, Douglas Sborov, Nicola J. Camp. Characterization of quantitative gene-expression dimensions in myeloma tumors [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr A40.
Abstract IA01: Opportunities in technology and connected health for population science
Authors: Kibbe Warren A. 
Published: June 2022

Abstract
The revolution in consumer-based wearables, smart homes, and ubiquitous computing provides a new foundation for understanding with data the patient experience, and just as importantly understanding the health trajectories of people as they go through their lives outside of the health system. Likewise, coupling these data with patient-reported outcomes data for cancer patients provides new avenues for understanding the experience and outcomes of cancer patients as they go through various therapeutic regimes. Providing flexible, well-described mechanisms for storing and analyzing these many data sources is critical for enabling the use of these data for the generation of novel insights and improving patient surveillance, screening, care and survivorship.
Citation Format: Warren A. Kibbe. Opportunities in technology and connected health for population science [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr IA01.
Abstract IA06: Wearable sweat sensor for personalized health monitoring
Authors: Gao Wei 
Published: June 2022

Abstract
The rising research interest in personalized and precision medicine promises to revolutionize traditional medical practices. This presents a tremendous opportunity for developing wearable devices toward predictive analytics and treatment. In this talk, I will introduce fully integrated flexible biosensors for multiplexed in situ perspiration analysis, which can selectively and accurately measure a wide spectrum of sweat analytes (e.g., metabolites, electrolytes, heavy metals, drugs, and other small molecules). This platform allows us to gain real-time insight into the sweat secretion and gland physiology. I will also demonstrate an integrated wearable sweat extraction and sensing system that can be programmed to induce sweat on demand with various secretion profiles. To demonstrate the clinical value of our wearable sweat-sensing platform, human subject studies were performed toward fitness monitoring, physiologic monitoring, disease diagnosis, and drug monitoring. These wearable and flexible devices open the door to a wide range of personalized monitoring and diagnostic applications.
Citation Format: Wei Gao. Wearable sweat sensor for personalized health monitoring [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr IA06.