bluuebunny/crossref_metadata_2025 huggingface dataset:
Significant Mortality Associated With COVID-19 and Comorbid Cerebrovascular Disease: A Quantitative Systematic Review
Authors: Sursal Tolga , Gandhi Chirag D. , Clare Kevin , Feldstein Eric , Frid Ilya , Kefina Martin , Galluzzo Daniela , Kamal Haris , Nuoman Rolla , Amuluru Krishna , Muh Carrie R. , Pisapia Jared M. , Gulko Edwin , Overby Philip , Chandy Dipak , Etienne Mill , Kurian Christeena , Kaur Gurmeen , Dakay Katarina , AlHamid May , Al-Jehani Hosam , Mayer Stephan A. , Al-Mufti Fawaz
Published: December 2022

We report the first quantitative systematic review of cerebrovascular disease in coronavirus disease 2019 (COVID-19) to provide occurrence rates and associated mortality. Through a comprehensive search of PubMed we identified 8 cohort studies, 5 case series, and 2 case reports of acute cerebrovascular disease in patients with confirmed COVID-19 diagnosis. Our first meta-analysis utilizing the identified publications focused on comorbid cerebrovascular disease in recovered and deceased patients with COVID-19. We performed 3 additional meta-analyses of proportions to produce point estimates of the mortality and incidence of acute cerebrovascular disease in COVID-19 patients. Patient’s with COVID-19 who died were 12.6 times more likely to have a history of cerebrovascular disease. We estimated an occurrence rate of 2.6% (95% confidence interval, 1.2–5.4%) for acute cerebrovascular disease among consecutively admitted patients with COVID-19. While for those with severe COVID-19‚ we estimated an occurrence rate of 6.5% (95% confidence interval, 4.4–9.6%). Our analysis estimated a rate of 35.5% for in-hospital mortality among COVID-19 patients with concomitant acute cerebrovascular disease. This was consistent with a mortality rate of 34.0% which we obtained through an individual patient analysis of 47 patients derived from all available case reports and case series. COVID-19 patients with either acute or chronic cerebrovascular disease have a high mortality rate with higher occurrence of cerebrovascular disease in patients with severe COVID-19.
The association between diabetes type, age of onset, and age at natural menopause: a retrospective cohort study using the Canadian Longitudinal Study on Aging
Authors: Mehra Vrati M. , Costanian Christy , McCague Hugh , Riddell Michael C. , Tamim Hala
Published: December 2022

Objectives

With growing incidence of type 1 diabetes (T1D), type 2 diabetes (T2D), and gestational diabetes, more women are expected to spend a larger proportion of their reproductive years living with a diabetes diagnosis. It is important to understand the long-term implications of premenopausal diabetes type on women's reproductive health including their age at natural menopause (ANM).

Methods

Baseline data from the Comprehensive Cohort of Canadian Longitudinal Study on Aging were used. Females who reported premenopausal diagnosis of diabetes were considered exposed. Kaplan-Meier cumulative survivorship estimates and multivariable Cox regression models were used to assess the association between diabetes types and ANM. Sociodemographic, lifestyle, and premenopausal clinical factors were adjusted in the final model as covariates.

Results

The sample comprised 11,436 participants, weighted to represent 1,474,412

Canadian females aged 45 to 85 years. The median ANM was 52 years. After adjusting for ethnicity, education, smoking, and premenopausal clinical factors, early age of diagnosis of both T1D (<30 years) and T2D (30-39 years) were associated with earlier menopause (T1D, <30: hazard ratio [HR], 1.55; 95% confidence interval [CI], 1.05-2.28; T2D, 30-39: HR, 1.82; 95% CI, 1.12-2.94), as compared with nondiabetics. In addition, later age of diagnosis of T2D (≥40 years) was associated with later ANM (T2D: HR, 0.63; 95% CI, 0.50-0.80). No significant association between gestational diabetes and ANM was noted.

Conclusions

Our results point to early menopause among young women living with a diabetes diagnosis. These findings should allow for more focused research geared toward understanding the long-term health implications of diabetes on women's reproductive health and aging.
Estimation of placebo effect in randomized placebo-controlled trials for moderate or severe vasomotor symptoms: a meta-analysis
Authors: Zhou Tianyu
Published: December 2022

Objective

The Food and Drug Administration guidance recommended that for the indication of vasomotor symptoms (VMS), studies should enroll participants with minimum of seven to eight moderate to severe VMS per day at baseline, and coprimary endpoints should be the mean change in frequency/severity at weeks 4 and 12. This study aimed to estimate placebo effects in randomized controlled trials (RCTs) fulfilling this guidance.

Methods

PubMed was searched using the following terms: “vasomotor symptom or hot flash or hot flashes or hot flash or hot flashes [title/abstract],” “menopause or climacteric,” “RCT or randomized controlled or randomized controlled,” “placebo [title/abstract],” and “frequency or severity.” Inclusion criteria were as follows: (1) placebo controlled RCTs, (2) enrolling women with moderate or severe VMS with a minimal frequency more than seven to eight times per day or 50 times per week, and (3) efficacy measurements including mean change in VMS frequency from baseline at week 12. A random-effects model was used in the meta-analysis.

Results

Seventeen studies were included for the estimation of VMS frequency reduction and 13 studies for severity. Estimated change of VMS frequency in placebo arms was −5.44 times per day (95% CI, −5.81 to −5.07 times per day) at week 12. For VMS severity, the estimated change at week 12 was −0.36 (95% CI, −0.46 to −0.27).

Conclusion

Substantial and consistent placebo effects were observed in RCTs for VMS treatment. These data suggest a reduction of 5.44 times per day in frequency and 0.36 in severity might be observed as a placebo effect.
Treatment and resource utilization for menopausal symptoms in the United States: a retrospective review of real-world evidence from US electronic health records
Authors: DePree Barbara , Houghton Katherine , Shiozawa Aki , Esterberg Elizabeth , King Deanna D. , Kim Janet , Mancuso Shayna
Published: December 2022

Objective

The aim of this study was to generate real-world evidence documenting use of prescription and nonprescription therapies recorded by health care providers for women experiencing vasomotor symptoms (VMS) associated with menopause.

Methods

This noninterventional, retrospective, observational cohort study used data from US patient medical records. Participating health care providers were gynecologists, internal medicine/family physicians, or advanced practice providers who typically saw three or more women per week presenting with menopausal symptoms and could identify eligible medical records; providers were recruited from local medical association directories and from listings from previously conducted research. Eligible women presented January 2016 through December 2019, were 40 to 60 years of age, and reported experiencing bothersome hot flashes at least twice within 24 hours.

Results

A total of 283 health care providers provided data for 1,016 women. The most common symptoms at initial presentation were hot flashes (91.2%), sleep problems (49.9%), and vaginal dryness (47.0%). At least one therapy for menopausal symptoms was recorded for 883 women (86.9%), and 611 (60.1%) had documentation of prescription medication, most commonly hormone therapy (70.4%). Nearly 40% of women had no prescription medication documented, and approximately 13% had no therapy documented. Despite experiencing bothersome menopausal symptoms, approximately 50% delayed seeking care for more than 6 months. Women had a mean of 2.1 (SD, 2.0) office visits related to menopause from initial presentation to completion of review, and health care resource utilization did not vary by treatment status. Subgroup analyses indicated nominal differences in treatment use across ethnic groups and varying prescribing patterns for menopausal symptoms by practitioner type and US region.

Conclusions

A high proportion of women with VMS remain untreated even when experiencing bothersome symptoms of menopause. Improved management of VMS is required to provide relief from the symptoms effectively and safely.
Building prediction models of clinically significant intraocular lens tilt and decentration for age-related cataract
Authors: Gu Xiaoxun , Zhang Miao , Liu Zhenzhen , Ruan Xiaoting , Tan Xuhua , Zhang Enen , Chen Xiaoyun , Luo Lixia , Liu Yizhi
Published: December 2022

Purpose:

To explore the risk factors and construct nomogram models to predict the risks of clinically significant intraocular lens (IOL) tilt and decentration after cataract surgery in patients with age-related cataract.

Setting:

Zhongshan Ophthalmic Center, Guangzhou, China.

Design:

Prospective cohort study.

Methods:

207 patients (207 eyes) who underwent phacoemulsification combined with IOL implantation were enrolled in the study. Casia2 was used to measure the tilt and decentration of crystalline lenses and IOLs before and 3 months after surgery. Univariate and multivariate logistic regression analyses were used to determine the risk factors of clinically significant IOL tilt and decentration, and nomogram prediction models were constructed according to the results of the multivariate logistic regression analysis.

Results:

Two hundred and seven patients were included in analysis. 24 eyes (11.59%) and 16 eyes (7.73%) had clinically significant IOL tilt and decentration at 3 months after cataract surgery. Multivariate logistic regression analysis revealed that preoperative crystalline lens tilt and decentration were the risk factors for clinically significant IOL tilt (odds ratio [OR], 3.519,P< .001) and decentration (OR, 410.22,P= .001), respectively. Axial length was another association factor for clinically significant IOL decentration (OR, 2.155,P= .019). The risk models demonstrated good calibrations and discriminations for the predictions of clinically significant IOL tilt (receiver operating characteristic [ROC] area = 0.833, cutoff value = 6.5) and decentration (ROC area = 0.757, cutoff value = 0.08).

Conclusions:

The good performances of our models suggested that they may be useful risk prediction tools for postoperative IOL tilt and decentration. The measurement of preoperative crystalline lens tilt and decentration should be one of the routine examinations before cataract surgery, especially for toric and multifocal IOLs.
Cardiometabolic Diseases and Quality-of-Life Outcomes in Adults With HIV in the Deep South: A Cross-sectional Study
Authors: Enogela Ene M. , Jones Raymond , Buford Thomas W. , Vance David E. , Fazeli Pariya L.
Published: December 2022

The role of cardiometabolic diseases (CMDs) on physical health–related quality of life (P-HRQoL) and quality of sleep was examined among 261 PLWH ≥40 years, recruited from a university-affiliated HIV clinic in the Deep U.S. South. Using a cross-sectional study design, participants completed the Medical Outcomes Study HIV Health Survey (MOS-HIV; P-HRQoL) and Pittsburgh Sleep Quality Index. The overall prevalence of self-reporting ≥1 CMD was 64.4%. P-HRQoL scores were lower in PLWH with ≥1 CMD compared with those with no CMDs (45.53 ± 11.54 vs. 49.67 ± 10.77, p <.01). Poor sleep quality was higher among participants with ≥1 CMD compared with those with no CMDs (9.28 ± 4.42 vs. 7.26 ± 4.17, p<.01). Each additional CMD resulted in a 1.83-point decrease in P-HRQoL and 0.74-point increase in poor sleep quality scores. Interventions that focus on targeting these quality-of-life domains in PLWH with CMDs are needed.
Influence of Shift Work on Arterial Stiffness and Systemic Inflammation
Authors: Skogstad Marit , Aass Hans Christian D. , Sirnes Per Anton , Mamen Asgeir , Skare Øivind , Matre Dagfinn , Hammer Stine Eriksen , Goffeng Elisabeth , Lunde Lars-Kristian
Published: December 2022

Objective

To assess changes in cardiovascular disease risk factors during a 3-year follow-up among 57 rotating shift workers and 29 day workers in industry.

Methods

We collected demographics by questionnaire, examined blood pressure, heart rate, pulse wave velocity, carotid media thickness, and maximal oxygen uptake. We assessed blood samples for determination of lipids, glycosylated hemoglobin, C-reactive protein, markers of inflammation, and particle concentrations/respirable dust. Baseline comparisons were analyzed using logistic regression (plaque) and linear regression for all other outcomes. We applied mixed models to assess differences in change in health outcomes between the shift workers and the day workers.

Results

At baseline, the adhesion molecules soluble vascular cell adhesion molecule 1 and soluble P-selectin were elevated among the shift workers compared with that of the day workers. There was a significant difference in change in pulse wave velocity between shift workers (1.29-m/s increase) and day workers (0.11-m/s increase) over the 3-year follow-up. Respirable dust levels were below the Norwegian occupational exposure limit.

Conclusions

Shift work in industry is associated with arterial stiffening reflecting increased risk for future cardiovascular disease. More uncertainly, we found some support for systemic inflammation.
Mediating and Moderating Effects of Psychological Detachment on the Association Between Stressors and Depression
Authors: Kiuchi Keita , Sasaki Takeshi , Takahashi Masaya , Kubo Tomohide , Yoshikawa Toru , Matsuo Tomoaki , Liu Xinxin
Published: December 2022

Objectives

This study examines the mediating and moderating effects of psychological detachment (PD) based on the stressor-detachment model in the long term.

Methods

Two waves of Web-based surveys, 28 months apart, yielded 3556 responses from Japanese workers. Comparisons between models that included mediating and moderating effects of PD and reverse direction mediating effects (strain → PD → stressor) were made by structural equation modeling. Differences in depression as a strain between combinations of high and low stressors and PD were also examined.

Results

The best-fitting model was the moderation/reciprocal partial-mediation model. The effect of PD was significant in the group with stable or decreasing stressor.

Conclusion

According to the worker's level of stressors, PD, and depression, targeted interventions may effectively prevent physical and mental health problems caused by chronic stress.
PISCovid-1_final_preprint.docx
Authors: AbdelMassih Antoine , Hanafy Maram , ElAhmady Maryam , Kozman Sylvia , Diab Nourine , Husseiny Reem , Deyab Ashrakat M , Mady Aalaa , Yasser Alya , AbdelHalim Amira , Mohyeldin Aya , Serour Aya Sayed , AbdelGadir Ayat , Abdelaziz Eslam , ElGhamry Farida , Amr Hana , Milad Karim , Fouda Lamya , Hesham Mawada , Riad Mina Adly , Aoun Mohamed , AbdelTawab Rana , Sayed Rana , ElSenbawy Salma , Abdelkhalek Sara ElAhmady , Gamal Nada , Omar Yasmin
Published: December 2022

  

Introduction:

Coronavirus Disease 2019 (COVID-19) is by far the most world-altering pandemic to ever hit modern humanity. Three years after the very first case emerged in December 2019, the virus continues to bring upon global disarray in the acute phase of the infection as well as months afterwards, causing the virus’s morbidity and mortality to further skyrocket. This systematic literature review was conducted up till December 2022, comprising all the case reports that thoroughly discuss a myriad of non-Multisystem Inflammatory Syndrome In Children (non-MIS-C) post-acute sequalae of COVID-19 (PASC) in the paediatric population, also known as Long COVID Syndrome.  In this review, we aimed to highlight the prevalent time interval between COVID-19 infection and the development of various non-MISC post-infectious sequalae (PIS). 

Methods:

We conducted a holistic literature search on PubMed, Google Scholar, Google Search, and Scopus. Data bases were searched for studies that met our inclusion and exclusion criteria. The systematic review was performed on all case reports containing relevant outcome parameters such as age, sex, the interval between COVID-19 infection and subsequent PASC and, lastly, the need for hospitalization during the course of the disease.

Results: 

We collected a total of 78 case reports discussing the various post-infectious immune sequalae following COVID-19 infection in the paediatric population, consisting of a total of 109 patients. The final screening revealed an equal sex distribution, whereas the two commonest age intervals were school-aged children and adolescents, with 38% of the patients having been older than six years. Interestingly, hospital admission throughout the course of COVID-19 wasn’t a predictor of the subsequent PASC; forty-nine patients (44.9%) were hospitalized while sixty patients (55.1%) were not hospitalized. More importantly, the most predominant time interval between COVID-19 infection and the developing PASC was observed to be within 14 days since the start of COVID-19 infection, accounting for 61% of the cases. 

Conclusion: 

These findings suggest a crucial link is slowly but surely unfolding between COVID-19 and an abundance of systemic post-infectious immune sequalae in the paediatric population, especially amongst children older than six years. Accordingly, meticulous follow-up and prompt management is largely encouraged for the paediatric population in case of unusual symptoms and signs following COVID-19 infection, regardless of COVID-19’s severity.  
Optimizing Innervation in Radial Forearm Phalloplasty: Consider the Posterior Antebrachial Cutaneous Nerve
Authors: Peters Blair R. , Richards Holden W. , Berli Jens U.
Published: December 2022

One goal of an ideal phallic reconstruction is achieving tactile and erogenous sensation. Traditionally, the most common flap used in phalloplasty has been the radial forearm flap, where the medial and lateral antebrachial cutaneous nerves are coapted to meet this goal. The purpose of this article is to draw attention to the lesser-known posterior antebrachial cutaneous nerve (PABC) as an alternative or additional nerve for coaptation that innervates a majority of the shaft, where sensation is most desired. The presence, anatomical location, and territory of innervation of the antebrachial cutaneous nerves were assessed in a series of 12 consecutive in vivo radial forearm phalloplasties. A literature review was conducted to establish which nerves have traditionally been used for sensory reinnervation of the phallus. The PABC was the first nerve encountered on the radial border of the flap lying on the fascia in the interval between the brachioradialis and extensor carpi radials longus. The posterior and lateral antebrachial cutaneous nerves innervated the phallic shaft, whereas the anterior branch of the medial antebrachial cutaneous nerve innervated the phallic urethra. There were no articles in our review that used PABC for nerve coaptation in radial forearm phalloplasty. The skin innervated by the PABC represents a significant portion of the phallic shaft when using the standard template for radial forearm phalloplasty. Despite this, its use is not described in the literature. The authors introduce the PABC as an alternative or additional nerve for coaptation in radial forearm phalloplasty.
Speech Outcomes following Mandibular Distraction Osteogenesis for Robin Sequence: Midchildhood Results
Authors: Kosyk Mychajlo S. , Zapatero Zachary D. , Kalmar Christopher L. , Carlson Anna R. , Cohen Marilyn , Swanson Jordan W. , Bartlett Scott P. , Taylor Jesse A.
Published: December 2022

Background:

The aim of this study was to compare midchildhood speech outcomes in patients with nonsyndromic Robin sequence with cleft palate (RSCP) treated with mandibular distraction osteogenesis (MDO) to patients with nonsyndromic Veau class I and Veau class II cleft palate (CP).

Methods:

The authors performed a retrospective review of patients with nonsyndromic Robin sequence from 2000 to 2017, comparing those who underwent MDO to patients with nonsyndromic CP. Demographics, operative details, length of hospital stay, complications, and Pittsburgh Weighted Speech Scale scores were collected.

Results:

Thirty-three patients met inclusion criteria in the MDO group with 127 patients as controls. Despite similar median age (RSCP, 4.5 years; CP only, 4.6 years) and Veau cleft type at early evaluation, there was a significant increase in composite Pittsburgh Weighted Speech Scale score within the MDO cohort (P ≤ 0.002); specifically, with worse visible nasal emission (P ≤ 0.007), hypernasality (P ≤ 0.001), and compensatory articulation (P ≤ 0.015). However, these differences were not present at age-matched midchildhood evaluation (median, RSCP, 6.5; CP only, 7.1; P ≥ 0.092). Median age-matched follow-up was 6.4 years in the MDO group and 7.1 years in the control group (P ≥ 0.136). There was also no difference in the rate of secondary speech surgery at midchildhood evaluation (P ≥ 0.688).

Conclusions:

The authors’ retrospective comparison of speech outcomes in RSCP versus CP only demonstrates no difference in midchildhood speech, conflicting with recent reports. Although patients with Robin sequence treated with MDO had worse visible nasal emission, hypernasality, and compensatory articulation in early childhood, this appears to have resolved in the interim without additional intervention. Longitudinal follow-up is needed to fully understand the speech ramifications of RSCP.

CLINICAL QUESTION/LEVEL OF EVIDENCE:

Risk, II.
Relating Molecular T Cell–mediated Rejection Activity in Kidney Transplant Biopsies to Time and to Histologic Tubulitis and Atrophy-fibrosis
Authors: Madill-Thomsen Katelynn S. , Böhmig Georg A. , Bromberg Jonathan , Einecke Gunilla , Eskandary Farsad , Gupta Gaurav , Myslak Marek , Viklicky Ondrej , Perkowska-Ptasinska Agnieszka , Solez Kim , Halloran Philip F. ,   the INTERCOMEX Investigators
Published: December 2022

Background.

We studied the variation in molecular T cell–mediated rejection (TCMR) activity in kidney transplant indication biopsies and its relationship with histologic lesions (particularly tubulitis and atrophy-fibrosis) and time posttransplant.

Methods.

We examined 175 kidney transplant biopsies with molecular TCMR as defined by archetypal analysis in the INTERCOMEX study (ClinicalTrials.gov #NCT01299168). TCMR activity was defined by a molecular classifier.

Results.

Archetypal analysis identified 2 TCMR classes, TCMR1 and TCMR2: TCMR1 had higher TCMR activity and more antibody-mediated rejection (“mixed”) activity and arteritis but little hyalinosis, whereas TCMR2 had less TCMR activity but more atrophy-fibrosis. TCMR1 and TCMR2 had similar levels of molecular injury and tubulitis. Both TCMR1 and TCMR2 biopsies were uncommon after 2 y posttransplant and were rare after 10 y, particularly TCMR1. Within late TCMR biopsies, TCMR classifier activity and activity molecules such as IFNG fell progressively with time, but tubulitis and molecular injury were sustained. Atrophy-fibrosis was increased in TCMR biopsies, even in the first year posttransplant, and rose with time posttransplant. TCMR1 and TCMR2 both reduced graft survival, but in random forests, the strongest determinant of survival after biopsies with TCMR was molecular injury, not TCMR activity.

Conclusions.

TCMR varies in intensity but is always strongly related to molecular injury and atrophy-fibrosis, which ultimately explains its effect on survival. We hypothesize, based on the reciprocal relationship with hyalinosis, that the TCMR1-TCMR2 gradient reflects calcineurin inhibitor drug underexposure, whereas the time-dependent decline in TCMR activity and frequency after the first year reflects T-cell exhaustion.
A Usability Evaluation of YouDiagnose: Artificial Intelligence Powered Physician Consultation
Authors: Misro Aswini , Kadoglou Naim , Mishra Nishikant , Whittington Paul , Dogan Huseyin
Published: December 2022

The COVID-19 Pandemic has resulted in a forced transition to tele-medicine, where history-taking and clinical assessments are performed remotely during video or telephonic consultations. While telemedicine has added to safety and social distancing during the pandemic, the manual and resource-intense process of telephonic and video consultations has not helped to ease the patient backlog, rather has added to this snowballing issue. This paper describes about YouDiagnose pre-consultation exercise that automates patient triage and clinical assessment using artificial intelligence technologies delivered through either a Smart Questionnaire or Chatbot. A usability evaluation was conducted with participants from the Patient and Public Involvement and Engagement Senate (PIES) of the Innovation Agency (an Academic Health Science Network) Qualitative feedback was obtained from the participants on both modalities and quantitative feedback in the form of the System Usability Scale (SUS), comparing the usability of both interaction modalities. The SUS scores were analysed using the Adjective Rating Scale that revealed the Smart Questionnaire had ‘Good Usability’ compared to ‘OK Usability’ of the Chatbot. The results shows the user experience and untapped potential of process automation and artificial intelligence in clinical services.
Comparing scientific abstracts generated by ChatGPT to original abstracts using an artificial intelligence output detector, plagiarism detector, and blinded human reviewers
Authors: Gao Catherine A. , Howard Frederick M. , Markov Nikolay S. , Dyer Emma C. , Ramesh Siddhi , Luo Yuan , Pearson Alexander T.
Published: December 2022

Background

Large language models such as ChatGPT can produce increasingly realistic text, with unknown information on the accuracy and integrity of using these models in scientific writing.

Methods

We gathered ten research abstracts from five high impact factor medical journals (n=50) and asked ChatGPT to generate research abstracts based on their titles and journals. We evaluated the abstracts using an artificial intelligence (AI) output detector, plagiarism detector, and had blinded human reviewers try to distinguish whether abstracts were original or generated.

Results

All ChatGPT-generated abstracts were written clearly but only 8% correctly followed the specific journal’s formatting requirements. Most generated abstracts were detected using the AI output detector, with scores (higher meaning more likely to be generated) of median [interquartile range] of 99.98% [12.73, 99.98] compared with very low probability of AI-generated output in the original abstracts of 0.02% [0.02, 0.09]. The AUROC of the AI output detector was 0.94. Generated abstracts scored very high on originality using the plagiarism detector (100% [100, 100] originality). Generated abstracts had a similar patient cohort size as original abstracts, though the exact numbers were fabricated. When given a mixture of original and general abstracts, blinded human reviewers correctly identified 68% of generated abstracts as being generated by ChatGPT, but incorrectly identified 14% of original abstracts as being generated. Reviewers indicated that it was surprisingly difficult to differentiate between the two, but that the generated abstracts were vaguer and had a formulaic feel to the writing.

Conclusion

ChatGPT writes believable scientific abstracts, though with completely generated data. These are original without any plagiarism detected but are often identifiable using an AI output detector and skeptical human reviewers. Abstract evaluation for journals and medical conferences must adapt policy and practice to maintain rigorous scientific standards; we suggest inclusion of AI output detectors in the editorial process and clear disclosure if these technologies are used. The boundaries of ethical and acceptable use of large language models to help scientific writing remain to be determined.
Benign biopsy effect on artificial intelligence cancer detector in screening mammography – a retrospective study
Authors: Zouzos Athanasios , Molovanovic Alexandra , Dembrower Karin , Strand Fredrik
Published: December 2022

Artificial intelligence (AI) cancer detectors are showing promising results and may soon be used for clinical breast cancer screening in radiology departments. Validation of such programs in different settings is mandatory.

This is a retrospective study after the application of a commercial AI cancer detector program to a cancer-enriched mammography screening dataset where 10 889 women with a median age for the study population of 56 years and a range between 40 and 74 years old where included. The program is intended for 2D mammography and it generate a prediction score for tumor presence with a decimal number between 0 and 1, where 1 represented the highest level of suspicion. The AI score median and interquartile range for women who were healthy, who had a benign biopsy, and who were diagnosed with breast cancer, was calculated. For women with a previous benign biopsy, the time between mammogram and the biopsy was stratified. The effect of increasing age was examined using stratified analysis and linear regression modelling. The proportion of healthy women above the AI abnormality threshold (0.4) defined at our hospital was 3.5%, 11% and 84% for healthy women without a benign biopsy, healthy women with a benign biopsy, and for women with breast cancer, respectively (p<0.001) and the AI score correlated positively with increasing age of the women in the cancer group (p<0.05). While 16% of the women who had a benign biopsy after mammography had an AI score above the cut-off point, there were 33% of those when they had their biopsy before the mammography. AI cancer detection systems can reliable be used in a screening setting. Adding information about possible prior benign biopsy and other symptoms can probably improve accuracy and subsequently reduce the workload for radiologists.
The response to BTN62b2 booster doses demonstrates that serum antibodies do not predict the establishment of immune B-cell memory in common variable immune deficiencies
Authors: Piano Mortari E. , Pulvirenti F. , Marcellini V. , Terreri S. , Fernandez Salinas A. , Ferrari S. , Di Napoli G. , Guadagnolo D. , Sculco E. , Albano C. , Guercio M. , Di Cecca S. , Milito C. , Garzi G. , Pesce A.M. , Bonanni L. , Sinibaldi M. , Di Cecilia S. , Agrati C. , Quintarelli C. , Zaffina S. , Locatelli F. , Carsetti R. , Quinti I.
Published: December 2022

In patients with common variable immune deficiencies, primary vaccination followed by two booster doses is recommended for protection against COVID-19. Seroconversion has been shown in 60% of patients. We have no information on whether serum antibodies reflect the generation of durable immune memory.

In a longitudinal study on 47 common variable immune deficiencies patients who received the third and fourth vaccine dose, we show that the measurement of specific antibodies is not sufficient to predict the establishment of immune memory and the ability to respond to antigen re-exposure.

Our results indicate that the combination of antibodies and memory B cells responses represents a more reliable read-out of vaccine immune efficacy in vulnerable patients.

This analysis may not only identify individuals remaining unprotected after vaccination and unable to respond to additional booster doses, but also address the search for the underlying immune defect and suggest patient-tailored management strategies.
Development and Validation of a Machine Learning Algorithm to Classify Lower Urinary Tract Symptoms
Authors: Chiang Jeffrey N. , Dallas Kai B. , Caron Ashley T. , Anger Jennifer T. , Kaufman Melissa R. , Ackerman A. Lenore
Published: December 2022

Objective

Lower urinary tract symptoms (LUTS), such as urinary urgency, frequency, and incontinence, affect the majority of the population, causing substantial morbidity, yet few receive effective care. Sizeable symptomatic overlap between LUTS categories leads to high rates of misdiagnosis. To improve diagnostic accuracy, we sought to employ machine learning approaches to LUTS categorization to generate diagnostic groupings based on patient-reported clinical data, creating a novel tool for diagnosis of patients with voiding complaints.

Methods

Questionnaire responses in a Development Dataset of 514 female subjects were used for model development, identifying 4 major clusters and 9 specific phenotypes of LUTS using agglomerative hierarchical clustering. Each cluster and phenotype was assigned a clinical identity consistent with recognized causes of voiding dysfunction by the consensus of two urologic specialists. Then, a random forest classifier was trained to assign unseen patients into these phenotypes. That model was then applied to a Validation Dataset of 571 additional subjects to confirm the diagnostic algorithm.

Results

This data-driven, hierarchical clustering approach captured overlapping symptoms inherent in typical patients, recognizing common uncomplicated diagnoses (i.e., overactive bladder) as well as several underrecognized diagnostic categories (i.e., myofascial pelvic pain). A diagnostic algorithm derived by supervised machine learning to assign unseen subjects into these phenotypes demonstrated good reproducibillty of the phenotypes and their symptomatic patterns in an independent Validation Dataset.

Conclusions

We describe the generation of a machine learning algorithm relying only on validated, patient-reported symptoms for diagnostic classification. Given a growing physician shortage and increasing challenges for patients accessing specialist care, this type of digital technology holds great potential to improve the recognition and diagnosis of functional urologic conditions.
A COMPARATIVE STUDY OF DUMPSITES METAL LOADS AND ECOLOGICAL RISK IN SELECTED COMMUNITIES IN KWARA AND EKITI STATES, NIGERIA
Authors: Abolayo T.T. , Sawyerr H.O. , Yusuf R.O , Ajai T.S. , Towolawi A.T.
Published: December 2022

This study compared the presence of selected heavy metals in Gbagede dumpsite (GD) and Ilokun dumpsite (ID) dumpsite in Kwara and Ekiti State with the host communities Gbagede community (GC) and Ilokun community (IC). Ten soil samples were collected randomly at 10 cm depth, digested and analyzed for Cadmium (Cd), Copper (Cu), Manganese (Mn), Zink (Zn) and iron (Fe) respectively. The results were compared with control and standard, and subjected to ecological risk indices: Enrichment factor (EF), Contamination factor (CF), and Index of geo-accumulation (Igeo). Metal concentrations were higher (p < 0.05 except Cu) than the control; ranged from 41.2 times (Mn in GD) to 7.08 times (Zn in ID), GD had highest metals except Cu. Metal concentrations at ID > IC (except Cu) and GD> GC. The standard <Cd and Mn,Cu at GD and GC. The EF was significant (5≤EF<20) for Zn at GD and ID, and for Mn except at GD where there was a very high (20≤EF<40). Mn and Zn indicated high contamination (Cf≥6) at GD and ID while Cd and Fe indicated moderate contamination (1≤Cf<3) except at IC (Cf<1). Moderately polluted (1<Igeo≤2) effects were shown by Fe except at IC and Mn at GD and GC. Conclusively, it was found that the Dumpsites contributed to soil metal loads and ecological risk.
A Bayesian network-based framework to uncover the causal effects of genes on complex traits based on GWAS data
Authors: Yin Liangying , Feng Yaning , Lau Alexandria , Qiu Jinghong , Sham Pak-Chung , So Hon-Cheong
Published: December 2022

Deciphering the relationships between genes and complex traits could help us better understand the biological mechanisms leading to phenotypic variations and disease onset. Univariate gene-based analyses are widely used to characterize gene-phenotype relationships, but are subject to the influence of confounders. Furthermore, while some genes directly contribute to traits variations, others may exert their effects through other genes. How to quantify individual genes’ direct and indirect effects on complex traits remains an important yet challenging question.

We presented a novel framework to decipher the total and direct causal effects of individual genes using imputed gene expression data from GWAS and raw gene expression from GTEx. The study was partially motivated by the quest to differentiate “core” genes (genes with direct causal effect on the phenotype) from “peripheral” ones. Our proposed framework is based on a Bayesian network (BN) approach, which produces a directed graph showing the relationship between genes and the phenotype. The approach aims to uncover the overall causal structure, to examine the role of individual genes and quantify the direct and indirect effects by each gene.

An important advantage and novelty of the proposed framework is that it allows gene expression and disease trait(s) to be evaluated in different samples, significantly improving the flexibility and applicability of the approach. It uses IDA and jointIDA incorporating a novel p-value-based regularization approach to quantify the causal effects (including total causal effects, direct causal effects, and medication effects) of genes. The proposed approach can be extended to decipher the joint causal network of 2 or more traits, and has high specificity and precision (a.k.a., positive predictive value), making it particularly useful for selecting genes for follow-up studies.

We verified the feasibility and validity of the proposed framework by extensive simulations and applications to 52 traits in the UK Biobank (UKBB). Split-half replication and stability selection analyses were performed to demonstrate the accuracy and efficiency of our proposed method to identify causally relevant genes. The identified (direct) causal genes were found to be significantly enriched for genes highlighted in the OpenTargets database, and the enrichment was stronger than achieved by conventional univariate gene-based tests. Encouragingly, many enriched pathways were supported by the literature, and some of the enriched drugs have been tested or used to treat patients in clinical practice. Our proposed framework provides powerful a way to prioritize genes with large direct or indirect causal effects and to quantify the importance of such genes.
Understanding disruptions in cancer care to reduce increased cancer burden
Authors: Davis Kia L. , Ackermann Nicole , Klesges Lisa M. , Leahy Nora , Callie Walsh-Bailey , Humble Sarah , Drake Bettina , Sanders Thompson Vetta L.
Published: December 2022

Background

This study seeks to understand how and for whom COVID-19 disrupted cancer care to understand the potential for cancer health disparities across the cancer prevention and control continuum.

Methods

In this cross-sectional study, participants age 30+ residing in an 82-county region in Missouri and Illinois completed an online survey from June-August 2020. Descriptive statistics were calculated for all variables separately and by care disruption status. Logistic regression modeling was conducted to determine the correlates of care disruption.

Results

Participants (N=680) reported 21% to 57% of cancer screening or treatment appointments were canceled from March 2020 through the end of 2020. Approximately 34% of residents stated they would need to know if their doctor’s office is taking the appropriate COVID-related safety precautions to return to care. Higher education (OR=1.26, 95%CI:1.11-1.43), identifying as female (OR=1.60, 95%CI:1.12-2.30), experiencing more discrimination in healthcare settings (OR= 1.40, 95%CI:1.13-1.72), and having scheduled a telehealth appointment (OR=1.51, 95%CI:1.07-2.15) were associated with higher odds of care disruption. Factors associated with care disruption were not consistent across races. Higher odds of care disruption for White residents were associated with higher education, female identity, older age, and having scheduled a telehealth appointment, while higher odds of care disruption for Black residents were associated only with higher education.

Conclusion(s)

This study provides an understanding of the factors associated with cancer care disruption and what patients need to return to care. Results may inform outreach and engagement strategies to reduce delayed cancer screenings and encourage returning to cancer care.

Funding Support

This study was supported by the National Cancer Institute’s Administrative Supplements for P30 Cancer Center Support Grants (P30CA091842-18S2 and P30CA091842-19S4). Kia L. Davis, Lisa Klesges, and Bettina Drake were supported by the National Cancer Institute’s P50CA244431 and Kia L. Davis was also supported by the Breast Cancer Research Foundation. Callie Walsh-Bailey was supported by NIMHD T37 MD014218. The content does not necessarily represent the official view of these funding agencies and is solely the responsibility of the authors.

Availability of data and material

The dataset generated for the study is not publicly available but is available by request. Interested individuals should contact the corresponding author with a brief description of how the data will be used and proof of IRB approval or exemption. Then a de-identified dataset will be shared.
Exome sequencing reveals aggregates of rare variants in glycosyltransferase and other genes influencing immunoglobulin G and transferrin glycosylation
Authors: Landini Arianna , Timmers Paul R.H.J. , Frkatović-Hodžić Azra , Trbojević-Akmačić Irena , Vučković Frano , Pribić Tea ,   Regeneron Genetics Center, Tzoneva Gannie , Shuldiner Alan R. , Polašek Ozren , Hayward Caroline , Lauc Gordan , Wilson James F. , Klarić Lucija
Published: December 2022

It is often difficult to be certain which genes underlie the effects seen in association studies. However, variants that disrupt the protein, such as predicted loss of function (pLoF) and missense variants, provide a shortcut to identify genes with a clear biological link to the phenotype of interest. Glycosylation is one of the most common post-translationalmodifications of proteins, and an important biomarker of both disease and its progression. Here, we utilised the power of genetic isolates, gene-based aggregation tests and intermediate phenotypes to assess the effect of rare (MAF<5%) pLoF and missense variants from whole exome sequencing on the N-glycome of plasma transferrin (N=1907) and immunoglobulin G (N=4912), and their effect on diseases. We identified significant gene-based associations for transferrin glycosylation at 5 genes (p<8.06×10−8) and for IgG glycan traits at 4 genes (p<1.19×10−7). Associations in three of these genes (FUT8, MGAT3andRFXAP) are driven by multiple rare variants simultaneously contributing to protein glycosylation. Association atST6GAL1, with a 300-fold up-drifted variant in the Orkney Islands, was detectable by a single-point exome-wide association analysis. Glycome-associated aggregate associations are located in genes already known to have a biological link to protein glycosylation (FUT6, FUT8for transferrin;FUT8, MGAT3andST6GAL1for IgG) but also in genes which have not been previously reported (e.g.RFXAPfor IgG). To assess the potential impact of rare variants associated with glycosylation on other traits, we queried public repositories of gene-based tests, discovering a potential connection between transferrin glycosylation,MSR1, galectin-3, insulin-like growth factor 1 and diabetes. However, the exact mechanism behind these connections requires further elucidation.
Instar determination by constrained gaussian mixture models according to Dyar’s rule
Authors: Ji Sungmin
Published: December 2022

Despite its importance in ecological studies and pest controls, the lack of knowledge of the life cycle and the ambiguity of data challenge the accurate determination of insect nymphs regarding many insect species. Finite mixture models are often utilized to classify instars without knowing the instar number. This study derives parsimonious gaussian mixture models using parameter constraints motivated by Dyar’s rule. Dyar’s rule explains the growth pattern of larvae and nymphs of insects by assuming a constant ratio of head capsule width for every two adjacent development stages. Accordingly, every mean value of log-transformed data in each instar stage is considered a linear function, where two Dyar constants are an intercept and a slope for the instar stages, respectively, to infer the instar stage of samples. The common variance for every instar stage regarding log-transformed data can be assumed in a mixture model, as well. If valid, these assumptions will allow an efficient estimation of the model by reducing free parameters. As a result, four model hypotheses are proposed for each assumption of instar counts depending on whether these two parameter constraints are applied. After model estimation, the proposed method uses the ICL criterion to choose the optimal counts of nymphal stages, and parametric bootstrap LR tests are applied to decide the most efficient model regarding parameter constraints. The proposed method could attain the correct model settings during the simulation study. This study also discusses the interpretation of the results of real insect data sets that concord with Dyar’s rule or not.
IGHV allele similarity clustering improves genotype inference from adaptive immune receptor repertoire sequencing data
Authors: Peres Ayelet , Lees William D. , Rodriguez Oscar L. , Lee Noah Y. , Polak Pazit , Hope Ronen , Kedmi Meirav , Collins Andrew M. , Ohlin Mats , Kleinstein Steven H. , Watson Corey T , Yaari Gur
Published: December 2022

In adaptive immune receptor repertoire analysis, determining the germline variable (V) allele associated with each T- and B-cell receptor sequence is a crucial step. This process is highly impacted by allele annotations. Aligning sequences, assigning them to specific germline alleles, and inferring individual genotypes are challenging when the repertoire is highly mutated, or sequence reads do not cover the whole V region.

Here, we propose an alternative naming scheme for the V alleles as well as a novel method to infer individual genotypes. We demonstrate the strength of the two by comparing their outcomes to other genotype inference methods and validated the genotype approach with independent genomic long read data.

The naming scheme is compatible with current annotation tools and pipelines. Analysis results can be converted from the proposed naming scheme to the nomenclature determined by the International Union of Immunological Societies (IUIS). Both the naming scheme and the genotype procedure are implemented in a freely available R package (PIgLET). To allow researchers to explore further the approach on real data and to adapt it for their future uses, we also created an interactive website (https://yaarilab.github.io/IGHV_reference_book).