bluuebunny/crossref_metadata_2025_split huggingface dataset:
Expectant vs Medical Management for Retained Products of Conception After Medical Termination of Pregnancy: A Randomized Controlled Study
Authors: Tzur Yossi , Berkovitz Shperling Roza , Goitein Inbar Tamar , Bar-On Shikma , Gil Yaron , Levin Ishai , Cohen Aviad 
Published: October 2022

(Abstracted from Am J Obstet Gynecol 2022;227:599.e1–599.e9)
There has been an increase in the use of medical treatments for the termination of pregnancy. However, no prospective trials have evaluated the efficacy of misoprostol in treating retained products of conception following induced termination of pregnancy.
Prediction of Admission Costs Following Anterior Cervical Discectomy and Fusion Utilizing Machine Learning
Authors: Gowd Anirudh K. , Agarwalla Avinesh , Beck Edward C. , Derman Peter B. , Yasmeh Siamak , Albert Todd J. , Liu Joseph N. 
Published: October 2022

Study Design.
Retrospective case series.

Objective.
Predict cost following anterior cervical discectomy and fusion (ACDF) within the 90-day global period using machine learning models.

Background.
The incidence of ACDF has been increasing with a disproportionate decrease in reimbursement. As bundled payment models become common, it is imperative to identify factors that impact the cost of care.

Materials and Methods.
The Nationwide Readmissions Database (NRD) was accessed in 2018 for all primary ACDFs by the International Classification of Diseases 10th Revision (ICD-10) procedure codes. Costs were calculated by utilizing the total hospital charge and each hospital’s cost-to-charge ratio. Hospital characteristics, such as volume of procedures performed and wage index, were also queried. Readmissions within 90 days were identified, and cost of readmissions was added to the total admission cost to represent the 90-day healthcare cost. Machine learning algorithms were used to predict patients with 90-day admission costs >1 SD from the mean.

Results.
There were 42,485 procedures included in this investigation with an average age of 57.7±12.3 years with 50.6% males. The average cost of the operative admission was $24,874±25,610, the average cost of readmission was $25,371±11,476, and the average total cost was $26,977±28,947 including readmissions costs. There were 10,624 patients who were categorized as high cost. Wage index, hospital volume, age, and diagnosis-related group severity were most correlated with the total cost of care. Gradient boosting trees algorithm was most predictive of the total cost of care (area under the curve=0.86).

Conclusions.
Bundled payment models utilize wage index and diagnosis-related groups to determine reimbursement of ACDF. However, machine learning algorithms identified additional variables, such as hospital volume, readmission, and patient age, that are also important for determining the cost of care. Machine learning can improve cost-effectiveness and reduce the financial burden placed upon physicians and hospitals by implementing patient-specific reimbursement.
Predicting Bone Health using Machine Learning in Patients undergoing Spinal Reconstruction Surgery
Authors: Shen Yong , Sardar Zeeshan M. , Chase Herbert , Coury Josephine R. , Cerpa Meghan , Lenke Lawrence G. 
Published: October 2022

Study Design.
Retrospective study of data collected prospectively.

Objective.
The goal of this study is to create a predictive model of preoperative bone health status in adult patients undergoing adult spinal reconstructive (ASR) surgery using machine learning (ML).

Summary of Background Data.
Despite understanding that bone health impacts spine surgery outcomes, spine surgeons lack the tools to risk stratify patients preoperatively to determine who should undergo bone health screening. An ML approach mines patterns in data to determine the risk for poor bone health in ASR patients.

Methods.
211 subjects over the age of 30 with DEXA scans, who underwent spinal reconstructive surgery were reviewed. Data was collected by manual and automated collection from the EHRs. The Weka software was used to develop predictive models for multi-class classification of healthy, osteopenia (OPE), and osteoporosis (OPO) bone status. Bone status was labeled according to the WHO criteria using DEXA T-scores. The accuracy, sensitivity, specificity, and area under the receiver-operating-curve (AUC) were calculated. The model was evaluated on a test set of unseen data for generalizability.

Results.
The prevalence of OPO was 23.22% and OPE was 52.61%. The random forest model achieved optimal performance with an average sensitivity of 0.81, specificity of 0.95, and AUC of 0.96 on the training set. The model yielded an averaged sensitivity of 0.64, specificity of 0.78, and AUC of 0.69 on the test set. The model was best at predicting osteoporosis in patients. Numerous patient features exhibited predictive value, such as BMI, insurance type, serum sodium level, serum creatinine level, history of bariatric surgery, and the use of medications such as selective serotonin reuptake inhibitors.

Conclusion.
Predicting bone health status in ASR patients is possible with an ML approach. Additionally, data mining using ML can find unrecognized risk factors for bone health in ASR surgery patients.
Identification of Persister Drug Combination Clinafloxacin + Cefuroxime + Gentamicin That Eradicates Persistent Pseudomonas aeruginosa Infection in a Murine Cystic Fibrosis Model
Authors: Yuan Yuting , Yee Rebecca , Gour Naina , Dong Xinzhong , Feng Jie , Shi Wanliang , Zhang Ying 
Published: October 2022

Abstract

Pseudomonas aeruginosa can cause persistent infections, such as biofilm infections, in cystic fibrosis (CF) patients, which are difficult to cure due to non-growing persister bacteria that are not effectively killed by the current treatments. While antibiotic activity against growing P. aeruginosa is well documented, their activity against non-growing stationary phase cultures is less clear. Here, we evaluated six major classes of antibiotics, including cell wall and cell membrane inhibitors, protein synthesis inhibitors, DNA synthesis inhibitors, RNA synthesis inhibitors, sulfa drugs and nitrofurantoin, for their activity against growing and non-growing P. aeruginosa. We found that cell wall and cell membrane inhibitors (cefuroxime and colistin), DNA synthesis inhibitors (clinafloxacin) and sulfa drugs (sulfamethoxazole) had good activity against stationary-phase bacteria, while protein synthesis inhibitors (gentamicin), RNA synthesis inhibitor (rifampin) and nitrofurantoin showed relatively poor activity. Clinafloxacin was the only drug able to completely eradicate stationary-phase bacteria within 4 days. The cefuroxime + gentamicin + clinafloxacin combination was able to kill all bacteria from a biofilm within 2 days, whereas the clinically used drug combination cefuroxime + gentamicin/colistin only partially killed the biofilm bacteria. In a murine persistent CF lung infection model, only the cefuroxime + gentamicin + clinafloxacin drug combination eradicated all bacteria from the lungs, whereas clinafloxacin alone, cefuroxime + clinafloxacin, or the currently recommended drug combination cefuroxime + gentamicin failed to do so. The complete eradication is a property of the clinafloxacin combination, as the otherwise identical levofloxacin combination did not clear the bacterial loads from the lungs. Our findings offer new therapeutic options for more effective treatment of persistent P. aeruginosa infections, with possible implications for treating other persistent infections.
Experiences of COVID-19-Related Stigma: A Qualitative Study on Nurses Caring for Patients With COVID-19
Authors: TSUKUDA Makoto , KAYANO Tomonori , ITO Yoshiyasu 
Published: October 2022

ABSTRACT

Background
Healthcare workers caring for patients with Coronavirus Disease 2019 (COVID-19) have been a primary target of stigmatization and discrimination during the COVID-19 outbreak. Thus, there is an urgent need to develop a support system for Asian healthcare workers who care for patients with COVID-19.

Purpose
This study was designed to understand the characteristics of COVID-19-related stigma experienced by nurses caring for patients with COVID-19.

Methods
A qualitative content analysis methodology was used. This study was conducted between April 2020 and March 2021. The participants were 10 female registered nurses working at three medical facilities that accepted patients with COVID-19. The data included specific narratives on the instances of stigma experienced when caring for patients with COVID-19, including connected situations and ideas. The data were collected using focus group interviews with three or four participants in each group. Data analysis was conducted based on the inductive qualitative analysis approach of Krippendorff.

Results
The content analysis identified two categories and seven subcategories of stigma experienced by clinical nurses. The category “directly experienced prejudice and discrimination” included the subcategories “being avoided,” “being treated as dirty,” “discrimination toward family members,” and “others prying.” The category “self-imposed coping behavior” included the subcategories “keeping oneself apart,” “feeling guilty,” and “nondisclosure.”

Conclusions/Implications for Practice
The participants internalized their experiences of stigma, as Japanese culture emphasizes keeping such things to oneself. Therefore, there is an urgent need to strengthen the support system for nurses who care for patients with COVID-19. This study addressed the problem of the stigmatization of these nurses and their families by others as well as their colleagues. The main findings were that stigma was directly experienced as discrimination and prejudice and often resulted in self-imposed coping behavior. The major implication of these findings is the need to establish systematic, active, and ongoing organizational support programs for nurses who are discriminated against because of COVID-19-related stigma.
Nurse practitioner practice under the COVID-19 public health emergency: Did policy change persist?
Authors: Klein Tracy A. , Bindler Ross , Kaplan Louise 
Published: October 2022

ABSTRACT
The COVID-19 public health emergency (PHE) offers opportunities to study legislative and policy changes to nurse practitioner (NP) practice limitations, including factors that affect persistence. We evaluated states with restricted or reduced practice as identified by the American Association of Nurse Practitioners. This analysis 1) identified and correlated key changes in policy during the PHE with state regulatory, governmental, and practice variables; 2) modeled predictive characteristics that facilitate or impede policy persistence; and 3) explored the lived experience of NPs working in eligible states with policy changes during the PHE. Focus group interviews with NP leaders and bivariate correlations with regression analysis from the 2019 to 2021 legislative sessions were conducted. Nurse practitioner identified three types of persistence during the PHE: the power differential between MDs and NPs; the existing day-to-day environment; and barriers to change. In 2019, significantly more legislation was passed in states with sunset laws (Spearman rho: −0.38; p-value = .046). During 2020, 15 states introduced a total of 22 bills focused on NP practice, although only four passed one bill each. In 2021, states with an independent board structure introduced more NP legislation than did those states with a nonindependent board structure (Spearman rho: −0.406; p-value = .032). Few PHE policies persisted, despite robust predictions that this was likely to occur. Independent board structure and sunset laws were associated with legislation introduction and passage. Policy persistence is complex and based on multiple state and environmental variables. We urge persistence in NP advocacy strategies.
Selection criteria and triage in extracorporeal membrane oxygenation during coronavirus disease 2019
Authors: Nardelli Pasquale , Scandroglio Anna Mara , De Piero Maria Elena , Mariani Silvia , Lorusso Roberto 
Published: October 2022

Purpose of review
Coronavirus disease 2019 (COVID-19) pandemic changed the way we had to approach hospital- and intensive care unit (ICU)-related resource management, especially for demanding techniques required for advanced support, including extracorporeal membrane oxygenation (ECMO).

Recent findings
Availability of ICU beds and ECMO machines widely varies around the world. In critical conditions, such a global pandemic, the establishment of contingency capacity tiers might help in defining to which conditions and subjects ECMO can be offered. A frequent reassessment of the resource saturation, possibly integrated within a regional healthcare coordination system, may be of help to triage the patients who most likely will benefit from advanced techniques, especially when capacities are limited.

Summary
Indications to ECMO during the pandemic should be fluid and may be adjusted over time. Candidacy of patients should follow the same prepandemic rules, taking into account the acute disease, the burden of any eventual comorbidity and the chances of a good quality of life after recovery; but the current capacity of healthcare system should also be considered, and frequently reassessed, possibly within a wide hub-and-spoke healthcare system.

Video Abstract

http://links.lww.com/COCC/A43.
Addressing population health inequities: investing in the social determinants of health for children and families to advance child health equity
Authors: Thornton Rachel L.J. , Yang Tracy J. 
Published: October 2022

Purpose of review
This review provides a critical assessment of recent pediatric population health research with a specific focus on child health equity. The review addresses: the role of the healthcare sector in addressing fundamental social drivers of health, challenges within healthcare organizations in addressing health-related social needs and the social determinants of health, and the rationale for incorporating race and racism in pediatric population health research and practice.

Recent findings
The coronavirus disease 2019 pandemic brought greater attention to the disparities and inequities in American health and healthcare. In response to these stark inequities, many health systems are adopting efforts and initiatives to address social needs, social determinants of health, racism, and health equity. However, empirical evaluation detailing the effectiveness of these interventions and initiatives is limited.

Summary
While attention to identifying social needs among pediatric populations is increasing, there is limited evidence regarding the effectiveness of these interventions in producing sustained reductions in health disparities. To advance child health equity, researchers should move beyond individual behavior modification and directly examine fundamental drivers of health inequities. These drivers include government and health policies as well as societal forces such as systemic racism.
Relationship Between Opioid Prescriptions and Number of Chronic Pain Conditions in Women With Interstitial Cystitis
Authors: Duncan Jordann-Mishael , Hong Christopher X. , Harvie Heidi S. , Brown Lily A. , Arya Lily A. , Kim Edward K. 
Published: October 2022

(Abstracted from Urogynecology 2022;28:547–553)
Up to 8 million women in the United States are affected by interstitial cystitis (IC), which is a chronic condition characterized by coexisting urinary and pelvic pain conditi0ons. Managing the condition frequently proves challenging due to its chronic nature and a lack of effective IC treatments, but several medical organizations (such as the American Urological Association, Canadian Urological Association, the European Association of Urology, and the Royal College of Obstetricians and Gynecologists) have issued guidelines for management.
Prospective single-center paradigm shift of surgical stabilization of rib fractures with decreased length of stay and operative time with an intrathoracic approach
Authors: Tay-Lasso Erika , Alaniz Leonardo , Grant William , Hovis Gabrielle , Frank Madelyn , Kincaid Colin , Brynn Sargent , Pieracci Fredric M. , Nahmias Jeffry , Barrios Cristobal , Rockne Wendy , Chin Theresa , Swentek Lourdes , Schubl Sebastian D. 
Published: October 2022

INTRODUCTION
Intrathoracic surgical stabilization of rib fractures allows for a novel approach to rib fracture repair. This approach can help minimize muscle disruption, which may improve patient recovery compared with traditional extrathoracic plating. We hypothesized patients undergoing intrathoracic plating (ITP) to have a shorter length of stay (LOS) and intensive care unit (ICU) LOS compared with extrathoracic plating (ETP).

METHODS
A prospective observational paradigm shift study was performed from November 2017 until September 2021. Patients 18 and older who underwent surgical stabilization of rib fractures were included. Patients with ahead Abbreviated Injury Scale score ≥3 were excluded. Patients undergoing ETP (July 2017 to October 2019) were compared with ITP (November 2019 to September 2021) with Pearson χ2 tests and Mann-Whitney U tests, with the primary outcome being LOS and ICU LOS.

RESULTS
Ninety-six patients were included, 59 (61%) underwent ETP and 37 (38%) underwent ITP. The most common mechanism of injury was motor vehicle collision (29%) followed by falls (23%). There were no differences between groups in age, comorbidities, insurance, discharge disposition and injury severity score (18 vs. 19, p = 0.89). Intrathoracic plating had a shorter LOS (10 days vs. 8 days, p = 0.04) when compared with ETP but no difference in ICU LOS (4 days vs. 3 days, p = 0.12) and ventilator days. Extrathoracic plating patients more commonly received epidural anesthesia (56% vs. 24%, p < 0.001) and intercostal nerve block (56% vs. 29%, p = 0.01) compared with ITP. However, there was no difference in median morphine equivalents between cohorts. Operative time was shorter for ITP with ETP (279 minutes vs. 188 minutes, p < 0.001) after adjusting for numbers of ribs fixed.

CONCLUSION
In this single-center study, patients who underwent ITP had a decreased LOS and operative time in comparison to ETP in patients with similar injury severity. Future prospective multicenter research is needed to confirm these findings and may lead to further adoption of this minimally invasive technique.

LEVEL OF EVIDENCE
Therapeutic/Care Management; Level IV.
Mapping, clustering, and analysis of research in psychiatric genomics
Authors: Yadav Sabita , Chhabra Ayushi , Mahesh G. 
Published: October 2022

Introduction
The distribution pattern and knowledge structure of psychiatric genomics were surveyed based on literature dealing with both psychiatry and genomics/genetics. Coword analysis and bibliographic coupling of the records retrieved from Scopus and PubMed for 2016–2020 revealed the subsurface research aspects.

Method
The data were analyzed using coword analysis and clustering methods using Sci2 and VOSviewer.

Result
Analysis of ~3800 records showed that psychiatric genomics is, as expectedly, covered largely under biomedical subjects with a visible interest in other disciplines such as humanities and ethics. A coword analysis was done for all the years, followed by a year-wise analysis based on the keywords, and then a bibliographic coupling based on the cited references. This led to the generation of different clusters of prevalent research areas. The centrality values described the position of each component.

Discussion
‘Schizophrenia’, ‘depression’, ‘pharmacogenomics’, and ‘immunopathogenesis’ were the research topics of overarching interest. ‘Gut-brain axis’ and ‘gene-environment interaction’ were the emerging topics, whereas certain topics such as ‘child and adolescent psychiatry’ remained priorities when compared to earlier studies. The keywords and research focus were diverse. They ranged from genetics to transcriptomics and epigenetics to proteomics of psychiatric disorders. We found a stagnation of science communication in the field with only 0.2% of the articles from the entire corpus relevant to it. The research categories identified in this study reflect the current publication and research trends in psychiatric genomics.
A Neuroimaging-based Precision Medicine Framework for Depression
Authors: Xiao Yao , Dong Shuai , Zhu Rongxin , Womer Fay Y. , Zhang Ran , Yang Jingyu , Zhang Luheng , M.D. Juan Liu , Zhang Weixiong , Liu Zhongchun , Zhang Xizhe , Wang Fei 
Published: October 2022

ABSTRACTObjectiveDeveloping a neuroimaging-based precision medicine framework for depression.MethodsThe study was conducted in two stages at two sites: development of a neuroimaging-based subtyping and precise repetitive transcranial magnetic stimulation (rTMS) strategy for depression at Center 1 and its clinical application at Center 2. Center 1 identified depression subtypes and subtype-specific rTMS targets based on amplitude of low frequency fluctuation (ALFF) in a cohort of 238 major depressive disorder patients and 66 healthy controls (HC). Subtypes were identified using a Gaussian Mixture Model, and subtype-specific rTMS targets were selected based on dominant brain regions prominently differentiating depression subtypes from HC. Subsequently, one classifier trained per Center 1 findings for subtyping and subtype-specific rTMS targets were employed to deliver two-week precise rTMS to 72 hospitalized, depressed youths at Center 2. MRI and clinical assessments were obtained at baseline, midpoint, and treatment completion for evaluation.ResultsTwo neuroimaging subtypes of depression, archetypal and atypical depression, were identified based on distinct frontal-posterior functional imbalance patterns as measured by ALFF. The dorsomedial prefrontal cortex was identified as the rTMS target for archetypal depression, and the occipital cortex for atypical depression. Following precise rTMS, ALFF alterations were normalized in both archetypal and atypical depressed youths, corresponding with symptom response of 90.00% in archetypal depression and 70.73% in atypical depression.ConclusionsA precision medicine framework for depression was developed based on frontal-posterior functional imbalance and implemented with promising results. Future randomized controlled trials are warranted.Chinese Clinical Trial Registry identifier: ChiCTR2100045391