Association of foods consumption and physical activity with prefrailty and frailty among Chinese older adults in urban communities: A cross-sectional study.

BACKGROUND AND OBJECTIVES: Frailty has become a public health challenge in China. To investigate the association of foods consumption and physical activity with prefrailty and frailty among older Chinese adults in urban communities. METHODS AND STUDY DESIGN: In a cross-sectional study from February to July 2023, 1183 older adults aged between 65y-88y were enrolled from urban communities in Chongqing and Shandong province, China. Frailty Index (FI) was applied to measure prefrailty and frailty. Partial proportional odds model was used to assess the association between foods consumption, physical activity and prefrailty/frailty. RESULTS: Higher Dietary Diversity Score (DDS), (OR=0.61, 95% CI=0.46-0.80; OR=0.47, 95% CI=0.28-0.79), Consuming animal-based foods ≥2 times/day (OR=0.62, 95% CI=0.47-0.82; OR=0.54, 95% CI=0.33-0.88), soy products ≥2 times/week (OR=0.69, 95% CI=0.53-0.89; OR=0.51, 95% CI=0.31-0.84), fresh vegetables ≥2 times/day (OR=0.42, 95% CI=0.31-0.57; OR=0.41, 95% CI=0.23-0.72), and nuts ≥2 times/week (OR=0.71, 95% CI=0.55-0.91; OR=0.52, 95% CI=0.32-0.85) was associated with a lower risk of prefrailty and frailty. In addition, higher frequency and longer duration of walking (OR=0.61, 95% CI=0.42-0.88; OR=0.63, 95% CI=0.48-0.81), exercise (OR=0.48, 95% CI=0.35-0.64; OR=0.44, 95% CI=0.32-0.61) per week were significantly associated with lower risk of prefrailty. Furthermore, higher frequency and longer duration of walking (OR=0.42, 95% CI=0.25-0.72; OR=0.46, 95% CI=0.29-0.74), and housework (OR=0.39, 95% CI=0.24-0.65; OR=0.57, 95% CI=0.34-0.96) per week, were significantly associated with lower frailty. CONCLUSIONS: Higher DDS and higher frequency of animal-based foods, soy products, fresh vegetables, and nuts consumption is significantly associated with lower risk of prefrailty and frailty. Additionally, walking and exercising are significantly associated with lower risk of prefrailty, while walking and doing housework is significantly associated with lower frailty.

Impact of comprehensive nursing on hand-foot syndrome caused by oral capecitabine in breast cancer patients.

This study examines the effects of comprehensive nursing care on hand-foot syndrome (HFS) in breast cancer patients treated with capecitabine. A retrospective analysis was conducted on 71 patients, divided into a study group receiving comprehensive care and a control group receiving conventional care. Results showed that the study group experienced significant improvements in skin symptoms, self-efficacy, quality of life, and lower anxiety and depression levels compared to the control group. Additionally, patients who were compliant with medications were notably better in the study group. Comprehensive care effectively alleviates the symptoms of hand-foot syndrome in breast cancer patients treated with capecitabine and enhances patient well-being.

Cette étude examine les effets des soins infirmiers complets sur le syndrome main-pied (SMP) chez les patientes atteintes de cancer du sein traitées par capécitabine. Une analyse rétrospective a été réalisée sur 71 patientes, divisées en un groupe d'étude recevant des soins complets et un groupe témoin recevant des soins conventionnels. Les résultats ont montré que le groupe d'étude a connu des améliorations significatives des symptômes cutanés, de l'auto-efficacité, de la qualité de vie, ainsi qu'une réduction des niveaux d'anxiété et de dépression par rapport au groupe témoin. De plus, les patientes adhérant au traitement médicamenteux étaient notablement meilleures dans le groupe d'étude. Les soins complets atténuent efficacement les symptômes du syndrome main-pied chez les patientes atteintes de cancer du sein traitées par capécitabine et améliorent leur bien-être.

Patient-reported outcomes of taste alterations and quality of life in patients with nasopharyngeal carcinoma.

Objective: To investigate patient-reported outcomes of taste alterations and quality of life (QoL) in patients with nasopharyngeal carcinoma (NPC). Methods: In this single-center retrospective study medical records of 191 patients with NPC undergoing chemoradiotherapy (CRT) in the Department of Radiotherapy, Jiangsu Cancer Hospital, the Affiliated Cancer Hospital of Nanjing Medical University from January 2021 to December 2021 were reviewed. A total of 120 patients met eligibility criteria and were included. The taste alterations and QoL at multiple time points during radiotherapy (RT) were compared. Results: There were significant differences in the intensity of taste, discomfort, phantogeusia and parageusia or overall taste alterations at multiple time points during CRT (p-Value<0.001). These four parameters were significantly higher two or four weeks after CRT, or at the end of CRT compared to before CRT (p-Value <0.001). The intensity of taste, discomfort, phantogeusia and parageusia or overall taste alterations were all significantly higher four weeks after CRT compared to two weeks after CRT (p-Value <0.001), and at the end of CRT compared to four weeks after CRT (p-Value <0.001). The chemotherapy-induced taste alteration scale (CiTAS) scores were highest at the end of CRT (p-Value <0.001). There were significant differences in QoL at multiple time points during CRT (p-Value <0.001), and each parameter differed significantly at various time points (p <0.05). The QoL of all areas at the end of CRT were significantly higher than those before CRT, or two or four weeks after CRT (p-Value <0.001). Conclusions: In patients with NPC undergoing CRT, taste alterations increasingly worsen as treatment progresses, with poor QoL outcomes.

Classifying social determinants of health from unstructured electronic health records using deep learning-based natural language processing.

OBJECTIVE: Social determinants of health (SDOH) are non-medical factors that can profoundly impact patient health outcomes. However, SDOH are rarely available in structured electronic health record (EHR) data such as diagnosis codes, and more commonly found in unstructured narrative clinical notes. Hence, identifying social context from unstructured EHR data has become increasingly important. Yet, previous work on using natural language processing to automate extraction of SDOH from text (a) usually focuses on an ad hoc selection of SDOH, and (b) does not use the latest advances in deep learning. Our objective was to advance automatic extraction of SDOH from clinical text by (a) systematically creating a set of SDOH based on standard biomedical and psychiatric ontologies, and (b) training state-of-the-art deep neural networks to extract mentions of these SDOH from clinical notes. DESIGN: A retrospective cohort study. SETTING AND PARTICIPANTS: Data were extracted from the Medical Information Mart for Intensive Care (MIMIC-III) database. The corpus comprised 3,504 social related sentences from 2,670 clinical notes. METHODS: We developed a framework for automated classification of multiple SDOH categories. Our dataset comprised narrative clinical notes under the "Social Work" category in the MIMIC-III Clinical Database. Using standard terminologies, SNOMED-CT and DSM-IV, we systematically curated a set of 13 SDOH categories and created annotation guidelines for these. After manually annotating the 3,504 sentences, we developed and tested three deep neural network (DNN) architectures - convolutional neural network (CNN), long short-term memory (LSTM) network, and the Bidirectional Encoder Representations from Transformers (BERT) - for automated detection of eight SDOH categories. We also compared these DNNs to three baselines models: (1) cTAKES, as well as (2) L2-regularized logistic regression and (3) random forests on bags-of-words. Model evaluation metrics included micro- and macro- F1, and area under the receiver operating characteristic curve (AUC). RESULTS: All three DNN models accurately classified all SDOH categories (minimum micro-F1 = 0.632, minimum macro-AUC = 0.854). Compared to the CNN and LSTM, BERT performed best in most key metrics (micro-F1 = 0.690, macro-AUC = 0.907). The BERT model most effectively identified the "occupational" category (F1 = 0.774, AUC = 0.965) and least effectively identified the "non-SDOH" category (F = 0.491, AUC = 0.788). BERT outperformed cTAKES in distinguishing social vs non-social sentences (BERT F1 = 0.87 vs. cTAKES F1 = 0.06), and outperformed logistic regression (micro-F1 = 0.649, macro-AUC = 0.696) and random forest (micro-F1 = 0.502, macro-AUC = 0.523) trained on bag-of-words. CONCLUSIONS: Our study framework with DNN models demonstrated improved performance for efficiently identifying a systematic range of SDOH categories from clinical notes in the EHR. Improved identification of patient SDOH may further improve healthcare outcomes.

Lycorine inhibits cell proliferation and induced oxidative stress-mediated apoptosis via regulation of the JAK/STAT3 signaling pathway in HT-3 cells.

Human cervical cancer is the fourth most common carcinoma in women in the world. The JAK/STAT3 signaling pathways crucially regulate cell growth and apoptosis. It is a significant target signaling pathway for the development of novel antitumor medicine. This study intended to explore whether lycorine could prevent HT-3 proliferation and induce apoptosis by targeting the JAK/STAT3 signaling cascade. The HT-3 cells were treated with various lycorine dosages and we analyzed cell growth, lipid peroxidation, antioxidants, mitochondrial membrane potential (ΔΨm), DNA damage, apoptosis markers by different in vitro methodologies. Our results revealed that lycorine substantially reserved cell growth via decreased antioxidants, augmented reactive oxygen species (ROS) generation which leads to loss of ΔΨm, increased nuclear crumbling and chromatin condensation, thus resulting in representative increased apoptotic cell death. Furthermore, we analyzed that the molecular mechanical action of lycorine considerably repressed JAK1/STAT3 transactional activation and decrease its downstream molecules Bcl-2, and enhances the expressional activity of Bax, cytochrome c, caspase 3 and 9 in HT-3 cells. Finally, the fact that N-acetylcysteine inhibits lycorine-induced ROS-mediated apoptosis was confirmed in HT-3 cells. Thus, the results indicate that lycorine efficiently enhances apoptosis and inhibits HT-3 cell proliferation. These outcomes collectively proposed that lycorine could be a beneficial chemotherapeutic agent for treating and managing human cervical carcinoma.

Correlation Between High Expression of FOXA2 and Improved Overall Survival in Ovarian Cancer Patients.

BACKGROUND The aim of the present work was to evaluate FOXA2 expression in ovarian cancer and to use integrated bioinformatics analysis to correlate it with patient prognosis. MATERIAL AND METHODS FOXA2 expression was evaluated in multiple cancers in The Cancer Genome Atlas database. A protein-protein interaction (PPI) network relevant to FOXA2 was constructed using the Search Tool for Retrieval of Interacting Genes/Proteins (STRIN). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed of FOXA2 and relevant genes. Correlations between overall survival (OS), disease-free survival, and FOXA2 expression were evaluated. An immunohistochemical assay (IHC) was used to test for FOXA2 protein expression in 79 ovarian cancer specimens. RESULTS FOXA2 mRNA was upregulated in colorectal, stomach, liver, and endometrial cancers. In the PPI network, 21 protein nodes and 533 edges were constructed with a local clustering coefficient of 0.698, which indicated significant PPI enrichment (P<0.01). FOXA2 and relevant genes were mainly enriched in the signaling pathways regulating pluripotency of stem cells, cancer, and AMPK. A survival analysis indicated that OS was significantly longer in patients with higher versus lower FOXA2 protein expression (HR=0.73, P<0.01). The IHC assay showed that the FOXA2 protein was mainly positively expressed in the nucleoplasm of tumor cells with brown-yellow staining. Of the 79 ovarian cancer samples, 31 (39.2%) highly expressed FOXA2. The FOXA2 gene was correlated with International Federation of Gynecology and Obstetrics staging and with lymph node metastasis (both P<0.05). CONCLUSIONS Upregulation of the FOXA2 gene was correlated with improved OS in patients with ovarian cancer and it can be used as a prognostic biomarker and potential treatment target.

The relationship between occupational stress, job burnout and quality of life among surgical nurses in Xinjiang, China.

BACKGROUND: Nursing is a high-risk occupation that involves exposure to stress. The physical and mental health of nurses is directly related to the quality of medical services, so the quality of life of nurses cannot be ignored. This study is a Chinese nursing study that investigated occupational stress, job burnout, and quality of life of surgical nurses in Xinjiang, China. METHODS: This study employed the cluster random sampling method and carried out a questionnaire survey among 488 surgical nurses from five hospitals from May 2019 to September 2019. The study analyzed the relationship between occupational stress, job burnout and quality of life. The Effort-Reward Imbalance questionnaire (ERI), Maslach Burnout Inventory General Survey (MBI-GS) and the 36-item Short Form Health Survey (SF-36) were used to evaluate occupational stress, job burnout and quality of life among surgical nurses. RESULTS: A total of 550 questionnaires were distributed in this study, and 488 were retrieved, with an effective recovery rate of 88.73 %. The results revealed that the quality of life score among surgical nurses was not high, and differences were observed in the quality of life score of patients according to gender, age, title, and frequency of night shifts (P < 0.05). There was a positive correlation between occupational stress and job burnout. Higher levels of occupational stress and job burnout were associated with a poorer quality of life score. Occupational stress and job burnout were identified as risk factors for quality of life, and the interaction between high levels of stress and burnout seriously reduced quality of life. The structural equation model revealed that occupational stress and job burnout had a direct impact on quality of life, occupational stress had a direct impact on job burnout, and job burnout was identified as a mediating factor in the relationship between occupational stress and quality of life. CONCLUSIONS: Surgical nurses have a high level of occupational stress and burnout, and low quality of life score. Quality of life is correlated with occupational stress and job burnout. According to the individual characteristics and psychological state of nurses, managers can implement personalized intervention measures promptly and effectively to relieve their tension and burnout, and improve the quality of life of surgical nurses.

Effects of Occupational Stress and Circadian CLOCK Gene Polymorphism on Sleep Quality of Oil Workers in Xinjiang, China.

BACKGROUND This study investigated the effect of occupational stress and circadian clock gene polymorphism on sleep disorder of oil workers in Xinjiang, China. MATERIAL AND METHODS We enrolled 2300 Xinjiang oil workers who had been working for at least 1 year. The Chinese revised version of the Occupational Stress Questionnaire (OSI-R), the Pittsburgh Sleep Quality Index (PSQI), and General Survey Questionnaire were used. A total of 308 subjects were selected for stress hormone measurements and gene polymorphism analysis of the circadian clock genes CLOCK, PER2, and PER3. RESULTS The occupational stress scores were influenced by sex, smoking, marital status, age, and work type. Different work shift groups and different professional title groups had statistically significant sleep disorder incidences (P<0.05). The middle and high occupational stress groups had significantly higher subjective sleep quality, total PSQI scores, daytime dysfunction factor scores, and sleep disorder than in the low occupational stress group (P<0.05). CLOCK gene rs1801260 locus carrying TC genotype (OR=0.412, 95% CI=0.245-0.695), and CLOCK gene rs6850524 locus carrying GC and CC genotypes decreased sleep disorder risk (OR1=0.357, 95% CI1=0.245-0.695; OR2=0.317, 95% CI2=0.128-0.785). The main factors affecting the sleep quality of oil workers were length of service, individual strain capacity, glucocorticoid levels, Per3 gene, and the rs6850524 loci of CLOCK gene. CONCLUSIONS Occupational stress has an adverse effect on the sleep quality of workers. CLOCK gene and Per3 gene may increase risk of sleep disorders.

Predictive modeling for classification of positive valence system symptom severity from initial psychiatric evaluation records.

In response to the challenges set forth by the CEGS N-GRID 2016 Shared Task in Clinical Natural Language Processing, we describe a framework to automatically classify initial psychiatric evaluation records to one of four positive valence system severities: absent, mild, moderate, or severe. We used a dataset provided by the event organizers to develop a framework comprised of natural language processing (NLP) modules and 3 predictive models (two decision tree models and one Bayesian network model) used in the competition. We also developed two additional predictive models for comparison purpose. To evaluate our framework, we employed a blind test dataset provided by the 2016 CEGS N-GRID. The predictive scores, measured by the macro averaged-inverse normalized mean absolute error score, from the two decision trees and Naïve Bayes models were 82.56%, 82.18%, and 80.56%, respectively. The proposed framework in this paper can potentially be applied to other predictive tasks for processing initial psychiatric evaluation records, such as predicting 30-day psychiatric readmissions.

[Effect of accordion technique and deferoxamine on promoting bone regeneration in distraction osteogenesis].

Objective: To compare the effects of hypoxia-inducible drugs using deferoxamine (DFO) and accordion technique (AT) on activating the hypoxia-inducible factor 1α (HIF-1α)/vascular endothelial growth factor (VEGF) signaling pathway to promote bone regeneration and remodelling during consolidation phase of distraction osteogenesis (DO). Methods: Forty-five specific-pathogen-free adult male Sprague-Dawley (SD) rats were randomly divided into the control group, DFO group, and AT group, with 15 rats in each group. All rats underwent osteotomy to establish a right femur DO model. Then, continuous distraction was started for 10 days after 5 days of latency in each group. During the consolidation phase after distraction, no intervention was performed in the control group; DFO was locally perfused into the distraction area in the DFO group starting at the 3rd week of consolidation phase; cyclic stress stimulation was given in the AT group starting at the 3rd week of consolidation phase. The general condition of rats in each group was observed. X-ray films were conducted at the end of the distraction phase and at the 2nd, 4th, and 6th weeks of the consolidation phase to observe the calcification in the distraction area. At the 4th and 6th weeks of the consolidation phase, peripheral blood was taken for ELISA detection (HIF-1α, VEGF, CD31, and Osterix), femoral specimens were harvested for gross observation, histological staining (HE staining), and immunohistochemical staining [HIF-1α, VEGF, osteopontin (OPN), osteocalcin (OCN)]. At the 6th week of the consolidation phase, Micro-CT was used to observe the new bone mineral density (BMD), bone volume/tissue volume (BV/TV), trabecular separation (Tb.Sp), trabecular number (Tb.N), and trabecular thickness (Tb.Th) in the distraction area, and biomechanical test (ultimate load, elastic modulus, energy to failure, and stiffness) to detect bone regeneration in the distraction area. Results: The rats in all groups survived until the termination of the experiment. ELISA showed that the contents of HIF-1α, VEGF, CD31, and Osterix in the serum of the AT group were significantly higher than those of the DFO group and control group at the 4th and 6th weeks of the consolidation phase ( P<0.05). General observation, X-ray films, Micro-CT, and biomechanical test showed that bone formation in the femoral distraction area was significantly better in the DFO group and AT group than in the control group, and complete recanalization of the medullary cavity was achieved in the AT group, and BMD, BV/TV, Tb.Sp, Tb.N, and Tb.Th, as well as ultimate load, elastic modulus, energy to failure, and stiffness in the distraction area, were better in the AT group than in the DFO group and control group, and the differences were significant ( P<0.05). HE staining showed that trabecular bone formation and maturation in the distraction area were better in the AT group than in the DFO group and control group. Immunohistochemical staining showed that at the 4th week of consolidation phase, the expression levels of HIF-1α, VEGF, OCN, and OPN in the distraction area of the AT group were significantly higher than those of the DFO group and control group ( P<0.05); however, at 6th week of consolidation phase, the above indicators were lower in the AT group than in the DFO group and control group, but there was no significant difference between groups ( P>0.05). Conclusion: Both continuous local perfusion of DFO in the distraction area and AT during the consolidation phase can activate the HIF-1α/VEGF signaling pathway. However, AT is more effective than local perfusion of DFO in promoting the process of angiogenesis, osteogenesis, and bone remodelling.

Risk for Suicide Attempts Assessed Using the Patient Health Questionnaire-9 Modified for Teens.

Importance: Suicide is a leading cause of death in US youths. Objective: To assess whether screening with supplemental items 10 to 13 on the Patient Health Questionnaire-9 modified for teens (PHQ-9M) improves prediction of youth suicide attempts beyond the information provided by the first 9 items alone (the PHQ-9). Design, Setting, and Participants: This retrospective cohort study used a retrospective cohort of adolescents aged 12 to 17 years who were screened for depression in outpatient facilities within a pediatric health care system between January 1, 2016, and December 31, 2022, with up to 1 year of follow-up to assess the occurrence of suicidal behavior. Follow-up was completed on December 31, 2023. Exposure: Screening with the PHQ-9M. Main Outcomes and Measures: This study developed and compared prediction using 3 Cox proportional hazards regression models (CR-9, CR-13, and CR-3) of subsequent suicide attempts, determined by the hospital's electronic health records up to 1 year following the last PHQ-9M screening. The CR-9 model used the PHQ-9 and the CR-13 model used all 13 items of PHQ-9M. The CR-3 model used the 3 most impactful variables selected from the 13 PHQ-9M items and PHQ-9 total score. All models were evaluated across 4 prediction horizons (30, 90, 180, and 365 days) following PHQ-9M screenings. Evaluation metrics were the area under the receiver operating characteristic curve (AUROC) and the area under the precision recall curve (AUPRC). Results: Of 130 028 outpatients (65 520 [50.4%] male) with 272 402 PHQ-9M screenings, 549 (0.4%) had subsequent suicide attempts within 1 year following the PHQ-9M screening. The AUROC of the CR-9 model in the 365-day horizon was 0.77 (95% CI, 0.75-0.79); of the CR-13 model, 0.80 (95% CI, 0.78-0.82); and of the CR-3 model, 0.79 (95% CI, 0.76-0.81); the AUPRC of the CR-9 model was 0.02 (95% CI, 0.02-0.03); of the CR-13 model, 0.03 (95% CI, 0.02-0.03); and of the CR-3 model, 0.02 (95% CI, 0.02-0.03). The 3 most impactful items using adjusted hazard ratios were supplemental item 13 (lifetime suicide attempts; 3.06 [95% CI, 2.47-3.80]), supplemental item 10 (depressed mood severity in the past year; 2.99 [95% CI, 2.32-3.86]), and supplemental item 12 (serious suicidal ideation in the past month; 1.63 [95% CI, 1.25-2.12]). All of the models achieved higher AUROCs as prediction horizons shortened. Conclusions and Relevance: In this cohort study of adolescent PHQ-9M screenings, the supplemental items on PHQ-9M screening improved prediction of youth suicide attempts compared with screening using the PHQ-9 across all prediction horizons, suggesting that PHQ-9M screening should be considered during outpatient visits to improve prediction of suicide attempts.

Extracting social determinants of health events with transformer-based multitask, multilabel named entity recognition.

OBJECTIVE: Social determinants of health (SDOH) are nonclinical, socioeconomic conditions that influence patient health and quality of life. Identifying SDOH may help clinicians target interventions. However, SDOH are more frequently available in narrative notes compared to structured electronic health records. The 2022 n2c2 Track 2 competition released clinical notes annotated for SDOH to promote development of NLP systems for extracting SDOH. We developed a system addressing 3 limitations in state-of-the-art SDOH extraction: the inability to identify multiple SDOH events of the same type per sentence, overlapping SDOH attributes within text spans, and SDOH spanning multiple sentences. MATERIALS AND METHODS: We developed and evaluated a 2-stage architecture. In stage 1, we trained a BioClinical-BERT-based named entity recognition system to extract SDOH event triggers, that is, text spans indicating substance use, employment, or living status. In stage 2, we trained a multitask, multilabel NER to extract arguments (eg, alcohol "type") for events extracted in stage 1. Evaluation was performed across 3 subtasks differing by provenance of training and validation data using precision, recall, and F1 scores. RESULTS: When trained and validated on data from the same site, we achieved 0.87 precision, 0.89 recall, and 0.88 F1. Across all subtasks, we ranked between second and fourth place in the competition and always within 0.02 F1 from first. CONCLUSIONS: Our 2-stage, deep-learning-based NLP system effectively extracted SDOH events from clinical notes. This was achieved with a novel classification framework that leveraged simpler architectures compared to state-of-the-art systems. Improved SDOH extraction may help clinicians improve health outcomes.

Oncology nurses' and oncologists' experience of addressing sexual health concerns in breast cancer patients: A qualitative study.

PURPOSE: This study aimed to explore the experiences of Chinese oncology nurses and oncologists who provide sexual health education for breast cancer patients in their practical work. METHODS: This was a qualitative study using semistructured face-to-face interviews. Eleven nurses and eight oncologists who provided sexual health education to breast cancer patients were purposively recruited from eight hospitals in seven provinces of China. Data were analyzed using the thematic analysis method. RESULTS: Four main themes emerged: the surface of sexual health, stress and benefit finding, cultural sensitivity and communication, needs and changes. Both oncology nurses and oncologists found it difficult to solve sexual health problems, which were beyond their responsibilities and competencies. They felt helpless about the limitations of external support. Nurses hoped oncologists could participate in more sexual health education. CONCLUSIONS: Oncology nurses and oncologists experienced great challenges in educating breast cancer patients about sexual health. They are eager to obtain more formal education and learning resources for sexual health education. Specific training to improve the sexual health education competence of healthcare professionals is needed. Furthermore, more support is needed to create conditions to encourage patients to reveal their sexual challenges. It is necessary for oncology nurses and oncologists to communicate on sexual health in breast cancer patients, and to promote interdisciplinary communication and share responsibility.

Prediction of Return of Spontaneous Circulation in a Pediatric Swine Model of Cardiac Arrest Using Low-Resolution Multimodal Physiological Waveforms.

Monitoring physiological waveforms, specifically hemodynamic variables (e.g., blood pressure waveforms) and end-tidal CO2 (EtCO2), during pediatric cardiopulmonary resuscitation (CPR) has been demonstrated to improve survival rates and outcomes when compared to standard depth-guided CPR. However, waveform guidance has largely been based on thresholds for single parameters and therefore does not leverage all the information contained in multimodal data. We hypothesize that the combination of multimodal physiological features improves the prediction of the return of spontaneous circulation (ROSC), the clinical indicator of short-term CPR success. We used machine learning algorithms to evaluate features extracted from eight low-resolution (4 samples per minute) physiological waveforms to predict ROSC. The waveforms were acquired from the 2nd to 10th minute of CPR in pediatric swine models of cardiac arrest (N = 89, 8-12 kg). The waveforms were divided into segments with increasing length (both forward and backward) for feature extraction, and machine learning algorithms were trained for ROSC prediction. For the full CPR period (2nd to 10th minute), the area under the receiver operating characteristics curve (AUC) was 0.93 (95% CI: 0.87-0.99) for the multivariate model, 0.70 (0.55-0.85) for EtCO2 and 0.80 (0.67-0.93) for coronary perfusion pressure. The best prediction performances were achieved when the period from the 6th to the 10th minute was included. Poor predictions were observed for some individual waveforms, e.g., right atrial pressure. In conclusion, multimodal waveform features carry relevant information for ROSC prediction. Using multimodal waveform features in CPR guidance has the potential to improve resuscitation success and reduce mortality.

A Template for Translational Bioinformatics: Facilitating Multimodal Data Analyses in Preclinical Models of Neurological Injury.

Background: Pediatric neurological injury and disease is a critical public health issue due to increasing rates of survival from primary injuries (e.g., cardiac arrest, traumatic brain injury) and a lack of monitoring technologies and therapeutics for the treatment of secondary neurological injury. Translational, preclinical research facilitates the development of solutions to address this growing issue but is hindered by a lack of available data frameworks and standards for the management, processing, and analysis of multimodal data sets. Methods: Here, we present a generalizable data framework that was implemented for large animal research at the Children's Hospital of Philadelphia to address this technological gap. The presented framework culminates in an interactive dashboard for exploratory analysis and filtered data set download. Results: Compared with existing clinical and preclinical data management solutions, the presented framework accommodates heterogeneous data types (single measure, repeated measures, time series, and imaging), integrates data sets across various experimental models, and facilitates dynamic visualization of integrated data sets. We present a use case of this framework for predictive model development for intra-arrest prediction of cardiopulmonary resuscitation outcome. Conclusions: The described preclinical data framework may serve as a template to aid in data management efforts in other translational research labs that generate heterogeneous data sets and require a dynamic platform that can easily evolve alongside their research.

Analysis of risky driving behaviors among bus drivers in China: The role of enterprise management, external environment and attitudes towards traffic safety.

Several studies have shown that enterprise management (e.g. culture, salary) and external environment (e.g. traffic congestion) predict risky driving behaviors and accident involvement. However, this process has not been systematically investigated in bus drivers. The present study uses structural equation model to assess whether enterprise management and external environment are associated with risky self-reported driving behaviors both directly and indirectly, through the effects of attitudes towards traffic safety in a large sample of bus drivers. Three hundred and thirty-one bus drivers (mean age = 39.5, SD = 5.6 years) completed a structured and anonymous questionnaire measuring enterprise management, external environment, attitudes toward traffic safety, and self-reported risky driving behaviors (i.e., speeding, fatigue driving, running the light) in the last 6 months. Structural equation modeling analysis revealed that enterprise management, and external environment were associated with risky driving behaviors both directly and indirectly. In particular both of them were directly correlated with bus drivers' attitudes toward traffic safety which, in turn, were related to the five types of self-reported risky driving behaviors. The present findings suggest that measures related to the impact factors could be carried out to reduce the probabilities of the risky driving behaviors among bus drivers, such as improving the salary level of bus drivers, setting up bus lanes and priority signals to alleviate road congestion, optimizing shift schedules, implementing effective safety education, etc. These findings can provide the empirical basis for evidence-based road safety interventions in the context of public transport.

Using Data-Driven Machine Learning to Predict Unplanned ICU Transfers with Critical Deterioration from Electronic Health Records.

OBJECTIVE: We aimed to develop a data-driven machine learning model for predicting critical deterioration events from routinely collected EHR data in hospitalized children. MATERIALS: This retrospective cohort study included all pediatric inpatients hospitalized on a medical or surgical ward between 2014-2018 at a quaternary children's hospital. METHODS: We developed a large data-driven approach and evaluated three machine learning models to predict pediatric critical deterioration events. We evaluated the models using a nested, stratified 10-fold cross-validation. The evaluation metrics included C-statistic, sensitivity, and positive predictive value. We also compared the machine learning models with patients identified as high-risk Watchers by bedside clinicians. RESULTS: The study included 57,233 inpatient admissions from 34,976 unique patients. 3,943 variables were identified from the EHR data. The XGBoost model performed best (C-statistic=0.951, CI: 0.946 ∼ 0.956). CONCLUSIONS: Our data-driven machine learning models accurately predicted patient deterioration. Future sociotechnical analysis will inform deployment within the clinical setting.

Early prediction of clinical deterioration using data-driven machine-learning modeling of electronic health records.

OBJECTIVES: To develop and evaluate a high-dimensional, data-driven model to identify patients at high risk of clinical deterioration from routinely collected electronic health record (EHR) data. MATERIALS AND METHODS: In this single-center, retrospective cohort study, 488 patients with single-ventricle and shunt-dependent congenital heart disease <6 months old were admitted to the cardiac intensive care unit before stage 2 palliation between 2014 and 2019. Using machine-learning techniques, we developed the Intensive care Warning Index (I-WIN), which systematically assessed 1028 regularly collected EHR variables (vital signs, medications, laboratory tests, and diagnoses) to identify patients in the cardiac intensive care unit at elevated risk of clinical deterioration. An ensemble of 5 extreme gradient boosting models was developed and validated on 203 cases (130 emergent endotracheal intubations, 34 cardiac arrests requiring cardiopulmonary resuscitation, 10 extracorporeal membrane oxygenation cannulations, and 29 cardiac arrests requiring cardiopulmonary resuscitation onto extracorporeal membrane oxygenation) and 378 control periods from 446 patients. RESULTS: At 4 hours before deterioration, the model achieved an area under the receiver operating characteristic curve of 0.92 (95% confidence interval, 0.84-0.98), 0.881 sensitivity, 0.776 positive predictive value, 0.862 specificity, and 0.571 Brier skill score. Performance remained high at 8 hours before deterioration with 0.815 (0.688-0.921) area under the receiver operating characteristic curve. CONCLUSIONS: I-WIN accurately predicted deterioration events in critically-ill infants with high-risk congenital heart disease up to 8 hours before deterioration, potentially allowing clinicians to target interventions. We propose a paradigm shift from conventional expert consensus-based selection of risk factors to a data-driven, machine-learning methodology for risk prediction. With the increased availability of data capture in EHRs, I-WIN can be extended to broader applications in data-rich environments in critical care.

[Study on effect of berberine on modulating lipid and CPT I A gene expression].

OBJECTIVE: To investigate the modulating effect on lipid and gene expressions of CPT I A caused by berberine (Ber) in experimental hyperlipidemia rats. METHOD: Male SD rats were randomly divided into 5 groups according to the blood lipid values: normal group, hyperlipidemia group, 300 mg x kg(-1) x d(-1) Ber-treated group, 60 mg x kg(-1) x d(-1) Ber-treated group, and 7.2 mg x kg(-1) x d(-1) lovastatin-treated group. Normal group were fed with base diet and other groups were fed with high fat and cholesterol diet. 12 weeks after drugs were given the TC, TG, LDL-C, and HDL-C from rat blood samples were tested by automatic biochemistry analyzer. Gene expressions of CPT I A and PPARalpha were evaluated by RT-PCR and Western blot, respectively. RESULT: It was shown that Ber significantly decreased TC and LDL-C, but increased HDL-C in dose-dependent manner, elevated expressions of CPT I A mRNA and protein without influence on PPARalpha expression. Similar effects from lovastatin on lipidemia were observed except the Ber effect on CPT I A gene expression. CONCLUSION: Ber has modulating effect on the lipid metabolism, the mechanism of which may be by promoting the CPT I A gene expression.

The application value of operating room ventilation with laminar airflow for surgical site infection: A protocol for a systematic review and meta-analysis.

BACKGROUND: The presence of biological particles in the air inside operating theatres has the potential to cause severe surgical site infections. Recently, laminar airflow systems have been regarded as a means to reducing surgical site infections using airborne microbes. Still, other publications have argued the benefits of laminar airflow systems, stating the likelihood of adverse effects. Therefore, we will conduct this systematic study to evaluate the applicational value of adopting laminar airflow systems in operating theatres to minimize surgical site infections. METHODS: Reporting of this study adheres to the guidelines of Preferred Reporting Items for Systematic Review and Meta-analysis Protocols. The authors will perform a systematic search on MEDLINE, Web of Science, EMBASE, the China national knowledge infrastructure, and the Cochrane Library from their commencement until June 2021. The search will identify relevant randomized and non-randomized controlled trials that evaluates the applicational value of using laminar airflow ventilation in surgical theatres to minimize surgical site infections. There are no restrictions on language. Two authors will independently screen the identified studies, perform data extraction, and use an appropriate method to evaluate the bias risk in the included studies. RESULTS: The work done in the present study will enhance the existing literature on the applicational value of laminar airflow ventilation in surgical theatre to reduce surgical site infections. CONCLUSION: The outcomes are a reference for healthcare practitioners and patients when making informed decisions regarding care during surgeries.