The Effect of Preoperative Anemia on the Odds of Allogeneic Blood Transfusion and Patient Outcomes in Colorectal Neoplasm Patients.

BACKGROUND: The optimal preoperative hemoglobin (Hb) value of colorectal neoplasm patients is still being debated. This study aimed at determining the effect of preoperative anemia on patient outcomes and allogeneic blood transfusion (ABT). METHODS: This retrospective cohort study enrolled colorectal neoplasm patients, that underwent surgery, from January 1, 2012, to December 31, 2021. The primary outcomes were the association between anemia and average length of stay (ALOS) and the odds of ABT. The secondary outcomes were the risk factors of the primary outcomes. Univariate and multivariate logistic regression analyses were applied to identify the association and risk factors. RESULTS: A total of 14,352 inpatients were included in the study, of whom 3,035 experienced (21.15%) mild anemia, 1,500 (10.45%) moderate anemia, and 104 (0.72%) severe anemia. Overall, 1,418 (9.88%) patients received ABT during the hospitalization, and 546 (3.80%) patients received perioperative ABT. In the multivariate logistic regression analysis, compared with the no anemic group, the odds ratio [OR] of ABT during the hospitalization for patients with mild/moderate/severe anemia were 5.915, 95% confidence interval [CI]: 4.717 - 7.418; 104.777, 95% CI: 84.345 - 130.160; and 13,361.442, 95% CI: 816.004 - 218,783.511, respectively, and the OR of periopera¬tive ABT were 4.332, 95% CI: 3.245 - 5.785; 27.492, 95% CI: 20.974 - 36.037; and 20.912, 95% CI: 11.832 - 36.959, respectively. Besides, the ALOS was longer, ß were 0.619, 95% CI: 0.346 - 0.892; 1.188, 95% CI: 0.821 - 1.554; and 1.395, 95% CI: 0.107 - 2.684, respectively. CONCLUSIONS: Anemia is a common phenomenon in colorectal neoplasm surgical patients, and even mild anemia could be a deleterious predictor on the outcomes of colorectal neoplasm patients that underwent surgery.

Quasi-Solid-State Na-O2 Battery with Composite Polymer Electrolyte.

Na-O2 batteries have emerged as promising candidates due to their high theoretical energy density (1,601 Wh kg-1), the potential for high energy storage efficiency, and the abundance of sodium in the earth's crust. Considering the safety issue, quasi-solid-state composite polymer electrolytes are among the promising solid-state electrolyte candidates. Their higher mechanical toughness provides superior resistance to dendritic penetration compared with traditional liquid electrolytes. The flexibility of the composite polymer electrolyte matrix allows it to conform to various battery configurations and considerably reduces safety concerns related to the combustion risks associated with conventional liquid electrolytes. In this study, we employed poly(ethylene oxide) (PEO) and sodium bis(trifluoromethanesulfonyl)imide (NaTFSI) as the polymer matrix and sodium ion-conducting agent, respectively. We incorporated nanosized NZSP (25 wt %) to create the composite polymer electrolyte membrane. This CPE design facilitates ion conduction pathways through both sodium salt and NZSP. By utilizing a liquid electrolyte infiltration method, we successfully enhanced its ionic conductivity, achieving an ionic conductivity of 10-4 S cm-1 at room temperature.

The safety and efficacy of transfusing red blood cells stored for different durations: a systematic review and meta-analysis of randomized controlled trials.

OBJECTIVE: The aim of this work was to resolve the uncertainty of whether transfusion of fresher red blood cells (RBCs) is better or not with regard to the safety and efficacy. METHODS: This systematic review was performed in accordance with our protocol registered on PROSPERO (https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022379183). RESULTS: After a literature search, 13,247 records were identified, and 26 randomized controlled trials (RCTs) involving 53,859 participants were eligible and included in this review. The results in our review suggested that there was no significant effect of fresher vs older RBCs on mortality (relative risk [RR] = 1.04; 95% CI, 0.99-1.09; P = .39; I2 = 0%), transfusion reactions (RR = 0.87; 95% CI, 0.57-1.33; P = .64; I2 = 0%). However, the transfusion of fresher RBCs might increase the risk of nosocomial infection (RR = 1.11; 95% CI, 1.02-1.20; P = .02; I2 = 0%), whereas there was no significant difference in the fresh vs old subgroup (RR = 0.87; 95% CI, 0.68 to 1.12; P = .28; I2 = 0%). CONCLUSION: Our study updated and reinforced the evidence of previously published systematic reviews that support the safety and efficiency of current practice of issuing the oldest available RBCs in the blood bank inventory.

Molecular engineering of a theranostic molecule that detects Aß plaques, inhibits Iowa and Dutch mutation Aß self-aggregation and promotes lysosomal biogenesis for Alzheimer's disease.

Extracellular clustering of amyloid-ß (Aß) and an impaired autophagy lysosomal pathway (ALP) are the hallmark features in the early stages of incurable Alzheimer's disease (AD). There is a pressing need to find or develop new small molecules for diagnostics and therapeutics for the early stages of AD. Herein, we report a small molecule, namely F-SLCOOH, which can bind and detect Aß1-42, Iowa mutation Aß, Dutch mutation Aß fibrils and oligomers exhibiting enhanced emission with high affinity. Importantly, F-SLCOOH can readily pass through the blood-brain barrier and shows highly selective binding toward the extracellular Aß aggregates in real-time in live animal imaging of a 5XFAD mice model. In addition, a high concentration of F-SLCOOH in both brain and plasma of wildtype mice after intraperitoneal administration was found. The ex vivo confocal imaging of hippocampal brain slices indicated excellent colocalization of F-SLCOOH with Aß positive NU1, 4G8, 6E10 A11 antibodies and THS staining dye, affirming its excellent Aß specificity and targetability. The molecular docking studies have provided insight into the unique and specific binding of F-SLCOOH with various Aß species. Importantly, F-SLCOOH exhibits remarkable anti-fibrillation properties against toxic Aß aggregate formation of Aß1-42, Iowa mutation Aß, and Dutch mutation Aß. F-SLCOOH treatment also exerts high neuroprotective functions and promotes autophagy lysosomal biogenesis in neuronal AD cell models. In summary, the present results suggest that F-SLCOOH is a highly promising theranostic agent for diagnosis and therapeutics of AD.

Uric acid to albumin ratio as a novel predictor for coronary slow flow phenomenon in patients with chronic coronary syndrome and non-obstructive coronary arteries.

BACKGROUND: The plasma uric acid to albumin ratio (UAR) is considered as a novel indicator for Inflammation. However, the association between UAR and coronary slow flow phenomenon (CSFP) remains unclear. METHODS: A total of 1328 individuals with chronic coronary syndrome (CCS) receiving coronary angiography (CAG) and found no obvious obstructive stenosis (< 40%) were included in this study. 79 individuals developed CSFP and were divided into CSFP group. The 1:2 age-matched patients with normal coronary blood flow were allocated to the control group (n = 158). The clinical characteristics, laboratory parameters including uric acid, albumin ratio, UAR and the angiographic characteristics were compared between the two groups. RESULTS: Patients with CSFP had a higher level of uric acid (392.3 ± 85.3 vs. 273.8 ± 71.5, P < 0.001), UAR (10.7 ± 2.2 vs. 7.2 ± 1.9, P < 0.001), but a lower level of plasma albumin (36.9 ± 4.2 vs. 38.5 ± 3.6, P = 0.003). Moreover, UAR increased as the numbers of vessels involved in CSFP increased. The logistic regression analysis demonstrated that UAR was independent predictors for CSFP. The Receiver operating characteristic (ROC) curve analysis showed that when UAR was more than 7.9, the AUC was 0.883 (95% CI: 0.840-0.927, p < 0.001), with the sensitivity and specificity were 78.2% and 88.2% respectively. CONCLUSION: Combined uric acid with plasma albumin, UAR could serve as an independent predictor for CSFP.

Functional Outcomes After Transanal Total Mesorectal Excision (taTME) for Rectal Cancer: Results from the Phase II North American Multicenter Prospective Observational Trial.

OBJECTIVE: To investigate fecal incontinence and defecatory, urinary, and sexual functional outcomes after taTME. SUMMARY BACKGROUND DATA: Proctectomy for rectal cancer may result in alterations in defecatory, urinary, and sexual function that persist beyond 12 months. The recent multicenter Phase II taTME trial demonstrated the safety of taTME in patients with stage I-III tumors. METHODS: Prospectively registered self-reported questionnaires were collected from 100 taTME patients. Fecal continence (FIQL, Wexner), defecatory function (COREFO), urinary function (IPSS), and sexual function (FSFI-female, IIEF-male) were assessed preoperatively (PQ), 3-4 months post-ileostomy closure (FQ1), and 12-18 months post-taTME (FQ2). RESULTS: Among 83 patients who responded at all three time points, FIQL, Wexner, and COREFO significantly worsened post-ileostomy closure. Between FQ1 and FQ2, FIQL lifestyle and coping, Wexner, and COREFO incontinence, social impact, frequency, and need for medication significantly improved, while FIQL depression and embarrassment did not change. IPSS did not change relative to preoperative scores. For females, FSFI declined for desire, orgasm, and satisfaction between PQ and FQ1, and did not improve between FQ1 and FQ2. In males, IIEF declined with no change between FQ1 and FQ2. CONCLUSIONS: Although taTME resulted in initial decline in defecatory function and fecal continence, most functional domains improved by 12 months after ileostomy closure, without returning to preoperative status. Urinary function was preserved while sexual function declined without improvement by 18 months post-taTME. Our results address patient expectations and inform shared decision-making regarding taTME.

Nephrotoxicity of organophosphate flame retardants in patients with chronic kidney disease: A 2-year longitudinal study.

Humans are extensively exposed to organophosphate flame retardants (OPFRs), an emerging group of organic contaminants with potential nephrotoxicity. Nevertheless, the estimated daily intake (EDI) and prognostic impacts of OPFRs have not been assessed in individuals with chronic kidney disease (CKD). In this 2-year longitudinal study of 169 patients with CKD, we calculated the EDIs of five OPFR triesters from urinary biomonitoring data of their degradation products and analyzed the effects of OPFR exposure on adverse renal outcomes and renal function deterioration. Our analysis demonstrated universal OPFR exposure in the CKD population, with a median EDIΣOPFR of 360.45 ng/kg body weight/day (interquartile range, 198.35-775.94). Additionally, our study revealed that high tris(2-chloroethyl) phosphate (TCEP) exposure independently correlated with composite adverse events and composite renal events (hazard ratio [95 % confidence interval; CI]: 4.616 [1.060-20.096], p = 0.042; 3.053 [1.075-8.674], p = 0.036) and served as an independent predictor for renal function deterioration throughout the study period, with a decline in estimated glomerular filtration rate of 4.127 mL/min/1.73 m2 (95 % CI, -8.127--0.126; p = 0.043) per log ng/kg body weight/day of EDITCEP. Furthermore, the EDITCEP and EDIΣOPFR were positively associated with elevations in urinary 8-hydroxy-2'-deoxyguanosine and kidney injury molecule-1 during the study period, indicating the roles of oxidative damage and renal tubular injury in the nephrotoxicity of OPFR exposure. To conclude, our findings highlight the widespread OPFR exposure and its possible nephrotoxicity in the CKD population.

Explainable Deep Learning Model for Predicting Serious Adverse Events in Hospitalized Geriatric Patients Within 72 Hours.

Background: The global aging population presents a significant challenge, with older adults experiencing declining physical and cognitive abilities and increased vulnerability to chronic diseases and adverse health outcomes. This study aims to develop an interpretable deep learning (DL) model to predict adverse events in geriatric patients within 72 hours of hospitalization. Methods: The study used retrospective data (2017-2020) from a major medical center in Taiwan. It included non-trauma geriatric patients who visited the emergency department and were admitted to the general ward. Data preprocessing involved collecting prognostic factors like vital signs, lab results, medical history, and clinical management. A deep feedforward neural network was developed, and performance was evaluated using accuracy, sensitivity, specificity, positive predictive value (PPV), and area under the receiver operating characteristic curve (AUC). Model interpretation utilized the Shapley Additive Explanation (SHAP) technique. Results: The analysis included 127,268 patients, with 2.6% experiencing imminent intensive care unit transfer, respiratory failure, or death during hospitalization. The DL model achieved AUCs of 0.86 and 0.84 in the validation and test sets, respectively, outperforming the Sequential Organ Failure Assessment (SOFA) score. Sensitivity and specificity values ranged from 0.79 to 0.81. The SHAP technique provided insights into feature importance and interactions. Conclusion: The developed DL model demonstrated high accuracy in predicting serious adverse events in geriatric patients within 72 hours of hospitalization. It outperformed the SOFA score and provided valuable insights into the model's decision-making process.

Development and Fabrication of a Multi-Layer Planar Solar Light Absorber Achieving High Absorptivity and Ultra-Wideband Response from Visible Light to Infrared.

The objective of this study is to create a planar solar light absorber that exhibits exceptional absorption characteristics spanning from visible light to infrared across an ultra-wide spectral range. The eight layered structures of the absorber, from top to bottom, consisted of Al2O3, Ti, Al2O3, Ti, Al2O3, Ni, Al2O3, and Al. The COMSOL Multiphysics® simulation software (version 6.0) was utilized to construct the absorber model and perform simulation analyses. The first significant finding of this study is that as compared to absorbers featuring seven-layered structures (excluding the top Al2O3 layer) or using TiO2 or SiO2 layers as substituted for Al2O3 layer, the presence of the top Al2O3 layer demonstrated superior anti-reflection properties. Another noteworthy finding was that the top Al2O3 layer provided better impedance matching compared to scenarios where it was absent or replaced with TiO2 or SiO2 layers, enhancing the absorber's overall efficiency. Consequently, across the ultra-wideband spectrum spanning 350 to 1970 nm, the average absorptivity reached an impressive 96.76%. One significant novelty of this study was the utilization of various top-layer materials to assess the absorption and reflection spectra, along with the optical-impedance-matching properties of the designed absorber. Another notable contribution was the successful implementation of evaporation techniques for depositing and manufacturing this optimized absorber. A further innovation involved the use of transmission electron microscopy to observe the thickness of each deposition layer. Subsequently, the simulated and calculated absorption spectra of solar energy across the AM1.5 spectrum for both the designed and fabricated absorbers were compared, demonstrating a match between the measured and simulated results.

Investigations of In2O3 Added SiC Semiconductive Thin Films and Manufacture of a Heterojunction Diode.

This study involved direct doping of In2O3 into silicon carbide (SiC) powder, resulting in 8.0 at% In-doped SiC powder. Subsequently, heating at 500 °C was performed to form a target, followed by the utilization of electron beam (e-beam) technology to deposit the In-doped SiC thin films with the thickness of approximately 189.8 nm. The first breakthrough of this research was the successful deposition of using e-beam technology. The second breakthrough involved utilizing various tools to analyze the physical and electrical properties of In-doped SiC thin films. Hall effect measurement was used to measure the resistivity, mobility, and carrier concentration and confirm its n-type semiconductor nature. The uniform dispersion of In ions in SiC was as confirmed by electron microscopy energy-dispersive spectroscopy and secondary ion mass spectrometry analyses. The Tauc Plot method was employed to determine the Eg values of pure SiC and In-doped SiC thin films. Semiconductor parameter analyzer was used to measure the conductivity and the I-V characteristics of devices in In-doped SiC thin films. Furthermore, the third finding demonstrated that In2O3-doped SiC thin films exhibited remarkable current density. X-ray photoelectron spectroscopy and Gaussian-resolved spectra further confirmed a significant relationship between conductivity and oxygen vacancy concentration. Lastly, depositing these In-doped SiC thin films onto p-type silicon substrates etched with buffered oxide etchant resulted in the formation of heterojunction p-n junction. This junction exhibited the rectifying characteristics of a diode, with sample current values in the vicinity of 102 mA, breakdown voltage at approximately -5.23 V, and open-circuit voltage around 1.56 V. This underscores the potential of In-doped SiC thin films for various semiconductor devices.

Deep learning assists in acute leukemia detection and cell classification via flow cytometry using the acute leukemia orientation tube.

This study aimed to evaluate the sensitivity of AI in screening acute leukemia and its capability to classify either physiological or pathological cells. Utilizing an acute leukemia orientation tube (ALOT), one of the protocols of Euroflow, flow cytometry efficiently identifies various forms of acute leukemia. However, the analysis of flow cytometry can be time-consuming work. This retrospective study included 241 patients who underwent flow cytometry examination using ALOT between 2017 and 2022. The collected flow cytometry data were used to train an artificial intelligence using deep learning. The trained AI demonstrated a 94.6% sensitivity in detecting acute myeloid leukemia (AML) patients and a 98.2% sensitivity for B-lymphoblastic leukemia (B-ALL) patients. The sensitivities of physiological cells were at least 80%, with variable performance for pathological cells. In conclusion, the AI, trained with ResNet-50 and EverFlow, shows promising results in identifying patients with AML and B-ALL, as well as classifying physiological cells.

Association between self-efficacy, spiritual well-being and the willingness to provide spiritual care among nursing staff in Taiwan: a cross-sectional study.

BACKGROUND: Spiritual care plays a significant role in holistic patient care, addressing not only physical ailments but also attending to patients' emotional and spiritual well-being. While the importance of spiritual care in nursing is widely recognized, there is often a gap in understanding nurses' willingness to provide such care. This cross-sectional study aimed to explore the association between self-efficacy, spiritual well-being, and willingness to provide spiritual care among nursing staff. METHODS: The study conducted a cross-sectional survey of full-time registered nurses at a hospital in Taiwan from January 2019 to December 2019. A sample comprising 168 nurses was selected for participation in the study through a random sampling method. In addition to collecting demographic variables, the assessment tools used in the study include the General Self-Efficacy Scale (GSES) for measuring self-efficacy, the Spiritual Index of Well-Being Chinese Version (SIWB-C) for evaluating spiritual well-being, and the Spiritual Care Needs Inventory (SCNI) to gauge willingness to provide spiritual care. RESULTS: Most participants in the study were female, accounting for 98.2% (n = 165). The mean age of all 168 nurses was 37.1 ± 9.3 years. Additionally, most participants held a Bachelor's degree (79.2%, n = 133) and possessed clinical experience was 10.5 ± 9.3 years. Through logistic regression analysis, it was found that regardless of whether participants have received sufficient spiritual care training, both GSES and SIWB-C remain influential factors in determining the provision of spiritual care. CONCLUSIONS: Collaboration between healthcare management and nursing staff is essential for fostering a healthcare environment that not only appreciates the physical and spiritual dimensions of patient care but also prioritizes the enhancement of nurses ' self-efficacy and well-being.

Yak genome database: a multi-omics analysis platform.

BACKGROUND: The yak (Bos grunniens) is a large ruminant species that lives in high-altitude regions and exhibits excellent adaptation to the plateau environments. To further understand the genetic characteristics and adaptive mechanisms of yak, we have developed a multi-omics database of yak including genome, transcriptome, proteome, and DNA methylation data. DESCRIPTION: The Yak Genome Database ( http://yakgenomics.com/ ) integrates the research results of genome, transcriptome, proteome, and DNA methylation, and provides an integrated platform for researchers to share and exchange omics data. The database contains 26,518 genes, 62 transcriptomes, 144,309 proteome spectra, and 22,478 methylation sites of yak. The genome module provides access to yak genome sequences, gene annotations and variant information. The transcriptome module offers transcriptome data from various tissues of yak and cattle strains at different developmental stages. The proteome module presents protein profiles from diverse yak organs. Additionally, the DNA methylation module shows the DNA methylation information at each base of the whole genome. Functions of data downloading and browsing, functional gene exploration, and experimental practice were available for the database. CONCLUSION: This comprehensive database provides a valuable resource for further investigations on development, molecular mechanisms underlying high-altitude adaptation, and molecular breeding of yak.

Association between organophosphate flame retardant exposure and lipid metabolism: data from the 2013-2014 National Health and Nutrition Examination Survey.

Organophosphate flame retardants (OPFRs) are emerging environmental pollutants that can be detected in water, dust, and biological organisms. Certain OPFRs can disrupt lipid metabolism in animal models and cell lines. However, the effects of OPFRs on human lipid metabolism remain unclear. We included 1,580 participants (≥20 years) from the 2013-2014 National Health and Nutrition Examination Survey (NHANES) to explore the relationship between OPFR exposure and lipid metabolism biomarkers. After adjusting for confounding factors, results showed that one-unit increases in the log levels of diphenyl phosphate (DPhP) (regression coefficient = -5.755; S.E. = 2.289; p = 0.023) and log bis-(1-chloro-2-propyl) phosphate (BCPP) (regression coefficient = -4.637; S.E. = 2.019; p = 0.036) were negatively associated with the levels of total cholesterol (TC) in all participants. One-unit increases in the levels of DPhP (regression coefficient = -2.292; S.E. = 0.802; p = 0.012), log bis (1,3-dichloro-2-propyl) phosphate (BDCPP) (regression coefficient = -2.046; S.E. = 0.825; p = 0.026), and log bis-2-chloroethyl phosphate (BCEP) (regression coefficient = -2.604; S.E. = 0.704; p = 0.002) were negatively associated with the levels of high-density lipoprotein cholesterol (HDL-C). With increasing quartiles of urine BDCPP levels, the mean TC levels significantly decreased in all participants (p value for trend = 0.028), and quartile increases in the levels of DPhP (p value for trend = 0.01), BDCPP (p value for trend = 0.001), and BCEP (p value for trend<0.001) were negatively corelated with HDL-C, with approximately 5.9, 9.9, and 12.5% differences between the upper and lower quartiles. In conclusion, DPhP, BDCPP, and BCEP were negatively related to HDL-C concentration, whereas DPhP and BCPP levels were negatively associated with TC level. Thus, exposure to OPFRs may interfere with lipid metabolism.

Speckle-Free, Angle-Free, Cavity-Free White Laser with a High Color Rendering Index.

The freedom from efficiency droop motivates monochromatic lasers to progress in general lighting applications due to the demand for more efficient and sustainable light sources. Still, a white light based on monochromatic lasers with high lighting quality, such as a high color rendering ability, an angle-independent output, and a speckle-free illumination, has not yet been fabricated nor demonstrated. Random lasers, with the special mechanism caused by multiple scattering, the angle-free emission, and the uncomplicated fabrication processes, inspire us to investigate the feasibility of utilizing them in general lighting. In this work, a white random laser with a high color rendering index (CRI) value, regardless of pumping energy and observing direction, was performed and discussed. We also investigated the stability of white RL as its CIE chromaticity coordinates exhibit negligible differences with increasing pump energy density, retaining its high-CRI measurement. Also, it exhibits angle-independent emission while having a high color rendering ability. After passing through a scattering film, it generated no speckles compared to the conventional laser. We demonstrated the advances in white laser illumination, showing that a white random laser is promising to be applied for high-brightness illumination, biological-friendly lighting, accurate color selections, and medical sensing.

New plasma diagnostic markers for colorectal cancer: transporter fragments of glutamate tRNA origin.

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths worldwide. Early diagnosis of the disease can greatly improve the clinical prognosis for patients with CRC. Unfortunately, there are no current simple and effective early diagnostic markers available. The transfer RNA (tRNA)-derived RNA fragments (tRFs) are a class of small non-coding RNAs (sncRNAs), which have been shown to play an important role in the development and prognosis of CRC. However, only a few studies on tRFs as early diagnostic markers in CRC have been conducted. In this study, previously ignored tRFs expression data were extracted from six paired small RNA sequencing data in the Sequence Read Archive (SRA) database using MINTmap. Three i-tRFs, derived from the tRNA that transports glutamate (i-tRF-Glu), were identified and used to construct a random forest diagnostic model. The model performance was evaluated using the receiver operating characteristic (ROC) curve and precision-recall (PR) curve. The area under the curves (AUC) for the ROC and PR was 0.941 and 0.944, respectively. We further verified the differences in expression of the these i-tRF-Glu in the tissue and plasma of both CRC patients and healthy subjects using quantitative real-time PCR (qRT-PCR). We found that the ROC-AUC of the three was greater than traditional plasma tumor markers such as CEA and CA199. Our bioinformatics analysis suggested that the these i-tRF-Glu are associated with cancer development and glutamate (Glu)-glutamine (Gln) metabolism. Overall, our study uncovered these i-tRF-Glu that have early diagnostic significance and therapeutic potential for CRC, this warrants further investigation into the diagnostic and therapeutic potential of these i-tRF-Glu in CRC.

Real-Time Machine Learning Alerts to Prevent Escalation of Care: A Nonrandomized Clustered Pragmatic Clinical Trial.

OBJECTIVES: Machine learning algorithms can outperform older methods in predicting clinical deterioration, but rigorous prospective data on their real-world efficacy are limited. We hypothesized that real-time machine learning generated alerts sent directly to front-line providers would reduce escalations. DESIGN: Single-center prospective pragmatic nonrandomized clustered clinical trial. SETTING: Academic tertiary care medical center. PATIENTS: Adult patients admitted to four medical-surgical units. Assignment to intervention or control arms was determined by initial unit admission. INTERVENTIONS: Real-time alerts stratified according to predicted likelihood of deterioration sent either to the primary team or directly to the rapid response team (RRT). Clinical care and interventions were at the providers' discretion. For the control units, alerts were generated but not sent, and standard RRT activation criteria were used. MEASUREMENTS AND MAIN RESULTS: The primary outcome was the rate of escalation per 1000 patient bed days. Secondary outcomes included the frequency of orders for fluids, medications, and diagnostic tests, and combined in-hospital and 30-day mortality. Propensity score modeling with stabilized inverse probability of treatment weight (IPTW) was used to account for differences between groups. Data from 2740 patients enrolled between July 2019 and March 2020 were analyzed (1488 intervention, 1252 control). Average age was 66.3 years and 1428 participants (52%) were female. The rate of escalation was 12.3 vs. 11.3 per 1000 patient bed days (difference, 1.0; 95% CI, -2.8 to 4.7) and IPTW adjusted incidence rate ratio 1.43 (95% CI, 1.16-1.78; p < 0.001). Patients in the intervention group were more likely to receive cardiovascular medication orders (16.1% vs. 11.3%; 4.7%; 95% CI, 2.1-7.4%) and IPTW adjusted relative risk (RR) (1.74; 95% CI, 1.39-2.18; p < 0.001). Combined in-hospital and 30-day-mortality was lower in the intervention group (7% vs. 9.3%; -2.4%; 95% CI, -4.5% to -0.2%) and IPTW adjusted RR (0.76; 95% CI, 0.58-0.99; p = 0.045). CONCLUSIONS: Real-time machine learning alerts do not reduce the rate of escalation but may reduce mortality.

Malnutrition risk assessment using a machine learning-based screening tool: A multicentre retrospective cohort.

BACKGROUND: Malnutrition is associated with increased morbidity, mortality, and healthcare costs. Early detection is important for timely intervention. This paper assesses the ability of a machine learning screening tool (MUST-Plus) implemented in registered dietitian (RD) workflow to identify malnourished patients early in the hospital stay and to improve the diagnosis and documentation rate of malnutrition. METHODS: This retrospective cohort study was conducted in a large, urban health system in New York City comprising six hospitals serving a diverse patient population. The study included all patients aged ≥ 18 years, who were not admitted for COVID-19 and had a length of stay of ≤ 30 days. RESULTS: Of the 7736 hospitalisations that met the inclusion criteria, 1947 (25.2%) were identified as being malnourished by MUST-Plus-assisted RD evaluations. The lag between admission and diagnosis improved with MUST-Plus implementation. The usability of the tool output by RDs exceeded 90%, showing good acceptance by users. When compared pre-/post-implementation, the rate of both diagnoses and documentation of malnutrition showed improvement. CONCLUSION: MUST-Plus, a machine learning-based screening tool, shows great promise as a malnutrition screening tool for hospitalised patients when used in conjunction with adequate RD staffing and training about the tool. It performed well across multiple measures and settings. Other health systems can use their electronic health record data to develop, test and implement similar machine learning-based processes to improve malnutrition screening and facilitate timely intervention.

[Research progress on development and utilization of minor ginsenosides].

Minor ginsenosides are a class of processed saponins with minor natural content, high bioavailability, and outstanding bio-logical activity, which are usually obtained by biological or chemical transformation of prototype saponins directly extracted from Panax plants. In recent years, with the clarification of the biosynthetic pathway of saponins and the development of synthetic biology, it has become possible to use synthetic metabolic engineering methods with microorganisms as hosts to produce saponins. Minor ginsenosides have received widespread attention because of their remarkable biological activities in enhancing the immune function of the body and antitumor property. At present, most of the reviews on minor ginsenosides focus on transformation preparation, process optimization, and pharmacological activity, but there are some deficiencies in industrial analysis. This study summarized structural types, pharmacological activities, sources of acquisition, and transformation pathways of minor ginsenosides based on the relevant literature in China and abroad, proposed problems in the preparation of existing minor ginsenosides, and discussed the future research and utilization prospects, to provide a theoretical basis for improving the basic research of minor ginsenosides and promoting their industrialization.