Development and validation of a predictive model for the risk of sarcopenia in the older adults in China.

BACKGROUND: Sarcopenia is a progressive age-related disease that can cause a range of adverse health outcomes in older adults, and older adults with severe sarcopenia are also at increased short-term mortality risk. The aim of this study was to construct and validate a risk prediction model for sarcopenia in Chinese older adults. METHODS: This study used data from the 2015 China Health and Retirement Longitudinal Study (CHARLS), a high-quality micro-level data representative of households and individuals aged 45 years and older adults in China. The study analyzed 65 indicators, including sociodemographic indicators, health-related indicators, and biochemical indicators. RESULTS: 3454 older adults enrolled in the CHARLS database in 2015 were included in the final analysis. A total of 997 (28.8%) had phenotypes of sarcopenia. Multivariate logistic regression analysis showed that sex, Body Mass Index (BMI), Mean Systolic Blood Pressure (MSBP), Mean Diastolic Blood Pressure (MDBP) and pain were predictive factors for sarcopenia in older adults. These factors were used to construct a nomogram model, which showed good consistency and accuracy. The AUC value of the prediction model in the training set was 0.77 (95% CI = 0.75-0.79); the AUC value in the validation set was 0.76 (95% CI = 0.73-0.79). Hosmer-Lemeshow test values were P = 0.5041 and P = 0.2668 (both P > 0.05). Calibration curves showed significant agreement between the nomogram model and actual observations. ROC and DCA showed that the nomograms had good predictive properties. CONCLUSIONS: The constructed sarcopenia risk prediction model, incorporating factors such as sex, BMI, MSBP, MDBP, and pain, demonstrates promising predictive capabilities. This model offers valuable insights for clinical practitioners, aiding in early screening and targeted interventions for sarcopenia in Chinese older adults.

Effect of a fall within three months of admission on delirium in critically Ill elderly patients: a population-based cohort study.

BACKGROUND: Delirium is common among elderly patients in the intensive care unit (ICU) and is associated with prolonged hospitalization, increased healthcare costs, and increased risk of death. Understanding the potential risk factors and early prevention of delirium is critical to facilitate timely intervention that may reverse or mitigate the harmful consequences of delirium. AIM: To clarify the effects of pre-admission falls on ICU outcomes, primarily delirium, and secondarily pressure injuries and urinary tract infections. METHODS: The study relied on data sourced from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Statistical tests (Wilcoxon rank-sum or chi-squared) compared cohort characteristics. Logistic regression was employed to investigate the association between a history of falls and delirium, as well as secondary outcomes, while Kaplan-Meier survival curves were used to assess short-term survival in delirium and non-delirium patients. RESULTS: Study encompassed 22,547 participants. Delirium incidence was 40%, significantly higher in patients with a history of falls (54.4% vs. 34.5%, p < 0.001). Logistic regression, controlling for confounders, not only confirmed that a history of falls elevates the odds of delirium (OR: 2.11; 95% CI: 1.97-2.26; p < 0.001) but also showed it increases the incidence of urinary tract infections (OR:1.50; 95% CI:1.40-1.62; p < 0.001) and pressure injuries (OR:1.36; 95% CI:1.26-1.47; p < 0.001). Elderly delirium patients exhibited lower 30-, 180-, and 360-day survival rates than non-delirium counterparts (all p < 0.001). CONCLUSIONS: The study reveals that history of falls significantly heighten the risk of delirium and other adverse outcomes in elderly ICU patients, leading to decreased short-term survival rates. This emphasizes the critical need for early interventions and could inform future strategies to manage and prevent these conditions in ICU settings.

Braden score can independently predict 90-day mortality in critically ill patients with dementia.

BACKGROUND: Dementia is a significant cause of death in the older population and is becoming an important public health issue as the population ages and the prevalence of dementia increases. The Braden score is one of the most commonly used clinical tools to assess the risk of skin pressure injury in patients, and some studies have reported that it may reflect the state of frailty of patients. The present study attempted to explore the association between Braden score and 90-day mortality, pressure injury, and aspiration pneumonia in older patients with dementia in the intensive care unit (ICU). METHODS: The study involved extracting crucial data from the Medical Information Market for Intensive Care IV (MIMIC-IV) database using Structured Query Language, with a license certificate obtained after completing the necessary training and examination available on the MIMIC-IV website. A retrospective analysis was performed on older patients with dementia, aged 65 or older, who were first admitted to the ICU. Ninth and tenth revision International Classification of Diseases codes were used to identify patients with dementia. The primary outcome was 90-day mortality. Cox proportional hazards models were used to determine the association between Braden score and death, and hazard ratios (HR) and 95% confidence intervals (CI) were calculated. Propensity score matching and E-value assessments were employed for sensitivity analysis. RESULTS: A total of 2892 patients with a median age of approximately 85 years (interquartile range 78.74-89.59) were included, of whom 1625 were female (56.2%). Patients had a median Braden score of 14 (interquartile range 12-15) at ICU admission. Braden score at ICU admission was inversely associated with 90-day mortality risk after adjustment for demographics, severity of illness, treatment and medications, delirium, and sepsis (adjusted HR: 0.92, 95% CI: 0.87-0.98, p = 0.006). Patients were divided into two groups with a cut-off value of 15: high-risk group and low-risk group. Compared to the low-risk group (Braden score >15), the risk of 90-day mortality was significantly increased in the high-risk group (Braden score ≤15) (adjusted HR: 1.52, 95% CI: 1.10-2.09, p = 0.011, E-value: 2.01), the risk of pressure injury (adjusted OR: 2.62, 95% CI: 2.02-3.43, E-value: 2.62) and aspiration pneumonia (adjusted OR: 2.55, 95% CI: 1.84-3.61, E-value: 2.57) was also significantly higher. CONCLUSIONS: The Braden score may be a quick and simple screening tool to identify the risk of adverse outcomes in critically ill older adults with dementia.

Association of birthweight and risk of incident dementia: a prospective cohort study.

Given the epidemiological studies investigating the relationship between birthweight and dementia are limited. Our study aimed to explore the association between birthweight and the risk of dementia, cognitive function, and brain structure. We included 275,648 participants from the UK Biobank, categorizing birthweight into quartiles (Q1 ≤ 2.95 kg; Q2 > 2.95 kg, ≤ 3.32 kg; Q3 > 3.32 kg, ≤ 3.66 kg; Q4 > 3.66 kg), with Q3 as the reference. Cox regression models and restricted cubic splines estimated the relationship between birthweight and the risk of all causes of dementia (ACD), Alzheimer's disease (AD), and vascular dementia (VD). Multivariable linear regression models assessed the relationship between birthweight, cognitive function, and MRI biomarkers. Over a median follow-up of 13.0 years, 3103 incident dementia cases were recorded. In the fully adjusted model, compared to Q3 (> 3.32 kg, ≤ 3.66 kg), lower birthweight in Q1 (≤ 2.95 kg) was significantly associated with increased risk of ACD (HR = 1.18, 95%CI 1.06-1.30, P = 0.001) and VD (HR = 1.32, 95%CI 1.07-1.62, P = 0.010), but no significant association with AD was found. Continuous birthweight showed a U-shaped nonlinear association with dementia. Lower birthweight was associated with worse performance in cognitive tasks, including reaction time, fluid intelligence, numeric, and prospective memory. Additionally, certain brain structure indices were identified, including brain atrophy and reductions in area, thickness, and volume of regional subcortical areas. Our study emphasizes the association between lower birthweight and increased dementia risk, correlating cognitive function and MRI biomarkers of brain structure, suggesting that in utero or early-life exposures might impact cognitive health in adulthood.

Finely Tuning Metal Ion Valences of [Fe3-xMx(µ3-OH)(Carboxyl)6(pyridyl)2] Cluster-Based ant-MOFs for Highly Improved CO2 Capture Performances.

Solvothermal reactions of different trinuclear precursors and 5-(pyridin-4-yl)isophthalic acid (H2L) successfully led to four anionic ant topological MOFs as Fe3-xMx(µ3-OH)(CH3COO)2(L)2·(DMA+)·DMF [M = Mn(II), Fe(II), Co(II), x = 0, 1, 2 and 3], namely, NJTU-Bai79 [NJTU-Bai = Nanjing Tech University Bai's group, Mn3(µ3-OH)], NJTU-Bai80 [Fe2Mn(µ3-OH)], NJTU-Bai81 [Fe3(µ3-OH)], and NJTU-Bai82 [Fe2Co(µ3-OH)], which possess the narrow pores (2.5-6.0 Å). NJTU-Bai80-82 is able to be tuned to the neutral derivatives [NJTU-Bai80-82(-ox), ox = oxidized] with M2+ ions oxidized to M3+ ones in the air and the OH- ions coordinated on M3+ ions. Very interestingly, selective CO2/N2 adsorptions of NJTU-Bai80-82(-ox) are significantly enhanced with the CO2 adsorption uptakes more than about 6 times that of NJTU-Bai79. GCMC simulations further revealed that neutral NJTU-Bai80-82(-ox) supplies more open frameworks around the -CH3 groups at separate spaces to the CO2 gas molecules with relatively more pores available to them after the removal of counterions. For the first time, finely tuning metal ion valences of metal clusters of ionic MOFs and making them from electrostatic to neutral were adopted for greatly improving their CO2 capture properties, and it would provide another promising strategy for the exploration of high-performance CO2 capture materials.

Does ICU admission dysphagia independently contribute to delirium risk in ischemic stroke patients? Results from a cohort study.

BACKGROUND: Delirium is prevalent in ischemic stroke patients, particularly those in the intensive care unit (ICU), and it poses a significant burden on patients and caregivers, leading to increased mortality rates, prolonged hospital stays, and impaired cognitive function. Dysphagia, a common symptom in critically ill patients with ischemic stroke, further complicates their condition. However, the association between dysphagia and delirium in this context remains unclear. The objective of this study was to investigate the correlation between dysphagia and delirium in ICU patients with ischemic stroke. METHODS: A retrospective analysis was conducted on adult patients diagnosed with ischemic stroke at a medical center in Boston. Ischemic stroke cases were identified using the ninth and tenth revisions of the International Classification of Diseases. Dysphagia was defined as a positive bedside swallowing screen performed by medical staff on the day of ICU admission, while delirium was assessed using the ICU Confusion Assessment Method and review of nursing notes. Logistic regression models were used to explore the association between dysphagia and delirium. Causal mediation analysis was employed to identify potential mediating variables. RESULTS: The study comprised 1838 participants, with a median age of approximately 70 years, and 50.5% were female. Among the total study population, the prevalence of delirium was 43.4%, with a higher prevalence observed in the dysphagia group (60.7% vs. 40.8%, p < 0.001) compared to the non-dysphagia group. After adjusting for confounding factors including age, sex, race, dementia, depression, sedative medications, history of falls, visual or hearing deficit, sequential organ failure score, and Glasgow coma score, multifactorial logistic regression analysis demonstrated a significant association between dysphagia and an increased likelihood of delirium (odds ratio [OR]: 1.48; 95% confidence interval [CI]: 1.07-2.05; p = 0.018; E-value = 1.73). Causal mediation analysis revealed that serum albumin levels partially mediated the association between dysphagia and delirium in critically ill patients with ischemic stroke (average causal mediated effect [ACME]: 0.02, 95% CI: 0.01 to 0.03; p < 0.001). CONCLUSION: ICU admission dysphagia may independently contribute to the risk of delirium in patients with ischemic stroke. Early identification and intervention in ischemic stroke patients with dysphagia may help mitigate the risk of delirium and improve patient prognosis.

ICU admission Braden score independently predicts delirium in critically ill patients with ischemic stroke.

BACKGROUND: Delirium is a common and severe complication in intensive care unit (ICU) patients with acute ischemic stroke, exacerbating cognitive and physical impairments. It prolongs hospitalization, increases healthcare costs, and raises mortality risk. Early prediction is crucial because it facilitates prompt interventions that could possibly reverse or alleviate the detrimental consequences of delirium. Braden scores, traditionally used to assess pressure injury risk, could also signal frailty, providing an early warning of delirium and aiding in prompt and effective patient management. OBJECTIVE: To examine the association between the Braden score and delirium. METHODS: A retrospective analysis of adult ischemic stroke patients in the ICU of a tertiary academic medical center in Boston from 2008 to 2019 was performed. Braden scores were obtained on admission for each patient. Delirium, the primary study outcome, was assessed using the Confusion Assessment Method for Intensive Care Unit and a review of nursing notes. The association between Braden score and delirium was determined using Cox proportional hazards modeling, with hazard ratios (HR) and 95% confidence intervals (CI) calculated. RESULTS: The study included 3,680 patients with a median age of 72 years, of whom 1,798 were women (48.9 %). The median Braden score at ICU admission was 15 (interquartile range 13-17). After adjustment for demographics, laboratory tests, severity of illness, and comorbidities, the Braden score was inversely associated with the risk of delirium (adjusted HR: 0.94, 95 % CI: 0.92-0.96, P < 0.001). CONCLUSIONS: The Braden score may serve as a convenient and simple screening tool to identify the risk of delirium in ICU patients with ischemic stroke. IMPLICATION FOR CLINICAL PRACTICE: The use of the Braden score as a predictor of delirium in ischemic stroke patients in the ICU allows early identification of high-risk patients. This facilitates timely intervention, thereby improving patient outcomes and potentially reducing healthcare costs.

Targeted mutagenesis of BnTTG1 homologues generated yellow-seeded rapeseed with increased oil content and seed germination under abiotic stress.

Yellow seed is one desirable trait with great potential to improve seed oil quality and yield. The present study surveys the redundant role of BnTTG1 genes in the proanthocyanidins (PA) biosynthesis, oil content and abiotic stress resistance. Stable yellow seed mutants were generated after mutating BnTTG1 by CRISPR/Cas9 genome editing system. Yellow seed phenotype could be obtained only when both functional homologues of BnTTG1 were simultaneously knocked out. Homozygous mutants of BnTTG1 homologues showed decreased thickness and PA accumulation in seed coat. Transcriptome and qRT-PCR analysis indicated that BnTTG1 mutation inhibited the expression of genes involved in phenylpropanoid and flavonoid biosynthetic pathways. Increased seed oil content and alteration of fatty acid (FA) composition were observed in homozygous mutants of BnTTG1 with enriched expression of genes involved in FA biosynthesis pathway. In addition, target mutation of BnTTG1 accelerated seed germination rate under salt and cold stresses. Enhanced seed germination capacity in BnTTG1 mutants was correlated with the change of expression level of ABA responsive genes. Overall, this study elucidated the redundant role of BnTTG1 in regulating seed coat color and established an efficient approach for generating yellow-seeded oilseed rape genetic resources with increase oil content, modified FA composition and resistance to multiple abiotic stresses.

Associations of Folate/Folic Acid Supplementation Alone and in Combination With Other B Vitamins on Dementia Risk and Brain Structure: Evidence From 466 224 UK Biobank Participants.

Previous researchers have tried to explore the association between folate/folic acid intake and dementia incidence, but the results remain controversial. We evaluated the associations of folate/folic acid supplementation alone and in combination with other B vitamins on dementia risk and brain structure. A total of 466 224 UK Biobank participants were investigated. Cox proportional hazards models were used to assess the associations between folate/folic acid supplementation status and the risk of Alzheimer's disease (AD) and vascular dementia (VD). Multivariable linear regression models were employed to evaluate the association between folate/folic acid supplementation status and brain structure. In the final model, folate/folic acid supplementation alone was significantly associated with a higher risk of AD (hazard ratio [HR] = 1.34, 95% confidence interval [CI] = 1.06-1.69, p = .015) and VD (HR = 1.61, 95% CI = 1.21-2.13, p = .001). Folate/folic acid supplementation alone was associated with a reduction in the hippocampus (ß = -95.25 mm3, 95% CI = -165.31 to -25.19 mm3, p = .014) and amygdala (ß = -51.85 mm3, 95% CI = -88.02 to -15.68 mm3, p = .012). The risk of AD and VD, as well as brain structure, in the group with combined folate/folic acid supplementation and other B vitamins did not show a statistically significant difference compared to the reference group (all p > .05). Folate/folic acid supplementation alone is significantly associated with a higher risk of AD and VD, as well as adverse alterations in brain structure. However, when combined with other B vitamins, these detrimental effects can be counteracted.

Geriatric nutritional risk index independently predicts delirium in older patients in intensive care units: A multicenter cohort study.

BACKGROUND: Malnutrition is associated with clinical outcomes in several diseases. However, the role of malnutrition in the risk of delirium in elderly patients in intensive care units (ICU) remains unclear. This study aimed to elucidate the association between the Geriatric Nutritional Risk Index (GNRI) and the risk of delirium in elderly patients in the ICU. METHODS: Elderly patients from the Medical Information Mart for Intensive Care IV (MIMIC-IV) and the eICU Collaborative Research Database (eICU-CRD) were included in this study, totaling 11,310 and 5,627, respectively. All subjects were stratified according to their GNRI score: those with no nutritional risk (GNRI > 98), mild nutritional risk (92 ≤ GNRI ≤ 98), moderate nutritional risk (82 ≤ GNRI ≤ 92), and severe nutritional risk (GNRI < 82). The primary outcome was delirium. RESULTS: The GNRI in MIMIC-IV and eICU-CRD were 93.82 (84.88, 101.26) and 83.39 (75.95, 89.35), respectively. Compared to the cohort without nutritional risk, there was an increased risk of delirium in patients with mild nutritional risk (OR: 1.39, 95 % CI: 1.23-1.58), moderate nutritional risk (OR: 1.72, 95 % CI: 1.52-1.95), and severe nutritional risk (OR: 2.07, 95 % CI: 1.79-2.39). Inclusion of the GNRI score in the multivariate models improved the prediction of delirium. Similar results were found in the eICU-CRD database. CONCLUSIONS: Nutritional assessment using the GNRI may be an independent predictor of the development of delirium in elderly patients in the ICU. The addition of the GNRI score to the delirium prediction model improves its predictive accuracy.

Establishment of new convenient two-line system for hybrid production by targeting mutation of OPR3 in allopolyploid Brassica napus.

The two-line pollination control system, which usually depends on the utilization of thermosensitive or photoperiod genic male-sterile lines, has been widely used in various crops. However, this system is susceptible to instability issues caused by uncontrollable weather fluctuations. A stable and handy two-line pollination control system is highly desirable in many crop species for heterosis exploitation. Oxophytodienoic acid reductase 3 (OPR3) was proven to be involved in jasmonate biosynthesis. In the present study, CRISPR/Cas9 (Clustered Regularly Interspaced Short Palindromic Repeat) was utilized to mutate two OPR3 homologs in Brassica napus. After two OPR3 homologs were simultaneously mutated, mutants exhibited complete male sterility, and fertility could be easily restored by exogenous MeJA treatment. Hybrids produced from crosses between the opr3 sterile lines and normal varieties exhibited heterosis. This new two-line system based on OPR3 mutation provides higher stability and convenience than traditional systems. By using exogenous MeJA treatment to restore fertility, the system enables more precise control of male fertility transition, which has great potential to significantly contribute to the maneuverable production of hybrid seeds in rapeseed as well as other Brassica species crops.

Can admission Braden skin score predict delirium in older adults in the intensive care unit? Results from a multicenter study.

AIMS AND OBJECTIVES: To investigate whether a low Braden Skin Score (BSS), reflecting an increased risk of pressure injury, could predict the risk of delirium in older patients in the intensive care unit (ICU). BACKGROUND: Delirium, a common acute encephalopathy syndrome in older ICU patients, is associated with prolonged hospital stay, long-term cognitive impairment and increased mortality. However, few studies have explored the relationship between BSS and delirium. DESIGN: Multicenter cohort study. METHODS: The study included 24,123 older adults from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database and 1090 older adults from the eICU Collaborative Research Database (eICU-CRD), all of whom had a record of BSS on admission to the ICU. We used structured query language to extract relevant data from the electronic health records. Delirium, the primary outcome, was primarily diagnosed by the Confusion Assessment Method for the ICU or the Intensive Care Delirium Screening Checklist. Logistic regression models were used to validate the association between BSS and outcome. A STROBE checklist was the reporting guide for this study. RESULTS: The median age within the MIMIC-IV and eICU-CRD databases was approximately 77 and 75 years, respectively, with 11,195 (46.4%) and 524 (48.1%) being female. The median BSS at enrollment in both databases was 15 (interquartile range: 13, 17). Multivariate logistic regression showed a negative association between BSS on ICU admission and the prevalence of delirium. Similar patterns were found in the eICU-CRD database. CONCLUSIONS: This study found a significant negative relationship between ICU admission BSS and the prevalence of delirium in older patients. RELEVANCE TO CLINICAL PRACTICE: The BSS, which is simple and accessible, may reflect the health and frailty of older patients. It is recommended that BSS assessment be included as an essential component of delirium management strategies for older patients in the ICU. NO PATIENT OR PUBLIC CONTRIBUTION: This is a retrospective cohort study, and no patients or the public were involved in the design and conduct of the study.

Triglyceride-glucose index as a valuable predictor for aged 65-years and above in critical delirium patients: evidence from a multi-center study.

BACKGROUND: The triglyceride-glucose index (TyG), an established indicator of insulin resistance, is closely correlated with the prognosis of several metabolic disorders. This study aims to investigate the association between the TyG index and the incidence of critical delirium in patients aged 65 years and older. METHODS: We focused on evaluating patients aged 65 years and older diagnosed with critical delirium. Data were obtained from the Medical Information Database for Intensive Care (MIMIC-IV) and the eICU Collaborative Research Database (eICU-CRD). Multivariate logistic regression and restricted cubic spline (RCS) regression were used to determine the relationship between the TyG index and the risk of delirium. RESULTS: Participants aged 65 years and older were identified from the MIMIC-IV (n = 4,649) and eICU-CRD (n = 1,844) databases. Based on optimal thresholds derived from RCS regression, participants were divided into two cohorts: Q1 (< 8.912), Q2 (≥ 8.912). The logistic regression analysis showed a direct correlation between the TyG index and an increased risk of critical delirium among ICU patients aged 65 and older. These findings were validated in the eICU-CRD dataset, and sensitivity analysis further strengthened our conclusions. In addition, the subgroup analysis revealed certain differences. CONCLUSION: This study highlights a clear, independent relationship between the TyG index and the risk of critical delirium in individuals aged 65 years and older, suggesting the importance of the TyG index as a reliable cardio-cerebrovascular metabolic marker for risk assessment and intervention.

Exploring patient medication adherence and data mining methods in clinical big data: A contemporary review.

BACKGROUND: Increasingly, patient medication adherence data are being consolidated from claims databases and electronic health records (EHRs). Such databases offer an indirect avenue to gauge medication adherence in our data-rich healthcare milieu. The surge in data accessibility, coupled with the pressing need for its conversion to actionable insights, has spotlighted data mining, with machine learning (ML) emerging as a pivotal technique. Nonadherence poses heightened health risks and escalates medical costs. This paper elucidates the synergistic interaction between medical database mining for medication adherence and the role of ML in fostering knowledge discovery. METHODS: We conducted a comprehensive review of EHR applications in the realm of medication adherence, leveraging ML techniques. We expounded on the evolution and structure of medical databases pertinent to medication adherence and harnessed both supervised and unsupervised ML paradigms to delve into adherence and its ramifications. RESULTS: Our study underscores the applications of medical databases and ML, encompassing both supervised and unsupervised learning, for medication adherence in clinical big data. Databases like SEER and NHANES, often underutilized due to their intricacies, have gained prominence. Employing ML to excavate patient medication logs from these databases facilitates adherence analysis. Such findings are pivotal for clinical decision-making, risk stratification, and scholarly pursuits, aiming to elevate healthcare quality. CONCLUSION: Advanced data mining in the era of big data has revolutionized medication adherence research, thereby enhancing patient care. Emphasizing bespoke interventions and research could herald transformative shifts in therapeutic modalities.

Associations Between Dysphagia and Adverse Health Outcomes in Older Adults with Dementia in Intensive Care Units: A Retrospective Cohort Study.

Background: Dysphagia is common in elderly patients with dementia and is one of the common clinical geriatric syndromes. It imposes a heavy burden on patients and their caregivers and is becoming an important public health problem. This study examined the association between dysphagia in older dementia patients in the ICU and the subsequent adverse health outcomes they experience. Patients and Methods: A retrospective analysis of adults (≥65 years) with dementia in ICUs of a Boston tertiary academic medical center was conducted. Using the International Classification of Diseases' Ninth and Tenth Revisions, dementia patients were identified. The study cohort comprised 1009 patients, median age 84.82 years, 56.6% female, predominantly White (72.9%). Patients were grouped based on swallowing function: dysphagia (n=282) and no-dysphagia (n=727). Dysphagia was identified via positive bedside swallowing screening. Primary outcomes were 90- and 180-day mortality, secondary outcomes included aspiration pneumonia, pressure injury, and delirium. Cohort characteristics were compared using the Wilcoxon rank-sum and chi-square tests. Dysphagia and outcomes correlations were examined via Kaplan-Meier survival analysis, Cox proportional-hazards regression models, logistic regression models, and subgroup analysis. Results: After adjusting for covariates, the results from multivariate Cox proportional-hazards regression indicated that dysphagia was significantly associated with increased 90-day (HR=1.36, 95% CI=1.07-1.73, E-value=1.78) and 180-day (HR=1.47, 95% CI=1.18-1.82, E-value=1.94) mortality; the multifactorial logistic regression results indicated that dysphagia was associated with significant increases in pressure injury (OR=1.58, 95% CI=1.11-2.23, E-value=1.83) and aspiration pneumonia occurrence (OR=4.04, 95% CI=2.72-6.01, E-value=7.54), but was not significantly associated with delirium prevalence (OR=1.27, 95% CI=0.93-1.74). Conclusion: Dysphagia is likely to increase the risk of adverse health outcomes in older adults with dementia in ICU, and these adverse outcomes mostly include 90- and 180-day mortality, aspiration pneumonia, and pressure injury.

A risk nomogram for predicting prolonged intensive care unit stays in patients with chronic obstructive pulmonary disease.

Background: Providing intensive care is increasingly expensive, and the aim of this study was to construct a risk column line graph (nomograms)for prolonged length of stay (LOS) in the intensive care unit (ICU) for patients with chronic obstructive pulmonary disease (COPD). Methods: This study included 4,940 patients, and the data set was randomly divided into training (n = 3,458) and validation (n = 1,482) sets at a 7:3 ratio. First, least absolute shrinkage and selection operator (LASSO) regression analysis was used to optimize variable selection by running a tenfold k-cyclic coordinate descent. Second, a prediction model was constructed using multifactorial logistic regression analysis. Third, the model was validated using receiver operating characteristic (ROC) curves, Hosmer-Lemeshow tests, calibration plots, and decision-curve analysis (DCA), and was further internally validated. Results: This study selected 11 predictors: sepsis, renal replacement therapy, cerebrovascular disease, respiratory failure, ventilator associated pneumonia, norepinephrine, bronchodilators, invasive mechanical ventilation, electrolytes disorders, Glasgow Coma Scale score and body temperature. The models constructed using these 11 predictors indicated good predictive power, with the areas under the ROC curves being 0.826 (95%CI, 0.809-0.842) and 0.827 (95%CI, 0.802-0.853) in the training and validation sets, respectively. The Hosmer-Lemeshow test indicated a strong agreement between the predicted and observed probabilities in the training (χ2 = 8.21, p = 0.413) and validation (χ2 = 0.64, p = 0.999) sets. In addition, decision-curve analysis suggested that the model had good clinical validity. Conclusion: This study has constructed and validated original and dynamic nomograms for prolonged ICU stay in patients with COPD using 11 easily collected parameters. These nomograms can provide useful guidance to medical and nursing practitioners in ICUs and help reduce the disease and economic burdens on patients.

Development and validation of a risk prediction model for frailty in patients with diabetes.

BACKGROUND: Frailty is the third most common complication of diabetes after macrovascular and microvascular complications. The aim of this study was to develop a validated risk prediction model for frailty in patients with diabetes. METHODS: The research used data from the China Health and Retirement Longitudinal Study (CHARLS), a dataset representative of the Chinese population. Twenty-five indicators, including socio-demographic variables, behavioral factors, health status, and mental health parameters, were analyzed in this study. The study cohort was randomly divided into a training set and a validation set at a ratio of 70 to 30%. LASSO regression analysis was used to screen the variables for the best predictors of the model based on a 10-fold cross-validation. The logistic regression model was applied to explore the associated factors of frailty in patients with diabetes. A nomogram was constructed to develop the prediction model. Calibration curves were applied to evaluate the accuracy of the nomogram model. The area under the receiver operating characteristic curve and decision curve analysis were conducted to assess predictive performance. RESULTS: One thousand four hundred thirty-six patients with diabetes from the CHARLS database collected in 2013 (n = 793) and 2015 (n = 643) were included in the final analysis. A total of 145 (10.9%) had frailty symptoms. Multivariate logistic regression analysis showed that marital status, activities of daily living, waist circumference, cognitive function, grip strength, social activity, and depression as predictors of frailty in people with diabetes. These factors were used to construct the nomogram model, which showed good concordance and accuracy. The AUC values of the predictive model and the internal validation set were 0.912 (95%CI 0.887-0.937) and 0.881 (95% CI 0.829-0.934). Hosmer-Lemeshow test values were P = 0.824 and P = 0.608 (both > 0.05). Calibration curves showed significant agreement between the nomogram model and actual observations. ROC and DCA indicated that the nomogram had a good predictive performance. CONCLUSIONS: Comprehensive nomogram constructed in this study was a promising and convenient tool to evaluate the risk of frailty in patients with diabetes, and contributed clinicians to screening the high-risk population.

Developing an explainable machine learning model to predict the mechanical ventilation duration of patients with ARDS in intensive care units.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is common in intensive care units with high mortality rate and mechanical ventilation (MV) is the most important related treatment. Early prediction of MV duration has benefit for patients risk stratification and care strategies support. OBJECTIVE: To develop an explainable model for predicting mechanical ventilation (MV) duration in patients with ARDS using the machine learning (ML) approach. METHOD: The number of 1,148, 1,697, and 29 ARDS patients admitted to intensive care units (ICU) in the MIMIC-IV, eICU-CRD, and AmsterdamUMCdb databases were included in the study. Features at MV initiation from the MIMIC-IV dataset were used to train prediction models based on seven supervised machine learning algorithms. After 5-fold cross-validation for hyperparameters tuning, the hyperparameters- optimized model of different algorithms was tested by external datasets extracted from eICU-CRD and Amsterdamumcdb. Finally, three descriptive machine learning explanation methods were conducted for the model explanation. RESULT: The XGBoosting model showed the most stable and accurate performance among two testing datasets (RMSE= 5.57 and 5.46 days in eICU-CRD and AmsterdamUMCdb) and was selected as the optimal model. The model explanation based on SHAP, LIME, and DALEX results showed a consistent result, vasopressor, PH, and SOFA score had the highest effect on MV duration prediction. CONCLUSION: ML models with features at MV initiation can accurate predict MV duration in patients with ARDS in ICUs. Among seven algorithms, XGB models showed the best performance (RMSE= 5.57 and 5.46 in two external datasets). LIME, SHAP, and Breakdown methods showed good performance as AXI methods.

Ligand-Functional Groups Induced Tuning MOFs' 2D into 1D Pore Channels for Pipeline Natural Gas Purification.

The solvothermal reactions of CoCl2 ⋅ 6H2 O, 3,5-pyridinedicarboxylic acid (H2 L) and isonicotinic acid (HL1 )/3-amino isonicotinic acid (HL2 )/3-chloro isonicotinic acid (HL3 ) successfully led to three tfz-d topological pillar-layer [Co4 (µ-F)2 (COO)6 (NC5 H4 )4 ] cluster-based MOFs, namely, [Co4 (µ-F)2 (L)2 (L1 )2 ⋅ 2DMA] ⋅ DMA ⋅ 2H2 O (SNNU-Bai76, SNNU-Bai=Shaanxi Normal University Bai's group), [Co4 (µ-F)2 (L)2 (L2 )2 ⋅ 2H2 O] ⋅ 2DMA ⋅ 2H2 O (SNNU-Bai77) and [Co4 (µ-F)2 (L)2 (L3 )2 ⋅ 2H2 O] ⋅ 2DMF ⋅ 2H2 O (SNNU-Bai78). With the 2D pore channels in SNNU-Bai76 and SNNU-Bai77 being tuned to the 1D pore channel in SNNU-Bai78, C3 H8 and C2 H6 adsorption uptakes are apparently improved and the IAST selectivities of C3 H8 /CH4 and C2 H6 /CH4 almost remain, which indicate that SNNU-Bai78 may be one potential separation material for the pipeline natural gas purification. These were further confirmed by the breakthrough experiments for the simulated pipeline natural gas (C3 H8 /C2 H6 /CH4 : 5/10/85 gas mixture) of three isostructural MOFs. Furthermore, GCMC simulations revealed that due to one of the pore channels blocked by Cl atoms in a couple of 3-chloro isonicotinic acid with the changed conformation as the pillar, the pore wall of the formed 1D pore channel in SNNU-Bai78 may interact with the adsorbed C3 H8 or C2 H6 molecule more strongly, for which more atoms of framework at the new adsorption site will interact with the adsorbed gas molecule by more intermolecular interactions. This was also evidenced by the increased binding energies, being consistent with the tuning of adsorption enthalpies for C3 H8 and C2 H6 gas molecules, and the reduced C3 H8 and C2 H6 gas diffusion coefficients in SNNU-Bai78. Very interestingly, this work is the first example of finely tuning the pore connectivity of MOFs toward strengthened host-guest interactions for the gas adsorption and separation.

A prospective multi-center randomized comparative trial evaluating outcomes of transrectal ultrasound (TRUS)-guided 12-core systematic biopsy, mpMRI-targeted 12-core biopsy, and artificial intelligence ultrasound of prostate (AIUSP) 6-core targeted biopsy for prostate cancer diagnosis.

BACKGROUND: Artificial intelligence ultrasound of prostate (AIUSP)-targeted biopsy has been used for prostate cancer (PCa) diagnosis. The objective of this prospective multi-center head-to-head clinical randomized comparative trail (RCT) is to compare PCa detection rate in the TRUS-guided 12-core standard systematic biopsy (TRUS-SB) group and cognitive fused mpMRI-guided 12-core biopsy (mpMRI) group against AIUSP group. METHODS: Four hundred patients were randomized to three arms and underwent biopsies by TRUS-SB (n = 133), mpMRI (n = 134), and AIUSP (n = 133) between January 2015 and December 2017. In TRUS-SB group, a standard 12-core systematic biopsy was performed. In mpMRI group, mpMRI-suspicious lesions (PI-RADS 3-5) were targeted by 2-core biopsy followed by a 10-core systematic biopsy. Otherwise, 12-core systematic biopsy was performed. In AIUSP group, a 6-core targeted biopsy was performed. The primary endpoint was PCa detection rate. RESULTS: AIUSP detected the highest rate of PCa (66/133, 49.6%) compared to TRUS-SB (46/133, 34.6%, p = 0.036) and mpMRI (48/134, 35.8%, p = 0.052). Compared to TRUS-SB (35/133, 26.3%) and mpMRI (31/134, 23.1%) groups, clinically significant PCa (csPCa) detection rate was 32.3% (43/133) in AIUSP group. Overall biopsy core positive rate in the TRUS-SB group (11.0%, 176/1598) and in the mpMRI group (12.7%, 204/1608) was significantly lower than that in the AIUSP group (22.7%, 181/798, p < 0.001). CONCLUSIONS: AIUSP detected the highest rate of overall and significant PCa compared to TRUS-SB and mpMRI, and could be used as an alternative to systematic biopsy in the future. REGISTRATION: This trial was registered in ISRCTN (ISRCTN18033113).