Stratification Index Research Articles

The 5-Item Modified Frailty Index (mFI-5) for risk stratification of patients with infective endocarditis undergoing cardiac surgery

Abstract Background population aging has led to an increased burden of frailty as an emerging global health issue, and variables for its quantification in patients with infective endocarditis (IE) are lacking in current surgical risks scores. The 5-item modified frailty index (mFI-5) score has shown to be effective in the prediction of surgical outcomes in other medical scenarios. Purpose this study aimed to assess the role of the mFI-5 in the prediction of surgical outcomes in patients with left-sided IE undergoing cardiac surgery. Methods a total of 112 cases of confirmed left-sided IE undergoing surgery, were consecutively collected and followed during one year after diagnosis in two tertiary hospitals between 2016 and 2021. The mFI-5 score included 5 baseline patient-specific comorbidities: diabetes, congestive heart failure, non-independent functional status (Barthel index <80), hypertension and chronic obstructive pulmonary disease (range 0-5), and patients were categorised as mFI-low (<2, n=65), and mFI-high (>=2, n=47). Results mean age was 66 [SD 15] years, 67% were men and community-acquired infections were 75%. As shown in Table 1, mFI-high patients were older and, aside from the specific comorbidities included in the score, with more chronic kidney disease. The most isolated pathogen was S. viridans (n=32), predominantly in mFI-low, in contrast to enterococcal and polymicrobial IEs, which were more frequent in mFI-high. Larger vegetations were reported in mFI-high [16 (10) vs 13 (9) mm, p 0.03], with no differences regarding infection site or periannular complications. Acute kidney injury, decompensated heart failure and higher natriuretic peptides were more common in mFI-high. Regarding mortality, in-hospital deaths were more frequent in mFI-high group. When analyzing mFI-score as a discrete variable, in-hospital mortality was associated with higher median scores values [2 (2) vs 1(1) points, p 0.02], being 2 points the optimal cutoff point for prediction [AUC 0.64 (95% CI 0.54-0.73), Fig.1A]. Among survivors who completed follow-up (n=82), rehospitalization and all-cause mortality rates in mFI-high exceeded those from mFI-low. Predictors of in-hospital and 1-year mortality were assessed by logistic regression (Fig. 1B), confirming the independent prognostic association of mFI-5-score in patients with IE undergoing surgery. Conclusions patients with IE undergoing cardiac surgery with higher mFI-5 scores were older, more predisposed to enterococcal and polymicrobial infections, and had a greater comorbidity burden with a more complicated clinical course. The mFI-score was independently associated with in-hospital mortality as well as rehospitalizations and 1-year mortality, positioning itself as an additional tool for risk stratification in this cluster of patients.Table 1Figure 1

A new prehospital cardiac risk assessment index derived from vital signs by first contact emergency medical service, including prehospital oxygen saturation, for accurate prehospital triage of acute m

Abstract Background: Rapid and accurate triage is essential to improve the prognosis of patients with severe acute myocardial infarction (AMI). However, prehospital triage using vital signs, including prehospital oxygen saturation (SpO2), by first medical contact has not been evaluated. Purpose: The purpose of this study was to develop a new risk stratification index for AMI using vital signs including SpO2 for rapid and accurate prehospital triage. Methods: From January 2013 to June 2022, 3006 AMI patients who were directly transported by ambulance were enrolled from the Mie ACS registry. Based on observed risk relationships in 3,006 AMI patients, we developed and evaluated a prehospital cardiac risk assessment index (P-CRAI) using age, heart rate, and systolic blood pressure (SBP) and SpO2 to predict 30-day mortality: (heart rate×[age/10]2)/SBP＋1.1(100-SpO2). We also analyzed whether P-CRAI predicted the need for mechanical circulatory support (MCS) or ventilator use. Results: In the receiver operating characteristic (ROC) curve analysis, P-CRAI 38.1 has a sensitivity of 84.4%, specificity of 72.7%, and accuracy of 84.3% for predicting 30-day mortality, and P-CRAI was a strong predictor of 30-day mortality compared with the other indices and variables (Figure 1A). When divided into two groups with P-CRAI 38, Kaplan-Meier survival curves showed significant differences in 30-day survival between the high and low groups (83.7% vs. 98.7%, P<0.001, Figure 1B). P-CRAI≥38 was the strongest independent predictor of 30-day mortality with a hazard ratio of 7.64 compared to the other factors by multivariate Cox regression analysis. The spline curve of 30-day mortality by P-CRAI shows a correlation with prognosis (Figure 2A). In this study, we then used the bootstrap method to generate a calibration curve and validate P-CRAI. The results showed an excellent fit and that P-CRAI accurately estimated patient prognosis (Figure 2B). In addition, P-CRAI was a robust predictor of the very early events of death at 24 hours and MCS or ventilator use by ROC curve analysis. (c-statistic 0.835 and 0.726, respectively, P<0.01). Conclusion: The P-CRAI was found to be a useful tool for prehospital triage of AMI patients, accurately predicting 30-day mortality and the need for MCS.Figure 1.Figure 2.

Seasonal Variations in the Thermal Stratification Responses and Water Quality of the Paldang Lake

We evaluated the thermal and chemical stratifications of Paldang Lake using Schmidt’s stability index (SSI) and the chemical stratification index (IC-i) with weekly data from 2013 to 2022. The temporal trends of stratification were analyzed alongside correlations with meteorological, hydrological, and water quality variables. Thermal stratification intensified with rising air temperature and sunshine duration, while hydrological factors like discharge and retention time affected SSI during periods with less than five days of water retention. During summer, fewer occurrences of intense rainfall or early rainfall before August led to stronger stratification. In fall, nutrient influx from external sources during summer stimulated algal growth, increasing Chlorophyll-α (Chl-α) concentrations. Summer rainfall had a significant impact on the strength and duration of stratification in Paldang Lake. Annual rainfall patterns and subsequent changes in discharge were key factors affecting the physical environment of the lake, which in turn determined water quality and the extent of algal blooms. We provide insights into the seasonal stratification and water quality variations in temperate river-type reservoirs like Paldang Lake. SSI and IC-i from this research can be applied to understand stratification and mixing dynamics in other lakes.

Development of a prognostic model for predicting long-term visual acuity after cataract surgery in children with bilateral congenital cataracts: a single centre retrospective, observational study

BackgroundTo evaluate factors influencing best corrected visual acuity (BCVA) in paediatric patients with bilateral congenital cataracts (CC) after cataract extraction and intraocular lens (IOL) implantation, as well as develop a robust model for predicting long-term visual acuity.MethodsThis retrospective study followed 194 paediatric patients with bilateral CC from January 2008 to December 2021. The endpoint event was defined as a final BCVA < 0.22 Log MAR at the last follow-up, which indicated good outcome. The probability of reaching this endpoint event was modelled using Cox proportional hazards regression analysis and internally validated through 200 iteration of 5-fold cross-validation.ResultsA prognostic model for long-term visual acuity in bilateral CC after surgical treatment was established as follows: ln h(t) = −0.009 × “age at cataract extraction” − 0.015 × “age at IOL implantation” − 2.934 × “without nystagmus at last follow − up” + ln h0(0), in which h0(t) represents the baseline risk equation that can be any non-negative equation for time (t); h(t) represents the probability of the endpoint event occurring at time (t) without any endpoint event occurring before it. The model was visualized using a nomogram and contour plot to facilitate clinical practice. The model demonstrated reasonably accurate discrimination with an area under the receiver operating characteristic curve of 0.712 (95% confidence interval [CI]: 0.589–0.835) and a C-index of 0.797 (95% CI: 0.683–0.911). According to the model, children with bilateral CC had a higher likelihood of achieving a good outcome (BCVA < 0.22 Log MAR) if they underwent cataract extraction before the age of six months (hazard ratio [HR] 1.80, 95% CI: 0.92–3.70), received IOL implantation before the age of thirty-one months (HR 3.70, 95% CI: 1.77–7.80), and presented without nystagmus during their last follow-up visit (HR 11.20, 95% CI: 3.96–31.80).ConclusionsThis long-term visual acuity prognostic model demonstrates adequate performance for individualized prediction and assists in clinical decision-making. The risk stratification index guides optimal timing for surgery.

Use of The VES-13 and IVCF-20 Instruments for Risk Stratification of the Older Adults By Primary Care Professionals

Objective: To analyze the use of the Vulnerable Elders Survey 13 (VES-13) and the 20-item Clinical-Functional Vulnerability Index (IVCF-20) instruments in identifying vulnerable elderly individuals or those at risk of vulnerability. Theoretical Framework: The index of vulnerable elderly individuals or those at risk of vulnerability is approximately 30%, justifying the need for research to verify the instruments used by health professionals in their identification. Method: Quantitative approach through a descriptive study. Data collection was carried out through a questionnaire administered to professionals from the Health Strategy teams in a municipality in 2022. Results and Discussion: The VES-13 is the most used instrument by health professionals. However, there were evident difficulties in interpreting the collected data and effectively applying it to improve elderly care. The IVCF-20 was unknown to almost all participants. Research Implications: Based on the results, an extension course was conducted to promote the IVCF-20 to nursing professionals and to recommend training for other professionals. Originality/Value: This study, by analyzing the knowledge and practice of the participants, encouraged the adoption of measures for both the municipality’s adoption of the most updated elderly vulnerability risk stratification index (IVCF-20) and the training of health professionals involved in care.

TCT-356 Morphological and Flow Dynamic Indices for Coronary Dilation Thrombus Stratification

TCT-356 Morphological and Flow Dynamic Indices for Coronary Dilation Thrombus Stratification

Utilization of Chronic Lymphocytic Leukemia—International Prognostic Index (CLL-IPI) for Prognostic Stratification in Newly Diagnosed CLL Patients

Utilization of Chronic Lymphocytic Leukemia—International Prognostic Index (CLL-IPI) for Prognostic Stratification in Newly Diagnosed CLL Patients

An interpretable survival model for diffuse large B-cell lymphoma patients using a biologically informed visible neural network

Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma (NHL) and is characterized by high heterogeneity. Assessment of its prognosis and genetic subtyping hold significant clinical implications. However, existing DLBCL prognostic models are mainly based on transcriptomic profiles, while genetic variation detection is more commonly used in clinical practice. In addition, current clustering-based subtyping methods mostly focus on genes with high mutation frequencies, providing insufficient explanations for the heterogeneity of DLBCL. Here, we proposed VNNSurv (https://bio-web1.nscc-gz.cn/app/VNNSurv), a survival model for DLBCL patients based on a biologically informed visible neural network (VNN). VNNSurv achieved an average C-index of 0.72 on the cross-validation set (HMRN cohort, n = 928), outperforming the baseline methods. The remarkable interpretability of VNNSurv facilitated the identification of the most impactful genes and the underlying pathways through which they act on patient outcomes. When only the 30 highest-impact genes were used as genetic input, the overall performance of VNNSurv improved, and a C-index of 0.70 was achieved on the external TCGA cohort (n = 48). Leveraging these high-impact genes, including 16 genes with low (<5 %) alteration frequencies, we devised a genetic-based prognostic index (GPI) for risk stratification and a subtype identification method. We stratified the patient group according to the International Prognostic Index (IPI) into three risk grades with significant prognostic differences. Furthermore, the defined subtypes exhibited greater prognostic consistency than clustering-based methods. Broadly, VNNSurv is a valuable DLBCL survival model. Its high interpretability has significant value for precision medicine, and its framework is scalable to other diseases.

Effect of soil management on carbon stock and soil aggregation in an area of natural regeneration and surrounding systems in the Atlantic Forest biome

This study aimed to quantify total organic carbon (TOC), carbon of humic substances (HS), and their stocks and evaluate the soil structural stability of areas with different uses under sandy loam soil texture. Soil samples were collected from managed areas and a reference area: Permanent Pasture (PP), No-Till (NT), Private Natural Heritage Reserve in the process of natural regeneration (PNHR) and Native Forest (FN). Dry mass analysis, carbon stock quantification, chemical fractionation of soil organic matter and soil aggregation were carried out. The NF area had the highest deposition of litter mass (ML). The PP and NT areas had the highest bulk density (Bd). TOC and Stock-C contents were higher in PNHR, followed by NF, and stratification index (STRATI) was also higher in the regeneration area. The NT, PNHR, and NF areas had a higher proportion of carbon fulvic acid fraction (C-FA) than carbon humic acid fraction (C-HA), but the fraction with the highest representation in all areas was carbon humin fraction (C-HUM). The PP, PNHR, and NF areas obtained the best aggregate stability indicators, as well as a higher proportion of macroaggregates, with the NT area having low aggregate stability. Recovery of C contents was observed in recent years in the area of PNHR, leading to a greater storage of C, which shows a quantitative recovery of C in the soil in this area after four years of natural regeneration. Furthermore, the PP and NT areas present a lower capacity for C sequestration, mainly due to the management conditions. Keywords: aggregate stability, climate change, crop production, soil quality.

Factors contributing to the minimum water column stability and timing of the winter turnover in the Ogouchi reservoir

Turnover in lakes and reservoirs causes circulation in the water column from the bottom to the surface when the water column stability becomes low. Previous studies commonly mentioned that turnover occurs when stratification indices become small, but the threshold is rarely discussed. While turnover phenomena have been extensively studied by evaluating changes in bottom dissolved oxygen (DO), the relationship between the disappearance of hypoxia and water temperature indices has not been determined. This study focused on the factors influencing the minimum thermal gradient (TG) and Schmidt Stability Index (SSI), and the timing of turnover events using DO as an indicator of mixing in the Ogouchi reservoir from 1992 to 2001. The results showed that the occurrence of minimum TG and SSI is mainly driven by inflow retention time and average maximum wind speed. Moreover, minimum air temperature and outflow retention time have few contributions to minimum SSI. It was found that 7 out of 10 years exhibited full winter turnover, while the remaining years showed incomplete mixing with persistent hypoxia at the reservoir bottom. This study identifies four cases based on onset thresholds of 0.0035 °C m−1 for TG and 30 J m−2 for SSI to explain turnover event: Case 1: an ideal state with stratification indices below the threshold, resulting in the disappearance of hypoxia; Case 2: indices above the threshold sustain hypoxia; Case 3: an irregular state where the indices exceed the threshold, yet hypoxia disappears; and Case 4: an unexpected persistence of hypoxia despite being below the threshold. The majority of the years (70 percent) were explained by thresholds. The multiple regression analysis indicated the importance of wind speed on the turnover event. Therefore, the effect of wind shear was analyzed for 30 percent of the years that cannot be explained by thresholds (cases 3 and 4). Case 3 shows turnover occurrence due to strong accumulated wind shear, despite exceeding thresholds. Conversely, Case 4 reveals weak wind shear preventing bottom water upwelling, even below thresholds. In conclusion, the precise TG and SSI thresholds for the onset of turnover event were determined using DO data. The thresholds explained the occurrence and non-occurrence of turnover event in most of the years and wind speed clarified unexplained cases by thresholds. The presented method successfully evaluated the timing of turnover and can be applicable elsewhere.

Utility of PSMA-PET derived volumetric parameters in initial risk stratification and prediction of prostate cancer metastasis - a head-to-head comparison of the radiotracers 18F-PSMA-1007 and 68Ga-PSMA-11.

This study aimed to explore and compare the utility of baseline 18F-PSMA-1007 and 68Ga-PSMA-11 PET/computed tomography (CT) derived volumetric parameters in initial risk stratification and prediction of prostate cancer (PCa) metastasis. Forty treatment-naïve, biopsy-proven intermediate-/high-risk PCa patients were prospectively recruited. Each patient underwent PET/CT with 68Ga-PSMA-11 and 18F-PSMA-1007 (within 2 weeks). The maximum and mean standardized uptake values (SUVmax and SUVmean) of primary tumor, prostate PSMA-tumor volume (PSMA-TVp), and prostate total lesion PSMA (TL-PSMAp) were measured. PSMA-TVp and TL-PSMAp (with both radiotracers) mostly exhibited moderate-to-strong correlation with Gleason score, serum prostate-specific antigen level and clinical tumor stage (Spearman ρ = 0.361-0.783, P-values ≤0.022). Primary tumor SUVmax values were similar across initial risk categories. PSMA-TVp and TL-PSMAp, however, were significantly higher in high-risk PCa compared to intermediate-risk PCa (P-values ≤0.001). Receiver operating characteristic (ROC) curve analysis revealed that F-PSMA-TVp, Ga-PSMA-TVp, F-TL-PSMAp, and Ga-TL-PSMAp (optimal cutoff values of 20.9, 23.4, 142.5, and 144.8, respectively) could effectively differentiate high-risk from intermediate-risk PCa [area under the ROC curve (AUCs) 0.859-0.898, P-values <0.001] with high sensitivity (~68.8-75%) and excellent specificity (100%). PSMA-TVp and TL-PSMAp (with both radiotracers) could predict presence of regional and extraregional nodal metastasis (AUCs 0.703-0.801, P-values ≤0.03) with moderate sensitivity (~47.8-70.6%) and excellent specificity (~82.6-94.1%). Our results suggest that baseline PSMA-PET primary tumor volumetric parameters provide a noninvasive, objective, and accurate index for initial risk stratification and can predict presence of regional and extraregional nodal metastasis in PCa patients. Larger studies are warranted to evaluate their incremental role over conventional parameters.

Comparative study on the predictive value of TG/HDL-C, TyG and TyG-BMI indices for 5-year mortality in critically ill patients with chronic heart failure: a retrospective study

BackgroundThe triglyceride glucose (TyG) index, TyG-body mass index (TyG-BMI), and triglyceride-density lipoprotein cholesterol ratio (TG/HDL-C) are substitute indicators for insulin resistance (IR). This study aimed to compare the predictive value of these indicators for 5-year mortality in critically ill patients with chronic heart failure (CHF).MethodsCritically ill patients with CHF were identified from the Multiparameter Intelligent Monitoring in Intensive Care (MIMIC) III and IV databases. The primary outcome was 5-year mortality. The relationship between the three indices and mortality risk was determined using multivariate Cox proportional hazards models, Kaplan–Meier (K‒M) analysis and restricted cubic splines analysis. A receiver operating characteristic (ROC) curve was generated to compare the ability of the three indices to predict mortality. Finally, whether the IR indices would further increase the predictive ability of the basic model including baseline variables with a significance level between survivors and non-survivors was evaluated by ROC curve.ResultsAltogether, 1329 patients with CHF were identified from the databases. Cox proportional hazards models indicated that the TyG index was independently associated with an elevated risk of 5-year mortality (hazard ratio [HR], 1.56; 95% confidence interval [CI] 1.29–1.9), while the TyG-BMI index and TG/HDL-C level were significantly associated with 5-year mortality, with an HR (95% CI) of 1.002 (1.000–1.003) and 1.01 (1.00–1.03), respectively. The K–M analysis revealed that the cumulative incidence of all-cause 5-year death increased with increasing quartiles of the TyG index, TyG-BMI index, or TG/HDL-C ratio. According to the ROC curve, the TyG index outperformed the TyG-BMI and TG/HDL-C ratio at predicting all-cause 5-year mortality (0.608 [0.571–0.645] vs. 0.558 [0.522–0.594] vs. 0.561 [0.524–0.598]). The effect of the TyG index on all-cause mortality was consistent across subgroups, with no significant interaction with randomized factors. Furthermore, adding the TyG index to the basic model for 5-year mortality improved its predictive ability (area under the curve, 0.762 for the basic model vs. 0.769 for the basic model + TyG index); however, the difference was not statistically significant.ConclusionAs continuous variables, all three indices were significantly associated with 5-year mortality risk in critically ill patients with CHF. Although these IR indices did not improve the predictive power of the basic model in patients with CHF, the TyG index appears to be the most promising index (vs. TyG-BMI and TG/HDL-C ratio) for prevention and risk stratification in critically ill patients with CHF.

Association of triglyceride-glucose index and its related parameters with atherosclerotic cardiovascular disease: evidence from a 15-year follow-up of Kailuan cohort

BackgroundTriglyceride glucose (TyG) index and its related parameters have been introduced as cost-effective surrogate indicators of insulin resistance, while prospective evidence of their effects on atherosclerotic cardiovascular disease (ASCVD) remained scattered and inconsistent. We aimed to evaluate the association of TyG and its related parameters with new-onset ASCVD, and the predictive capacity were further compared.MethodA total of 95,342 ASCVD-free participants were enrolled from the Kailuan study. TyG and its related parameters were defined by fasting blood glucose, triglyceride, body mass index (BMI), waist circumstance (WC) and waist-to-height ratio (WHtR). The primary outcome was incident ASCVD, comprising myocardial infarction (MI) and ischemic stroke (IS). Cox proportional hazard models and restricted cubic spline (RCS) analyses were adopted to investigate the association between each index and ASCVD. The C-index, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were used for comparison of their predictive value for ASCVD.ResultsDuring a median follow-up of 15.0 years, 8,031 new cases of ASCVD were identified. The incidence rate of ASCVD increased along with elevated levels of each index, and the relationships were found to be nonlinear in the RCS analyses. The hazard ratio (HR) and 95% confidence interval (95% CI) for ASCVD was 1.39 (1.35, 1.43), 1.46 (1.41, 1.50), 1.50 (1.46, 1.55), and 1.52 (1.48, 1.57) per 1 IQR increase of baseline TyG, TyG-BMI, TyG-WC, and TyG-WHtR, respectively, and the association were more pronounced for females and younger individuals aged < 60 years (Pfor interaction<0.05). Using the updated mean or time-varying measurements instead of baseline indicators did not significantly alter the primary findings. Additionally, TyG-WC and TyG-WHtR showed better performance in predicting risk of ASCVD than TyG, with the IDI (95% CI) of 0.004 (0.001, 0.004) and 0.004 (0.001, 0.004) and the category-free NRI (95% CI) of 0.120 (0.025, 0.138) and 0.143 (0.032, 0.166), respectively. Similar findings were observed for MI and IS.ConclusionsBoth the TyG index and its related parameters were significantly and positively associated with ASCVD. TyG-WC and TyG-WHtR had better performance in predicting incident ASCVD than TyG, which might be more suitable indices for risk stratification and enhance the primary prevention of ASCVD.

Disentangling influences of climate variability and lake-system evolution on climate proxies derived from isoprenoid and branched glycerol dialkyl glycerol tetraethers (GDGTs): the 250 kyr Lake Chala record

Abstract. High-resolution paleoclimate records from tropical continental settings are greatly needed to advance understanding of global climate dynamics. The International Continental Scientific Drilling Program (ICDP) project DeepCHALLA recovered a 214.8 m long sediment sequence from Lake Chala, a deep and permanently stratified (meromictic) crater lake in eastern equatorial Africa, covering the past ca. 250 000 years (250 kyr) of continuous lacustrine deposition since the earliest phase of lake-basin development. Lipid biomarker analyses on the sediments of Lake Chala can provide quantitative records of past variation in temperature and moisture balance from this poorly documented region. However, the degree to which climate proxies derived from aquatically produced biomarkers are affected by aspects of lake developmental history is rarely considered, even though it may critically influence their ability to consistently register a particular climate variable through time. Modern-system studies of Lake Chala revealed crucial information about the mechanisms underpinning relationships between proxies based on isoprenoid (iso-) and branched (br-) glycerol dialkyl glycerol tetraethers (GDGTs) and the targeted climate variables, but the persistence of these relationships in the past remains unclear. Here we assess the reliability of long-term climate signals registered in the sediments of Lake Chala by comparing downcore variations in GDGT distributions with major phases in lake-system evolution as reflected by independent proxies of lake depth, mixing regime and nutrient dynamics: seismic reflection data, lithology and fossil diatom assemblages. Together, these records suggest that during early lake history (before ca. 180–200 ka) the distinct mixing-related depth zones with which specific GDGT producers are associated in the modern-day lake were not yet formed, likely due to more open lake hydrology and absence of chemical water-column stratification. Consequently absolute GDGT concentrations dating to this period are relatively low, proxies sensitive to water-column stratification (e.g., branched versus isoprenoid tetraether (BIT) index) display highly irregular temporal variability, and correlations between proxies are dissimilar to expectations based on modern-system understanding. A sequence of lake-system changes between ca. 180–200 and ca. 80 ka first established and then strengthened the chemical density gradient, promoting meromictic conditions despite the overall decrease in lake depth due to the basin gradually being filled up with sediments. From ca. 180 ka onward some GDGTs and derived proxies (e.g., crenarchaeol concentration, BIT index and IR6Me) display strong ∼ 23 kyr periodicity, likely reflecting the predominantly precession-driven insolation forcing of Quaternary climate variability in low-latitude regions. Our results suggest that GDGT-based temperature and moisture-balance proxies in Lake Chala sediments reflect the climate history of eastern equatorial Africa from at least ca. 160 ka onwards, i.e., covering the complete last glacial–interglacial cycle and the penultimate glacial maximum. This work confirms the potential of lacustrine GDGTs for elucidating the climate history of tropical regions at Quaternary timescales, provided they are applied to suitably high-quality sediment archives. Additionally, their interpretation should incorporate a broader understanding of the extent to which lake-system evolution limits the extrapolation back in time of proxy-climate relationships established in the modern system.

Thermal stratification characteristics and cooling water shortage risks for pumped storage reservoir–green data centers under extreme climates

Utilizing the thermal stratification of reservoirs to obtain cold water for cooling green data centers (GDCs) is a new mode of energy conservation and emission reduction. However, global warming is expected to alter this phenomenon in deep reservoirs and thus may affect the digitalization process. While the frequency and intensity of extreme climate (EC) events are increasing under a changing climate, the impacts of these highly destructive events on thermal stratification and the related cascading effects on GDC cold-water supplies are still unclear. A two-lateral-dimensional thermohydrodynamic model was established to determine the characteristics of reservoir thermal stratification changes and its potential water environment impacts based on the heat extreme experienced by the Jinshuitan Reservoir, a large, pumped storage power station (PSPS) with a GDC in southeastern China. Fourteen different PSPS inlet/outlet schemes under 2 climate scenarios were designed, and two new indexes, namely, the risk index of cold-water shortage and the index of thermal stratification, were proposed to explore the impact of extreme climates on GDC water extraction. The results showed that compared to the present climate conditions, the reservoir experienced stronger thermal stratification with a 20.6 % average increase in thermal stability, a longer thermal stratification duration with a transitional trend from seasonal to permanent stratification, and a thinner cold-water layer with a 15-m average decrease. Changes in the thermal stratification of reservoirs under EC conditions will benefit some species, such as diatoms (except for early July and the period from mid-August to early October), green algae and cyanobacteria and the migration of warm-water fish, but adversely impact dissolved oxygen, diatoms and cold-water fish. Furthermore, the risk of cold-water shortages under EC conditions was consistently greater than that under average climate (AC) conditions (traditional assessment) when the elevation of pumped storage intake/outlet was less than 145 m. According to the traditional assessment method, the intake/outlet elevation of pumped storage reservoirs resulted in a 60.27 % increase in the risk of cold-water shortages during climate extremes. Furthermore, the demand for green cold-water withdrawal and optimal pumped storage power generation benefits were met when the PSPS intake/outlet elevation was 145 m. Beyond solving this specific case, this study elucidates the importance of linking the thermal stratification and data center of cold-water withdrawal to ECs. These findings provide new insights for increasing climate change resilience.

Aquatic photosynthetic carbon pump driven by periodic temperature variations affects dissolved inorganic carbon and hydrochemical characteristics in a groundwater-fed reservoir

Under the influence of periodic temperature variations, biogeochemical cycling in water bodies is markedly affected by the periodic thermal stratification processes in subtropical reservoirs or lakes. In current studies, there is insufficient research on the influence and mechanism of dissolved inorganic carbon (DIC) distribution in karst carbon-rich groundwater-fed reservoirs under the coupled effects of thermal structure stratification and the biological carbon pump (BCP) effect. To address this issue, the Dalongdong (DLD) reservoir in the subtropical region of southern China was chosen as the site for long-term monitoring and research on relevant physicochemical parameters of water, DIC, and its stable carbon isotope (δ13CDIC), CO2 emission flux, as well as the reservoir's thermal stratification index. The results show that: (1) the DLD reservoir is a typical warm monomictic reservoir, which exhibits regular variations of mixing period-stratification period-mixing period on a yearly scale due to thermal structure changes; (2) DIC was consumed by aquatic photosynthetic organisms in the epilimnion during the stratification period, leading to a decrease in DIC concentration, partial pressure of CO2 (pCO2) and CO2 emission flux, and an increase in stable carbon isotope (δ13CDIC). During the mixing period, the trend was reversed; (3) During the thermal stratification, aquatic photosynthesis and water temperature were the primary factors controlling DIC variations in both the epilimnion and thermocline. Regarding the hypolimnion, calcite dissolution, organic matter decomposition, and water temperature were the dominant controlling factors. These results indicate that although carbon-rich karst groundwater provides a plentiful supply of DIC in the DLD reservoir, its availability is still influenced by variations in the reservoir's thermal structure and the metabolic processes of aquatic photosynthetic organisms. Therefore, to better estimate the regional carbon budget in a reservoir or lake, future studies should especially consider the combined effects of BCP and thermal structure variations on carbon variations.

Live-donor kidney transplant outcome prediction (L-TOP) using artificial intelligence.

Outcome prediction for live-donor kidney transplantation improves clinical and patient decisions and donor selection. However, the concurrently used models are of limited discriminative or calibration power and there is a critical need to improve the selection process. We aimed to assess the value of various artificial intelligence (AI) algorithms to improve the risk stratification index. We evaluated pre-transplant variables among 66914 live-donor kidney transplants (performed between 01/12/2007-01/06/2021) from the United Network of Organ Sharing database, randomized into training (80%) and test (20%) sets. The primary outcome measure was death-censored graft survival. We tested four machine learning models for discrimination (time-dependent concordance index, CTD, and area under the ROC curve) and calibration (integrated Brier score, IBS). We used decision curve analysis to assess the potential clinical utility. Among the models, the deep Cox mixture model showed the best discriminative performance (AUC=0.70, 0.68, and 0.68 at 5, 10, and 13 years post-transplant, respectively). CTD reached 0.70, 0.67, and 0.66 at 5, 10, and 13 years post-transplant. The IBS score was 0.09, indicating good calibration. In comparison, applying the Living Kidney Donor Profile Index (LKDPI) on the same cohort produced a CTD of 0.56 and an AUC of 0.55-0.58 only. Decision curve analysis showed an additional net benefit compared to the LKDPI, 'Treat all' and 'Treat None' approaches. Our AI-based deep Cox mixture model, termed Live-Donor Kidney Transplant Outcome Prediction outperforms existing prediction models, including the LKDPI, with the potential to improve decisions for optimum live donor selection by ranking potential transplant pairs based on graft survival. This model could be adopted to improve the outcomes of paired exchange programs.

Risk Prediction of Post-Endoscopic Submucosal Dissection Coagulation Syndrome

Introduction: Endoscopic submucosal dissection (ESD) has been popular worldwide to treat laterally spreading tumors and large polyps. Post-ESD coagulation syndrome (PECS) is more common than the two major ESD-related complications, perforation, and bleeding. The aim of this study was to assess the prevalence of PECS, identify the risk factors for PECS, and create a risk prediction model for PECS. Methods: Retrospective cross-sectional study analyzed a total of 986 patients who underwent colorectal ESD. Logistic regression models were used to assess risk factors with PECS. Each risk factor was scored, and the 3-step risk stratification index of prediction model was assessed. Results: The prevalence of PECS was 21.4% (95% confidence interval [CI] = 18.9–24.1%). The risk factors of PECS in the multivariate logistic regression were tumor size (+1 cm: odds ratio [OR], 1.29; 95% CI, 1.16–7.09), cecal lesion (OR, 1.96; 95% CI, 1.09–1.53), procedure time (+30 min: OR, 1.19; 95% CI, 1.02–1.39), and ESD with snaring (OR, 0.64; 95% CI, 0.43–0.95). Applying a simplified weighted scoring system based on adjusted OR increments of 1, the risk of PECS was 12.3% (95% CI, 0.3–16.0%) for the low-risk group (score ≤4) and was 36.0% (95% CI = 29.4–43.2%) for the high-risk group (score ≥8). Overall discrimination (C-statistic = 0.629; 95% CI = 0.585–0.672) and calibration (p = 0.993) of the model were moderate to good. Conclusion: PECS occurs frequently, and the prediction model can be helpful for effective treatment and prevention of PECS.

Association of red blood cell distribution width to albumin ratio with prognosis in stroke patients.

Aim: The authors investigated the association of red blood cell distribution width to albumin ratio (RAR) with prognosis and severity in acute ischemic stroke (AIS). Methods: One hundred twenty-seven patients with AIS were prospectively analyzed. The NIH Stroke Scale was used to determine stroke severity. RAR was compared between severe and nonsevere patients. Results: RAR was significantly higher in severe compared with nonsevere patients (p<0.001). According toreceiver operating characteristic analysis, RAR alone predicted mortality better than red blood cell distribution width and albumin (area under the curve: 0.933, 0.911, 0.870, respectively). Additionally, RAR was significantly correlated with NIH Stroke Scale score (p<0.001). Conclusion: High RAR measured at presentation is a feasible index for prognosis and severity stratification in AIS.

CARDS, a Novel Prognostic Index for Risk Stratification and In-Hospital Monitoring.

Background: Sodium fluctuation is independently associated with clinical deterioration. We developed and validated a prognostic index based on sodium fluctuation for risk stratification and in-hospital monitoring. Methods: This study included 33,323 adult patients hospitalized at a tertiary care hospital in 2014. The first 28,279 hospitalizations were analyzed to develop the model and then the validity of the model was tested using data from 5044 subsequent hospitalizations. We predict in-hospital mortality using age, comorbidity, range of sodium fluctuation, and duration of sodium fluctuation, abbreviated as CARDS. Results: In-hospital mortality was similar in the derivation (0.6%) and validation (0.4%) cohorts. In the derivation cohort, four independent risk factors for mortality were identified using logistic regression: age (66-75, 2 points; >75, 3 points); Charlson comorbidity index (>2, 5 points); range of sodium fluctuation (7-10, 4 points; >10, 10 points); and duration of fluctuation (≤3, 3 points). The AUC was 0.907 (95% CI: 0.885-0.928) in the derivation cohort and 0.932 (95% CI: 0.895-0.970) in the validation cohort. In the derivation cohort, in-hospital mortality was 0.106% in the low-risk group (0-7 points), 1.076% in the intermediate-risk group (8-14 points), and 8.463% in the high-risk group (15-21 points). In the validation cohort, in-hospital mortality was 0.049% in the low-risk group, 1.064% in the intermediate-risk group, and 8.403% in the high-risk group. Conclusions: These results suggest that patients at low, intermediate, and high risk for in-hospital mortality may be identified by CARDS mainly based on sodium fluctuation.