Development and Validation of a Score to Assess Transmural Healing and Response in Patients with Crohn's Disease.

BACKGROUND & AIMS: Because transmural healing (TH) could be the best therapeutic target in Crohn's disease (CD), we aimed to build and validate a score to assess TH and transmural response (TR), and to confirm their association with favorable CD outcomes. METHODS: DEVISE-CD project encompassed 2 retrospective cohorts (274 and 224 patients with CD for development and validation phase, retrospectively) and 1 multicenter prospective validation cohort (N = 46 patients). A step-by-step process was used to build the modified Clermont score (C-score). The primary end points were time to bowel damage progression, and steroid-free clinical remission with fecal calprotectin <250 at 1 year for retrospective and prospective validation cohorts, respectively. RESULTS: Edema, ulcer, contrast enhancement, diffusion-weighted hyperintensity, fat wrapping, bowel thickening (>3 mm), and enlarged lymph nodes were associated to higher risk of bowel damage progression (P < .01). Edema, diffusion-weighted hyperintensity, post-gadolinium contrast enhancement, and bowel thickening were highly coexistent (>95%) and collinear (P < .0001). Bowel thickness had the highest sensitivity to change after treatment (standardized mean difference = 0.30 ± 1.0; P = .001). C-score was calculated as 0.2x(bowel thickness-3mm) + 1.5x enlarged lymph nodes + 2x ulcer. TH (C-score <0.5; hazard ratio [HR], 0.28 [0.13-0.63]; P = .002; adjusted HR [aHR], 0.15 [0.04-0.53]; P = .003), TR50 (50% decrease of C-score; HR, 0.30 [0.15-0.63]; P = .001; aHR, 0.36 [0.14-0.88]; P = .025), or TR25 (25% decrease of C-score; HR, 0.37 [0.19-0.71]; P = .003; aHR, 0.46 [0.23-0.94]; P = .034) prevented bowel damage progression in development and validation cohorts, respectively. In the prospective validation cohort, achieving TH (OR, 4.6 [1.3-15.6]; P = .016), TR50 (OR, 6.9 [1.8-26.0]; P = .008), or TR25 (OR, 6.0 [1.6-22.3]; P = .008) after 12 weeks of anti-tumor necrosis factor therapy led to higher rate of corticosteroid-free remission at 1 year. CONCLUSIONS: C-score is a validated, reliable, and easy-to-use tool to assess TH and TR in patients with CD.

Childhood-onset IgA nephropathy: is long-term recovery possible?

BACKGROUND: IgA nephropathy (IgAN) is the most common glomerulonephritis worldwide. While studies have primarily focused on identifying risk factors for disease progression, very few data exist on the likelihood of achieving complete recovery from the disease. METHODS: We conducted a single-center retrospective study on all consecutive patients with biopsy-proven IgAN diagnosed between 1986 and 2018 in our pediatric center. Biopsies were classified according to the MEST-C Oxford classification score. "Complete clinical remission" was defined as the absence of proteinuria, hematuria, and hypertension in patients with normal kidney function who had been off therapy for more than 2 years. RESULTS: Overall, 153 patients with age at onset of 10.6 ± 4 years were enrolled in the study. Of these, 41 achieved "complete clinical remission." The estimated probability of complete clinical remission at 10 years was 43% (95%CI 33-54). However, seven patients relapsed within 10 years. Multivariable analysis showed that higher age at onset (HR 0.89, 95%CI 0.80-0.98, p = 0.017) and segmental glomerulosclerosis lesions (HR 0.28, 95%CI 0.10-0.79, p = 0.017) decreased significantly the chances of achieving complete clinical remission. Immunosuppressive therapy was not significantly associated with clinical outcomes. CONCLUSIONS: Approximately one-third of patients with pediatric-onset IgAN achieve prolonged remission, in particular, very young children at disease onset without sclerotic glomerular lesions. Longer term follow-up is needed to assess if these patients have achieved permanent remission.

Coagulation potential in pediatric patients with immunoglobulin A nephropathy.

BACKGROUND: Immunoglobulin A nephropathy (IgAN) is the most prevalent primary chronic glomerular disease in children. Understanding the changes in coagulability caused by IgAN is important for clarifying pathophysiology and choice of treatment. The coagulation potential in patients with IgAN remains to be investigated, however. We aimed to assess comprehensive coagulation potential in pediatric patients with IgAN and explore its relationship with pathological disease severity. METHODS: Fourteen children with IgAN diagnosed by renal biopsy, who were admitted at Nara Medical University Hospital between 2015 and 2020, were analyzed. Rotational thromboelastometry was used to evaluate coagulation potential. Values of rotational thromboelastometry parameters in patients with IgAN were compared with those in control children. RESULTS: In patients with IgAN (aged median 9.5 year), clotting time plus clot formation time (CT + CFT) was shortened (P = 0.003) and α angle was greater (P < 0.001) than those in controls, indicating a hypercoagulable state. The rate of mesangial hypercellularity of glomeruli correlated with CT + CFT, α, and maximum clot firmness (MCF) (rs = -0.79, 0.56, and 0.37). The rate of cellular/fibrocellular crescent of glomeruli correlated with CT + CFT, α, and MCF (rs = -0.41, 0.60, and 0.50). Patients with mesangial hypercellularity ≥80% of glomeruli showed reduced CT + CFT and increased α angle (P = 0.007 and 0.03). Patients with cellular/fibrocellular crescent ≥10% of glomeruli showed decreased CT + CFT and increased α angle (both P = 0.02). CONCLUSIONS: The hypercoagulable state in pediatric patients with IgAN may be associated with the pathological severity of their disease.

A Novel Score for mHealth Apps to Predict and Prevent Mortality: Further Validation and Adaptation to the US Population Using the US National Health and Nutrition Examination Survey Data Set.

BACKGROUND: The C-Score, which is an individual health score, is based on a predictive model validated in the UK and US populations. It was designed to serve as an individualized point-in-time health assessment tool that could be integrated into clinical counseling or consumer-facing digital health tools to encourage lifestyle modifications that reduce the risk of premature death. OBJECTIVE: Our study aimed to conduct an external validation of the C-Score in the US population and expand the original score to improve its predictive capabilities in the US population. The C-Score is intended for mobile health apps on wearable devices. METHODS: We conducted a literature review to identify relevant variables that were missing in the original C-Score. Subsequently, we used data from the 2005 to 2014 US National Health and Nutrition Examination Survey (NHANES; N=21,015) to test the capacity of the model to predict all-cause mortality. We used NHANES III data from 1988 to 1994 (N=1440) to conduct an external validation of the test. Only participants with complete data were included in this study. Discrimination and calibration tests were conducted to assess the operational characteristics of the adapted C-Score from receiver operating curves and a design-based goodness-of-fit test. RESULTS: Higher C-Scores were associated with reduced odds of all-cause mortality (odds ratio 0.96, P<.001). We found a good fit of the C-Score for all-cause mortality with an area under the curve (AUC) of 0.72. Among participants aged between 40 and 69 years, C-Score models had a good fit for all-cause mortality and an AUC >0.72. A sensitivity analysis using NHANES III data (1988-1994) was performed, yielding similar results. The inclusion of sociodemographic and clinical variables in the basic C-Score increased the AUCs from 0.72 (95% CI 0.71-0.73) to 0.87 (95% CI 0.85-0.88). CONCLUSIONS: Our study shows that this digital biomarker, the C-Score, has good capabilities to predict all-cause mortality in the general US population. An expanded health score can predict 87% of the mortality in the US population. This model can be used as an instrument to assess individual mortality risk and as a counseling tool to motivate behavior changes and lifestyle modifications.

Practical Applicability of the ISARIC-4C Score on Severity and Mortality due to SARS-CoV-2 Infection in Patients with Type 2 Diabetes.

Background and objectives. There is a bidirectional relationship between SARS-CoV-2 infection and diabetes mellitus (DM), as people with DM are more vulnerable, and SARS-CoV-2 infections worsen the prognosis in these patients. The main purpose of the study was to evaluate the application validity of the ISARIC-4C score in patients confirmed with SARS-CoV-2 infection. Materials and Methods. The study included 159 patients previously known to have type 2 DM and confirmed positive for SARS-CoV-2 infection. We analyzed the concordance between the clinical evaluation of the patients and the ISARIC-4C score. Results. The mortality rate in hospitalized patients was 25.15%. The mortality risk was higher for ISARIC-4C values >14 than in the opposite group (63.93% vs. 31.24%; p < 0.001). The area under the curve (AUC) of the mortality score was 0.875 (95% CI: 0.820−0.930; p < 0.001), correctly classifying 77.36% of the cohort. A cut-off value of >14 had a sensitivity of 87.80% (95% CI: 87.66−87.93), specificity 73.72% (95% CI: 73.48−73.96), positive predictive value 53.73% (95% CI: 53.41−54.04), and negative predictive value 94.56% (95% CI: 94.5−94.62). The Cox regression model showed that the length of hospitalization (LH) was significantly influenced by body mass index, lung impairment, and aspartate aminotransferase, increasing the hazards, while lower HbA1c and lower SatO2 significantly decreased the hazards. Conclusions. ISARIC-4C score estimates the likelihood of clinical deterioration and the mortality risk in patients hospitalized with type 2 DM and positive for SARS-CoV-2, being useful in assessing the prognosis from the onset, as well as in developing therapeutic strategies.

The association of microhematuria with mesangial hypercellularity, endocapillary hypercellularity, crescent score and renal outcomes in immunoglobulin A nephropathy.

BACKGROUND: Microhematuria is common in immunoglobulin A nephropathy (IgAN). However, current prognostication is based on proteinuria and mesangial hypercellularity, endocapillary hypercellularity, segmental sclerosis, tubulointerstitial fibrosis and crescent (MEST-C) scores. METHODS: In this retrospective study, we evaluated whether MEST-C score components are associated with the presence of microhematuria at biopsy and whether the degree of microhematuria during follow-up is associated with change in estimated glomerular filtration rate (eGFR), after adjusting for clinical and histological parameters. We identified 125 patients with biopsy-proven IgAN and MEST-C scoring who were not on immunosuppressive therapy at biopsy. Microhematuria was defined as ≥3 red blood cells (RBCs)/high-power field (hpf). RESULTS: Of the 125 patients, 97 had microhematuria at baseline and were more likely to have M1, E1 and C ≥ 1 lesions (P < 0.05 for all) compared with patients without microhematuria. Of the 125 patients, 72 had follow-up data available. An increase in the degree of microhematuria was significantly associated with an eGFR decline of -0.81 mL/min/1.73 m2 [95% confidence interval (CI) -1.44 to -0.19, P = 0.01], after adjusting for follow-up time, proteinuria and T score. Severe microhematuria (≥21 RBCs/hpf) was associated with an even larger decline in eGFR (-3.99 mL/min/1.73 m2; 95% CI -6.9411 to -1.0552, P = 0.008), after similar adjustments. CONCLUSION: Degree of microhematuria during follow-up is an independent predictor of eGFR decline after adjusting for clinical and histological parameters. Therefore, monitoring the degree of microhematuria as well as proteinuria is important when evaluating patients with IgAN. Additional studies using improvement in microhematuria as a primary surrogate outcome are needed.

Treatment of IgA nephropathy in children: a land without KDIGO guidance.

IgA nephropathy (IgAN) in children is no longer considered a rare and benign disease but a nephritis with different presentations and various outcomes. The decision to initiate a treatment and the therapeutic choice depend on the individual risk of progression. The Kidney Disease: Improving Global Outcomes (KDIGO) clinical guidelines in 2012 considered that the risk factors for progression of IgAN were similar in both children and adults and suggested in some conditions to follow the adult schedules. In 2017 a KDIGO Controversies Conference on management and treatment of glomerular diseases decided not to include an update in children with IgAN since the level of evidence of treatments in children was too scarce. Children can follow the indications for adults as far as the disease is similar in the various ages. This review is aimed at discussing why the KDIGO guidelines are poorly suitable to treat children with IgAN, and there is a need to develop new prediction models for progression of IgAN in children to guide selection of the cases to be treated. The identification of different risk levels in children with IgAN may personalize the choice of available drugs and support the use of new targeted therapies.

Segregation structure in Odonata assemblages follows the latitudinal gradient.

Latitude is known to deeply affect life with effects generalizable into ecological rules; the increasing species diversity toward tropics is the most paradigmatic. Several hypotheses tested patterns of biotic interactions' intensity along latitude. Negative interactions (i.e. competition and predation) are expected to be among the processes that produce checkerboard distribution of species. However, no relationship between checkerboardness and latitude has been uncovered. We tested Odonata assemblages worldwide for segregation patterns using a faunistic dataset (395 species arranged in 386 natural communities) spanning a wide latitudinal range (87°). We used co-occurrence analyses (C-score index and Standardized Effect Size) as an estimate of checkerboardness then correlated the occurrence of segregation to latitude. Odonata followed the Latitudinal Diversity Gradient at the regional scale (i.e. country scale) within our analyzed assemblages spanning, whereas local richness (i.e. community scale) did not follow the same pattern. Odonata assemblages structured with segregation are more common going from high to low latitudes, and local species richness have no effect on the pattern. We summarized hypotheses on how biotic interactions or ecological and historical processes can influence the spatial patterns in the checkerboards of assemblages and presented promising ways to help to gain a better mechanistic understanding of the drivers of the Latitudinal Diversity Gradient.

IgA nephropathy: A brief review.

IgA nephropathy is a lifelong disease that is the most common primary glomerulopathy worldwide. It has a complicated and incompletely understood pathogenesis that is theorized as a four 'hit' process involving an improperly produced IgA. While it has a variety of histologic appearances, it is diagnosed by the presence of bright IgA deposits within the mesangium as seen on immunofluorescence and mesangial hypercellularity by light microscopy. This brief review explains the varied histologic features that are important in the diagnosis of IgA nephropathy and the calculation of the MEST-C score that was first introduced by the 2009 Oxford Classification working group.

Microangiopathic Lesions in IgA Nephropathy: A Cohort Study.

RATIONALE & OBJECTIVE: Renal arteriolar microangiopathic lesions may occur in immunoglobulin A nephropathy (IgAN), but their role in disease progression remains unclear. We sought to understand the prevalence and character of microangiopathic lesions in IgAN and their role in disease progression. STUDY DESIGN: A retrospective cohort study. SETTING & PARTICIPANTS: In this study, we enrolled a Chinese cohort with 944 adult patients with IgAN who had been followed up for at least 1 year. PREDICTORS: Renal arteriolar microangiopathic lesions. OUTCOMES: Composite kidney end point event defined as a>50% reduction in estimated glomerular filtration rate, end-stage kidney disease, or death. ANALYTICAL APPROACH: All kidney biopsies were independently reviewed by 2 investigators. Renal arteriolar microangiopathic lesions were detected using light microscopy. Multivariable Cox regression analysis was used to test the association between microangiopathic lesions and the outcomes. RESULTS: Overall, 194 (20.6%) patients had renal arteriolar microangiopathic lesions. Patients with microangiopathic lesions presented with higher blood pressures, more severe proteinuria, and lower estimated glomerular filtration rates (all P<0.001) than patients without microangiopathic lesions. After a median follow-up of 4.2 years, 75 (38.7%) patients with microangiopathic lesions and 83 (11.1%) patients without these lesions reached the composite kidney end point (P<0.001). In a multivariable Cox regression model adjusting for clinical and pathologic variables available at the time of biopsy, the presence of microangiopathic lesions was an independent risk factor for kidney failure (HR, 1.95; 95% CI, 1.34-2.83; P<0.001). Renal vascular sclerosis (arterial intimal fibrosis or arteriolar hyalinosis) was not a risk factor for kidney disease progression (P = 0.5). LIMITATIONS: A single Chinese center's experience, retrospective study, most patients were not tested for hemolytic markers (for example, haptoglobin level, lactate dehydrogenase level, and schistocytes). CONCLUSIONS: Renal arteriolar microangiopathic lesions are frequent in IgAN and their presence is independently associated with progression to kidney failure. If confirmed in other patient cohorts, such lesions could be considered for inclusion in formal classification schemes of IgAN.

Top-Down Characterization of Heavily Modified Histones Using 193 nm Ultraviolet Photodissociation Mass Spectrometry.

The characterization of protein post-translational modifications (PTMs) remains a significant challenge for traditional bottom-up proteomics methods owing to the lability of PTMs and the difficulty of mapping combinatorial patterns of PTMs based on analysis of small peptides. These shortcomings have accelerated interest in top-down MS/MS methods that focus on analysis of intact proteins. Simultaneous mapping of all PTMs requires extensive sequence coverage to confidently localize modifications. 193 nm ultraviolet photodissociation (UVPD) has been shown to generate unparalleled sequence coverage for intact proteins compared to traditional MS/MS methods. This study focuses on identification and localization of PTMs of histones by UVPD, higher-energy collisional dissociation (HCD), and the hybrid method electron-transfer/higher-energy collision dissociation (EThcD) via a high throughput liquid chromatography-mass spectrometry strategy. In total, over 500 proteoforms were characterized among these three activation methods with 46% of the identifications found in common by two or more activation methods. EThcD and UVPD afforded more extensive characterization of proteoforms than HCD with average gains in sequence coverage of 15% and C-scores that doubled on average.

Bi-dimensional null model analysis of presence-absence binary matrices.

Comparing the structure of presence/absence (i.e., binary) matrices with those of randomized counterparts is a common practice in ecology. However, differences in the randomization procedures (null models) can affect the results of the comparisons, leading matrix structural patterns to appear either "random" or not. Subjectivity in the choice of one particular null model over another makes it often advisable to compare the results obtained using several different approaches. Yet, available algorithms to randomize binary matrices differ substantially in respect to the constraints they impose on the discrepancy between observed and randomized row and column marginal totals, which complicates the interpretation of contrasting patterns. This calls for new strategies both to explore intermediate scenarios of restrictiveness in-between extreme constraint assumptions, and to properly synthesize the resulting information. Here we introduce a new modeling framework based on a flexible matrix randomization algorithm (named the "Tuning Peg" algorithm) that addresses both issues. The algorithm consists of a modified swap procedure in which the discrepancy between the row and column marginal totals of the target matrix and those of its randomized counterpart can be "tuned" in a continuous way by two parameters (controlling, respectively, row and column discrepancy). We show how combining the Tuning Peg with a wise random walk procedure makes it possible to explore the complete null space embraced by existing algorithms. This exploration allows researchers to visualize matrix structural patterns in an innovative bi-dimensional landscape of significance/effect size. We demonstrate the rational and potential of our approach with a set of simulated and real matrices, showing how the simultaneous investigation of a comprehensive and continuous portion of the null space can be extremely informative, and possibly key to resolving longstanding debates in the analysis of ecological matrices.

Validation of the Mayo Clinic Staging System in Determining Prognoses of Patients With Perihilar Cholangiocarcinoma.

BACKGROUND & AIMS: Most systems for staging perihilar cholangiocarcinoma (PHC) have been developed for the minority of patients with resectable disease. The recently developed Mayo Clinic system for staging PHC requires only clinical and radiologic variables, but has not yet been validated. We performed a retrospective study to validate the Mayo Clinic staging system. METHODS: We identified consecutive patients with suspected PHC who were evaluated and treated at 2 tertiary centers in The Netherlands, from January 2002 through December 2014. Baseline characteristics (performance status, carbohydrate antigen 19-9 level) used in the staging system were collected from medical records and imaging parameters (tumor size, suspected vascular involvement, and metastatic disease) were reassessed by 2 experienced abdominal radiologists. Overall survival was analyzed using the Kaplan-Meier method and comparison of staging groups was performed using the log-rank test and Cox proportional hazard regression analysis. Discriminative performance was quantified by the concordance index and compared with the radiologic TNM staging of the American Joint Committee on Cancer (7th ed). RESULTS: PHCs from 600 patients were staged according to the Mayo Clinic model (23 stage I, 80 stage II, 357 stage III, and 140 stage IV). The median overall survival time was 11.6 months. The median overall survival times for patients with stages I, II, III, and IV were 33.2 months, 19.7 months, 12.1 months, and 6.0 months, respectively; with hazard ratios of 1.0 (reference), 2.02 (95% confidence interval [CI], 1.14-3.58), 2.71 (95% CI, 1.59-4.64), and 4.00 (95% CI, 2.30-6.95), respectively (P < .001). The concordance index score was 0.59 for the entire cohort (95% CI, 0.56-0.61). The Mayo Clinic model performed slightly better than the radiologic American Joint Committee on Cancer TNM system. CONCLUSIONS: In a retrospective study of 600 patients with PHC, we validated the Mayo Clinic system for staging PHC. This 4-tier staging system may aid clinicians in making treatment decisions, such as referral for surgery, and predicting survival times.

A novel prognostic risk-scoring system based on m5C methylation regulator-mediated patterns for glioma patients.

N5-methylcytosine (m5C) methylation modification plays a crucial role in the epigenetic mechanisms underlying tumorigenesis, aggressiveness, and malignancy in diffuse glioma. Our study aimed to develop a novel prognostic risk-scoring system to assess the impact of m5C modification in glioma patients. Initially, we identified two distinct m5C clusters based on the expression level of m5C regulators in The Cancer Genome Atlas glioblastoma (TCGA-GBM) dataset. Differentially expressed genes (DEGs) between the two m5C cluster groups were determined. Utilizing these m5C regulation-related DEGs, we classified glioma patients into three gene cluster groups: A, B, and C. Subsequently, an m5C scoring system was developed through a univariate Cox regression model, quantifying the m5C modification patterns utilizing six DEGs associated with disease prognosis. The resulting scoring system allowed us to categorize patients into high- or low-risk groups based on their m5C scores. In test (TCGA-GBM) and validation (Chinese Glioma Genome Atlas [CGGA]-1018 and CGGA-301) datasets, glioma patients with a higher m5C score consistently exhibited shorter survival durations, fewer isocitrate dehydrogenase (IDH) mutations, less 1p/19q codeletion and higher World Health Organization (WHO) grades. Additionally, distinct immune cell infiltration characteristics were observed among different m5C cluster groups and risk groups. Our study developed a novel prognostic scoring system based on m5C modification patterns for glioma patients, complementing existing molecular classifications and providing valuable insights into prognosis for glioma patients.

Is the 4C Score Still a Valid Item to Predict In-Hospital Mortality in People with SARS-CoV-2 Infections in the Omicron Variant Era?

Since the start of the SARS-CoV-2 pandemic, several scores have been proposed to identify infected individuals at a higher risk of progression and death. The most famous is the 4C score. However, it was developed in early 2020. Our study aimed to evaluate the accuracy of the 4C score during the wave in which the Omicron variant was prevalent. An observational study was conducted at an Italian University Hospital between 1 January and 31 July 2022. A receiver operating characteristic (ROC) curve analysis was performed to evaluate the ability of the 4C score to predict mortality. Overall, 1186 people were recruited, of which 160 (13.5%) died. According to the 4C score, 177 (11.6%) were classified as having a low risk of mortality, 302 (25.5%) were intermediate, 596 (50.3%) were high, and 151 (12.7%) were very high. The ROC curve of the 4C score showed an AUC (95% CI) value of 0.78 (0.74−0.82). At the criterion value of > 10, the sensitivity was 76.2% and the specificity was 62.67%. Similar to previous studies, the 4C mortality score performed well in our sample, and it is still a useful tool for clinicians to identify patients with a high risk of progression. However, clinicians must be aware that the mortality rate reported in the original studies was higher than that observed in our study.

Performance of CURB-65 and ISARIC 4C mortality scores for hospitalized patients with confirmed COVID-19 infection in Saudi Arabia.

Background: The COVID-19 pandemic continues with new waves that could persist with the arrival of new SARS-CoV-2 variants. Therefore, the availability of validated and effective triage tools is the cornerstone for proper clinical management. Thus, this study aimed to assess the validity of the ISARIC-4C score as a triage tool for hospitalized COVID-19 patients in Saudi Arabia and to compare its performance with the CURB-65 score. Material and methods: This retrospective observational cohort study was conducted between March 2020 and May 2021 at KFHU, Saudi Arabia, using 542 confirmed COVID-19 patient data on the variables relevant to the application of the ISARIC-4C mortality score and the CURB-65 score. Chi-square and t-tests were employed to study the significance of the CURB-65 score and the ISARIC-4C score variables considering the ICU requirements and the mortality of COVID-19 hospitalized patients. In addition, logistic regression was used to predict the variables related to COVID-19 mortality. In addition, the diagnostic accuracy of both scores was validated by calculating sensitivities, specificities, positive predictive value, negative predictive value, and Youden's J indices (YJI). Results: ROC analysis showed an AUC value of 0.834 [95% CI; 0.800-0.865]) for the CURB-65 score and 0.809 [95% CI; 0.773-0.841]) for the ISARIC-4C score. The sensitivity for CURB-65 and ISARIC-4C is 75% and 85.71%, respectively, while the specificity was 82.31% and 62.66%, respectively. The difference between AUCs was 0.025 (95% [CI; -0.0203-0.0704], p = 0.2795). Conclusion: Study results support external validation of the ISARIC-4C score in predicting the mortality risk of hospitalized COVID-19 patients in Saudi Arabia. In addition, the CURB-65 and ISARIC-4C scores showed comparable performance with good consistent discrimination and are suitable for clinical utility as triage tools for hospitalized COVID-19 patients.

A Comparison of ICU Mortality Scoring Systems Applied to COVID-19.

Background Over the past three years, COVID-19 has been a major source of mortality in intensive care units around the world. Many scoring systems have been developed to estimate mortality in critically ill patients. Our intent with this study was to compare the efficacy of these systems when applied to COVID-19. Methods The was a multicenter, retrospective cohort study of critically ill patients with COVID-19 admitted to 16 hospitals in Texas from February 2020 to March 2022. The Simplified Acute Physiology Score (SAPS) II, Acute Physiology and Chronic Health Evaluation (APACHE) II, Sequential Organ Failure Assessment (SOFA) score, and 4C Mortality scores were calculated on the initial day of ICU admission. Primary endpoints were all-cause mortality, ICU length of stay, and hospital length of stay. Results Initially, 62,881 patient encounters were assessed, and the cohort of 292 was selected based on the inclusion of the requisite values for each of the scoring systems. The median age was 56 +/- 14.93 years and 61% of patients were male. Mortality was defined as patients who expired or were discharged to hospice and was 78%. The different scoring systems were compared using logistic regression, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC) analysis to compare the accuracy of prediction of the mortality and length of stay. The multivariate analysis showed that SOFA, APACHE II, SAPS II, and 4C scores were all significant predictors of mortality. The SOFA score had the highest AUC, though the confidence intervals for all of the models overlap therefore one model could not be considered superior to any of the others. Linear regression was performed to evaluate the models' ability to predict ICU and hospital length of stay, and none of the tested systems were found to be significant predictors of length of stay. Conclusion The SOFA, APACHE II, ISARIC 4-C, and SAPS II scores all accurately predicted mortality in critically ill patients with COVID-19. The SOFA score trended to perform the best.

Niche overlap and species co-occurrence patterns in carabid communities of the northern Chinese steppes.

Understanding how species sort themselves into communities is essential to explain the mechanisms that maintain biodiversity. Important insights into potential mechanisms of coexistence may be obtained from observation of non-random patterns in community assembly. The spatial niche overlap (Pianka index) and co-occurrence (c-score) patterns in carabid species in three types of steppes (desert steppe, typical steppe, and meadow steppe) in China was investigated. Non randomness was tested using null models. Niche overlap values were significantly higher than expected by chance in the desert steppe, where vegetation cover is less abundant and less uniformly distributed, which possibly forces species to concentrate in certain places. In the typical and meadow steppes, results were influenced by the scale of the analysis. At a broad scale, niche separation was found as a result of species segregation among different sectors (habitats) within these steppes, but when the analysis was conducted at a finer scale, species appeared to be no more segregated than expected by chance. The high co-occurrence averages found in the meadow and typical steppes indicate that the distributions of the species found in a site may be negatively affected by the presence of other species, which suggests that some species tend to exclude (or reduce the abundance of) others. The very low c-score average observed in the desert steppe suggests that competition is not involved there. Thus, in more homogeneous landscapes (such as the typical and meadow steppes), competition might play some role in community structure, whereas spatial variation in the abundances of species is more driven by the uneven spatial distribution of vegetation in the landscape where productivity is lower and less uniformly distributed.

Development and Validation of Risk Scores for All-Cause Mortality for a Smartphone-Based "General Health Score" App: Prospective Cohort Study Using the UK Biobank.

BACKGROUND: Given the established links between an individual's behaviors and lifestyle factors and potentially adverse health outcomes, univariate or simple multivariate health metrics and scores have been developed to quantify general health at a given point in time and estimate risk of negative future outcomes. However, these health metrics may be challenging for widespread use and are unlikely to be successful at capturing the broader determinants of health in the general population. Hence, there is a need for a multidimensional yet widely employable and accessible way to obtain a comprehensive health metric. OBJECTIVE: The objective of the study was to develop and validate a novel, easily interpretable, points-based health score ("C-Score") derived from metrics measurable using smartphone components and iterations thereof that utilize statistical modeling and machine learning (ML) approaches. METHODS: A literature review was conducted to identify relevant predictor variables for inclusion in the first iteration of a points-based model. This was followed by a prospective cohort study in a UK Biobank population for the purposes of validating the C-Score and developing and comparatively validating variations of the score using statistical and ML models to assess the balance between expediency and ease of interpretability and model complexity. Primary and secondary outcome measures were discrimination of a points-based score for all-cause mortality within 10 years (Harrell c-statistic) and discrimination and calibration of Cox proportional hazards models and ML models that incorporate C-Score values (or raw data inputs) and other predictors to predict the risk of all-cause mortality within 10 years. RESULTS: The study cohort comprised 420,560 individuals. During a cohort follow-up of 4,526,452 person-years, there were 16,188 deaths from any cause (3.85%). The points-based model had good discrimination (c-statistic=0.66). There was a 31% relative reduction in risk of all-cause mortality per decile of increasing C-Score (hazard ratio of 0.69, 95% CI 0.663-0.675). A Cox model integrating age and C-Score had improved discrimination (8 percentage points; c-statistic=0.74) and good calibration. ML approaches did not offer improved discrimination over statistical modeling. CONCLUSIONS: The novel health metric ("C-Score") has good predictive capabilities for all-cause mortality within 10 years. Embedding the C-Score within a smartphone app may represent a useful tool for democratized, individualized health risk prediction. A simple Cox model using C-Score and age balances parsimony and accuracy of risk predictions and could be used to produce absolute risk estimations for app users.

Using MEST-C Scores and the International Study of Kidney Disease in Children Classification to Predict Outcomes of Henoch-Schönlein Purpura Nephritis in Children.

Introduction: Henoch-Schönlein purpura nephritis (HSPN) and IgA nephropathy (IgAN) bear similarities in some aspects. The histological classification of HSPN was built on the International Study of Kidney Disease in Children (ISKDC) criteria, while IgAN was established on the 2016 Oxford classification (MEST-C scores). The purpose of this paper was to discuss the predictive value of the ISKDC classification and MEST-C scores in children with HSPN. Methods: We performed a retrospective study of 877 children with HSPN in a single center between 2001 and 2019. The primary outcome was defined as chronic kidney disease-estimated glomerular filtration rate (eGFR) <90 ml/min/1.73 m2. Results: During the follow-up period of 23.3 (10.9-47.9) months, 51 (5.8%) patients reached the primary outcome. As revealed in a Kaplan-Meier plot, segmental glomerulosclerosis (S) (P < 0.001) and tubular atrophy/interstitial fibrosis (T) (P < 0.001) significantly predict poor renal outcome. Other Oxford lesions and the ISKDC classification, however, did not show a significant difference in a worse outcome. In a multivariate Cox model adjusted for pathological and clinical factors, eGFR [hazard ratio (HR) = 2.831, 95% confidence interval (95% CI) = 1.359-5.896], S lesion (HR = 3.936, 95% CI = 2.078-7.457), and T lesion (HR = 4.002, 95% CI = 1.733-9.242) were independent risk factors for the renal outcome. Conclusion: This series constitutes the largest series reported so far in the literature of such patients. According to our findings, S and T of the Oxford classification, which are ignored by the ISKDC classification, could be applied to predict the renal prognosis of children with HSPN.