Difference-Deformable Convolution with Pseudo Scale Instance Map for Cell Localization.

Cell localization still faces two unresolved challenges: 1) the dramatic variations in cell morphology, coupled with the heterogeneous intensity distribution of lightly stained cells; 2) existing cell location maps lack scale information, resulting in insufficient supervision for point maps and inaccurate supervision for density maps. 1) To address the first challenges, we introduce a novel gradient-aware and shape-adaptive Difference-Deformable Convolution (DDConv), which enhances the model's robustness to color by leveraging gradient information while adaptively adjusting the shape of the convolutional kernel to tackle the substantial variability in cell morphology. 2) To overcome the issue of unreasonable location maps, we propose the Pseudo-Scale Instance (PSI) map, which can adaptively provide the corresponding scale information for each cell to realize accurate supervision. We analyze and evaluate DDConv and the PSI map in three challenging cell localization tasks. In comparison to existing methods, our proposed approach significantly enhances localization performance, setting a new benchmark for the cell localization task. Our code is available at https://github.com/ChyaZhang/DDConv-PSI.

Prognostic value of the prognostic nutritional index for patients with acute myocardial infarction undergoing percutaneous coronary intervention with variable glucose metabolism statuses: a retrospective cohort study.

BACKGROUND: The prognostic nutritional index (PNI) and different glucose metabolisms have been separately reported to be correlated with long-term prognosis in patients with acute myocardial infarction (AMI) undergoing percutaneous coronary intervention (PCI). However, PNI application in patients with an impaired glucose metabolism has not been well validated, especially in pre-diabetic patients. This study evaluated whether PNI influences a long-term risk of mortality along different glucose metabolism statuses. METHODS: A total of 17,697 patients with AMI and a history of PCI were enrolled in this retrospective observational cohort study from January 2007 to December 2020. Three subgroups with different glucose metabolism statuses, including normal glucose regulation (NGR), pre-diabetes mellitus (pre-DM), and diabetes mellitus (DM), were divided into three groups according to the tertiles of PNI, respectively. RESULTS: All-cause mortality occurred in 2613 (14.8%) patients within a median of 4.1 years of follow-up. Upon analyzing the Kaplan-Meier plots for the NGR, pre-DM, and DM groups, the incidence of all-cause or cardiovascular mortality in the low PNI (PNI-L, ≤ 42.7) subgroup was significantly higher than that in the median PNI (PNI-M, > 42.7 and ≤ 48.2) and high PNI (PNI-H, > 48.2) subgroups (all, P < 0.001). After adjusting for confounding factors, the hazard ratio (HR) for all-cause mortality in the PNI-L group significantly increased compared to that in the PNI-H subgroups of the NGR group (HR, 1.35; 95% CI 1.14-1.66; P < 0.001), pre-DM group (HR, 1.29; 95% CI 1.02-1.62; P < 0.001), and DM group (HR, 1.36; 95% CI 1.13-1.63; P < 0.001). Given that there was evidence of interactions between PNI and different glucose statuses (P for interaction < 0.001), patients were divided into nine subgroups, and we found that DM patients with PNI-L statuses had the highest risk of all-cause mortality compared to NGR patients with PNI-H statuses (HR, 1.69; 95% CI 1.42-2.01; P < 0.001). CONCLUSION: Lower PNI is a significant and independent risk factor for all-cause mortality in AMI patients undergoing PCI with different glucose metabolism statuses, and this risk further increases with DM compared to NGR or pre-DM statuses.

Predicting neoadjuvant chemotherapy benefit using deep learning from stromal histology in breast cancer.

Neoadjuvant chemotherapy (NAC) is a standard treatment option for locally advanced breast cancer. However, not all patients benefit from NAC; some even obtain worse outcomes after therapy. Hence, predictors of treatment benefit are crucial for guiding clinical decision-making. Here, we investigated the predictive potential of breast cancer stromal histology via a deep learning (DL)-based approach and proposed the tumor-associated stroma score (TS-score) for predicting pathological complete response (pCR) to NAC with a multicenter dataset. The TS-score was demonstrated to be an independent predictor of pCR, and it not only outperformed the baseline variables and stromal tumor-infiltrating lymphocytes (sTILs) but also significantly improved the prediction performance of the baseline variable-based model. Furthermore, we discovered that unlike lymphocytes, collagen and fibroblasts in the stroma were likely associated with a poor response to NAC. The TS-score has the potential to better stratify breast cancer patients in NAC settings.

Comparison Between Two Definitions of Contrast-Associated Acute Kidney Injury in Patients With Congestive Heart Failure.

Background: Different definitions of contrast-associated acute kidney injury (CA-AKI) have different predictive effects on prognosis. However, few studies explored the relationship between these definitions and long-term prognosis in patients with congestive heart failure (CHF). Thus, we aimed to evaluate this association and compared the population attributable risks (PAR) of different CA-AKI definitions. Methods: This study enrolled 2,207 consecutive patients with CHF undergoing coronary angiography (CAG) in Guangdong Provincial People's Hospital. Two different definitions of CA-AKI were used: CA-AKIA was defined as an increase ≥.5 mg/dl or > 25% in serum creatinine (SCr) from baseline within 72 h after CAG, and CA-AKIB was defined as an increase of ≥.3 mg/dl or > 50% in SCr from baseline within 48 h after CAG. Kaplan-Meier methods and Cox regression were applied to evaluate the association between CA-AKI with long-term mortality. Population attributable risk (PAR) of different definitions for long-term prognosis was also calculated. Results: During the 3.8-year median follow-up (interquartile range 2.1-6), the overall long-term mortality was 24.9%, and the long-term mortality in patients with the definitions of CA-AKIA and CA-AKIB were 30.4% and 34.3%, respectively. We found that CA-AKIA (HR: 1.44, 95% CI 1.19-1.74) and CA-AKIB (HR: 1.48, 95% CI 1.21-1.80) were associated with long-term mortality. The PAR was higher for CA-AKIA (9.6% vs. 8%). Conclusions: Our findings suggested that CA-AKI was associated with long-term mortality in patients with CHF irrespective of its definitions. The CA-AKIA was a much better definition of CA-AKI in patients with CHF due to its higher PAR. For these patients, cardiologists should pay more attention to the presence of CA-AKI, especially CA-AKIA.

Few-Shot Object Detection Using Multimodal Sensor Systems of Unmanned Surface Vehicles.

The object detection algorithm is a key component for the autonomous operation of unmanned surface vehicles (USVs). However, owing to complex marine conditions, it is difficult to obtain large-scale, fully labeled surface object datasets. Shipborne sensors are often susceptible to external interference and have unsatisfying performance, compromising the results of traditional object detection tasks. In this paper, a few-shot surface object detection method is proposed based on multimodal sensor systems for USVs. The multi-modal sensors were used for three-dimensional object detection, and the ability of USVs to detect moving objects was enhanced, realizing metric learning-based few-shot object detection for USVs. Compared with conventional methods, the proposed method enhanced the classification results of few-shot tasks. The proposed approach achieves relatively better performance in three sampled sets of well-known datasets, i.e., 2%, 10%, 5% on average precision (AP) and 28%, 24%, 24% on average orientation similarity (AOS). Therefore, this study can be potentially used for various applications where the number of labeled data is not enough to acquire a compromising result.

Paradoxical Association Between Baseline Apolipoprotein B and Prognosis in Coronary Artery Disease: A 36,460 Chinese Cohort Study.

BACKGROUND: Apolipoprotein B (ApoB) and low-density lipoprotein cholesterol (LDL-C) were identified targets for blood lipid management among coronary artery disease (CAD) patients. However, previous studies reported an inverse correlation between baseline LDL-C concentration and clinical outcomes. This study aims to explore the definite association between baseline ApoB and long-term prognosis. METHODS: A total of 36,460 CAD patients admitted to Guangdong Provincial People's Hospital were enrolled and categorized into two groups: high ApoB (≥65 mg/dL) group and low ApoB (<65 mg/dL) group. The association between baseline ApoB and long-term all-cause mortality was evaluated by the Kaplan-Meier method, Cox regression analyses and restricted cubic splines. RESULTS: The overall mortality was 12.49% (n = 4,554) over a median follow-up period of 5.01 years. Patients with low baseline ApoB levels were paradoxically more likely to get a worse prognosis. There was no obvious difference in risk of long-term all-cause mortality when only adjusted for age, gender, and comorbidity (aHR: 1.07, 95% CI: 0.99-1.16). When CONUT and total bilirubin were adjusted, the risk of long-term all-cause mortality would reduce in the low-ApoB (<65 mg/dL) group (aHR: 0.86, 95% CI: 0.78-0.96). In the fully covariable-adjusted model, patients in the ApoB <65 mg/d group had a 10.00% lower risk of long-term all-cause mortality comparing to patients with ApoB ≥65 mg/dL (aHR: 0.90; 95% CI:0.81-0.99). CONCLUSION: This study found a paradoxical association between baseline ApoB and long-term all-cause mortality. Malnutrition and bilirubin mainly mediate the ApoB paradox. Increased ApoB concentration remained linearly associated with an increased risk of long-term all-cause mortality.

Non-HDL cholesterol paradox and effect of underlying malnutrition in patients with coronary artery disease: A 41,182 cohort study.

BACKGROUND & AIMS: Non-high-density lipoprotein cholesterol (non-HDL-C) and low-density lipoprotein cholesterol (LDL-C) were established as the target for blood lipid management among patients with coronary artery disease (CAD). Previous study reported a negative relation between baseline LDL-C levels and long-term prognosis. However, the association between baseline non-HDL-C concentration and clinical outcomes is unknown. METHODS: A total of 41,182 CAD patients admitted to Guangdong Provincial People's Hospital in China were included in this study from January 2007 to December 2018 and divided into two groups (non-HDL-C < 2.2 mmol/L, n = 3236; non-HDL-C ≥ 2.2 mmol/L, n = 37,946). The Kaplan-Meier method, Cox regression analyses and restricted cubic splines were used to assess the association between non-HDL-C levels and long-term all-cause mortality. RESULTS: The overall mortality was 12.74% (n = 5247) over a median follow-up period of 5.20 years. Kaplan-Meier analysis showed that low non-HDL-C levels were paradoxically associated with a worse prognosis. After adjustment for baseline confounders (e.g., age, sex and comorbidities, etc.), multivariate Cox regression analysis revealed that low non-HDL-C levels (<2.2 mmol/L) were not significantly associated with all-cause mortality (adjusted HR, 1.03; 95% CI, 0.93-1.14). After adjustment for nutritional status, the risk of all-cause mortality in patients with low non-HDL-C levels decreased (adjusted HR, 0.86; 95% CI, 0.78-0.95). In the final multivariate Cox model adjusting for full covariates, low non-HDL-C level was related to better prognosis (adjusted HR, 0.88; 95% CI, 0.80-0.98). CONCLUSION: This study found a paradoxical association between baseline non-HDL-C concentration and long-term all-cause mortality. Malnutrition mainly mediates to the non-HDL-C paradox. Elevated non-HDL-C concentration is still a risk factor of long-term all-cause mortality after considering nutritional status.

Mild Malnutrition Contributes the Greatest to the Poor Prognosis in Coronary Artery Disease With Well-Controlled Low-Density Lipoprotein Cholesterol Levels: A 4,863 Chinese Cohort Study.

Background: Previous studies reported that patients with coronary artery disease (CAD) and well-controlled baseline LDL-C (<1.8 mmol/L) still had higher long-term all-cause mortality. However, no study has been conducted to explore the independent risk factors for long-term mortality. In addition, there also was no study evaluating the population attributable risk (PAR) of independent risk factors in combination with their prevalence and relative risk. Therefore, we aimed to identify the independent risk factors and estimate their PAR in patients with CAD and well-controlled baseline LDL-C (<1.8 mmol/L). Methods: We analyzed 4,863 consecutive CAD patients with well-controlled baseline LDL-C admitted to Guangdong Provincial People's Hospital in China from January 2007 to December 2018. Independent risk factors for long-term all-cause death were evaluated through stepwise approach and multivariable Cox regression analysis. PAR of independent risk factors was calculated with their hazard ratio and prevalence among our cohort. Results: The overall mortality was 16.00% (n = 778) over a median follow-up period of 5.93 years. Independent risk factors for all-cause death included malnutrition, age ≥75 years, congestive heart failure (CHF), chronic kidney disease (CKD) and atrial fibrillation. Among these risk factors of interest, the hazard ratio (HR) of severe malnutrition was the highest (HR 2.82, 95% CI: 1.86-4.26), and the PAR of mild malnutrition was the highest (19.49%, 95% CI: 0.65-36.01%). Conclusion: Malnutrition, age ≥75 years, CHF, CKD and atrial fibrillation were independent predictors for long-term all-cause mortality in CAD patients with well-controlled LDL-C levels. Considering prevalence of these risk factors, more attention should be paid to the occurrence of mild malnutrition for these patients. Clinical Trial Registration: ClinicalTrials.gov, identifier: NCT04407936.

Hypertension as a Risk Factor for Contrast-Associated Acute Kidney Injury: A Meta-Analysis Including 2,830,338 Patients.

OBJECTIVE: Previous studies have shown that the relationship between hypertension (HT) and contrast-associated acute kidney injury (CA-AKI) is not clear. We apply a systematic review and meta-analysis to assess the association between HT and CA-AKI. METHODS: We searched for articles on the study of risk factors for CA-AKI in the Embase, Medline, and Cochrane Database of Systematic Reviews (by March 25, 2021). Two authors independently performed quality assessment and extracted data such as the studies' clinical setting, the definition of CA-AKI, and the number of patients. The CA-AKI was defined as a serum creatinine (SCr) increase ≥25% or ≥0.5 mg/dL from baseline within 72 h. We used fixed or random models to pool adjusted OR (aOR) by STATA. RESULTS: A total of 45 studies (2,830,338 patients) were identified, and the average incidence of CA-AKI was 6.48%. There was an increased risk of CA-AKI associated with HT (aOR: 1.378, 95% CI: 1.211-1.567, I2 = 67.9%). In CA-AKI with a SCr increase ≥50% or ≥0.3 mg/dL from baseline within 72 h, an increased risk of CA-AKI was associated with HT (aOR: 1.414, 95% CI: 1.152-1.736, I2 = 0%). In CA-AKI with a Scr increase ≥50% or ≥0.3 mg/dL from baseline within 7 days, HT increases the risk of CA-AKI (aOR: 1.317, 95% CI: 1.049-1.654, I2 = 51.5%). CONCLUSION: Our meta-analysis confirmed that HT is an independent risk factor for CA-AKI and can be used to identify risk stratification. Physicians should pay more attention toward prevention and treatment of patients with HT in clinical practice.

Exploring the Pleiotropic Genes and Therapeutic Targets Associated with Heart Failure and Chronic Kidney Disease by Integrating metaCCA and SGLT2 Inhibitors' Target Prediction.

BACKGROUND: Previous studies have shown that heart failure (HF) and chronic kidney disease (CKD) have common genetic mechanisms, overlapping pathophysiological pathways, and therapeutic drug-sodium-glucose cotransporter 2 (SGLT2) inhibitors. METHODS: The genetic pleiotropy metaCCA method was applied on summary statistics data from two independent meta-analyses of GWAS comprising more than 1 million people to identify shared variants and pleiotropic effects between HF and CKD. Targets of SGLT2 inhibitors were predicted by SwissTargetPrediction and DrugBank databases. To refine all genes, we performed using versatile gene-based association study 2 (VEGAS2) and transcriptome-wide association studies (TWAS) for HF and CKD, respectively. Gene enrichment and KEGG pathway analyses were used to explore the potential functional significance of the identified genes and targets. RESULTS: After metaCCA analysis, 4,624 SNPs and 1,745 genes were identified to be potentially pleiotropic in the univariate and multivariate SNP-multivariate phenotype analyses, respectively. 21 common genes were detected in both metaCCA and SGLT2 inhibitors' target prediction. In addition, 169 putative pleiotropic genes were identified, which met the significance threshold both in metaCCA analysis and in the VEGAS2 or TWAS analysis for at least one disease. CONCLUSION: We identified novel variants associated with HF and CKD using effectively incorporating information from different GWAS datasets. Our analysis may provide new insights into HF and CKD therapeutic approaches based on the pleiotropic genes, common targets, and mechanisms by integrating the metaCCA method, TWAS and VEGAS2 analyses, and target prediction of SGLT2 inhibitors.

Deep learning-based predictive biomarker of pathological complete response to neoadjuvant chemotherapy from histological images in breast cancer.

BACKGROUND: Pathological complete response (pCR) is considered a surrogate endpoint for favorable survival in breast cancer patients treated with neoadjuvant chemotherapy (NAC). Predictive biomarkers of treatment response are crucial for guiding treatment decisions. With the hypothesis that histological information on tumor biopsy images could predict NAC response in breast cancer, we proposed a novel deep learning (DL)-based biomarker that predicts pCR from images of hematoxylin and eosin (H&E)-stained tissue and evaluated its predictive performance. METHODS: In total, 540 breast cancer patients receiving standard NAC were enrolled. Based on H&E-stained images, DL methods were employed to automatically identify tumor epithelium and predict pCR by scoring the identified tumor epithelium to produce a histopathological biomarker, the pCR-score. The predictive performance of the pCR-score was assessed and compared with that of conventional biomarkers including stromal tumor-infiltrating lymphocytes (sTILs) and subtype. RESULTS: The pCR-score derived from H&E staining achieved an area under the curve (AUC) of 0.847 in predicting pCR directly, and achieved accuracy, F1 score, and AUC of 0.853, 0.503, and 0.822 processed by the logistic regression method, respectively, higher than either sTILs or subtype; a prediction model of pCR constructed by integrating sTILs, subtype and pCR-score yielded a mean AUC of 0.890, outperforming the baseline sTIL-subtype model by 0.051 (0.839, P = 0.001). CONCLUSION: The DL-based pCR-score from histological images is predictive of pCR better than sTILs and subtype, and holds the great potentials for a more accurate stratification of patients for NAC.

Association between Prognostic Nutritional Index and Contrast-Associated Acute Kidney Injury in Patients Complicated with Chronic Kidney Disease and Coronary Artery Disease.

BACKGROUND: Contrast-associated acute kidney injury (CA-AKI) is a major adverse effect of coronary angiography (CAG). Patients with chronic kidney disease (CKD) and coronary artery disease (CAD) are at high risk of CA-AKI. This study aimed to investigate the association between prognostic nutritional index (PNI) and CA-AKI in this high-risk population. METHODS: This study enrolled a total of 4,391 patients. CA-AKI was defined as a serum creatinine increase ≥0.3 mg/dL or 50% from baseline within the first 48 hours following CAG. The PNI was calculated upon hospital admission: serum albumin (g/L) + 5 × total lymphocyte count (109/L). PNI was analysed from the high level to low level as a continuous variable and categorical variable which was divided into four groups by quartile. Restricted cubic splines and logistic regression were applied. RESULTS: Overall, 13.09% (575/4391) of patients developed CA-AKI. PNI score was significantly lower in patients with CA-AKI than that in patients without CA-AKI (P < 0.01). The relationship between PNI score and CA-AKI was linear. A logistic regression model revealed that decreased PNI score was associated with increased risk of CA-AKI [per 1-point decrement; adjusted OR = 1.08, 95% CI, 1.05-1.09; compared with Quartile 1 (PNI ≥ 46.30), Quartile 4 (PNI < 37.90), adjusted OR = 1.88, 95% CI: 1.41-2.51; and Quartile 3 (37.90 ≤ PNI < 42.15), adjusted OR = 1.37, 95% CI: 1.02-1.84]. CONCLUSION: Our study indicated a negative linear relationship between PNI score and CA-AKI in patients undergoing CAG complicated with CKD and CAD. It suggested that malnutrition is associated with increased risk of CA-AKI in this population.

The global incidence and mortality of contrast-associated acute kidney injury following coronary angiography: a meta-analysis of 1.2 million patients.

BACKGROUND: Contrast-associated acute kidney injury (CA-AKI) is a common complication after coronary angiography (CAG), which brings a poor prognosis. But up to now, there were fewer studies to discuss the incidence of CA-AKI comprehensively. We comprehensively explore the incidence of CA-AKI after coronary angiography. METHODS: We searched Medline, Embase, and Cochrane Database of Systematic Reviews (to 30th June 2019). We evaluated the world's incidence of the CA-AKI, and associated mortality, and to described geographic variations according to countries, regions, and economies. CA-AKI was defined as an increase in serum creatinine ≥ 0.5 mg/dl or ≥ 25% within 72 h. Random effects model meta-analyses and meta-regressions was performed to derive the sources of heterogeneity. RESULTS: A total of 134 articles (1,211,106 participants) were included in our meta-analysis. Most studies originated from China, Japan, Turkey and United States, from upper middle income and high income countries. The pooled incidence of CA-AKI after coronary angiography was 12.8% (95% CI 11.7-13.9%), and the CA-AKI associated mortality was 20.2% (95% CI 10.7-29.7%). The incidence of CA-AKI and the CA-AKI associated mortality were not declined over time (Incidence rate change: 0.23% 95% CI - 0.050 to 0.510 p = 0.617; Mortality rate change: - 1.05% 95% CI - 3.070 to 0.970 p = 0.308, respectively). CONCLUSION: CA-AKI was a universal complication in many regions, and the burden of CA-AKI remains severe. In clinical practice, physicians should pay more attention to the occurrence and active prevention and treatment of CA-AKI.

Malnutrition affects cholesterol paradox in coronary artery disease: a 41,229 Chinese cohort study.

BACKGROUND: Several studies have found that a low baseline low -density lipoprotein cholesterol (LDL-C) concentration was associated with poor prognosis in patients with acute coronary syndrome (ACS), which is called the "cholesterol paradox". Low LDL-C concentration may reflect underlying malnutrition, which was strongly associated with increased mortality. The aim of this study was to investigate the cholesterol paradox in patients with CAD and the effects of malnutrition. METHOD: A total of 41,229 CAD patients admitted to Guangdong Provincial People's Hospital in China were included in this study from January 2007 to December 2018 and divided into two groups (LDL-C < 1.8 mmol/L, n = 4863; LDL-C ≥ 1.8 mmol/L, n = 36,366). The Kaplan-Meier method and Cox regression analyses were used to assess the association between LDL-C levels and long-term all-cause mortality and the effect of malnutrition. RESULT: In this real-world cohort (mean age 62.9 years; 74.9% male), there were 5257 cases of all-cause death during a median follow-up of 5.20 years [interquartile range (IQR): 3.05-7.78 years]. Kaplan-Meier analysis showed that low LDL-C levels were associated with a worse prognosis. After adjusting for baseline confounders (e.g., age, sex and comorbidities, etc.), multivariate Cox regression analysis revealed that a low LDL-C level (< 1.8 mmol/L) was not significantly associated with all-cause mortality (adjusted HR, 1.04; 95% CI, 0.96-1.24). After adjustment for nutritional status, the risk of all-cause mortality in patients with low LDL-C levels decreased (adjusted HR, 0.90; 95% CI, 0.83-0.98). In the final multivariate Cox model, a low LDL-C level was related to better prognosis (adjusted HR, 0.91; 95% CI, 0.84-0.99). CONCLUSION: This study demonstrated that the cholesterol paradox existed in CAD patients but disappeared after accounting for the effects of malnutrition.

Baseline Low-Density-Lipoprotein Cholesterol Modifies the Risk of All-Cause Death Associated With Elevated Lipoprotein(a) in Coronary Artery Disease Patients.

Background: The prognostic value of elevated lipoprotein(a) [Lp(a)] in coronary artery disease (CAD) patients is inconsistent in previous studies, and whether such value changes at different low-density-lipoprotein cholesterol (LDL-C) levels is unclear. Methods and Findings: CAD patients treated with statin therapy from January 2007 to December 2018 in the Guangdong Provincial People's Hospital (NCT04407936) were consecutively enrolled. Individuals were categorized according to the baseline LDL-C at cut-off of 70 and 100 mg/dL. The primary outcome was 5-year all-cause death. Multivariate Cox proportional models and penalized spline analyses were used to evaluate the association between Lp(a) and all-cause mortality. Among 30,908 patients, the mean age was 63.1 ± 10.7 years, and 76.7% were men. A total of 2,383 (7.7%) patients died at 5-year follow-up. Compared with Lp(a) <50 mg/dL, Lp(a) ≥ 50 mg/dL predicted higher all-cause mortality (multivariable adjusted HR = 1.19, 95% CI 1.07-1.31) in the total cohort. However, when analyzed within each LDL-C category, there was no significant association between Lp(a) ≥ 50 mg/dL and higher all-cause mortality unless the baseline LDL-C was ≥ 100 mg/dL (HR = 1.19, 95% CI 1.04-1.36). The results from penalized spline analyses were robust. Conclusions: In statin-treated CAD patients, elevated Lp(a) was associated with increased risks of all-cause death, and such an association was modified by the baseline LDL-C levels. Patients with Lp(a) ≥ 50 mg/dL had higher long-term risks of all-cause death compared with those with Lp(a) <50 mg/dL only when their baseline LDL-C was ≥ 100 mg/dL.

A comparison between two different definitions of contrast-associated acute kidney injury for long-term mortality in patients with diabetes undergoing coronary angiography: a prospective cohort study.

BACKGROUND: The definitions of contrast-associated acute kidney injury (CA-AKI) are diverse and have different predictive effects for prognosis, which are adverse for clinical practice. Few articles have discussed the relationship between these definitions and long-term prognosis in patients with diabetes. METHODS: A total of 1154 diabetic patients who were undergoing coronary angiography (CAG) were included in this study. Two definitions of CA-AKI were used: CA-AKIA was defined as an increase ≥ 0.3 mg/dl or > 50% in serum creatinine (SCr) from baseline within 72 h after CAG, and CA-AKIB was defined as an increase ≥ 0.5 mg/dl or > 25% in SCr from baseline within 72 h after CAG. We used Cox regression to evaluate the association of these two CA-AKI definitions with long-term mortality and calculate the population attributable risks (PARs) of different definitions for long-term prognosis. RESULTS: During the median follow-up period of 7.4 (6.2-8.2) years, the overall long-term mortality was 18.84%, and the long-term mortality in patients with CA-AKI according to both CA-AKIA and CA-AKIB criteria were 36.73% and 28.86%, respectively. We found that CA-AKIA (HR: 2.349, 95% CI 1.570-3.517, p = 0.001) and CA-AKIB (HR: 1.608, 95% CI 1.106-2.339, p = 0.013) were associated with long-term mortality. The PARs were the highest for CA-AKIA (31.14%), followed by CA-AKIB (14.93%). CONCLUSIONS: CA-AKI is a common complication in diabetic patients receiving CAG. The two CA-AKI definitions are significantly associated with a poor long-term prognosis, and CA-AKIA, with the highest PAR, needs more clinical attention.

A prediction model of contrast-associated acute kidney injury in patients with hypoalbuminemia undergoing coronary angiography.

BACKGROUND: Risk stratification is recommended as the key step to prevent contrast-associated acute kidney injury (CA-AKI) among at-risk patients following coronary angiography (CAG) and/or percutaneous coronary intervention (PCI). Patients with hypoalbuminemia are prone to CA-AKI and do not have their own risk stratification tool. Therefore, this study developed and validated a new model for predicting CA-AKI among hypoalbuminemia patients CAG/PCI. METHODS: 1272 patients with hypoalbuminemia receiving CAG/PCI were enrolled and randomly allocated (2:1 ratio) into the development cohort (n = 848) and the validation cohort (n = 424). CA-AKI was defined as an increase of ≥0.3 mg/dL or 50% in serum creatinine (SCr) compared to baseline in the 48 to 72 h after CAG/PCI. A prediction model was established with independent predictors according to stepwise logistic regression, showing as a nomogram. The discrimination of the new model was evaluated by the area under the curve (AUC) and was compared to the classic Mehran CA-AKI model. The Hosmer-Lemeshow test was conducted to assess the calibration of our model. RESULTS: Overall, 8.4% (71/848) patients of the development group and 11.2% (48/424) patients of the validation group experienced CA-AKI. A new nomogram included estimated glomerular filtration rate (eGFR), serum albumin (ALB), age and the use of intra-aortic balloon pump (IABP); showed better predictive ability than the Mehran score (C-index 0.756 vs. 0.693, p = 0.02); and had good calibration (Hosmer-Lemeshow test p = 0.187). CONCLUSIONS: We developed a simple model for predicting CA-AKI among patients with hypoalbuminemia undergoing CAG/PCI, but our findings need validating externally. TRIAL REGISTRATION: http://www.ClinicalTrials.gov NCT01400295 , retrospectively registered 21 July 2011.

FRET-Created Traffic Light Immunoassay Based on Polymer Dots for PSA Detection.

There have been enormous efforts for developing the next generations of fluorometric lateral flow immunochromatographic strip (ICTS) owing to the great advances in fluorescent materials in these years. Here we developed one type of fluorometric ICTS based on ultrabright semiconducting polymer dots (Pdots) in which the traffic light-like signals were created by energy transfer depending on the target concentration. This platform was successfully applied for qualitatively rapid screening and quantitatively precise analysis of prostate-specific antigen (PSA) in 10 min from merely one drop of the whole blood sample. This FRET-created traffic light ICTS possesses excellent specificity and an outstanding detection sensitivity of 0.32 ng/mL for PSA. Moreover, we conducted proof-of-concept experiments to demonstrate its potential for multiplexed detection of cancer biomarkers at the same time in an individual test strip by taking advantage of the traffic light signals. To the best of our knowledge, it is the first model of a traffic light-like immunoassay test strip based on Pdots with multiplexing ability. These results would pave an avenue for designing the next generation of point-of-care diagnostics.

Multiplexed Detection of Tumor Markers with Multicolor Polymer Dot-Based Immunochromatography Test Strip.

There have been ongoing efforts to develop more sensitive and fast quantitative screening of cancer markers by use of fluorometric immunochromatographic test strips (ICTS) since the remarkable advances in fluorescent nanomaterials. Semiconducting polymer dots (Pdots) have recently emerged as a new type of biocompatible fluorescent probe with extraordinary brightness which is suitable for biological and clinical use. Here, we developed Pdot-based ICTS for quantitative rapid screening of prostate-specific antigen (PSA), α-fetoprotein (AFP), and carcinoembryonic antigen (CEA) in 10 min. Through use of the ultrahigh fluorescence brightness of Pdots, this immunosensor enabled much better detection sensitivity (2.05, 3.30, and 4.92 pg/mL for PSA, AFP, and CEA, respectively), in which the detection limit is at least 2 orders of magnitude lower than that of conventional fluorometric ICTS. Furthermore, we performed proof-of-concept experiments for simultaneous determination of multiple tumor markers in a single test strip. These results demonstrated that this Pdot-based ICTS platform is a promising candidate for developing new generations of point-of-care diagnostics. To the best of our knowledge, this is the first example of Pdot-based ICTS with multiplexing capability.