P3592Troponin level and mortality risk in an unselected population of over 250,000 patients (TROP-RISK study)

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
A Kaura ◽  
V Panoulas ◽  
B Glampson ◽  
J Davies ◽  
A Mulla ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Health Informatics ◽  
Cox Regression ◽  
Cubic Spline ◽  
Research Centre ◽  
Current Evidence ◽  
Diagnostic Code ◽  
Troponin Level ◽  
Elevated Troponin ◽  
Cox Regression Analysis

Abstract Background Current evidence suggests a direct relationship between the magnitude of troponin elevation and mortality, albeit over a limited range of troponin levels, and clinicians generally work under the impression that higher troponins signify higher mortality in all age groups. Purpose The objective was to use big data to determine the relationship between the full spectrum of troponin level and mortality in patients in whom troponin testing has been performed for clinical purposes. Methods As part of the National Institute for Health Research Health Informatics Collaborative project, all troponin values measured during the study period (2010 to 2017) were assembled from five cardiovascular centres. Troponin concentrations were standardised as a multiple of each laboratory's 99th-percentile of the upper limit of normal (ULN). All patients were followed up until death or censoring on 1st April 2017. To model the relation between peak troponin level and all-cause mortality we used restricted cubic spline Cox regression analysis. Splines were adjusted for patient age, gender, haemoglobin, creatinine, white cell count and C-reactive protein. Results 257,948 patients underwent troponin assessment. During a median follow-up of 1,198 (IQR, 514–1,866) days, there were 55,850 (21.7%) deaths. Using multivariable-adjusted restricted cubic spline Cox regression analysis, an inverted-U shaped relationship was observed between peak troponin level and mortality in all patients (Figure 1A). Among patients who were admitted to hospital, the recorded diagnostic code was acute coronary syndrome (ACS) in 14,468 patients and non-ACS in 120,049 patients. The revascularisation rate within 3 months was 61.0% (n=8,820) in ACS versus 4.0% (n=4,793) in non-ACS patients. There was a very different rate of revascularisation across the spectrum of troponin. The rate was only 1.4% for troponins below 1 xULN, and 6.1% between 1 and 10 xULN. Beyond 10 xULN, rate of revascularisation rose rapidly to over 85% for greater than 10,000 xULN (Figure 1B). Stratifying patients by revascularisation, the restricted cubic spline Cox regression curve showed a progressive increase in mortality within both the revascularised and non-revascularised strata, even to very high peak troponin levels (Figure 1C). Overall, revascularisation was associated with lower hazard ratios across all troponin levels. A similar pattern was seen when patients were stratified by the presence or absence of ACS diagnosis. Figure 1. Troponin level and mortality Conclusions An elevated troponin, even slightly above the ULN should be taken seriously. The inverted-U shaped mortality relationship with troponin occurred because patients with the highest troponin formed a different clinical subgroup who underwent different clinical management with a high revascularisation rate. These data on troponin level and mortality may help to inform clinical practice decisions and guide future risk stratification algorithms for patients with elevated troponin. Acknowledgement/Funding Funded by NIHR Imperial Biomedical Research Centre (BRC) using NIHR Health Informatics Collaborative data service, supported by OUH, GSTT & UCLH BRCs

2231HsCRP predicts mortality beyond troponin in 102,337 patients with suspected acute coronary syndrome (CRP-RISK study)

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
A Kaura ◽  
A Hartley ◽  
V Panoulas ◽  
B Glampson ◽  
J Davies ◽  
...  
Keyword(s):  
Real World ◽  
Health Informatics ◽  
Cox Regression ◽  
White Cell ◽  
Research Centre ◽  
Troponin Level ◽  
Cox Regression Analysis ◽  
Cumulative Mortality ◽  
Coronary Syndrome ◽  
Cell Counts

Abstract Background The incremental long-term prognostic value of high-sensitivity C-reactive protein (hsCRP) above troponin in a large real-world cohort of unselected patients presenting with suspected acute coronary syndromes (ACS) is unknown. Purpose We hypothesised that a mildly elevated hsCRP is associated with mortality risk in patients with suspected ACS, independent of troponin level. Methods We used the National Institute for Health Research Health Informatics Collaborative data of 257,948 patients who had a troponin measured at 5 cardiac centres. We excluded patients with clinically abnormal white cell counts and hsCRP >15 mg/L to try limiting the population to those without overt infections, malignancies or systemic inflammatory conditions that may confound our analyses. Patients were divided into four hsCRP groups (<2, 2–4.9, 5–9.9 and 10–15 mg/L) and the association between hsCRP levels and all-cause mortality assessed. Results There were 102,337 patients included in the analysis (hsCRP <2 mg/L (n=38,390), 2–4.9 mg/L (n=27,397), 5–9.9 mg/L (n=26,957) and 10–15 mg/L (n=9,593)). Figure 1A displays cumulative mortality per hsCRP group, revealing increasing mortality with each consecutive group. Figure 1B further stratifies the groups according to dichotomised peak troponin level as positive or negative. This shows the greatest mortality for patients in the highest hsCRP group who also had a positive troponin assay (36.0% at 3 years). In Cox regression analysis with time-dependent covariates, even mildly raised hsCRP was an independent predictor of mortality over time, after adjusting for age, gender, haemoglobin, white cell count, platelet count, creatinine and troponin positivity. There was a positive and graded relationship between hsCRP level and mortality at baseline, which remained at 3-years (hazard ratio (95% CI) of 1.32 (1.18–1.48) for those with hsCRP 2.0–4.9mg/L, and 1.40 (1.26–1.57), and 2.00 (1.75–2.28) for those with hsCRP 5–9.9 mg/L and 10–15 mg/L, respectively. We explored whether inclusion of hsCRP could better reclassify the population into at-risk mortality groups. The association with 30-day, 1-year and 3-year mortality was assessed using three different risk models (model 1: age, gender, haemoglobin, creatinine; model 2: model 1 plus troponin (positivity versus negativity); model 3: model 2 plus hsCRP groups. For cumulative mortality at each time point, each successive model was better able to discriminate risk than its precursor (p<0.0001); such that inclusion of troponin and hsCRP gave the most robust risk discrimination. Model 3 achieved an AUROC >0.8 at 30 days, 1-year and 3-year mortality, surpassing the use of troponin on its own. Figure 1. Kaplan-Meier mortality curves Conclusions These multi-centre, real-world data from a large cohort of patients with suspected ACS identify hsCRP as a clinically meaningful prognostic marker in addition to troponin levels and point to its potential utility in selecting patients for novel treatments targeting inflammation. Acknowledgement/Funding Funded by NIHR Imperial Biomedical Research Centre (BRC) using NIHR Health Informatics Collaborative data service, supported by OUH, GSTT & UCLH BRCs

scholarly journals Glycemic Control and Risk of Sepsis and Subsequent Mortality in Type 2 Diabetes

2021 ◽  
Author(s):  
Anca Balintescu ◽  
Marcus Lind ◽  
Mikael Andersson Franko ◽  
Anders Oldner ◽  
Maria Cronhjort ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Regression Analysis ◽  
Cox Regression ◽  
Cubic Spline ◽  
Hazard Ratio ◽  
Adjusted Hazard Ratio ◽  
Cox Regression Analysis ◽  
Risk Of Death ◽  
Increased Risk

<b>Objective</b> <p>To investigate the nature of<b> </b>the relationship between HbA1c and sepsis among individuals with type 2 diabetes and to assess the association of sepsis and all-cause mortality in such patients.<b></b></p> <p><b>Research design and methods</b></p> <p>We included 502,871 individuals with type 2 diabetes recorded in the Swedish National Diabetes Register and used multivariable Cox regression and restricted cubic spline analyses to assess the association between time-updated HbA1c values and sepsis occurrence between January 1, 2005 and December 31, 2015. The association between sepsis and death was examined using multivariable Cox regression analysis.</p> <p><b>Result</b></p> <p>Overall, 14,534 (2.9%) patients developed sepsis during the study period. On multivariable Cox regression analysis, compared with an HbA1c of 48-52 mmol/mol (6.5-6.9%), the adjusted hazard ratio for sepsis was 1.15 (95% CI 1.07-1.24) for HbA1c <43 mmol/mol (6.1%); 0.93 (0.87-0.99) for HbA1c 53-62 mmol/mol (7.0-7.8%); 1.05 (0.97-1.13) for HbA1c 63-72 mmol/mol (7.9-8.7%); 1.14 (1.04-1.25) for HbA1c 73-82 mmol/mol (8.8-9.7%); and 1.52 (1.37-1.68) for HbA1c >82 mmol/mol (9.7%). In the cubic spline model, a reduction of the adjusted risk was observed within the lower HbA1c range until 53 mmol/mol (7.0%), with a hazard ratio of 0.78 (0.73-0.82) per standard deviation, and increased thereafter (P for non-linearity <0.001). As compared to patients without sepsis, the adjusted hazard ratio for death among patients with sepsis was 4.16 (4.03-4.30).</p> <p><b>Conclusions</b></p> <p>In a nationwide cohort of individuals with type 2 diabetes, we found a U-shaped association between HbA1c and sepsis and a four-fold increased risk of death among those developing sepsis. </p>

scholarly journals Glycemic Control and Risk of Sepsis and Subsequent Mortality in Type 2 Diabetes

2021 ◽  
Author(s):  
Anca Balintescu ◽  
Marcus Lind ◽  
Mikael Andersson Franko ◽  
Anders Oldner ◽  
Maria Cronhjort ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Regression Analysis ◽  
Cox Regression ◽  
Cubic Spline ◽  
Hazard Ratio ◽  
Adjusted Hazard Ratio ◽  
Cox Regression Analysis ◽  
Risk Of Death ◽  
Increased Risk

<b>Objective</b> <p>To investigate the nature of<b> </b>the relationship between HbA1c and sepsis among individuals with type 2 diabetes and to assess the association of sepsis and all-cause mortality in such patients.<b></b></p> <p><b>Research design and methods</b></p> <p>We included 502,871 individuals with type 2 diabetes recorded in the Swedish National Diabetes Register and used multivariable Cox regression and restricted cubic spline analyses to assess the association between time-updated HbA1c values and sepsis occurrence between January 1, 2005 and December 31, 2015. The association between sepsis and death was examined using multivariable Cox regression analysis.</p> <p><b>Result</b></p> <p>Overall, 14,534 (2.9%) patients developed sepsis during the study period. On multivariable Cox regression analysis, compared with an HbA1c of 48-52 mmol/mol (6.5-6.9%), the adjusted hazard ratio for sepsis was 1.15 (95% CI 1.07-1.24) for HbA1c <43 mmol/mol (6.1%); 0.93 (0.87-0.99) for HbA1c 53-62 mmol/mol (7.0-7.8%); 1.05 (0.97-1.13) for HbA1c 63-72 mmol/mol (7.9-8.7%); 1.14 (1.04-1.25) for HbA1c 73-82 mmol/mol (8.8-9.7%); and 1.52 (1.37-1.68) for HbA1c >82 mmol/mol (9.7%). In the cubic spline model, a reduction of the adjusted risk was observed within the lower HbA1c range until 53 mmol/mol (7.0%), with a hazard ratio of 0.78 (0.73-0.82) per standard deviation, and increased thereafter (P for non-linearity <0.001). As compared to patients without sepsis, the adjusted hazard ratio for death among patients with sepsis was 4.16 (4.03-4.30).</p> <p><b>Conclusions</b></p> <p>In a nationwide cohort of individuals with type 2 diabetes, we found a U-shaped association between HbA1c and sepsis and a four-fold increased risk of death among those developing sepsis. </p>

scholarly journals Prognostic Factors and Diseases-Specific Survival Outcome in Patients with Glioblastoma: A Population-Based Study

2020 ◽  
Author(s):  
Lihua Wu ◽  
Jianbo Song ◽  
Junping Zhang ◽  
Wenhui Yang ◽  
Mengxian Zhang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Regression Analysis ◽  
Prognostic Factors ◽  
Tumor Size ◽  
Cox Regression ◽  
Cubic Spline ◽  
Age At Diagnosis ◽  
Lasso Regression ◽  
Cox Regression Analysis ◽  
Risk Effect

Abstract ObjectiveThis study aimed to determine the prognostic factors for disease-specific survival (DSS) of glioblastoma (GBM) and establish a corresponding effective nomogram for clinical prediction.Methods This study was based on Surveillance, Epidemiology, and End Results database between 2004 and 2015. Kaplan-Meier survival analysis was used to evaluate the effect of various prognostic factors on DSS. Lasso regression was used to determine the independent prognostic factors of DSS and multivariate cox regression analysis was performed correspondingly. Additional restricted cubic spline cox regression was used to analyze the trend of the risk effect (hazard ratio) of continuous variables on DSS. Based on the multivariate cox regression model, a nomogram was established to predict DSS. ResultsThe average age at diagnosis of all enrolled patients was 59.8±12.2 years, of which 40.5% were women and 59.5% were men. Lasso regression analysis showed that age at diagnosis, sex, marital status, race, tumor size, primary site, laterality, surgery, radiotherapy and chemotherapy, radiotherapy sequence with surgery, and year of diagnosis were independent prognostic factors for DSS. Multivariate cox regression analysis showed that elderly, males, unmarried status, larger tumors were all risk factors for DSS. Restricted cubic spline cox regression showed that the risk of death from GBM was significantly increased for the elderly, especially older than 75 years. When the tumor was smaller than 75mm, an increasing risk linearly was associated with DSS, but the risk effect remained constant after 75mm. Constructing the nomogram to predict the DSS probability of 1-, 3- and 5-year respectively, and its good predictive performance was proved by the calibration curve.ConclusionThe advanced age was one of the significant risk factors for GBM. How the change of tumor size affected DSS needed further study and discussion. The established nomogram was robust in predicting 1-, 3-, and 5- year DSS.

Red Blood Cell Indices in Relation to Post-stroke Psychiatric Disorders: A Longitudinal Study in a Follow-up Stroke Clinic

2020 ◽  
Vol 17 (3) ◽  
pp. 218-223
Author(s):  
Haichao Wang ◽  
Li Gong ◽  
Xiaomei Xia ◽  
Qiong Dong ◽  
Aiping Jin ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Ischemic Stroke ◽  
Blood Cell ◽  
Cox Regression ◽  
Depression And Anxiety ◽  
Cox Regression Analysis ◽  
Post Stroke ◽  
Rbc Indices ◽  
Post Stroke Depression

Background: Depression and anxiety after stroke are common conditions that are likely to be neglected. Abnormal red blood cell (RBC) indices may be associated with neuropsychiatric disorders. However, the association of RBC indices with post-stroke depression (PSD) and poststroke anxiety (PSA) has not been sufficiently investigated. Methods: We aimed to investigate the trajectory of post-stroke depression and anxiety in our follow- up stroke clinic at 1, 3, and 6 months, and the association of RBC indices with these. One hundred and sixty-two patients with a new diagnosis of ischemic stroke were followed up at 1, 3, and 6 months, and underwent Patient Health Questionnaire-9 (PHQ-9) and the general anxiety disorder 7-item (GAD-7) questionnaire for evaluation of depression and anxiety, respectively. First, we used Kaplan-Meier analysis to investigate the accumulated incidences of post-stroke depression and post-stroke anxiety. Next, to explore the association of RBC indices with psychiatric disorders after an ischemic stroke attack, we adjusted for demographic and vascular risk factors using multivariate Cox regression analysis. Results: Of the 162 patients with new-onset of ischemic stroke, we found the accumulated incidence rates of PSD (1.2%, 17.9%, and 35.8%) and PSA (1.2%, 13.6%, and 15.4%) at 1, 3, and 6 months, respectively. The incident PSD and PSA increased 3 months after a stroke attack. Multivariate Cox regression analysis indicated independent positive associations between PSD risk and higher mean corpuscular volume (MCV) (OR=1.42, 95% CI=1.16-1.76), older age (OR=2.63, 95% CI=1.16-5.93), and a negative relationship between male sex (OR=0.95, 95% CI=0.91-0.99) and PSA. Conclusion: The risks of PSD and PSA increased substantially 3 months beyond stroke onset. Of the RBC indices, higher MCV, showed an independent positive association with PSD.

scholarly journals Identification and development of an independent immune-related genes prognostic model for breast cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Lin Chen ◽  
Yuxiang Dong ◽  
Yitong Pan ◽  
Yuhan Zhang ◽  
Ping Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
Risk Scores ◽  
Validation Dataset ◽  
Immune Gene ◽  
Cox Regression Analysis ◽  
Immune Genes ◽  
Immune Related Genes

Abstract Background Breast cancer is one of the main malignant tumors that threaten the lives of women, which has received more and more clinical attention worldwide. There are increasing evidences showing that the immune micro-environment of breast cancer (BC) seriously affects the clinical outcome. This study aims to explore the role of tumor immune genes in the prognosis of BC patients and construct an immune-related genes prognostic index. Methods The list of 2498 immune genes was obtained from ImmPort database. In addition, gene expression data and clinical characteristics data of BC patients were also obtained from the TCGA database. The prognostic correlation of the differential genes was analyzed through Survival package. Cox regression analysis was performed to analyze the prognostic effect of immune genes. According to the regression coefficients of prognostic immune genes in regression analysis, an immune risk scores model was established. Gene set enrichment analysis (GSEA) was performed to probe the biological correlation of immune gene scores. P < 0.05 was considered to be statistically significant. Results In total, 556 immune genes were differentially expressed between normal tissues and BC tissues (p < 0. 05). According to the univariate cox regression analysis, a total of 66 immune genes were statistically significant for survival risk, of which 30 were associated with overall survival (P < 0.05). Finally, a 15 immune genes risk scores model was established. All patients were divided into high- and low-groups. KM survival analysis revealed that high immune risk scores represented worse survival (p < 0.001). ROC curve indicated that the immune genes risk scores model had a good reliability in predicting prognosis (5-year OS, AUC = 0.752). The established risk model showed splendid AUC value in the validation dataset (3-year over survival (OS) AUC = 0.685, 5-year OS AUC = 0.717, P = 0.00048). Moreover, the immune risk signature was proved to be an independent prognostic factor for BC patients. Finally, it was found that 15 immune genes and risk scores had significant clinical correlations, and were involved in a variety of carcinogenic pathways. Conclusion In conclusion, our study provides a new perspective for the expression of immune genes in BC. The constructed model has potential value for the prognostic prediction of BC patients and may provide some references for the clinical precision immunotherapy of patients.

scholarly journals The Role of Hydraulic Silicate Cements on Long-Term Properties and Biocompatibility of Partial Pulpotomy in Permanent Teeth

Materials ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 305
Author(s):  
Chung-Min Kang ◽  
Saemi Seong ◽  
Je Seon Song ◽  
Yooseok Shin
Keyword(s):  
Regression Analysis ◽  
Cox Regression ◽  
Antimicrobial Properties ◽  
Permanent Teeth ◽  
Success Rates ◽  
Pulp Tissue ◽  
Cox Regression Analysis ◽  
Clinical Variables

The use of hydraulic silicate cements (HSCs) for vital pulp therapy has been found to release calcium and hydroxyl ions promoting pulp tissue healing and mineralized tissue formation. The present study investigated whether HSCs such as mineral trioxide aggregate (MTA) affect their biological and antimicrobial properties when used as long-term pulp protection materials. The effect of variables on treatment outcomes of three HSCs (ProRoot MTA, OrthoMTA, and RetroMTA) was evaluated clinically and radiographically over a 48–78 month follow-up period. Survival analysis was performed using Kaplan–Meier survival curves. Fisher’s exact test and Cox regression analysis were used to determine hazard ratios of clinical variables. The overall success rate of MTA partial pulpotomy was 89.3%; Cumulative success rates of the three HSCs were not statistically different when analyzed by Cox proportional hazard regression analysis. None of the investigated clinical variables affected success rates significantly. These HSCs showed favorable biocompatibility and antimicrobial properties in partial pulpotomy of permanent teeth in long-term follow-up, with no statistical differences between clinical factors.

scholarly journals The prognostic and diagnostic significance of the neutrophil-to-lymphocyte ratio in hepatocellular carcinoma: a prospective controlled study

2021 ◽  
Author(s):  
Philip J. Johnson ◽  
Sofi Dhanaraj ◽  
Sarah Berhane ◽  
Laura Bonnett ◽  
Yuk Ting Ma
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Prognostic Factor ◽  
Cox Regression ◽  
Prognostic Models ◽  
Controlled Study ◽  
Cox Regression Analysis ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Significant Difference

Abstract Background The neutrophil–lymphocyte ratio (NLR), a presumed measure of the balance between neutrophil-associated pro-tumour inflammation and lymphocyte-dependent antitumour immune function, has been suggested as a prognostic factor for several cancers, including hepatocellular carcinoma (HCC). Methods In this study, a prospectively accrued cohort of 781 patients (493 HCC and 288 chronic liver disease (CLD) without HCC) were followed-up for more than 6 years. NLR levels between HCC and CLD patients were compared, and the effect of baseline NLR on overall survival amongst HCC patients was assessed via multivariable Cox regression analysis. Results On entry into the study (‘baseline’), there was no clinically significant difference in the NLR values between CLD and HCC patients. Amongst HCC patients, NLR levels closest to last visit/death were significantly higher compared to baseline. Multivariable Cox regression analysis showed that NLR was an independent prognostic factor, even after adjustment for the HCC stage. Conclusion NLR is a significant independent factor influencing survival in HCC patients, hence offering an additional dimension in prognostic models.

scholarly journals The Investigation of Associations between TP53 rs1042522, BBC3 rs2032809, CCND1 rs9344, EGFR rs2227983 Polymorphisms and Breast Cancer Phenotype and Prognosis

Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1419
Author(s):  
Justina Bekampytė ◽  
Agnė Bartnykaitė ◽  
Aistė Savukaitytė ◽  
Rasa Ugenskienė ◽  
Erika Korobeinikova ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Cancer Prognosis ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Cox Regression Analysis ◽  
Pcr Rflp ◽  
Oncological Diseases ◽  
Cancer Phenotype

Breast cancer is one of the most common oncological diseases among women worldwide. Cell cycle and apoptosis—related genes TP53, BBC3, CCND1 and EGFR play an important role in the pathogenesis of breast cancer. However, the roles of single nucleotide polymorphisms (SNPs) in these genes have not been fully defined. Therefore, this study aimed to analyze the association between TP53 rs1042522, BBC3 rs2032809, CCND1 rs9344 and EGFR rs2227983 polymorphisms and breast cancer phenotype and prognosis. For the purpose of the analysis, 171 Lithuanian women were enrolled. Genomic DNA was extracted from peripheral blood; PCR-RFLP was used for SNPs analysis. The results showed that BBC3 rs2032809 was associated with age at the time of diagnosis, disease progression, metastasis and death. CCND1 rs9344 was associated with tumor size, however an association resulted in loss of significance after Bonferroni correction. In survival analysis, significant associations were observed between BBC3 rs2032809 and OS, PFS and MFS. EGFR rs2227983 also showed some associations with OS and PFS (univariate Cox regression analysis). However, the results were in loss of significance (multivariate Cox regression analysis). In conclusion, BBC3 rs2032809 polymorphism was associated with breast cancer phenotype and prognosis. Therefore, it could be applied as potential markers for breast cancer prognosis.

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