Predicting mortality in bronchiectasis using bronchiectasis severity index and FACED scores: a 19-year cohort study

2015 ◽  
Vol 47 (2) ◽  
pp. 482-489 ◽  
Author(s):  
Huw C. Ellis ◽  
Steven Cowman ◽  
Michele Fernandes ◽  
Robert Wilson ◽  
Michael R. Loebinger
Keyword(s):  
Predictive Power ◽  
Characteristic Curve ◽  
Cohort Analysis ◽  
Scoring Systems ◽  
Severity Index ◽  
Receiver Operator Characteristic Curve ◽  
Mortality Prediction ◽  
Prediction Of Mortality ◽  
Long Term Mortality

The clinical course of bronchiectasis is unpredictable, posing a challenge both in clinical practice and in research. Two mortality prediction scores, the bronchiectasis severity index (BSI) and FACED scores, have recently been developed. The aim of this study was to assess the ability of these scores to predict long-term mortality and to compare the two scores.The study was a single-centre retrospective cohort analysis consisting of 91 subjects originally recruited in 1994. BSI and FACED scores were calculated at the time of enrolment and long-term mortality ascertained. Data was available for 74 patients with a median of 18.8 years of follow-up.Both scoring systems had similar predictive power for 5-year mortality (area under receiver operator characteristic curve (AUC) 0.79 for BSI and 0.8 for FACED). Both scores were able to predict 15-year mortality with the FACED score showing slightly superior predictive power (AUC 0.82 versus 0.69, p=0.0495).This study provides further validation of the FACED and BSI scores for the prediction of mortality in bronchiectasis and demonstrates their utility over a longer period than originally described. Whilst both scores had excellent predictive power, the FACED score was superior for 15-year mortality.

scholarly journals Association Between Preoperative Monocyte to High-Density Lipoprotein Ratio on In-hospital and Long-Term Mortality in Patients Undergoing Endovascular Repair for Acute Type B Aortic Dissection

2022 ◽  
Vol 8 ◽  
Author(s):  
Enmin Xie ◽  
Fan Yang ◽  
Songyuan Luo ◽  
Yuan Liu ◽  
Ling Xue ◽  
...  
Keyword(s):  
Aortic Dissection ◽  
Characteristic Curve ◽  
Density Lipoprotein ◽  
Receiver Operator Characteristic Curve ◽  
Hospital Death ◽  
Acute Type ◽  
Type B Aortic Dissection ◽  
Optimal Cutoff ◽  
Long Term Mortality

Aims: The monocyte to high-density lipoprotein ratio (MHR), a novel marker of inflammation and cardiovascular events, has recently been found to facilitate the diagnosis of acute aortic dissection. This study aimed to assess the association of preoperative MHR with in-hospital and long-term mortality after thoracic endovascular aortic repair (TEVAR) for acute type B aortic dissection (TBAD).Methods: We retrospectively evaluated 637 patients with acute TBAD who underwent TEVAR from a prospectively maintained database. Multivariable logistic and cox regression analyses were conducted to assess the relationship between preoperative MHR and in-hospital as well as long-term mortality. For clinical use, MHR was modeled as a continuous variable and a categorical variable with the optimal cutoff evaluated by receiver operator characteristic curve for long-term mortality. Propensity score matching was used to diminish baseline differences and subgroups analyses were conducted to assess the robustness of the results.Results: Twenty-one (3.3%) patients died during hospitalization and 52 deaths (8.4%) were documented after a median follow-up of 48.1 months. The optimal cutoff value was 1.13 selected according to the receiver operator characteristic curve (sensitivity 78.8%; specificity 58.9%). Multivariate analyses showed that MHR was independently associated with either in-hospital death [odds ratio (OR) 2.11, 95% confidence interval (CI) 1.16-3.85, P = 0.015] or long-term mortality [hazard ratio (HR) 1.78, 95% CI 1.31-2.41, P < 0.001). As a categorical variable, MHR > 1.13 remained an independent predictor of in-hospital death (OR 4.53, 95% CI 1.44-14.30, P = 0.010) and long-term mortality (HR 4.16, 95% CI 2.13-8.10, P < 0.001). Propensity score analyses demonstrated similar results for both in-hospital death and long-term mortality. The association was further confirmed by subgroup analyses.Conclusions: MHR might be useful for identifying patients at high risk of in-hospital and long-term mortality, which could be integrated into risk stratification strategies for acute TBAD patients undergoing TEVAR.

APPLICATION OF DECAF AND BAP-65 TO PREDICT THE IN-HOSPITAL MORTALITY OF ACUTE EXACERBATION OF COPD IN SRMSIMS

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Shruti Jain ◽  
Anurag Agrawal ◽  
Lalit Singh ◽  
Rajeev Tandon
Keyword(s):  
Hospital Mortality ◽  
Sensitivity And Specificity ◽  
Area Under Curve ◽  
Characteristic Curve ◽  
Scoring Systems ◽  
Receiver Operator Characteristic Curve ◽  
Minimum Area ◽  
Prediction Of Mortality ◽  
Acute Exacerbations ◽  
Exacerbation Of Copd

INTRODUCTION: Hospitalisation due to acute exacerbations of COPD is common, and subsequent mortality high. The DECAF and BAP 65 score was derived for accurate prediction of mortality and risk stratification to inform patient care. We aimed to validate these scores, and to compare them. Comparison of DECAF, BAP-65 scores in predicting in hospital mortality in AECOPD MATERIAL AND METHODS: 106 patients of AECOPD, admitted during 6 months period were scored at admission using all 2 scores and their ability to predict in-hospital mortality was analysed. RESULTS: On receiver-operator characteristic curve analysis, the area under curve for prediction of in-hospital mortality was 0.791and 0.885 respectively for DECAF and BAP-65 scores respectively. Thus, among the two scoring systems BAP-65 had maximum area under curve while DECAF had minimum area under curve. Sensitivity and specificity values for prediction of in-hospital mortality were 83.3% and 54.3% for DECAF and 83.3% and 84.0% for BAP-65. Thus BAP-65 was the best predictor with adequate sensitivity and specificity for the in-hospital mortality.CONCLUSION: BAP-65 was most effective in prediction of in-hospital mortality

scholarly journals Blood Biomarkers to Predict Long-Term Mortality after Ischemic Stroke

Life ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 135
Author(s):  
Laura Ramiro ◽  
Laura Abraira ◽  
Manuel Quintana ◽  
Paula García-Rodríguez ◽  
Estevo Santamarina ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Cox Regression ◽  
Tumor Necrosis Factor Receptor ◽  
Mortality Prediction ◽  
Blood Biomarkers ◽  
Clinical Predictors ◽  
Prediction Of Mortality ◽  
Z Scores ◽  
Long Term Mortality

Stroke is a major cause of disability and death globally, and prediction of mortality represents a crucial challenge. We aimed to identify blood biomarkers measured during acute ischemic stroke that could predict long-term mortality. Nine hundred and forty-one ischemic stroke patients were prospectively recruited in the Stroke-Chip study. Post-stroke mortality was evaluated during a median 4.8-year follow-up. A 14-biomarker panel was analyzed by immunoassays in blood samples obtained at hospital admission. Biomarkers were normalized and standardized using Z-scores. Multiple Cox regression models were used to identify clinical variables and biomarkers independently associated with long-term mortality and mortality due to stroke. In the multivariate analysis, the independent predictors of long-term mortality were age, female sex, hypertension, glycemia, and baseline National Institutes of Health Stroke Scale (NIHSS) score. Independent blood biomarkers predictive of long-term mortality were endostatin > quartile 2, tumor necrosis factor receptor-1 (TNF-R1) > quartile 2, and interleukin (IL)-6 > quartile 2. The risk of mortality when these three biomarkers were combined increased up to 69%. The addition of the biomarkers to clinical predictors improved the discrimination (integrative discriminative improvement (IDI) 0.022 (0.007–0.048), p < 0.001). Moreover, endostatin > quartile 3 was an independent predictor of mortality due to stroke. Altogether, endostatin, TNF-R1, and IL-6 circulating levels may aid in long-term mortality prediction after stroke.

scholarly journals Haemoconcentration as a predictor of severity in acute pancreatitis

2016 ◽  
Vol 4 (1) ◽  
pp. 3-7
Author(s):  
Tanka Prasad Bohara ◽  
Dimindra Karki ◽  
Anuj Parajuli ◽  
Shail Rupakheti ◽  
Mukund Raj Joshi
Keyword(s):  
Acute Pancreatitis ◽  
Pearson Correlation ◽  
Characteristic Curve ◽  
Scoring Systems ◽  
Cost Effective ◽  
Receiver Operator Characteristic Curve ◽  
First Episode ◽  
P Value ◽  
Receiver Operator Characteristic ◽  
Chi Square

Background: Acute pancreatitis is usually a mild and self-limiting disease. About 25 % of patients have severe episode with mortality up to 30%. Early identification of these patients has potential advantages of aggressive treatment at intensive care unit or transfer to higher centre. Several scoring systems are available to predict severity of acute pancreatitis but are cumbersome, take 24 to 48 hours and are dependent on tests that are not universally available. Haematocrit has been used as a predictor of severity of acute pancreatitis but some have doubted its role.Objectives: To study the significance of haematocrit in prediction of severity of acute pancreatitis.Methods: Patients admitted with first episode of acute pancreatitis from February 2014 to July 2014 were included. Haematocrit at admission and 24 hours of admission were compared with severity of acute pancreatitis. Mean, analysis of variance, chi square, pearson correlation and receiver operator characteristic curve were used for statistical analysis.Results: Thirty one patients were included in the study with 16 (51.61%) male and 15 (48.4%) female. Haematocrit at 24 hours of admission was higher in severe acute pancreatitis (P value 0.003). Both haematocrit at admission and at 24 hours had positive correlation with severity of acute pancreatitis (r: 0.387; P value 0.031 and r: 0.584; P value 0.001) respectively.Area under receiver operator characteristic curve for haematocrit at admission and 24 hours were 0.713 (P value 0.175, 95% CI 0.536 - 0.889) and 0.917 (P value 0.008, 95% CI 0.813 – 1.00) respectively.Conclusion: Haematocrit is a simple, cost effective and widely available test and can predict severity of acute pancreatitis.Journal of Kathmandu Medical College, Vol. 4(1) 2015, 3-7

Lymphopenia and risk for long-term mortality among patients undergoing coronary angiography

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
B Zafrir ◽  
R Jaffe ◽  
H Sliman ◽  
O Barnett-Griness ◽  
W Saliba
Keyword(s):  
Coronary Angiography ◽  
Mortality Risk ◽  
Predictive Accuracy ◽  
Cohort Analysis ◽  
Cox Proportional Hazards ◽  
Cross Sectional ◽  
Distribution Width ◽  
Increased Risk ◽  
Long Term Mortality

Abstract Background Lymphopenia has been shown to be associated with adverse prognosis in chronic disease states that are related to immune dysregulation. Purpose We aimed to determine the association between lymphopenia and all-cause mortality in patients presenting to coronary angiography with or without acute coronary syndromes (ACS). We also investigated whether elevated red blood cell distribution width (RDW), an established cardiovascular prognostic marker, further refines risk stratification and improves predictive accuracy beyond lymphocytes count. Methods Retrospective cohort analysis of patients undergoing coronary angiography for evaluation or treatment of coronary artery disease between 2003 and 2018. Long-term mortality risk associated with relative (1000–1500 /μL) or severe (&lt;1000 /μL) lymphopenia was analyzed using Cox proportional hazards regression models, adjusting for comorbidities, ACS and RDW. Results Overall, 15179 patients underwent coronary angiography, at a mean age of 65±12 years. On cross-sectional analysis, lymphopenia was associated with kidney disease, cancer, heart failure and presentation with ACS, but lower rates of smoking and obesity. During a median follow-up of 7 (IQR 3.5–11.5) years, 4253 patients died. Compared to normal lymphocytes count (1500–5000 /μL), the multivariable adjusted hazard ratio (HR) (95% confidence interval) for mortality was 1.31 (1.21–1.41) and 1.97 (1.75–2.22) for relative and severe lymphopenia, respectively. The increase in mortality associated with severe lymphopenia was significant in patients presenting with non-ACS [HR 2.18 (1.74–2.73)], ST-segment elevation myocardial infarction (STEMI) [HR 1.59 (1.15–2.21)], or unstable angina/non-STEMI [HR 2.00 (1.70–2.34)]; p-for-interaction 0.626. The association of lymphopenia with mortality remained significant after additional adjustment to RDW. High RDW (&gt;14.5%) was associated with increased mortality risk in each of the lymphocytes count groups, and improved the predictive accuracy with AUC increase from 0.609 (0.601–0.616) to 0.646 (0.639–0.654) (p&lt;0.001). Conclusions Lymphopenia is associated with increased risk for long-term mortality in patients undergoing coronary angiography, regardless of coronary presentation. High RDW may enhance the predictive ability of lymphopenia. Lymphocyte count and mortality risk Funding Acknowledgement Type of funding source: None

scholarly journals Accuracy of conventional and novel scoring systems in predicting severity and outcomes of acute pancreatitis: a retrospective study

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Qing Wu ◽  
Jie Wang ◽  
Mengbin Qin ◽  
Huiying Yang ◽  
Zhihai Liang ◽  
...  
Keyword(s):  
Acute Pancreatitis ◽  
Organ Failure ◽  
Scoring System ◽  
Characteristic Curve ◽  
Failure Prediction ◽  
Scoring Systems ◽  
Mortality Prediction ◽  
Severity Prediction ◽  
Index Of Severity ◽  
Glasgow Score

Abstract Background Recently, several novel scoring systems have been developed to evaluate the severity and outcomes of acute pancreatitis. This study aimed to compare the effectiveness of novel and conventional scoring systems in predicting the severity and outcomes of acute pancreatitis. Methods Patients treated between January 2003 and August 2020 were reviewed. The Ranson score (RS), Glasgow score (GS), bedside index of severity in acute pancreatitis (BISAP), pancreatic activity scoring system (PASS), and Chinese simple scoring system (CSSS) were determined within 48 h after admission. Multivariate logistic regression was used for severity, mortality, and organ failure prediction. Optimum cutoffs were identified using receiver operating characteristic curve analysis. Results A total of 1848 patients were included. The areas under the curve (AUCs) of RS, GS, BISAP, PASS, and CSSS for severity prediction were 0.861, 0.865, 0.829, 0.778, and 0.816, respectively. The corresponding AUCs for mortality prediction were 0.693, 0.736, 0.789, 0.858, and 0.759. The corresponding AUCs for acute respiratory distress syndrome prediction were 0.745, 0.784, 0.834, 0.936, and 0.820. Finally, the corresponding AUCs for acute renal failure prediction were 0.707, 0.734, 0.781, 0.868, and 0.816. Conclusions RS and GS predicted severity better than they predicted mortality and organ failure, while PASS predicted mortality and organ failure better. BISAP and CSSS performed equally well in severity and outcome predictions.

scholarly journals Can Functional Performance Predict Long-Term Mortality Post Hip Fracture in Older Adults (65–100 Years of Age)?

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 268-268
Author(s):  
Rashmita Bajracharya ◽  
Denise Orwig ◽  
Jay Magaziner ◽  
Jack M Guralnik
Keyword(s):  
Hip Fracture ◽  
Grip Strength ◽  
Performance Measures ◽  
Gait Speed ◽  
Functional Performance ◽  
Underlying Disease ◽  
Prediction Of Mortality ◽  
Hazard Ratios ◽  
Long Term Mortality

Abstract Functional performance measures (grip strength, Short Physical Performance Battery (SPPB), and 3-meter gait speed) represent underlying disease progression and predict mortality. However, there is little information regarding whether these measures assessed at 2-months post-hip fracture predict long-term mortality (10-year follow-up). To address this gap, a longitudinal analysis of Baltimore Hip Studies-7 cohort, with mortality verified by National Death Index, was conducted. Mean difference in 2-month functional performance measures (n=242, men n=121, female n=121) among those who survived and did not survive over 10 years was determined using t-test. Prediction of mortality by these measures, overall and by sex, was estimated using cox proportional hazard models, for which Hazard ratios (HR) with 95% confidence intervals (CI) were estimated. We found that, gait speed [0.47(standard deviation,SD=0.39) versus 0.31(SD=0.27)] and SPPB score [4.89(SD=3.31) versus 2.83(SD=2.24)] were significantly higher at 2 months among those surviving compared to those who did not. Adjusting for covariates, functional performance predicted long-term mortality in men and women. Increase in gait speed by 0.1m/s predicted 15% decrease in mortality for men [HR=0.85(0.55-0.96)] and 17% for women [HR=0.83 (0.74-0.93)]. Increase in SPPB by 1 unit predicted decrease in mortality by 14% for men [HR=0.86(0.77-0.95)] and 17% for women [HR=0.83(0.74-0.93). Increase in grip strength by 1 kg predicted 5% decrease in mortality for men [HR=0.94(0.92-0.97)] and 9% for women [HR=0.90(0.86-0.95)]. Functional performance measured at 2-months post-hip fracture predicted long-term mortality. Those with poor functional performance at 2-months can be referred for further assessment to optimize their care to promote survival.

Abstract 15183: Do Two Scoring Systems of Coronary Stenosis, Syntax Score and Gensini Score, Similarly Predict Clinical Outcome After Pci in Patients With Stable Angina Pectoris?

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Naoto Murakami ◽  
Nobuaki Kokubu ◽  
Junichi Nishida ◽  
Mamoru Hase ◽  
Takefumi Fujito ◽  
...  
Keyword(s):  
Clinical Outcome ◽  
Coronary Stenosis ◽  
Characteristic Curve ◽  
Scoring Systems ◽  
Syntax Score ◽  
Heart Team ◽  
Gensini Score ◽  
The Mean ◽  
Stable Cad

Background: Few studies have examined if two score systems of coronary stenosis, SYNTAX score and Gensini score, are different as predictors of prognosis in patients with coronary artery disease (CAD). Here we examined this issue in patients with stable CAD after percutaneous coronary intervention (PCI). Methods: We retrospectively analyzed 795 consecutive patients who underwent coronary angiography for suspected stable CAD from January 2007 to August 2012. One hundred fifty-nine patients received PCI according to consensus of the Heart Team in our institute and patients’ consents. Overall severity of coronary stenosis and complexity in each patient was quantified by both the SYNTAX score and Gensini score, and patients were divided into high score group and low score group by the mean of the score in overall patients. Follow-up period was 15.9 ± 14.4 months, and MACE was defined as a composite of cardiac death, myocardial infarction, target vessel revascularization and/or congestive heart failure. Results: The mean SYNTAX score and Gensini score were 19.0 ± 12.4 and 47.8 ± 26.9, respectively. Long-term MACE in a group with high SYNTAX score (≧19, n=71) tended to be higher than a group with low SYNTAX score (<19, n=78), but not significant (Figure 1). However, long-term MACE was significantly higher in a group with high Gensini score (≧48, n=62) than that in a group with low Gensini score (<48, n=97) (Figure 2). In receiver operating characteristic curve analysis, optimal cut-off value of Gensini score to predict MACE was 66.5, of which sensitivity and specificity were 41.2% and 85.6%, respectively (area under curve 0.63, p=0.008). Conclusion: Gensini score is not inferior to SYNTAX in prediction of the clinical outcome after PCI in patients with stable CAD. Prognosis after PCI is favorable in patients with low Gensini score (especially those with GS<66.5).

scholarly journals A new approach to scoring systems to improve identification of acute medical admissions that will require critical care

2011 ◽  
Vol 56 (4) ◽  
pp. 195-202 ◽  
Author(s):  
H A Carmichael ◽  
E Robertson ◽  
J Austin ◽  
D Mccruden ◽  
C M Messow ◽  
...  
Keyword(s):  
Early Warning ◽  
Characteristic Curve ◽  
Medical Patient ◽  
Scoring Systems ◽  
Receiver Operator Characteristic Curve ◽  
Early Warning Score ◽  
Peripheral Oxygen Saturation ◽  
Logistic Regression Models ◽  
Prospective Application ◽  
Gas Measurements

Removal of the intensive care unit (ICU) at the Vale of Leven Hospital mandated the identification and transfer out of those acute medical admissions with a high risk of requiring ICU. The aim of the study was to develop triaging tools that identified such patients and compare them with other scoring systems. The methodology included a retrospective analysis of physiological and arterial gas measurements from 1976 acute medical admissions produced PREEMPT-1 (PRE-critical Emergency Medical Patient Triage). A simpler one for ambulance use (PREAMBLE-1 [PRE-Admission Medical Blue-Light Emergency]) was produced by the addition of peripheral oxygen saturation to a modification of MEWS (Modified Early Warning Score). Prospective application of these tools produced a larger database of 4447 acute admissions from which logistic regression models produced PREEMPT-2 and PREAMBLE-2, which were then compared with the original systems and seven other early warning scoring systems. Results showed that in patients with arterial gases, the area under the receiver operator characteristic curve was significantly higher in PREEMPT-2 (89·1%) and PREAMBLE-2 (84.4%) than all other scoring systems. Similarly, in all patients, it was higher in PREAMBLE-2 (92.4%) than PREAMBLE-1 (88.1%) and the other scoring systems. In conclusion, risk of requiring ICU can be more accurately predicted using PREEMPT-2 and PREAMBLE-2, as described here, than by other early warning scoring systems developed over recent years.

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