Dynamic Predictive Scores for Cardiac Surgery-Associated Agitated Delirium: a single-center retrospective observational study

Abstract Background Prevention, screening, and early treatment are the mainstays of postoperative delirium management. Score system is an objective and effective tool to stratify potential delirium risk for patients undergoing cardiac surgery Methods Patients undergoing cardiac surgery from January 1, 2012, to January 1, 2019, were enrolled in our retrospective study. The patients were divided into a derivation cohort (n = 45,744) and a validation cohort (n = 11,436). The agitated delirium (AD) predictive systems were formulated using multivariate logistic regression analysis at three time points: preoperation, ICU admittance, and 24 hours after ICU admittance. Results The prevalence of AD after cardiac surgery in the whole cohort was 3.6% (2,085/57,180). The dynamic scoring system included preoperative LVEF ≤ 45%, serum creatinine > 100 umol/L, emergency surgery, coronary artery disease, hemorrhage volume > 600 mL, intraoperative platelet or plasma use, and postoperative LVEF ≤ 45%. The area under the receiver operating characteristic curve (AUC) values for AD prediction of 0.68 (preoperative), 0.74 (on the day of ICU admission), and 0.75 (postoperative). The Hosmer-Lemeshow test indicated that the calibration of the preoperative prediction model was poor (P = 0.01), whereas that of the pre- and intraoperative prediction model (P = 0.49) and the pre-, intra- and postoperative prediction model (P = 0.35) was good. Conclusions Using perioperative data, we developed a dynamic scoring system for predicting the risk of AD following cardiac surgery. The dynamic scoring system may improve early recognition of and interventions for AD.

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188 Predicting Posttraumatic Hydrocephalus: Derivation and Validation of a Risk Scoring System Based on Clinical Characteristics

Neurosurgery ◽

10.1093/neuros/nyx417.188 ◽

2017 ◽

Vol 64 (CN_suppl_1) ◽

pp. 250-250

Author(s):

Hao Chen

Keyword(s):

High Risk ◽

Scoring System ◽

Clinical Characteristics ◽

Injury Severity ◽

Characteristic Curve ◽

Derivation Cohort ◽

Radiologic Findings ◽

Fisher Grade ◽

Risk Scoring ◽

Risk Scoring System

Abstract INTRODUCTION Posttraumatic hydrocephalus (PTH) is a common complication of traumatic brain injury (TBI) and often has a high risk of clinical deterioration and worse outcomes. The incidence and risk factors for the development of PTH after decompressive craniectomy (DC) has been assessed in previous studies, but rare studies identify patients with higher risk for PTH among all TBI patients. This study aimed to develop and validate a risk scoring system to predict PTH after TBI. METHODS Demographics, injury severity, duration of coma, radiologic findings, and DC were evaluated to determine the independent predictors of PTH during hospitalization until 6 months following TBI through logistic regression analysis. A risk stratification system was created by assigning a number of points for each predictor and validated both internally and externally. The model accuracy was assessed by the area under the receiver operating characteristic curve (AUC). RESULTS >Of 526 patients in the derivation cohort, 57 (10.84%) developed PTH during 6 months follow up. Age >50 (Odd ratio [OR] = 1.91, 95% confidence interval [CI] 1.09 3.75, 4 points), duration of coma = 1 w (OR = 5.68, 95% CI 2.57 13.47, 9 points), Fisher grade III (OR = 2.19, 95% CI 1.24 4.36, 5 points) or IV (OR = 3.87, 95% CI 1.93 8.43, 7 points), bilateral DC (OR = 6.13, 95% CI 2.82 18.14, 9 points), and extra herniation after DC (OR = 2.36, 95% CI 1.46 4.92, 5 points) were independently associated with PTH. Rates of PTH for the low- (0-12 points), intermediate- (13-22 points) and high-risk (23-34 points) groups were 1.16%, 35.19% and 78.57% (P < 0.0001). The corresponding rates in the validation cohort, where 17/175 (9.71%) developed PTH, were 1.35%, 37.50% and 81.82% (P < 0.0001). The risk score model exhibited good-excellent discrimination in both cohorts, with AUC of 0.839 versus 0.894 (derivation versus validation) and good calibration (Hosmer-Lemshow P = 0.56 versus 0.68). CONCLUSION A risk scoring system based on clinical characteristics accurately predicted PTH. This model will be useful to identify patients at high risk for PTH who may be candidates for preventive interventions, and to improve their outcomes.

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Prediction Scores for Acute Kidney Injury following Adult Cardiac Surgery

10.21203/rs.3.rs-88293/v1 ◽

2020 ◽

Author(s):

Yu Tian ◽

Wei Zhao ◽

Yuefu Wang ◽

Chunrong Wang ◽

Xiaolin Diao ◽

...

Keyword(s):

Acute Kidney Injury ◽

Cardiac Surgery ◽

Prediction Model ◽

Prediction Models ◽

Area Under The Curve ◽

Kidney Injury ◽

Scoring Systems ◽

Multivariable Logistic Regression Analysis ◽

Derivation Cohort ◽

Associated Risk Factors

Abstract Background In the development of scoring systems for acute kidney injury (AKI) following cardiac surgery, previous investigations have primarily and solely attached importance to preoperative associated risk factors without any consideration for surgery-derived physiopathology. We sought to internally derive and then validate risk score systems using pre- and intraoperative variables to predict the occurrence of any-stage (stage 1-3) and stage-3 AKI within 7 days.Methods Patients undergoing cardiac surgery from Jan 1, 2012, to Jan 1, 2019, were enrolled in our retrospective study. The clinical data were divided into a derivation cohort (n= 43799) and a validation cohort (n= 14600). Multivariable logistic regression analysis was used to develop the prediction models.Results The overall prevalence of any-stage and stage-3 AKI after cardiac surgery was 34.3% and 1.7%, respectively. Any-stage AKI prediction-model discrimination measured by the area under the curve (AUC) was acceptable (AUC = 0.69, 95% CI: 0.68, 0.69), and the prediction model calibration measured by the Hosmer-Lemshow test was good (P = 0.95). The stage-3 AKI prediction model had an AUC of 0.84 (95% CI 0.83, 0.85) and good calibration according to the Hosmer-Lemshow test (P = 0.73).Conclusions Using pre- and intraoperative data, we developed two scoring systems for any-stage AKI and stage-3 AKI in a cardiac surgery population. These scoring systems can potentially be adopted clinically in the field of AKI recognition and therapeutic intervention.

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A Prediction Model Based on DNA Methylation Biomarkers and Radiological Characteristics for Identifying Malignant From Benign Pulmonary Nodules

10.21203/rs.3.rs-97310/v1 ◽

2020 ◽

Author(s):

Wenqun Xing ◽

Haibo Sun ◽

Chi Yan ◽

Chengzhi Zhao ◽

Dongqing Wang ◽

...

Keyword(s):

Lung Cancer ◽

Dna Methylation ◽

Prediction Model ◽

Characteristic Curve ◽

Multivariate Logistic Regression Analysis ◽

Pulmonary Nodules ◽

Diagnostic Value ◽

Receiver Operator Characteristic Curve ◽

Model Based ◽

Diagnosis Of Lung Cancer

Abstract BackgroundLung cancer remains the leading cause of cancer deaths across the world. Early detection of lung cancer by low-dose computed tomography (LDCT) can reduce the mortality rate. However, making a definitive preoperative diagnosis of malignant pulmonary nodules (PNs) found by LDCT is a clinical challenge. This study aimed to develop a prediction model based on DNA methylation biomarkers and radiological characteristics for identifying malignant pulmonary nodules from benign PNs. MethodsWe assessed three DNA methylation biomarkers (PTGER4, RASSF1A, and SHOX2) in a training cohort of 110 individuals with PNs. Using univariate and multivariate logistic regression analysis, we developed a prediction model based on the three DNA methylation biomarkers and one radiological characteristic for identifying malignant from benign PNs. The performance of the prediction model with that of the methylation biomarkers and the Mayo Clinic model were compared using the non-parametric approach of DeLong et al. with the area under a receiver operator characteristic curve (AUC) analysis. ResultsThe developed prediction model achieved a sensitivity of 87.3% and a specificity of 95.7% with an AUC value of 0.951 in malignant PNs diagnosis, being significantly higher than the three DNA methylation biomarkers (84.1% sensitivity and 89.4% specificity, p=0.013) or clinical/radiological characteristics (76.2% sensitivity and 87.2% specificity, p=0.001) alone. Validation of the prediction model in the testing cohort of 100 subjects with PNs confirmed the diagnostic value.ConclusionWe have shown that integrating DNA methylation biomarkers and radiological characteristics could more accurately identify lung cancer in subjects with CT-found PNs. The prediction model developed in our study may provide clinical utility in combination with LDCT to improve the over-all diagnosis of lung cancer.

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Development and validation of a new scoring system for prognostic prediction of community-acquired pneumonia in older adults

Scientific Reports ◽

10.1038/s41598-021-03440-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Masahiro Shirata ◽

Isao Ito ◽

Tadashi Ishida ◽

Hiromasa Tachibana ◽

Naoya Tanabe ◽

...

Keyword(s):

Confidence Interval ◽

Scoring System ◽

Older Patients ◽

Characteristic Curve ◽

External Validation ◽

Albumin Level ◽

Community Acquired Pneumonia ◽

Derivation Cohort ◽

Prognostic Prediction ◽

New Scoring

AbstractThe discriminative power of CURB-65 for mortality in community-acquired pneumonia (CAP) is suspected to decrease with age. However, a useful prognostic prediction model for older patients with CAP has not been established. This study aimed to develop and validate a new scoring system for predicting mortality in older patients with CAP. We recruited two prospective cohorts including patients aged ≥ 65 years and hospitalized with CAP. In the derivation (n = 872) and validation cohorts (n = 1,158), the average age was 82.0 and 80.6 years and the 30-day mortality rate was 7.6% (n = 66) and 7.4% (n = 86), respectively. A new scoring system was developed based on factors associated with 30-day mortality, identified by multivariate analysis in the derivation cohort. This scoring system named CHUBA comprised five variables: confusion, hypoxemia (SpO2 ≤ 90% or PaO2 ≤ 60 mmHg), blood urea nitrogen ≥ 30 mg/dL, bedridden state, and serum albumin level ≤ 3.0 g/dL. With regard to 30-day mortality, the area under the receiver operating characteristic curve for CURB-65 and CHUBA was 0.672 (95% confidence interval, 0.607–0.732) and 0.809 (95% confidence interval, 0.751–0.856; P < 0.001), respectively. The effectiveness of CHUBA was statistically confirmed in the external validation cohort. In conclusion, a simpler novel scoring system, CHUBA, was established for predicting mortality in older patients with CAP.

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Performance of the EuroSCORE II and the STS score for cardiac surgery in octogenarians

Turkish Journal of Thoracic and Cardiovascular Surgery ◽

10.5606/tgkdc.dergisi.2021.21403 ◽

2021 ◽

Vol 29 (2) ◽

pp. 174-182

Author(s):

Hüseyin Kuplay ◽

Sevinç Bayer Erdoğan ◽

Murat Baştopçu ◽

Eren Karpuzoğlu ◽

Halit Er

Keyword(s):

Cardiac Surgery ◽

Scoring System ◽

Characteristic Curve ◽

Area Under The Curve ◽

Population Based ◽

Mortality Prediction ◽

Urgent Surgery ◽

Significant Difference ◽

Sts Score ◽

The Mean

Background: We aimed to investigate the predictive value of Society of Thoracic Surgeons (STS) and European System for Cardiac Operative Risk Evaluation (EuroSCORE II) scores for mortality in octogenarian cardiac surgery patients. Methods: Between January 2016 and December 2019, cardiac operations performed in 116 octogenarian patients (73 males, 43 females; mean age: 82.9±3.1 years; range, 80 to 97 years) were retrospectively analyzed. The patients with and without mortality were compared for their demographic and operative factors. The STS and EuroSCORE II scores, and observed mortality rates were assessed. Results: Mean STS score was 3.7±11.1 and mean EuroSCORE II was 5.2±5.4. For any operation type, the mean EuroSCORE II was significantly higher (8.1±7.4 vs. 4.1±4.0, respectively; p=0.006) in the patients with mortality. For elective operations, the mean EuroSCORE II was higher in cases with mortality (7.2±7.3 vs. 3.7±3.9, respectively; p=0.006); however, for urgent cases, there was no significant difference between the scores. Using the receiver operating characteristic curve, the EuroSCORE II had a higher area under the curve for all cases and elective cases than the STS scores. Conclusion: The EuroSCORE II performed better than the STS score for mortality prediction in octogenarians, whereas the predictions of either scoring system was unsatisfactory for urgent surgery and combined procedures. Population-based validation studies are needed for a better risk scoring system in this age group.

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A novel scoring system for assessing the severity of electrolyte and acid-base disorders and predicting outcomes in hospitalized patients

Journal of Investigative Medicine ◽

10.1136/jim-2018-000900 ◽

2018 ◽

Vol 67 (4) ◽

pp. 750-760

Author(s):

Yimei Wang ◽

Jiachang Hu ◽

Xuemei Geng ◽

Xiaoyan Zhang ◽

Xialian Xu ◽

...

Keyword(s):

Risk Score ◽

Scoring System ◽

Validation Cohort ◽

Characteristic Curve ◽

Multiple Logistic Regression Analysis ◽

Survival Rates ◽

Hospitalized Patients ◽

Hospital Death ◽

Acid Base ◽

Derivation Cohort

Electrolyte and acid-base disorders are commonly seen in critically ill and other hospitalized patients. A scoring system is needed to assess the severity of electrolyte and acid-base disorders and to predict outcome in hospital patients. Herein, we prospectively enrolled a total of 322,046 patients, including 84,700 patients in the derivation cohort and 237,346 in the validation cohort, in a large, tertiary hospital in East China from 2014 to 2017. A points-scoring system of general electrolyte and acid-base disorders with a sum of 20.8 points was generated by multiple logistic regression analysis of the derivation cohort. Receiver operating characteristic curve analysis showed that the optimal cut-off value of 2.0 was associated with 65.4% sensitivity and 88.4% specificity (area under the curve: 0.818 (95% CI 0.809 to 0.827)) to predict hospital mortality in the validation cohort. On Kaplan-Meier survival analysis, the five intervals of risk score (Q1: 0 to 2.0; Q2: 2.1 to 2.5; Q3: 2.6 to 3.3; Q4: 3.4 to 4.5; and Q5: >4.5 points) showed differences in hospital survival (p<0.001). Elevated (delta) risk score >2 during hospitalization increased the risk of hospital death, while those with a delta risk score <0 and <−2 points had higher survival rates. This novel scoring system could be used to evaluate and to dynamically monitor the severity of electrolyte and acid-base disorders in hospitalized patients.

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Prediction of progression of interstitial lung disease in patients with systemic sclerosis: the SPAR model

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2018-213201 ◽

2018 ◽

Vol 77 (9) ◽

pp. 1326-1332 ◽

Cited By ~ 38

Author(s):

Wanlong Wu ◽

Suzana Jordan ◽

Mike Oliver Becker ◽

Rucsandra Dobrota ◽

Britta Maurer ◽

...

Keyword(s):

Systemic Sclerosis ◽

Interstitial Lung Disease ◽

Prediction Model ◽

Lung Disease ◽

Validation Cohort ◽

Pulmonary Function Tests ◽

Characteristic Curve ◽

Airflow Obstruction ◽

Derivation Cohort

ObjectivesTo identify the predictive clinical characteristics and establish a prediction model for the progression of mild interstitial lung disease (ILD) in patients with systemic sclerosis (SSc).MethodsPatients with SSc from two independent prospective cohorts were included in this observational study. All patients fulfilled the 2013 American College of Rheumatology/European League Against Rheumatism criteria, had mild ILD at baseline diagnosed by High-Resolution Computed Tomography (HRCT), available baseline and ≥1 annual follow-up pulmonary function tests and no concomitant pulmonary hypertension or airflow obstruction. ILD progression was defined as a relative decrease in forced vital capacity (FVC)%≥15%, or FVC%≥10% combined with diffusing capacity for carbon monoxide %≥15% at 1-year follow-up. Candidate predictors for multivariate logistic regression were selected by expert opinion based on clinical significance. A prediction model for ILD progression was established in the derivation cohort and validated in the multinational validation cohort.ResultsA total of 25/98 and 25/117 patients with SSc showed ILD progression in the derivation cohort and the validation cohort, respectively. Lower SpO2 after 6 min walk test (6MWT) and arthritis ever were identified as independent predictors for ILD progression in both cohorts. The optimal cut-off value of SpO2 after 6MWT for predicting ILD progression was determined as 94% by receiver operating characteristic curve analysis. The derived SPAR model combining both predictors (SPO2 and ARthritis) increased the prediction rate from 25.5% to 91.7% with an area under the curve (95% CI) of 0.83 (0.73 to 0.93).ConclusionsThe evidence-based SPAR prediction model developed in our study might be helpful for the risk stratification of patients with mild SSc-ILD in clinical practice and cohort enrichment for future clinical trial design.

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Validation of Cardiac Surgery Score (CASUS) in Postoperative Cardiac Patients

Seminars in Cardiothoracic and Vascular Anesthesia ◽

10.1177/1089253220936786 ◽

2020 ◽

Vol 24 (4) ◽

pp. 304-312

Author(s):

Sarah Raut ◽

Azar Hussain ◽

Priyadharshanan Ariyaratnam ◽

Ananthakrishnan Ananthasayanam ◽

Ajith Vijayan ◽

...

Keyword(s):

Cardiac Surgery ◽

Intensive Care ◽

Scoring System ◽

Characteristic Curve ◽

Scoring Systems ◽

Apache Ii ◽

Cardiac Patients ◽

Research Centre ◽

Logistic Euroscore ◽

Cardiac Operative Risk Evaluation

Introduction. Cardiac Surgery Score (CASUS) was introduced in 2005 as the first postoperative scoring system specific for patients who had cardiac surgery. Prior to this, European System for Cardiac Operative Risk Evaluation (EuroSCORE) has been used preoperatively, while Intensive Care National Audit and Research Centre Score (ICNARC) and Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, which are widely used in general intensive care unit population, have been used to score cardiac patients postoperatively. The development of CASUS by Hekmat and colleagues for use in postoperative cardiac patients aims to change this. We wanted to validate CASUS against the well-established preoperative Logistic EuroSCORE, and postoperative APACHE II and ICNARC scores. Method. Institutional approval for this study was granted by the Audit and Clinical Governance Committee. We analyzed prospectively collected data of patients who had cardiac surgery in Castle Hill Hospital between January 2016 and September 2018. All patients who underwent surgery in the unit would have had Logistic EuroSCORE, APACHE, and ICNARC scores calculated as standard. CASUS was then calculated for these patients based on their day 1 postoperative variables. The scoring systems were compared and data presented as area under the receiver operating characteristic curve. Result. Our study shows that CASUS is the best predictor of mortality followed by ICNARC, Logistic EuroSCORE, and APACHE II. ICNARC score remains the most accurate predictor of renal and pulmonary complication followed by CASUS. Conclusion. CASUS is a useful scoring system in post-cardiac surgery patients. The accuracy of CASUS and ICNARC scores in predicting mortality, pulmonary, and renal complications are comparable.

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Early recognition of cardiac surgery-associated acute kidney injury: lack of added value of TIMP2 IGFBP7 over short-term changes in creatinine (an observational pilot study)

BMC Anesthesiology ◽

10.1186/s12871-021-01387-6 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Karim Lakhal ◽

Edith Bigot-Corbel ◽

Emilie Sacchetto ◽

Floris Chabrun ◽

Thomas Senage ◽

...

Keyword(s):

Acute Kidney Injury ◽

Cardiac Surgery ◽

Early Recognition ◽

Characteristic Curve ◽

Kidney Injury ◽

Primary Objective ◽

Added Value ◽

Tissue Inhibitor Of Metalloproteinase ◽

Neutrophil Gelatinase Associated Lipocalin ◽

Postoperative Changes

Abstract Background For the detection of cardiac surgery-associated acute kidney injury (CS-AKI), the performance of urine tissue inhibitor of metalloproteinase 2 insulin-like growth factor-binding protein 7 (TIMP2 IGFBP7) has never been compared with that of very early changes in plasma creatinine (∆pCr). We hypothesized that, in the context of perioperative haemodilution, lack of postoperative decrease in pCr would be of honourable performance for the detection of CS-AKI. We therefore aimed at comparing these biomarkers and their kinetics (primary objective). As secondary objectives, we assessed plasma neutrophil gelatinase-associated lipocalin (pNGAL), cystatin C (pCysC) and urea (pUrea). We also determined the ability of these biomarkers to early discriminate persistent from transient CS-AKI. Methods Patients over 75 years-old undergoing aortic valve replacement with cardiopulmonary bypass (CPB) were included in this prospective observational study. Biomarkers were measured before/after CPB and at the sixth postoperative hour (H6). Results In 65 patients, CS-AKI occurred in 27 (42%). ∆pCr from post-CPB to H6 (∆pCrpostCPB-H6): outperformed TIMP2 IGFBP7 at H6 and its intra- or postoperative changes: area under the receiver operating characteristic curve (AUCROC) of 0.84 [95%CI:0.73–0.92] vs. ≤0.67 [95%CI:0.54–0.78], p ≤ 0.03. The AUCROC of pNGAL, pCysC and pUrea did not exceed 0.72 [95%CI:0.59–0.83]. Indexing biomarkers levels for blood or urine dilution did not improve their performance. Combining TIMP2 IGFBP7 and ∆pCrpostCPB-H6 was of no evident added value over considering ∆pCrpostCPB-H6 alone. For the early recognition of persistent CS-AKI, no biomarker outperformed ∆pCrpostCPB-H6 (AUCROC = 0.69 [95%CI:0.48–0.85]). Conclusions In this hypothesis-generating study mostly testing early detection of mild CS-AKI, there was no evident added value of the tested modern biomarkers over early minimal postoperative changes in pCr: despite the common perioperative hemodilution in the setting of cardiac surgery, if pCr failed to decline within the 6 h after CPB, the development of CS-AKI was likely. Confirmatory studies with more severe forms of CS-AKI are required.

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Developing and validating a model for predicting 7-day mortality of patients admitted from the emergency department: an initial alarm score by a prospective prediction model study

BMJ Open ◽

10.1136/bmjopen-2020-040837 ◽

2021 ◽

Vol 11 (1) ◽

pp. e040837

Author(s):

Ming-Ju Hsieh ◽

Nin-Chieh Hsu ◽

Yu-Feng Lin ◽

Chin-Chung Shu ◽

Wen-Chu Chiang ◽

...

Keyword(s):

Emergency Department ◽

Hospital Mortality ◽

Prediction Model ◽

Predictive Value ◽

Cancer Metastasis ◽

Validation Cohort ◽

Characteristic Curve ◽

Model Development ◽

Medical Patients ◽

Derivation Cohort

ObjectivesTo set up a prediction model for the 7-day in-hospital mortality of patients admitted from the emergency department (ED) because it is high but no appropriate initial alarm score is available.DesignThis is a prospective cohort study for prediction model development.SettingIn a tertiary referred hospital in northern Taiwan.ParticipantsED-admitted medical patients in hospitalist care wards were enrolled during May 2010 to October 2016. Two-thirds of them were randomly assigned to a derivation cohort for development of the model and cross-validation was performed in the validation cohort.Primary outcome measured7-day in-hospital mortality.ResultsDuring the study period, 8649 patients were enrolled for analysis. The mean age was 71.05 years, and 51.91% were male. The most common admission diagnoses were pneumonia (36%) and urinary tract infection (20.05%). In the derivation cohort, multivariable Cox proportional hazard regression revealed that a low Barthel Index Score, triage level 1 at the ED, presence of cancer, metastasis and admission diagnoses of pneumonia and sepsis were independently associated with 7 days in-hospital mortality. Based on the probability developed from the multivariable model, the area under the receiver operating characteristic curve in the derivation group was 0.81 (0.79–0.85). The result in the validation cohort was comparable. The prediction score modified by the six independent factors had high sensitivity of 88.03% and a negative predictive value of 99.51% for a cut-off value of 4, whereas the specificity and positive predictive value were 89.61% and 10.55%, respectively, when the cut-off value was a score of 6.ConclusionThe 7-day in-hospital mortality in the hospitalist care ward is 2.8%. The initial alarm score could help clinicians to prioritise or exclude patients who need urgent and intensive care.

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