The performance of qSOFA as a prognostic tool for early prediction of high-risk infective endocarditis

275 Background: Oncologists often struggle to know which patients are near end of life to enable a timely transition to supportive care. We developed a breast cancer-specific prognostic tool, using electronic health record data from CancerLinQ Discovery (CLQD), to help identify patients at high risk of near-term death. We created multiple candidate models with varying thresholds for defining high risk that will be considered for future clinical use. Methods: We included patients with breast cancer diagnosed between 1/1/2000 to 6/1/2020 who had at least one encounter with vital signs and evidence of metastatic breast cancer (MBC). All encounters from 1/1/2000 to 7/5/2020 were included. We used multiple imputation (MI) to impute missing numeric variables and treated missing values as a new level for categorical variables. We sampled one encounter per patient and oversampled within 30 days of death, so that the event rate (death within 30 days of encounter) was about 10%. We randomly divided these patients into training (70%) and test datasets (30%). We evaluated candidate predictors of the event using logistic regression with forward variable selection. Candidate predictors included age, vital signs, laboratory values, performance status, pain score, time since chemotherapy, and ER/PR/HER2 receptor status, and change from baseline and change rate of numeric variables. We obtained a single final model by combining resulted logistic regression model from 10 MI training sets. We evaluated this final model on the MI test sets. We varied the alert threshold (i.e., high-risk proportion) from 5% to 40%. Results: We identified 9,270 patients, representing 586,801 encounters. Significant predictors of mortality were: increased age, decreased age at diagnosis, negative change in body mass index, low albumin, high ALP, high AST, high WBC, low sodium, high creatinine, worse performance status, low pulse oximetry, increased age with increased creatinine, high pain score with no opiates, increased pulse rate, unknown/missing PR, opiate use in past 3 months, and prior chemotherapy in past 1 year but not past 30 days. Candidate models had prediction accuracy of 70-89% and positive predictive value of 31-77%. Conclusions: Demographic and clinical variables can be used to predict risk of death within 30 days of a clinical encounter for patients with MBC. Next steps include selection of a preferred model for clinical use, balancing performance characteristics and acceptability, followed by implementation and evaluation of the prognostic tool in the clinic. Candidate models, varying by threshold or percentage of patients assumed to be at high risk, for the outcome of death within 30 days among patients with metastatic breast cancer.[Table: see text]

Download Full-text

Early Prediction of Multiple Organ Dysfunction in the Pediatric Intensive Care Unit

Frontiers in Pediatrics ◽

10.3389/fped.2021.711104 ◽

2021 ◽

Vol 9 ◽

Author(s):

Sanjukta N. Bose ◽

Joseph L. Greenstein ◽

James C. Fackler ◽

Sridevi V. Sarma ◽

Raimond L. Winslow ◽

...

Keyword(s):

High Risk ◽

Random Forest ◽

Positive Predictive Value ◽

Organ Dysfunction ◽

Predictive Value ◽

Prediction Models ◽

Pediatric Intensive Care ◽

Multiple Organ ◽

High Risk Group ◽

Early Prediction

Objective: The objective of the study is to build models for early prediction of risk for developing multiple organ dysfunction (MOD) in pediatric intensive care unit (PICU) patients.Design: The design of the study is a retrospective observational cohort study.Setting: The setting of the study is at a single academic PICU at the Johns Hopkins Hospital, Baltimore, MD.Patients: The patients included in the study were <18 years of age admitted to the PICU between July 2014 and October 2015.Measurements and main results: Organ dysfunction labels were generated every minute from preceding 24-h time windows using the International Pediatric Sepsis Consensus Conference (IPSCC) and Proulx et al. MOD criteria. Early MOD prediction models were built using four machine learning methods: random forest, XGBoost, GLMBoost, and Lasso-GLM. An optimal threshold learned from training data was used to detect high-risk alert events (HRAs). The early prediction models from all methods achieved an area under the receiver operating characteristics curve ≥0.91 for both IPSCC and Proulx criteria. The best performance in terms of maximum F1-score was achieved with random forest (sensitivity: 0.72, positive predictive value: 0.70, F1-score: 0.71) and XGBoost (sensitivity: 0.8, positive predictive value: 0.81, F1-score: 0.81) for IPSCC and Proulx criteria, respectively. The median early warning time was 22.7 h for random forest and 37 h for XGBoost models for IPSCC and Proulx criteria, respectively. Applying spectral clustering on risk-score trajectories over 24 h following early warning provided a high-risk group with ≥0.93 positive predictive value.Conclusions: Early predictions from risk-based patient monitoring could provide more than 22 h of lead time for MOD onset, with ≥0.93 positive predictive value for a high-risk group identified pre-MOD.

Download Full-text

Corrigendum to: Incidence of infective endocarditis among patients considered at high risk

European Heart Journal ◽

10.1093/eurheartj/ehy001 ◽

2018 ◽

Vol 39 (25) ◽

pp. 2367-2367

Keyword(s):

Infective Endocarditis ◽

High Risk

Download Full-text

Abstract 19639: Infective Endocarditis Following Transcatheter Valve Implantation: A Systematic Review

Circulation ◽

10.1161/circ.130.suppl_2.19639 ◽

2014 ◽

Vol 130 (suppl_2) ◽

Author(s):

Ignacio J Amat-Santos ◽

Henrique B Ribeiro ◽

Marina Urena ◽

Ricardo Allende ◽

Cristine Houde ◽

...

Keyword(s):

Infective Endocarditis ◽

High Risk ◽

Hospital Mortality ◽

Risk Profile ◽

Electronic Search ◽

Transcatheter Valve ◽

Few Data ◽

Valve Implantation ◽

Transcatheter Valves ◽

Very High

Objectives: To describe the incidence, features, predisposing factors and outcomes of infective endocarditis (IE) following transcatheter valve implantation (TVI). Background: Very few data exist on IE following TVI. Methods: Studies published between 2000 and 2013 regarding IE in patients with aortic (TAVI) or pulmonary (TPVI) transcatheter valves were identified through systematic electronic search. Result: A total of 28 publications describing 60 patients (32 TAVI, 28 TPVI) were identified. Most TAVI patients (66% males, 80±7 years) had a very high-risk profile (LogEuroSCORE: 30.4±14.0%, p<0.001 compared to previous TAVI registries). In TPVI patients (90% males, 19±6 years), IE was more frequent in stenotic conduit/valve (61%) (p <0.001 vs. previous TPVI series). Median time between TVI and IE was 5.5 (2-12) months. Typical microorganisms were mostly found with a higher incidence of enterococci after TAVI (34.4% vs. 0%, p =0.009), and S.aureus after TPVI (29.4% vs. 6.2%, p =0.041). Up to 60% of the TAVI-IE patients were managed medically despite related complications such as local extension, embolism and/or heart failure in >50% of patients. Valve explantation rate was 57% and 23% in balloon- and self-expandable valves, respectively (p=0.07). In-hospital mortality for TAVI-IE was 34.4%. Most TPVI-IE patients (75%) were managed surgically, and in-hospital mortality was 7.1%. Conclusions: Most cases of IE post-TVI were males, with a very high-risk profile (TAVI) or underlying stenotic conduit/valve (TPVI). Typical -but different- microorganisms of IE were involved in half of the TAVI and TPVI cases. Most TPVI-IE patients were managed surgically as opposed to TAVI patients, and mortality rate was high in both cohorts.

Download Full-text

SHARPEN score accurately predict in-hospital mortality in infective endocarditis: a real-world validation study

European Heart Journal ◽

10.1093/ehjci/ehaa946.2023 ◽

2020 ◽

Vol 41 (Supplement_2) ◽

Author(s):

S.G Alves ◽

F.B Filippini ◽

G.P Dannenhauer ◽

G Seroiska ◽

L.F.S Birk ◽

...

Keyword(s):

Multivariate Analysis ◽

Cardiac Surgery ◽

Infective Endocarditis ◽

High Risk ◽

Hospital Mortality ◽

Rank Test ◽

C Statistic ◽

Kaplan Meier ◽

Duke Criteria ◽

High Negative Predictive Value

Abstract Background Infective Endocarditis (IE) has impressive 30-day mortality of up to 30%. Prompt recognition of high-risk patients is required in order to optimize management and outcomes. The SHARPEN score was recently developed to predict intrahospital mortality in patients admitted due to IE, regardless of the need to undergo cardiac surgery. We aimed to evaluate the accuracy of the SHARPEN score to predict in-hospital mortality in comparison to Charlson Comorbidity Index (CCI). Methods Retrospective cohort of all consecutive adult admissions between 2000 and 2016 with diagnosis of definitive IE according to the Modified Duke Criteria. The SHARPEN score was applied comprising: Systolic blood pressure at presentation, Heart failure, Age, Raised creatinine, Pneumonia, Elevated peak CRP and Non-intravenous drug abuser. The CCI was applied to assess comorbidities. Accuracy in predict mortality was estimated with C-statistic. DeLong test was used to compare the areas under the curve (AUC). Survival probabilities were estimated by Kaplan-Meier method and differences between survival curves analyzed using the log-rank test. Multivariate analysis using Poisson Regression with robust variation was performed to determine independent predictors of in-hospital mortality. Results 179 cases of IE were registered (70% male; 55±17 years-old) with an in-hospital mortality of 22%. Cardiac surgery was required in 68 (38%) of the patients. Calculated SHARPEM and CCI scores were 9 (7–11) and 3 (1–6) points respectively. SHARPEN was able to predict in-hospital mortality with an AUC of 0.76 (95% CI 0.7–0.8; p<0.001) and cut-off >10 points (Sen=69%; Sp=71%; PPV=40%; NPV=89%). Mortality was significant higher (40% vs 11%; p<0.001) in patients with SHARPEN >10 points (FIGURE). CCI had a similar AUC of 0.7 (95% CI 0.6 - 0.8; p<0.001) with SHARPEN (p=0.32). However, in a multivariate analysis, SHARPEN score >10 points a stronger predictor related with in-hospital mortality (OR 2.3; 95% CI 1.1 - 4.8; p=0.03) in comparison to CCI >3 points (OR 1.4; 95% CI 0.7–2.8; p=0.3). Conclusion SHARPEN score demonstrated a good accuracy in predict in-hospital mortality independently of other variables, with a high negative predictive value. These findings suggest that SHARPEN score may be useful to stratify high-risk IE patients in a clinical setting. Funding Acknowledgement Type of funding source: None

Download Full-text

The use of antibiotic prophylaxis in radiology departments for patients at high-risk of infective endocarditis

Clinical Radiology ◽

10.1016/s0009-9260(96)80061-4 ◽

1996 ◽

Vol 51 (9) ◽

pp. 649-650 ◽

Cited By ~ 1

Author(s):

D.C. Howlett ◽

P.N. Malcolm ◽

P.L. Scott-Mackie ◽

A.B. Ayers

Keyword(s):

Infective Endocarditis ◽

High Risk ◽

Antibiotic Prophylaxis

Download Full-text

Prognostic Indices in Older DLBCL Patients Receiving R-CHOP: An Analysis of the U.S. Intergroup Study (E4494, CALGB 9793).

Blood ◽

10.1182/blood.v108.11.813.813 ◽

2006 ◽

Vol 108 (11) ◽

pp. 813-813

Author(s):

R.H. Advani ◽

H. Chen ◽

T.M. Habermann ◽

V.A. Morrison ◽

E. Weller ◽

...

Keyword(s):

Overall Survival ◽

High Risk ◽

Univariate Analysis ◽

Risk Groups ◽

Low Risk ◽

Risk Category ◽

Free Survival ◽

Prognostic Tool ◽

The Impact ◽

The U.S

Abstract Background: We reported that addition of rituximab (R) to chemotherapy significantly improves outcome in DLBCL patients (pt) >60 years (JCO24:3121–27, 2006). Although the IPI is a robust clinical prognostic tool in DLBCL, Sehn et al (ASH 2005: abstract 492) reported that a revised (R) IPI more accurately predicted outcome in pt treated with rituximab-chemotherapy. Methods: We evaluated outcomes of the Intergroup study with respect to the standard IPI, R-IPI, age-adjusted (aa) IPI for evaluable pt treated with R-CHOP alone or with maintenance rituximab. We further assessed a modified IPI (mIPI) using age ≥ 70 y as a cutoff rather than age 60 y. Results: The 267 pt in this analysis were followed for a median of 4 y. Pt characteristics were: age > 70 (48%) (median=69), male 52%, stage III/IV 75%, >1 EN site 30%, LDH elevated 60%, PS ≥2 15%. On univariate analysis all of these characteristics were significant for 3 y failure-free survival (FFS) and overall survival (OS). The IPI provided additional discrimination of risk compared to the R-IPI with significant differences in FFS and OS for 3 vs 4–5 factors. The aa-IPI defined relatively few pt as low or high risk. The impact of age was studied using a cut-off of 70 years in a modified IPI, yielding 4 risk groups as shown below. Conclusions: For pt ≥ 60 treated with rituximab-chemotherapy the distinction between 3 vs 4,5 factors in the IPI was significant.The IPI also provided additional discrimination of risk compared to the R-IPI. In this older group of pt, use of an age cutoff ≥70 y placed more patients in the low risk category. It is of interest to apply the mIPI in other datasets with DLBCL pt >60 y. Group # Factors # Pt % 3y FFS* % 3y OS* *All risk groups significantly different; logrank p < 0.001 **95 % CI: FFS (0.46,0.66), OS (0.58,0.78) ***95 % CI: FFS (0.21,0.45), OS (0.31,0.55) L: Low, LI: Low Intermediate, HI: High Intermediate, H; High IPI L 0–1 12 78 83 LI 2 28 70 80 HI 3 33 56** 68** H 4–5 37 33*** 43*** R-IPI Very Good 0 0 - - Good 1–2 40 72 81 Poor 3–5 60 46 57 aa-IPI L 0 12 78 83 LI 1 35 68 78 HI 2 44 47 59 H 3 9 31 35 mIPI (age ≥ 70) L 0–1 27 77 86 LI 2 28 62 74 HI 3 29 47 58 H 4–5 16 28 36

Download Full-text

Quantifying infective endocarditis risk in patients with predisposing cardiac conditions

European Heart Journal ◽

10.1093/eurheartj/ehx655 ◽

2017 ◽

Vol 39 (7) ◽

pp. 586-595 ◽

Cited By ~ 47

Author(s):

Martin H Thornhill ◽

Simon Jones ◽

Bernard Prendergast ◽

Larry M Baddour ◽

John B Chambers ◽

...

Keyword(s):

Infective Endocarditis ◽

High Risk ◽

Hospital Admissions ◽

Previous History ◽

Prosthetic Material ◽

Moderate Risk ◽

Prosthetic Valves ◽

English Population ◽

Risk Patients ◽

History Of

Abstract Aims There are scant comparative data quantifying the risk of infective endocarditis (IE) and associated mortality in individuals with predisposing cardiac conditions. Methods and results English hospital admissions for conditions associated with increased IE risk were followed for 5 years to quantify subsequent IE admissions. The 5-year risk of IE or dying during an IE admission was calculated for each condition and compared with the entire English population as a control. Infective endocarditis incidence in the English population was 36.2/million/year. In comparison, patients with a previous history of IE had the highest risk of recurrence or dying during an IE admission [odds ratio (OR) 266 and 215, respectively]. These risks were also high in patients with prosthetic valves (OR 70 and 62) and previous valve repair (OR 77 and 60). Patients with congenital valve anomalies (currently considered ‘moderate risk’) had similar levels of risk (OR 66 and 57) and risks in other ‘moderate-risk’ conditions were not much lower. Congenital heart conditions (CHCs) repaired with prosthetic material (currently considered ‘high risk’ for 6 months following surgery) had lower risk than all ‘moderate-risk’ conditions—even in the first 6 months. Infective endocarditis risk was also significant in patients with cardiovascular implantable electronic devices. Conclusion These data confirm the high IE risk of patients with a history of previous IE, valve replacement, or repair. However, IE risk in some ‘moderate-risk’ patients was similar to that of several ‘high-risk’ conditions and higher than repaired CHC. Guidelines for the risk stratification of conditions predisposing to IE may require re-evaluation.

Download Full-text

Potential screening strategies for early prediction of pre-eclampsia

International Journal of Reproduction Contraception Obstetrics and Gynecology ◽

10.18203/2320-1770.ijrcog20211116 ◽

2021 ◽

Vol 10 (4) ◽

pp. 1436

Author(s):

Hymavathi K. ◽

Sandhya Rani Davuluru ◽

Sameera Shaik ◽

Sahithi Kaviti

Keyword(s):

High Risk ◽

Pregnant Women ◽

Uterine Artery ◽

Strong Association ◽

First Trimester ◽

Maternal Serum ◽

Screening Tools ◽

Early Prediction ◽

Inhibin A ◽

Study Results

Background: This study was conducted to evaluate the efficacy of different biochemical and biophysical markers in the early weeks of gestation as screening tools for early prediction of preeclampsia.Methods: This hospital-based prospective observational study conducted on 52 pregnant women, at less than 13 weeks of gestation were recruited. Maternal serum inhibin A and USG uterine artery PI levels were analyzed among the pregnant women who subsequently developed PE and compare with those who did not develop PE. Methods used for the detection of markers were: chemiluminescence immunoassay (CLIA) for serum inhibin A levels, and uterine artery Doppler velocimetry was done by PHILIPS HD11XE transabdominal ultrasound machine using a 4-6 MHz probe with the same sonographer.Results: The present study revealed a significant rise of inhibin A in preeclamptic women when compared to normotensive women (p<0.0001). The mean levels of 1st and 2nd trimester uterine artery PI significantly high in women who subsequently developed PE when compared to those who did not develop preeclampsia (p<0.0001). Study results showed a strong association between gestational age at delivery and neonatal outcome (neonatal birth weight and APGAR) with preeclampsia. The maternal serum inhibin A, and uterine artery PI found to have good sensitivity and specificity for early prediction of PE.Conclusions: Study concluded that the women who are prone to develop PE subsequently, had high levels of MAP, UAPI, inhibin A. In our setting, MAP, UAPI, inhibin A, appeared to be better screening modalities. Combination of the biochemical markers with the biophysical markers, demographic characteristics, and other novel markers will establish the effective screening models for early prediction of PE. Early identification of high-risk cases will offer an opportunity for prophylactic therapy, such as Low- dose Aspirin in selected groups of high-risk women screened in the first trimester, thus improving the maternal and perinatal outcome.

Download Full-text