Risk Stratification in Women Enrolled in the Acute Decompensated Heart Failure National Registry Emergency Module (ADHERE-EM)

Objectives:  It has been reported that the mortality risk for heart failure differs between men and women. It has been postulated that this is due to differences in comorbid features. Variation in risk profiles by gender may limit the performance of stratification algorithms available for heart failure in women. This analysis examined the ability of a published risk stratification model to predict outcomes in women.
Methods:  The Acute Decompensated Heart Failure National Registry Emergency Module (ADHERE-EM) database was used. Characteristics, treatments, and outcomes for men and women were compared. The ADHERE registry classification and regression tree (CART) analysis was used for the risk stratification evaluation.
Results:  Of 10,984 ADHERE-EM patients, 5,736 (52.2%) were women. In-hospital mortality was similar between men and women (p = 0.727). Significant differences (p < 0.0002) were noted by gender in all three variables in the CART model (blood urea nitrogen [BUN] ≥ 43 mg/dL, systolic blood pressure < 115 mm Hg, and serum creatinine ≥ 2.75 mg/dL). However, the CART model effectively stratified both genders into distinct risk groups with no significant difference in mortality by gender within stratified groups.
Conclusions:  The ADHERE Registry CART tool is effective at predicting risk in ED patients, regardless of gender.     

The potential value of the neutrophil to lymphocyte ratio for early differential diagnosis and prognosis assessment in patients with aortic dissection

ObjectivesThe aim of the study was to assess the diagnostic performance and clinical utility of the neutrophil to lymphocyte ratio (NLR) in patients with suspected aortic dissection (AD) and investigate its role in predicting in-hospital mortality in AD.MethodsNLR values were calculated and compared in 467 consecutive patients with initially suspected AD. A receiver operating characteristic (ROC) curve analysis with the area under the curve (AUC) was used to evaluate the discriminative accuracy and predictive capability of the NLR for AD. Clinical utility was determined by decision curve analysis (DCA). The association between NLR and in-hospital mortality was investigated by logistic regression analyses in patients diagnosed with AD.ResultsThe NLR was significantly elevated in patients with AD, and the optimal cut-off point for the NLR to distinguish AD from other acute chest pain diseases was 5.67 [AUC (95% CI): 0.877 (0.844–0.905)]. We recommended an NLR of 2.43 as the appropriate cut-off point with 96.9% sensitivity and a negative likelihood ratio (LR) of 0.09 to satisfy clinical requirements for diagnosis. DCA showed that the use of NLR had a positive net benefit. The deceased patients with AD had a higher NLR than the discharged patients. Moreover, the NLR was an independent predictor of in-hospital mortality for AD [adjusted odds ratio (OR): 1.084 (1.029–1.142)], and patients with higher NLR values tended to have a higher risk of in-hospital mortality. The optimal cut-off point for the NLR to predict in-hospital mortality was 9.20 [AUC (95% CI): 0.695 (0.619–0.765)].ConclusionsAs an easily available and inexpensive parameter, the NLR could serve as a valuable clinical biomarker for early differential diagnosis and prognosis assessment of AD.     

The pediatric sepsis biomarker risk model

Introduction

The intrinsic heterogeneity of clinical septic shock is a major challenge. For clinical trials, individual patient management, and quality improvement efforts, it is unclear which patients are least likely to survive and thus benefit from alternative treatment approaches. A robust risk stratification tool would greatly aid decision-making. The objective of our study was to derive and test a multi-biomarker-based risk model to predict outcome in pediatric septic shock.

Methods

Twelve candidate serum protein stratification biomarkers were identified from previous genome-wide expression profiling. To derive the risk stratification tool, biomarkers were measured in serum samples from 220 unselected children with septic shock, obtained during the first 24 hours of admission to the intensive care unit. Classification and Regression Tree (CART) analysis was used to generate a decision tree to predict 28-day all-cause mortality based on both biomarkers and clinical variables. The derived tree was subsequently tested in an independent cohort of 135 children with septic shock.

Results

The derived decision tree included five biomarkers. In the derivation cohort, sensitivity for mortality was 91% (95% CI 70 - 98), specificity was 86% (80 - 90), positive predictive value was 43% (29 - 58), and negative predictive value was 99% (95 - 100). When applied to the test cohort, sensitivity was 89% (64 - 98) and specificity was 64% (55 - 73). In an updated model including all 355 subjects in the combined derivation and test cohorts, sensitivity for mortality was 93% (79 - 98), specificity was 74% (69 - 79), positive predictive value was 32% (24 - 41), and negative predictive value was 99% (96 - 100). False positive subjects in the updated model had greater illness severity compared to the true negative subjects, as measured by persistence of organ failure, length of stay, and intensive care unit free days.

Conclusions

The pediatric sepsis biomarker risk model (PERSEVERE; PEdiatRic SEpsis biomarkEr Risk modEl) reliably identifies children at risk of death and greater illness severity from pediatric septic shock. PERSEVERE has the potential to substantially enhance clinical decision making, to adjust for risk in clinical trials, and to serve as a septic shock-specific quality metric.     

A new prediction model for assessing the clinical outcomes of ICU patients with community-acquired pneumonia: a decision tree analysis

Purpose: We aimed to develop a new scoring index based on decision-tree analysis to predict clinical outcomes of patients with community-acquired pneumonia (CAP) admitted to the intensive care unit (ICU).

Methods: Data of 3519 ICU patients with CAP were obtained from the Medical Information Mart for Intensive Care III (MIMIC III) 2001–2012 database and analysed between 30-d survivors and non-survivors. Accuracy, sensitivity, and specificity of the new decision tree model were compared with those of CURB-65 and SOAR.

Results: The newly developed classification and regression tree (CART) model identified coexisting illnesses as the most important single discriminating factor between survivors and non-survivors. The CART model area under the curve (AUC) 0.661 was superior to that of CURB-65 (0.609) and SOAR (0.589). CART sensitivity was 73.4%, and specificity 49.0%. CURB-65 and SOAR sensitivity for predicting 30-d mortality were 74.5 and 80.7%, and specificity was 42.3 and 33.9%, respectively. After smoothing, the CART model had higher sensitivity and specificity than both CURB-65 and SOAR.

Conclusions: The new CART prediction model has higher specificity and better receiver operating characteristics (ROC) curves than CURB-65 and SOAR score indices although its accuracy and sensitivity are only moderately better than the other systems.

• Key messages

• The new CART prediction model has higher specificity and better ROC curves than CURB-65 and SOAR score indices.

• However, accuracy and sensitivity of the new CART prediction model are only moderately better than the other systems in predicting 30-day mortality in CAP patients.

     

Prediction of failure in vancomycin-treated methicillin-resistant Staphylococcus aureus bloodstream infection: a clinically useful risk stratification tool

Methicillin-resistant Staphylococcus aureus (MRSA) is a common cause of bloodstream infection (BSI) and is often associated with invasive infections and high rates of mortality. Vancomycin has remained the mainstay of therapy for serious Gram-positive infections, particularly MRSA BSI; however, therapeutic failures with vancomycin have been increasingly reported. We conducted a comprehensive evaluation of the factors (patient, strain, infection, and treatment) involved in the etiology and management of MRSA BSI to create a risk stratification tool for clinicians. This study included consecutive patients with MRSA BSI treated with vancomycin over 2 years in an inner-city hospital in Detroit, MI. Classification and regression tree analysis (CART) was used to develop a risk prediction model that characterized vancomycin-treated patients at high risk of clinical failure. Of all factors, the Acute Physiology and Chronic Health Evaluation II (APACHE-II) score, with a cutoff point of 14, was found to be the strongest predictor of failure and was used to split the population into two groups. Forty-seven percent of the population had an APACHE-II score < 14, a value that was associated with low rates of clinical failure (11%) and mortality (4%). Fifty-four percent of the population had an APACHE-II score ≥ 14, which was associated with high rates of clinical failure (35%) and mortality (23%). The risk stratification model identified the interplay of three other predictors of failure, including the vancomycin MIC as determined by Vitek 2 analysis, the risk level of the source of BSI, and the USA300 strain type. This model can be a useful tool for clinicians to predict the likelihood of success or failure in vancomycin-treated patients with MRSA bloodstream infection.     

Risk prediction of in-hospital mortality in patients with venoarterial extracorporeal membrane oxygenation for cardiopulmonary support: The ECMO-ACCEPTS score

PurposeVenoarterial extracorporeal membrane oxygenation (VA-ECMO) is an increasingly used treatment option for patients in need of mechanical cardiopulmonary support, while available outcome data is limited. The aim of this study was to identify predictors for 30-day in-hospital mortality.Material and methodsWe analyzed baseline characteristics and outcomes of 8351 VA-ECMO procedures performed in Germany from 2007 to 2015. Using a multivariable model, we identified the ten most important variables to allow for prediction of 30-day in-hospital mortality. Based on these variables, we created a mortality prediction score (ECMO-ACCEPTS score) to enhance decision making in patients considered for or treated with VA-ECMO support.ResultsOf 8351 patients (71.7% male) 3567 had prior CPR. Mean age was 62 years in the present cohort. The overall 30-day in-hospital mortality was 61%. The ECMO-ACCEPTS score, derived among randomly selected 4175 patients, included ten independent predictors for in-hospital mortality. Internal validation in the remaining 4176 patients confirmed strong differentiation between low and high risk of 30-day in-hospital mortality (r = 0.97 for correlation of predicted with observed mortality, p < .001).ConclusionsThe ECMO-ACCEPTS score might help clinicians to improve risk prediction among VA-ECMO patients for refractory cardiogenic shock.     

Development of an optimized multimarker strategy for early risk assessment of patients with acute coronary syndromes

BACKGROUND: A multitude of biomarkers have been suggested for early risk-assessment in patients admitted to the emergency department with suspected acute coronary syndromes. We used logistic regression synergistically with classification and regression tree (CART) analysis to define a multimarker strategy and the cut-off values and sequencing needed to optimize risk stratification in a low to moderate risk population of the emergency department. METHODS: 432 unselected patients (59.7+/-14.5 y, 60.4% male) admitted to the emergency department (ED) with acute coronary syndromes (ACS) were enrolled. Cardiac troponin I (cTnI), N-terminal pro-B-Type natriuretic peptide (NT-proBNP), high sensitivity C-reactive protein (hsCRP), placental growth factor (PlGF), lipoprotein-associated phospholipase A(2) (Lp-PLA(2)) and D-dimers were measured by immunoassay and whole blood choline (WBCHO) and plasma choline (PLCHO) were measured using LC/MS from baseline samples. Logistic regression and CART analysis were used to define the importance of the various biomarkers tested and to define their hierarchy with respect to the prediction of major adverse cardiac events (MACE; cardiac death, non-fatal MI, unstable angina, CHF requiring admission, urgent PCI and CABG) over the 42-day follow-up period. RESULTS: A combination of NT-proBNP, WBCHO and Lp-PLA2 with cutoffs identified by CART-analysis was optimal for risk-stratification and superior to all other possible combinations of markers. Increased concentrations of both NT-proBNP (>1400 ng/l) and WBCHO (>21 mumol/l) identified patients with very high risk (RR=2.4, 39% primary endpoint) while low concentrations of NT-proBNP (17 mumol/l additionally identified a subgroup with intermediate risk (RR=3.0, 13.5% primary endpoint) in patients with NT-proBNP concentrations 相似文献   

Comparison of SYNTAX score II efficacy with SYNTAX score and TIMI risk score for predicting in-hospital and long-term mortality in patients with ST segment elevation myocardial infarction

SYNTAX score II (SS-II) has a powerful prognostic accuracy in patients with stable complex coronary artery disease who have undergone revascularization; however, there is limited data regarding the prognosis of patients with ST segment elevation myocardial infarction (STEMI). The aim of this study is to examine both the predictive performance of SS-II in determining in-hospital and long term mortality of STEMI patients and to compare SYNTAX score (SS) and TIMI risk score (TRS). Consecutive 1912 STEMI patients treated with primary percutaneous coronary intervention (p-PCI) retrospectively reviewed, and the remaining 1708 patients constituted the study population after exclusion. The patients were divided into three groups according to increased SS-II value: low (n:562; SS-II?≤?24.6); intermediate (n:563; 24.6?<?SS-II?<?34.4); and high tertile (n:583; SS-II?≥?34.4). In-hospital and long term mortality rate from all causes (0 vs. 0.5 vs. 10.6% and 1.8 vs. 3.2 vs. 18.1% respectively, p?≤?0.001) were significantly increased with SS-II tertiles and SS-II was found to be independent predictor of in-hospital and long term mortality (HR: 1.076 95% CI 1.060–1.092, p?<?0.001) and (HR: 1.070 95% CI 1.050–1.090, p?<?0.0001). The predictive power of SS-II, SS, and TRS were compared by ROC curve and decision curve analysis. SS-II surpassed SS and TRS in long-term and in-hospital mortality prediction. SS-II is a powerful tool to predict in-hospital and long-term mortality from all causes in STEMI patients treated with p-PCI.     

Decision tree analysis to predict the risk of intracranial haemorrhage after mild traumatic brain injury in patients taking DOACs

BackgroundAlthough the preliminary evidence seems to confirm a lower incidence of post-traumatic bleeding in patients treated with direct oral anticoagulants (DOACs) compared to those on vitamin K antagonists (VKAs), the recommended management of mild traumatic brain injury (MTBI) in patients on DOACs is the same as those on the older VKAs, risking excessive use of CT in the emergency department (ED).AimTo determine which easily identifiable clinical risk factors at the first medical evaluation in the ED may indicate an increased risk of post-traumatic intracranial haemorrhage (ICH) in patients on DOACs with MTBI.MethodsPatients on DOACs who were evaluated in the ED for an MTBI from 2016 to 2020 at four centres in Northern Italy were considered. A decision tree analysis using the chi-square automatic interaction detection (CHAID) method was conducted to assess the risk of post-traumatic ICH after an MTBI. Known pre- and post-traumatic clinical risk factors that are easily identifiable at the first medical evaluation in the ED were used as input predictor variables.ResultsAmong the 1146 patients on DOACs in this study, post-traumatic ICH was present in 6.5% (75/1146). Decision tree analysis using the CHAID method found post-traumatic TLOC, post-traumatic amnesia, major trauma dynamic, previous neurosurgery and evidence of trauma above the clavicles to be the strongest predictors associated with the presence of post-traumatic ICH in patients on DOACs. The absence of a concussion seems to indicate subgroups at very low risk of requiring neurosurgery.ConclusionsThe machine-based CHAID model identified distinct prognostic groups of patients with distinct outcomes based on clinical factors. Decision trees can be useful as guides for patient selection and risk stratification.     

Diabetes is an independent risk factor for in-hospital mortality from acute spontaneous intracerebral hemorrhage

OBJECTIVE: We tested the hypothesis that diabetes is an independent determinant of outcome after intracerebral hemorrhage (ICH). RESEARCH DESIGN AND METHODS: This was a hospital-based prospective study The setting was an acute care 350-bed hospital in the city of Barcelona, Spain. Spontaneous ICH was diagnosed in 229 (11%) of 2,000 consecutive stroke patients included in a prospective stroke registry during a 10-year period. Main outcome measures were frequency of demographic variables, risk factors, clinical events, neuroimaging data, and outcome in ICH patients with and without diabetes. Variables related to vital status at discharge (alive or dead) in the univariate analysis plus age were studied in 4 logistical regression models. RESULTS: A total of 35 patients (15.3%) had diabetes. The overall in-hospital mortality rate was 54.3% in the diabetic group and 26.3% in the nondiabetic group (P < 0.001). Previous cerebral infarction, altered consciousness, sensory symptoms, cranial nerve palsy, multiple topography of the hematoma, intraventricular hemorrhage, and infectious complications were significantly more frequent in diabetic patients than in nondiabetic patients. The presence of diabetes was a significant predictive variable in the model based on demographic variables and cardiovascular risk factors (odds ratio 2.98 [95% CI 1.37-6.46]) and in the models based on these variables plus clinical variables (5.76 [2.01-16.51]), neuroimaging variables (5.59 [1.87-16.691), and outcome data (6.10 [2.04-18.291). CONCLUSIONS: Diabetes is an independent determinant of death after ICH. ICH in diabetic individuals presents some different clinical features compared with ICH in nondiabetic patients.     

Prediction models in prehospital and emergency medicine research: How to derive and internally validate a clinical prediction model

Clinical prediction models are created to help clinicians with medical decision making, aid in risk stratification, and improve diagnosis and/or prognosis. With growing availability of both prehospital and in-hospital observational registries and electronic health records, there is an opportunity to develop, validate, and incorporate prediction models into clinical practice. However, many prediction models have high risk of bias due to poor methodology. Given that there are no methodological standards aimed at developing prediction models specifically in the prehospital setting, the objective of this paper is to describe the appropriate methodology for the derivation and validation of clinical prediction models in this setting. What follows can also be applied to the emergency medicine (EM) setting. There are eight steps that should be followed when developing and internally validating a prediction model: (1) problem definition, (2) coding of predictors, (3) addressing missing data, (4) ensuring adequate sample size, (5) variable selection, (6) evaluating model performance, (7) internal validation, and (8) model presentation. Subsequent steps include external validation, assessment of impact, and cost-effectiveness. By following these steps, researchers can develop a prediction model with the methodological rigor and quality required for prehospital and EM research.     

Lipoprotein-associated phospholipase A<Subscript>2</Subscript> for early risk stratification in patients with suspected acute coronary syndrome: a multi-marker approach

Aims Numerous markers have been identified as useful predictors of major adverse cardiac events (MACE) in patients with suspected acute coronary syndrome (ACS). However, only little is known about the relative benefit of the single markers in risk stratification and the best combination for optimising prognostic power. The aim of the present study was to define the role of the emerging cardiovascular risk marker lipoprotein-associated phospholipase A₂ (Lp-PLA₂) in a multi-marker approach in combination with troponin I (TnI), NT-proBNP, high sensitivity (hs)CRP, and D-dimer in patients with ACS. Methods and results A total of 429 consecutive patients (age 60.5±14.1 years, 60.6% male) who were admitted to the emergency room with suspected ACS were analysed in the study. Biochemical markers were measured by immunoassay techniques. All patients underwent point-of-care TnI testing and early coronary angiography if appropriate, in accordance with the current guidelines. Classification and regression trees (CART) and logistic regression techniques were employed to determine the relative predictive power of markers for the primary end-point defined as any of the following events within 42 days after admission: death, non-fatal myocardial infarction, unstable AP requiring admission, admission for decompensated heart failure or shock, percutaneous coronary intervention, coronary artery bypass grafting, life threatening arrhythmias or resuscitation. The incidence of the primary end-point was 13.1%, suggesting a mild to moderate risk population. The best overall risk stratification was obtained using NT-proBNP at a cut-off of 5000 pg/mL (incidence of 40% versus 10.3%, relative risk (RR) 3.9 (95% CI 2.4–6.3)). In the remaining lower risk group with an incidence of 10.3%, further separation was performed using TnI (cut-off 0.14 μg/L; RR= 3.1 (95% CI 1.7–5.5) 23.2% versus 7.5%) and again NT-proBNP (at a cut-off of 140 ng/L) in patients with negative TnI (RR=3.2 (95% CI 1.3–7.9), 11.7% versus 3.6%). A final significant stratification in patients with moderately elevated NT-proBNP levels was achieved using Lp-PLA₂ at a cut-off of 210 μg/L) (17.9% versus 6.9%; RR=2.6 (95% CI 1.1–6.6)). None of the clinical or ECG variables of the TIMI (Thrombolysis In Myocardial Infarction) risk score provided comparable clinically relevant information for risk stratification. Conclusions In the setting of stateof- the-art coronary care for patients with suspected ACS in the emergency room, NT-proBNP, troponin I, and Lp-PLA₂ are effective independent markers for risk stratification that proved to be superior to the TIMI risk score. Lp-PLA₂ turned out to be a more effective risk marker than hsCRP in these patients.     

Mean platelet volume in predicting short- and long-term morbidity and mortality in patients with or without ST-segment elevation myocardial infarction

Mean platelet volume (MPV) is a marker of platelet activation. An increased MPV is associated with acute myocardial infarction (AMI) and long-term mortality. The aim of this study was to compare MPV in patients with ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI). Also, we investigated the value of MPV on in-hospital mortality and long-term prognosis of patients with STEMI and NSTEMI. We studied 429 patients with AMI (70.4% male, 61.9 ± 12.4 years; 279 patients with STEMI, 150 patients with NSTEMI). MPV and platelet count were similar in both groups. Elevated MPV increased the risk of death by 3.1-fold (p < 0.001) in STEMI group during the hospitalization. However, increased MPV was not associated with in-hospital mortality in NSTEMI group. The area under the receiver operating characteristic curve of MPV was 0.868 (95% CI, 0.830-0.907) for predicting two-year mortality. A cut-off point of 11.1 fL showed a sensitivity of 81% and a specifity of 77% for prediction of two-year mortality. Kaplan-Meier survival curve showed two-year mortality rate of 12.5% in patients with MPV >11.1 fL versus 9.9% in patients with MPV <11.1 fL (p < 0.001). Cox regression analysis showed MPV to be an independent predictor of two-year mortality (Hazard ratio 1.7; 95% CI 1.5-1.9; p < 0.001). An increased MPV is an independent predictor of in-hospital mortality in patients with STEMI. However, elevated levels of MPV did not predict in hospital mortality in NSTEMI group. The increase in MPV values was independently correlated with two-year mortality in all study patients.     

Emergency Department Control of Blood Pressure in Intracerebral Hemorrhage

Background: Early treatment of elevated blood pressure (BP) in patients presenting with spontaneous intracerebral hemorrhage (ICH) may decrease hematoma enlargement and lead to better neurologic outcome. Study Objective: To determine whether early BP control in patients with spontaneous ICH is both feasible and tolerated when initiated in the Emergency Department (ED). Methods: A single-center, prospective observational study in patients with spontaneous ICH was performed to evaluate a protocol to lower, and maintain for 24 h, the mean arterial pressure (MAP) to a range of 100–110 mm Hg within 120 min of arrival to the ED. An additional goal of placing a functional arterial line within 90 min was specified in our protocol. Hematoma volume, neurologic disability, adverse events, and in-hospital mortality were recorded. Results: A total of 22 patients were enrolled over a 1-year study period. The average time to achieve our target MAP after implementation of our protocol was 123 min (range 19–297 min). The average time to arterial line placement was 84 min (range 36–160 min). Overall, 77% of the patients tolerated the 24-h protocol. The in-hospital mortality rate in this group of patients was 41%. Conclusions: Adopting a protocol to reduce and maintain the MAP to a target of 100–110 mm Hg within 120 min of ED arrival was safe and well tolerated in patients presenting with spontaneous ICH. If future trials demonstrate a clinical benefit of early BP control in spontaneous ICH, EDs should implement similar protocols.     

The value of patient-reported health status in predicting short-term outcomes after coronary artery bypass graft surgery

BACKGROUND: Risk stratification for comparison of outcomes after coronary artery bypass grafting (CABG) typically includes only clinical measures of risk. Patient-reported health status may be an important independent predictor of short-term health outcomes. OBJECTIVE: To determine whether patient-reported health status, as measured by the Physical and Mental Component Summary scores of the SF-36, predicts in-hospital mortality and prolonged length of stay after CABG, after controlling for other clinical predictors of those outcomes. RESEARCH DESIGN: Prospective cohort study conducted from September 1993 to November 1995. SUBJECTS: One thousand seven hundred seventy-eight adults who underwent isolated CABG for myocardial ischemia. MEASURES: In-hospital mortality and prolonged length of stay (> 14 days). RESULTS: There were 27 deaths and 223 patients with prolonged length of stay in the study sample. A 10-point decrease in the Physical Component Summary (PCS) score increased the odds of in-hospital mortality by 61% (OR, 1.61; 95% CI, 1.04-2.49), independent of established clinical risk factors. Similarly, a 10-point decrease in the PCS score increased the odds of prolonged length of stay by 33% (OR, 1.33; 95% CI, 1.13-1.57). A 10-point decrease in the Mental Component Summary score (MCS) decreased the odds of mortality by 36% (OR, 0.64; 95% CI, 0.43-0.95). CONCLUSIONS: The PCS score is independently and significantly associated with in-hospital mortality and prolonged length of stay, after controlling for clinical risk factors. The MCS score is independently and significantly associated only with mortality, though the direction of the effect is unexpected. The result likely reflects a property of the scoring of the MCS and not a finding of clinical substance. Although caution must be taken when interpreting the summary scores, the SF-36 yields information not otherwise captured by clinical data and may be useful in risk stratification for in-hospital mortality and prolonged length of stay after CABG.     

Natriuretic peptides in acute pulmonary embolism: a systematic review

Background  Patients with pulmonary embolism (PE) have a high risk of death, and it is important to recognize factors associated with higher mortality. Recently, several biomarkers have been studied for risk stratification in patients with PE. Objectives  Evaluate the available evidence on (a) the accuracy of brain natriuretic peptide (BNP) and N-terminal pro-brain natriuretic peptide (NT-proBNP) for the diagnosis of right ventricular dysfunction and (b) their value as a prognostic factor of all-cause in-hospital or short-term mortality in patients with PE. Data sources  MEDLINE, Embase, and citation review of relevant primary and review articles. Selection criteria  We selected studies evaluating the accuracy of BNP or NT-proBNP for the diagnosis of right ventricular dysfunction. We also selected studies that reported data on BNP or NT-proBNP as a predictor of short-term mortality in patients with PE. Results  Sixteen studies met our inclusion criteria. The pooled diagnostic odds ratio for the diagnosis of right ventricular dysfunction in pulmonary embolism was 39.45 (95% CI; 15.54–100.12) and 24.73 (95% CI 2.02–302.37) for BNP and NT-proBNP, respectively. The pooled odds ratio for all-cause in-hospital or short-term mortality was 6 (95% CI 1.31–27.43; p: 0.021) and 16.12 (95% CI 3.1–83.68; p: 0.001) for BNP (cutoff: 100 pg/ml) and NT-proBNP (cutoff: 600 ng/L), respectively. Conclusion  The results of this meta-analysis indicate that BNP and NT-proBNP are associated with the diagnosis of right ventricular dysfunction (RVD) in patients with an acute PE and are significant predictors of all-cause in-hospital or short-term mortality in these patients.     

Relationship between Time to Clinical Response and Outcomes among Pneumonia Outcomes Research Team (PORT) Risk Class III and IV Hospitalized Patients with Community-Acquired Pneumonia Who Received Ceftriaxone and Azithromycin

Recent Food and Drug Administration (FDA) guidance endorses the use of an early clinical response endpoint as the primary outcome for community-acquired bacterial pneumonia (CABP) trials. While antibiotics will now be approved for CABP, in practice they will primarily be used to treat patients with community-acquired pneumonia (CAP). More importantly, it is unclear how achievement of the new FDA CABP early response endpoint translates into clinically applicable real-world outcomes for patients with CAP. To address this, a retrospective cohort study was conducted among adult patients who received ceftriaxone and azithromycin for CAP of Pneumonia Outcomes Research Team (PORT) risk class III and IV at an academic medical center. The clinical response was defined as clinical stability for 24 h with improvement in at least one pneumonia symptom and with no symptom worsening. A classification and regression tree (CART) was used to determine the delay in response time, measured in days, associated with the greatest risk of a prolonged hospital length of stay (LOS) and adverse outcomes (in-hospital mortality or 30-day CAP-related readmission). A total of 250 patients were included. On average, patients were discharged 2 days following the achievement of a clinical response. In the CART analysis, adverse clinical outcomes were higher among day 5 nonresponders than those who responded by day 5 (22.4% versus 6.9%, P = 0.001). The findings from this study indicate that time to clinical response, as defined by the recent FDA guidance, is a reasonable prognostic indictor of real-world effectiveness outcomes among hospitalized PORT risk class III and IV patients with CAP who received ceftriaxone and azithromycin.     

Liver-to-abdominal area ratio for predicting the in-hospital mortality in advanced liver cirrhosis

Objectives: To identify the value of liver-to-abdominal area ratio (LAAR) score for predicting the in-hospital mortality in advanced cirrhotic patients.

Methods: All cirrhotic patients with Child-Pugh class B or C who were admitted between July 2012 and June 2014 and underwent abdominopelvic CT scans were considered in this retrospective observational study. The association of LAAR with in-hospital death was calculated. Receiver operating characteristic curve analysis was performed. The area under curve (AUC) was calculated.

Results: In the overall analysis of 128 cirrhotic patients with Child-Pugh class B or C, LAAR score was significantly associated with the risk of in-hospital death (p = 0.012). The AUC of LAAR score for predicting the in-hospital mortality was 0.764 (p < 0.0001). The best cut-off value was 0.29 with a sensitivity of 75% and a specificity of 73.33%. In the subgroup analysis of 37 patients with Child-Pugh class C, LAAR score was significantly associated with the risk of in-hospital death (p = 0.008). The AUC of LAAR score was 0.821. The best cut-off value was 0.29 with a sensitivity of 85.71% and a specificity of 80%. In the subgroup analysis of 80 patients with moderate-severe ascites, LAAR score was not significantly associated with the risk of in-hospital death (p = 0.072). The AUC of LAAR score was 0.684 (p = 0.0158). The best cut-off value was 0.29 with a sensitivity of 75% and a specificity of 63.89%.

Conclusion: LAAR score might be effective for predicting the in-hospital death of advanced cirrhosis.