Biomarker-based score for predicting in-hospital mortality of children admitted to the intensive care unit

2021 ◽  
pp. jim-2021-001855
Author(s):  
Yin Zhang ◽  
Qingxia Shi ◽  
Guochao Zhong ◽  
Xun Lei ◽  
Jilei Lin ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Predictive Model ◽  
Characteristic Curve ◽  
Calibration Plot ◽  
P Value ◽  
Lasso Regression ◽  
Risk Of Death ◽  
Lemeshow Test

This study aims to establish a new scoring system based on biomarkers for predicting in-hospital mortality of children admitted to the pediatric intensive care unit (PICU). The biomarkers were chosen using the least absolute shrinkage and selection operator (LASSO)-logistic regression in this observational case-control study. The performance of the new predictive model was evaluated by the area under the receiver operating characteristic curve (AUC). Calibration plot was established to validate the new score accompanied by the Hosmer-Lemeshow test. There were 8818 patients included in this study. Finally, six predictors were included in the LASSO-regression model. Albumin <40 g/L, lactate dehydrogenase >452 U/L, lactate >3.2 mmol/L, urea >5.6 mmol/L, arterial PH <7.3 and glucose >6.9 mmol/L were treated as risk factors for higher mortality. The new score ranged from 1 to 6 among all the included patients. In the training set, the AUC of the probability of in-hospital mortality for the new predictive model was 0.81 (95% CI 0.79 to 0.84), which is larger than for the Pediatric Critical Illness Score (PCIS) (0.69, 95% CI 0.66 to 0.72). Similarly, in the validating set, the AUC of the probability of in-hospital mortality was larger for the new score (0.80, 95% CI 0.77 to 0.84) than for PCIS (0.67, 95% CI 0.63 to 0.72). The calibration plot and Hosmer-Lemeshow test showed excellent calibration. The calculated ORs showed a trend that higher scores indicated higher risk of death (p value for trend <0.001). In summary, this study develops and validates a totally biomarker-based new score to predict in-hospital mortality for pediatric patients admitted to PICU. More attention and more positive care and treatment should be given to children with a higher score.

scholarly journals The Association between Nutritional Status and In-Hospital Mortality of COVID-19 in Critically-Ill Patients in the ICU

Nutrients ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 3302
Author(s):  
Michał Czapla ◽  
Raúl Juárez-Vela ◽  
Vicente Gea-Caballero ◽  
Stanisław Zieliński ◽  
Marzena Zielińska
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Nutritional Status ◽  
Hospital Mortality ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Invasive Mechanical Ventilation ◽  
Nutritional Risk ◽  
Risk Of Death ◽  
The Impact

Background: Coronavirus disease 2019 (COVID-19) has become one of the leading causes of death worldwide. The impact of poor nutritional status on increased mortality and prolonged ICU (intensive care unit) stay in critically ill patients is well-documented. This study aims to assess how nutritional status and BMI (body mass index) affected in-hospital mortality in critically ill COVID-19 patients Methods: We conducted a retrospective study and analysed medical records of 286 COVID-19 patients admitted to the intensive care unit of the University Clinical Hospital in Wroclaw (Poland). Results: A total of 286 patients were analysed. In the sample group, 8% of patients who died had a BMI within the normal range, 46% were overweight, and 46% were obese. There was a statistically significantly higher death rate in men (73%) and those with BMIs between 25.0–29.9 (p = 0.011). Nonsurvivors had a statistically significantly higher HF (Heart Failure) rate (p = 0.037) and HT (hypertension) rate (p < 0.001). Furthermore, nonsurvivors were statistically significantly older (p < 0.001). The risk of death was higher in overweight patients (HR = 2.13; p = 0.038). Mortality was influenced by higher scores in parameters such as age (HR = 1.03; p = 0.001), NRS2002 (nutritional risk score, HR = 1.18; p = 0.019), PCT (procalcitonin, HR = 1.10; p < 0.001) and potassium level (HR = 1.40; p = 0.023). Conclusions: Being overweight in critically ill COVID-19 patients requiring invasive mechanical ventilation increases their risk of death significantly. Additional factors indicating a higher risk of death include the patient’s age, high PCT, potassium levels, and NRS ≥ 3 measured at the time of admission to the ICU.

scholarly journals Predictive model for in-hospital mortality following cardiogenic shock

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
F Garcia-Rodeja Arias ◽  
M Perez Dominguez ◽  
J Martinon Martinez ◽  
J M Garcia Acuna ◽  
C Abou Joch Casas ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Cardiogenic Shock ◽  
Predictive Model ◽  
Risk Score ◽  
Roc Curve ◽  
Goodness Of Fit ◽  
Simplified Model ◽  
P Value ◽  
Final Model ◽  
Risk Of Death

Abstract Introduction and objectives Cardiogenic shock is a condition caused by reduced cardiac output and hypotension, resulting in end-organ damage and multiorgan failure. Although prognosis has been improved in recent years, this state is still associated with high morbidity and mortality. The aim of our study was to perform a predictive model for in-hospital mortality that allows stratifying the risk of death in patients with cardiogenic shock. Methods This is a retrospective analysis from a prospective registry, that included 135 patients from one Spanish Universitary Hospital between 2011 and 2020. Multivariate analysis was performed among those variables with significant association with short-term outcome of univariate analysis with a p-value &lt;0.2. Those variables which had a p-value &gt;0.1 in the multivariable analysis were excluded of the final model. Our method was assessed using the area under the ROC-curve (AUC). Goodness of fit was tested using Hosmer-Lemeshow statistic test. Finally, we performed a risk score using the pondered weight of the coefficients of a simplified model created after categorizing the continuous quantitative variables included in the final model, giving a maximum of 16 points and creating three categories of risk. Results The in-hospital mortality rate was 41.5%, the average of age was 74.2 years, 35.6% were females and acute coronary syndrome (ACS) was the main cause of shock (60.7%). Mitral regurgitation (moderate-severe), age, ACS etiology, NT-proBNP, blood hemoglobin and lactate at admission were included in the final model. Risk-adjustment model had good accuracy in predicting in-hospital mortality (AUC 0.85; 95% CI 0,78–0,90) and the goodness of fit test was p-value&gt;0.10. According to the risk score made with the simplified model, these patients were stratified into three categories: low (scores 0–6), intermediate (scores 7–10), and high (scores 11–16) risk with observed mortality of 12.9%, 49.1% and 87.5% respectively (p&lt;0,001). Conclusions Our predictive model using six variables, shows good discernment for in-hospital mortality and the risk score has identified three groups with significant differences in prognosis. This model could help in guiding treatments and clinical decision-making, so it needs external validation and to be compared with other models already published. FUNDunding Acknowledgement Type of funding sources: None. ROC curve Risk Score

scholarly journals Disparities in Intensive Care Unit Admission and Mortality Among Patients With Schizophrenia and COVID-19: A National Cohort Study

2020 ◽  
Author(s):  
Guillaume Fond ◽  
Vanessa Pauly ◽  
Marc Leone ◽  
Pierre-Michel Llorca ◽  
Veronica Orleans ◽  
...  
Keyword(s):  
Health Care ◽  
Intensive Care Unit ◽  
Mental Illness ◽  
Cohort Study ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Severe Mental Illness ◽  
Vulnerable Population ◽  
Icu Admission ◽  
Risk Of Death

Abstract Patients with schizophrenia (SCZ) represent a vulnerable population who have been understudied in COVID-19 research. We aimed to establish whether health outcomes and care differed between patients with SCZ and patients without a diagnosis of severe mental illness. We conducted a population-based cohort study of all patients with identified COVID-19 and respiratory symptoms who were hospitalized in France between February and June 2020. Cases were patients who had a diagnosis of SCZ. Controls were patients who did not have a diagnosis of severe mental illness. The outcomes were in-hospital mortality and intensive care unit (ICU) admission. A total of 50 750 patients were included, of whom 823 were SCZ patients (1.6%). The SCZ patients had an increased in-hospital mortality (25.6% vs 21.7%; adjusted OR 1.30 [95% CI, 1.08–1.56], P = .0093) and a decreased ICU admission rate (23.7% vs 28.4%; adjusted OR, 0.75 [95% CI, 0.62–0.91], P = .0062) compared with controls. Significant interactions between SCZ and age for mortality and ICU admission were observed (P = .0006 and P &lt; .0001). SCZ patients between 65 and 80 years had a significantly higher risk of death than controls of the same age (+7.89%). SCZ patients younger than 55 years had more ICU admissions (+13.93%) and SCZ patients between 65 and 80 years and older than 80 years had less ICU admissions than controls of the same age (−15.44% and −5.93%, respectively). Our findings report the existence of disparities in health and health care between SCZ patients and patients without a diagnosis of severe mental illness. These disparities differed according to the age and clinical profile of SCZ patients, suggesting the importance of personalized COVID-19 clinical management and health care strategies before, during, and after hospitalization for reducing health disparities in this vulnerable population.

scholarly journals A nomogram to predict in-hospital mortality of neonates admitted to the intensive care unit

2021 ◽  
Author(s):  
Xihua Huang ◽  
Zhenyu Liang ◽  
Tang Li ◽  
Yu Lingna ◽  
Wei Zhu ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Predictive Model ◽  
Sofa Score ◽  
Medical Information ◽  
Hospital Death ◽  
Operating Characteristics ◽  
Distribution Width ◽  
Mimic Iii

Abstract Background To explore the influencing factors for in-hospital mortality in the neonatal intensive care unit (NICU) and to establish a predictive nomogram. Methods Neonatal data were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. Both univariate and multivariate logit binomial general linear models were used to analyse the factors influencing neonatal death. The area under the receiver operating characteristics (ROC) curve was used to assess the predictive model, which was visualized by a nomogram. Results A total of 1258 neonates from the NICU in the MIMIC-III database were eligible for the study, including 1194 surviving patients and 64 deaths. Multivariate analysis showed that red cell distribution width (RDW) (odds ratio [OR] 0.813, p=0.003) and total bilirubin (TBIL; OR 0.644, p&lt;0.001) had protective effects on neonatal in-hospital death, while lymphocytes (OR 1.205, p=0.025), arterial partial pressure of carbon dioxide (PaCO2; OR 1.294, p=0.016) and sequential organ failure assessment (SOFA) score (OR 1.483, p&lt;0.001) were its independent risk factors. Based on this, the area under the curve of this predictive model was up to 0.865 (95% confidence interval 0.813 to 0.917), which was also confirmed by a nomogram. Conclusions The nomogram constructed suggests that RDW, TBIL, lymphocytes, PaCO2 and SOFA score are all significant predictors for in-hospital mortality in the NICU.

scholarly journals Outcome of cancer patients considered for intensive care unit admission in two university hospitals in the Netherlands: the danger of delayed ICU admissions and off-hour triage decisions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Esther N. van der Zee ◽  
Dominique D. Benoit ◽  
Marinus Hazenbroek ◽  
Jan Bakker ◽  
Erwin J. O. Kompanje ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
The Netherlands ◽  
Cancer Patients ◽  
Admission Policy ◽  
P Value ◽  
University Hospitals ◽  
Icu Admission ◽  
Risk Of Death ◽  
Triage Decisions

Abstract Background Very few studies assessed the association between Intensive Care Unit (ICU) triage decisions and mortality. The aim of this study was to assess whether an association could be found between 30-day mortality, and ICU admission consultation conditions and triage decisions. Methods We conducted a retrospective cohort study in two large referral university hospitals in the Netherlands. We identified all adult cancer patients for whom ICU admission was requested from 2016 to 2019. Via a multivariable logistic regression analysis, we assessed the association between 30-day mortality, and ICU admission consultation conditions and triage decisions. Results Of the 780 cancer patients for whom ICU admission was requested, 332 patients (42.6%) were considered ‘too well to benefit’ from ICU admission, 382 (49%) patients were immediately admitted to the ICU and 66 patients (8.4%) were considered ‘too sick to benefit’ according to the consulting intensivist(s). The 30-day mortality in these subgroups was 30.1%, 36.9% and 81.8%, respectively. In the patient group considered ‘too well to benefit’, 258 patients were never admitted to the ICU and 74 patients (9.5% of the overall study population, 22.3% of the patients ‘too well to benefit’) were admitted to the ICU after a second ICU admission request (delayed ICU admission). Thirty-day mortality in these groups was 25.6% and 45.9%. After adjustment for confounders, ICU consultations during off-hours (OR 1.61, 95% CI 1.09–2.38, p-value 0.02) and delayed ICU admission (OR 1.83, 95% CI 1.00–3.33, p-value 0.048 compared to “ICU admission”) were independently associated with 30-day mortality. Conclusion The ICU denial rate in our study was high (51%). Sixty percent of the ICU triage decisions in cancer patients were made during off-hours, and 22.3% of the patients initially considered “too well to benefit” from ICU admission were subsequently admitted to the ICU. Both decisions during off-hours and a delayed ICU admission were associated with an increased risk of death at 30 days. Our study suggests that in cancer patients, ICU triage decisions should be discussed during on-hours, and ICU admission policy should be broadened, with a lower admission threshold for critically ill cancer patients.

Predictors of survival in patients with gastrointestinal malignancies admitted to the intensive care unit.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e18050-e18050
Author(s):  
Heidi Chwan Ko ◽  
Melissa Yan ◽  
Rohan Gupta ◽  
Juhee Song ◽  
Kayla Kebbel ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Cancer Patients ◽  
Sofa Score ◽  
Icu Mortality ◽  
Gastrointestinal Malignancies ◽  
Icu Admission ◽  
Risk Of Death ◽  
Gi Cancer

e18050 Background: Cancer patients have a high use of healthcare utilization at the end of life which can frequently involve admissions to the intensive care unit (ICU). We sought to evaluate the predictors for outcome in gastrointestinal (GI) cancer patients admitted to the ICU for non-surgical conditions. Methods: The objective of this study was to determine the factors associated with ICU mortality, hospital mortality and overall survival (OS). A total of 200 patients with GI cancer admitted to the ICU at The University of Texas MD Anderson Cancer Center between November 2012 and February 2015 were retrospectively analyzed. Cancer characteristics, treatment characteristics, and Sequential Organ Failure Assessment (SOFA) scores defining severity based on 6 organ systems with scores ranging from 0 to 24 were analyzed for their effects on survival endpoints using multivariate logistic regression models and a multivariate Cox proportional hazards regression model. Results: The characteristics of the 200 patients were: 64.5% male, mean age of 60 years, median admission SOFA score of 6.0, and tumor types of primary intestinal (37.5%), hepatobiliary/pancreatic (36%), and gastroesophageal (GE) (24%). The ICU mortality was 26%, hospital mortality was 41%, and 6-month OS estimate was 25%. In multivariate analysis, ICU admission SOFA score > 10 (odds ratio (OR) 17.1, p < 0.0001), poorly differentiated tumor grade (OR 3.2, p = 0.02), and shorter duration of metastatic disease (OR 2.3, p = 0.07) were associated with increased odds of ICU mortality. These same variables were associated with increased odds of hospital mortality. In multivariate OS analysis, SOFA score 6-10 (hazard ratio (HR) 2.1, p = 0.0006) and SOFA score > 10 (HR 4.4, p < 0.0001), patients with GE primary (HR 2.2, p = 0.002) and patients with a poor outpatient performance status that precluded active chemotherapy (HR 2.2, p = 0.01) were associated with increased risk of death. Conclusions: The SOFA score was the most predictive factor for ICU mortality, hospital mortality, and OS for GI cancer patients admitted to the ICU. It should be utilized in all GI cancer patients upon ICU admission to improve both acute and longer-term prognostication.

scholarly journals Respiratory Modalities in Preventing Reintubation in a Pediatric Intensive Care Unit

2021 ◽  
Vol 8 ◽  
pp. 2333794X2199153
Author(s):  
Ameer Al-Hadidi ◽  
Morta Lapkus ◽  
Patrick Karabon ◽  
Begum Akay ◽  
Paras Khandhar
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Pediatric Intensive Care Unit ◽  
Noninvasive Positive Pressure Ventilation ◽  
Pediatric Intensive Care ◽  
Nasal Cannula ◽  
Respiratory Support ◽  
Positive Pressure ◽  
P Value

Post-extubation respiratory failure requiring reintubation in a Pediatric Intensive Care Unit (PICU) results in significant morbidity. Data in the pediatric population comparing various therapeutic respiratory modalities for avoiding reintubation is lacking. Our objective was to compare therapeutic respiratory modalities following extubation from mechanical ventilation. About 491 children admitted to a single-center PICU requiring mechanical ventilation from January 2010 through December 2017 were retrospectively reviewed. Therapeutic respiratory support assisted in avoiding reintubation in the majority of patients initially extubated to room air or nasal cannula with high-flow nasal cannula (80%) or noninvasive positive pressure ventilation (100%). Patients requiring therapeutic respiratory support had longer PICU LOS (10.92 vs 6.91 days, P-value = .0357) and hospital LOS (16.43 vs 10.20 days, P-value = .0250). Therapeutic respiratory support following extubation can assist in avoiding reintubation. Those who required therapeutic respiratory support experienced a significantly longer PICU and hospital LOS. Further prospective clinical trials are warranted.

scholarly journals 1412. The utility of respiratory viral panel testing for nosocomial fever in the neonatal intensive care unit

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S713-S713
Author(s):  
Carlo Fopiano Palacios ◽  
Eric Lemmon ◽  
James Campbell
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Linear Regression ◽  
Length Of Stay ◽  
Neonatal Intensive Care Unit ◽  
Neonatal Intensive Care ◽  
P Value ◽  
Fisher Exact Test ◽  
The Mean ◽  
Pcr Test

Abstract Background Patients in the neonatal intensive care unit (NICU) often develop fevers during their inpatient stay. Many neonates are empirically started on antibiotics due to their fragile clinical status. We sought to evaluate whether the respiratory viral panel (RVP) PCR test is associated with use of antibiotics in patients who develop a fever in the NICU. Methods We conducted a retrospective chart review on patients admitted to the Level 4 NICU of the University of Maryland Medical Center from November 2015 to June 2018. We included all neonates who developed a fever 48 hours into their admission. We collected demographic information and data on length of stay, fever work-up and diagnostics (including labs, cultures, RVP), and antibiotic use. Descriptive statistics, Fisher exact test, linear regression, and Welch’s ANOVA were performed. Results Among 347 fever episodes, the mean age of neonates was 72.8 ± 21.6 days, and 45.2% were female. Out of 30 total RVP samples analyzed, 2 were positive (6.7%). The most common causes of fever were post-procedural (5.7%), pneumonia (4.8%), urinary tract infection (3.5%), meningitis (2.6%), bacteremia (2.3%), or due to a viral infection (2.0%). Antibiotics were started in 208 patients (60%), while 61 neonates (17.6%) were already on antibiotics. The mean length of antibiotics was 7.5 ± 0.5 days. Neonates were more likely to get started on antibiotics if they had a negative RVP compared to those without a negative RVP (89% vs. 11%, p-value &lt; 0.0001). Patients with a positive RVP had a decreased length of stay compared to those without a positive RVP (30.3 ± 8.7 vs. 96.8 ± 71.3, p-value 0.01). On multivariate linear regression, a positive RVP was not associated with length of stay. Conclusion Neonates with a negative respiratory viral PCR test were more likely to be started on antibiotics for fevers. Respiratory viral PCR testing can be used as a tool to promote antibiotic stewardship in the NICU. Disclosures All Authors: No reported disclosures

The presence of liver cirrhosis is a strong negative predictor of survival for patients admitted to the intensive care unit – Cirrhosis in intensive care patients

2021 ◽  
Author(s):  
Jörg Bojunga ◽  
Mireen Friedrich-Rust ◽  
Alica Kubesch ◽  
Kai Henrik Peiffer ◽  
Hannes Abramowski ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Liver Cirrhosis ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Intensive Care Treatment ◽  
Matched Cohort ◽  
Care Treatment ◽  
Cirrhotic Patients ◽  
The Impact ◽  
Cirrhotic Group

Abstract Background and Aims Liver cirrhosis is a systemic disease that substantially impacts the body’s physiology, especially in advanced stages. Accordingly, the outcome of patients with cirrhosis requiring intensive care treatment is poor. We aimed to analyze the impact of cirrhosis on mortality of intensive care unit (ICU) patients compared to other frequent chronic diseases and conditions. Methods In this retrospective study, patients admitted over three years to the ICU of the Department of Medicine of the University Hospital Frankfurt were included. Patients were matched for age, gender, pre-existing conditions, simplified acute physiology score (SAPS II), and therapeutic intervention scoring system (TISS). Results A total of 567 patients admitted to the ICU were included in the study; 99 (17.5 %) patients had liver cirrhosis. A total of 129 patients were included in the matched cohort for the sensitivity analysis. In-hospital mortality was higher in cirrhotic patients than non-cirrhotic patients (p < 0.0001) in the entire and matched cohort. Liver cirrhosis remained one of the strongest independent predictors of in-hospital mortality (entire cohort p = 0.001; matched cohort p = 0.03) along with dialysis and need for transfusion in the multivariate logistic regression analysis. Furthermore, in the cirrhotic group, the need for kidney replacement therapy (p < 0.001) and blood transfusion (p < 0.001) was significantly higher than in the non-cirrhotic group.  Conclusions In the presented study, liver cirrhosis was one of the strongest predictors of in-hospital mortality in patients needing intensive care treatment along with dialysis and the need for ventilation. Therefore, concerted efforts are needed to improve cirrhotic patients’ outcomes, prevent disease progression, and avoid complications with the need for ICU treatment in the early stages of the disease.

scholarly journals Safety and efficacy of routine diagnostic test reduction interventions in patients admitted to the intensive care unit: A systematic review and meta-analysis

2021 ◽  
Vol 49 (1) ◽  
pp. 23-34
Author(s):  
Katherine P Hooper ◽  
Matthew H Anstey ◽  
Edward Litton
Keyword(s):  
Systematic Review ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Meta Analysis ◽  
Diagnostic Testing ◽  
Intervention Group ◽  
Cochrane Central Register ◽  
Safety And Efficacy ◽  
Significant Difference

Reducing unnecessary routine diagnostic testing has been identified as a strategy to curb wasteful healthcare. However, the safety and efficacy of targeted diagnostic testing strategies are uncertain. The aim of this study was to systematically review interventions designed to reduce pathology and chest radiograph testing in patients admitted to the intensive care unit (ICU). A predetermined protocol and search strategy included OVID MEDLINE, OVID EMBASE and the Cochrane Central Register of Controlled Trials from inception until 20 November 2019. Eligible publications included interventional studies of patients admitted to an ICU. There were no language restrictions. The primary outcomes were in-hospital mortality and test reduction. Key secondary outcomes included ICU mortality, length of stay, costs and adverse events. This systematic review analysed 26 studies (with more than 44,00 patients) reporting an intervention to reduce one or more diagnostic tests. No studies were at low risk of bias. In-hospital mortality, reported in seven studies, was not significantly different in the post-implementation group (829 of 9815 patients, 8.4%) compared with the pre-intervention group (1007 of 9848 patients, 10.2%), (relative risk 0.89, 95% confidence intervals 0.79 to 1.01, P = 0.06, I2 39%). Of the 18 studies reporting a difference in testing rates, all reported a decrease associated with targeted testing (range 6%–72%), with 14 (82%) studies reporting >20% reduction in one or more tests. Studies of ICU targeted test interventions are generally of low quality. The majority report substantial decreases in testing without evidence of a significant difference in hospital mortality.

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