scholarly journals Does the implementation of a novel intensive care discharge risk score and nurse-led inpatient review tool improve outcome? A prospective cohort study in two intensive care units in the UK

BMJ Open ◽  
2017 ◽  
Vol 7 (12) ◽  
pp. e018322
Author(s):  
Jez Fabes ◽  
William Seligman ◽  
Carolyn Barrett ◽  
Stuart McKechnie ◽  
John Griffiths
Keyword(s):  
Intensive Care ◽  
High Risk ◽  
Risk Score ◽  
Prospective Cohort ◽  
Data Set ◽  
High Risk Patients ◽  
Poor Outcome ◽  
Icu Discharge ◽  
Risk Patients ◽  
Risk Scoring

ObjectiveTo develop a clinical prediction model for poor outcome after intensive care unit (ICU) discharge in a large observational data set and couple this to an acute post-ICU ward-based review tool (PIRT) to identify high-risk patients at the time of ICU discharge and improve their acute ward-based review and outcome.DesignRetrospective patient cohort of index ICU admissions between June 2006 and October 2011 receiving routine inpatient review. Prospective cohort between March 2012 and March 2013 underwent risk scoring (PIRT) which subsequently guided inpatient ward-based review.SettingTwo UK adult ICUs.Participants4212 eligible discharges from ICU in the retrospective development cohort and 1028 patients included in the prospective intervention cohort.InterventionsMultivariate analysis was performed to determine factors associated with poor outcome in the retrospective cohort and used to generate a discharge risk score. A discharge and daily ward-based review tool incorporating an adjusted risk score was introduced. The prospective cohort underwent risk scoring at ICU discharge and inpatient review using the PIRT.OutcomesThe primary outcome was the composite of death or readmission to ICU within 14 days of ICU discharge following the index ICU admission.ResultsPIRT review was achieved for 67.3% of all eligible discharges and improved the targeting of acute post-ICU review to high-risk patients. The presence of ward-based PIRT review in the prospective cohort did not correlate with a reduction in poor outcome overall (P=0.876) or overall readmission but did reduce early readmission (within the first 48 hours) from 4.5% to 3.6% (P=0.039), while increasing the rate of late readmission (48 hours to 14 days) from 2.7% to 5.8% (P=0.046).ConclusionPIRT facilitates the appropriate targeting of nurse-led inpatient review acutely after ICU discharge but does not reduce hospital mortality or overall readmission rates to ICU.

Effect of a Real-Time Risk Score on 30-day Readmission Reduction in Singapore

2021 ◽  
Vol 12 (02) ◽  
pp. 372-382
Author(s):  
Christine Xia Wu ◽  
Ernest Suresh ◽  
Francis Wei Loong Phng ◽  
Kai Pik Tai ◽  
Janthorn Pakdeethai ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Risk ◽  
Real Time ◽  
Risk Score ◽  
Patient Specific ◽  
Learning Models ◽  
Medicine Department ◽  
High Risk Patients ◽  
Risk Patients ◽  
Machine Learning Models

Abstract Objective To develop a risk score for the real-time prediction of readmissions for patients using patient specific information captured in electronic medical records (EMR) in Singapore to enable the prospective identification of high-risk patients for enrolment in timely interventions. Methods Machine-learning models were built to estimate the probability of a patient being readmitted within 30 days of discharge. EMR of 25,472 patients discharged from the medicine department at Ng Teng Fong General Hospital between January 2016 and December 2016 were extracted retrospectively for training and internal validation of the models. We developed and implemented a real-time 30-day readmission risk score generation in the EMR system, which enabled the flagging of high-risk patients to care providers in the hospital. Based on the daily high-risk patient list, the various interfaces and flow sheets in the EMR were configured according to the information needs of the various stakeholders such as the inpatient medical, nursing, case management, emergency department, and postdischarge care teams. Results Overall, the machine-learning models achieved good performance with area under the receiver operating characteristic ranging from 0.77 to 0.81. The models were used to proactively identify and attend to patients who are at risk of readmission before an actual readmission occurs. This approach successfully reduced the 30-day readmission rate for patients admitted to the medicine department from 11.7% in 2017 to 10.1% in 2019 (p < 0.01) after risk adjustment. Conclusion Machine-learning models can be deployed in the EMR system to provide real-time forecasts for a more comprehensive outlook in the aspects of decision-making and care provision.

scholarly journals A Tumor Progression Related 7-Gene Signature Indicates Prognosis and Tumor Immune Characteristics of Gastric Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Fen Liu ◽  
Zongcheng Yang ◽  
Lixin Zheng ◽  
Wei Shao ◽  
Xiujie Cui ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
High Risk ◽  
Cancer Progression ◽  
Risk Score ◽  
Risk Model ◽  
Cox Regression ◽  
Hub Genes ◽  
Cox Regression Analysis ◽  
High Risk Patients ◽  
Risk Patients

BackgroundGastric cancer is a common gastrointestinal malignancy. Since it is often diagnosed in the advanced stage, its mortality rate is high. Traditional therapies (such as continuous chemotherapy) are not satisfactory for advanced gastric cancer, but immunotherapy has shown great therapeutic potential. Gastric cancer has high molecular and phenotypic heterogeneity. New strategies for accurate prognostic evaluation and patient selection for immunotherapy are urgently needed.MethodsWeighted gene coexpression network analysis (WGCNA) was used to identify hub genes related to gastric cancer progression. Based on the hub genes, the samples were divided into two subtypes by consensus clustering analysis. After obtaining the differentially expressed genes between the subtypes, a gastric cancer risk model was constructed through univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis. The differences in prognosis, clinical features, tumor microenvironment (TME) components and immune characteristics were compared between subtypes and risk groups, and the connectivity map (CMap) database was applied to identify potential treatments for high-risk patients.ResultsWGCNA and screening revealed nine hub genes closely related to gastric cancer progression. Unsupervised clustering according to hub gene expression grouped gastric cancer patients into two subtypes related to disease progression, and these patients showed significant differences in prognoses, TME immune and stromal scores, and suppressive immune checkpoint expression. Based on the different expression patterns between the subtypes, we constructed a gastric cancer risk model and divided patients into a high-risk group and a low-risk group based on the risk score. High-risk patients had a poorer prognosis, higher TME immune/stromal scores, higher inhibitory immune checkpoint expression, and more immune characteristics suitable for immunotherapy. Multivariate Cox regression analysis including the age, stage and risk score indicated that the risk score can be used as an independent prognostic factor for gastric cancer. On the basis of the risk score, we constructed a nomogram that relatively accurately predicts gastric cancer patient prognoses and screened potential drugs for high-risk patients.ConclusionsOur results suggest that the 7-gene signature related to tumor progression could predict the clinical prognosis and tumor immune characteristics of gastric cancer.

scholarly journals Impact of the Beta-Glucan Test on Management of Intensive Care Unit Patients at Risk for Invasive Candidiasis

2020 ◽  
Vol 58 (6) ◽  
Author(s):  
Antonios Kritikos ◽  
Julien Poissy ◽  
Antony Croxatto ◽  
Pierre-Yves Bochud ◽  
Jean-Luc Pagani ◽  
...  
Keyword(s):  
Intensive Care ◽  
High Risk ◽  
Invasive Candidiasis ◽  
Test Results ◽  
Beta Glucan ◽  
High Risk Patients ◽  
Therapeutic Decisions ◽  
Risk Patients ◽  
The Impact ◽  
Test Result

ABSTRACT The 1,3-beta-d-glucan (BDG) test is used for the diagnosis of invasive candidiasis (IC) in intensive care units (ICUs). However, its utility for patient management is unclear. This study assessed the impact of BDG test results on therapeutic decisions. This was a single-center observational study conducted in an ICU over two 6-month periods. All BDG test requests for the diagnosis of IC were analyzed. Before the second period, the ICU physicians received a pocket card instruction (algorithm) for targeted BDG testing in high-risk patients. The performance of the BDG test for IC diagnosis was assessed, as well as its impact on antifungal (AF) prescription. Overall, 72 patients had ≥1 BDG test, and 14 (19%) patients had an IC diagnosis. The BDG test results influenced therapeutic decisions in 41 (57%) cases. The impact of the BDG test was positive in 30 (73%) of them, as follows: AF abstention/interruption following a negative BDG result (n = 27), and AF initiation/continuation triggered by a positive BDG test result and subsequently confirmed IC (n = 3). In 10 (24%) cases, a positive BDG test result resulted in AF initiation/continuation with no further evidence of IC. A negative BDG result and AF abstention with subsequent IC diagnosis were observed in one case. The positive predictive value (PPV) of BDG was improved if testing was restricted to the algorithm’s indications (80% versus 36%, respectively). However, adherence to the algorithm was low (26%), and no benefit of the intervention was observed. The BDG result had an impact on therapeutic decisions in more than half of the cases, which consisted mainly of safe AF interruption/abstention. Targeted BDG testing in high-risk patients improves PPV but is difficult to achieve in ICU.

scholarly journals AKI in Low-Risk versus High-Risk Patients in Intensive Care

2014 ◽  
Vol 10 (2) ◽  
pp. 187-196 ◽  
Author(s):  
Florentina E. Sileanu ◽  
Raghavan Murugan ◽  
Nicole Lucko ◽  
Gilles Clermont ◽  
Sandra L. Kane-Gill ◽  
...  
Keyword(s):  
Intensive Care ◽  
High Risk ◽  
Low Risk ◽  
High Risk Patients ◽  
Risk Patients

scholarly journals Risk Factors for New Detection of Vancomycin-Resistant Enterococci in Acute-Care Hospitals That Employ Strict Infection Control Procedures

2003 ◽  
Vol 47 (8) ◽  
pp. 2492-2498 ◽  
Author(s):  
Alexander A. Padiglione ◽  
Rory Wolfe ◽  
Elizabeth A. Grabsch ◽  
Di Olden ◽  
Stephen Pearson ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care ◽  
High Risk ◽  
Infection Control ◽  
Broad Spectrum ◽  
Rectal Swab ◽  
High Risk Patients ◽  
Vancomycin Resistant Enterococci ◽  
Risk Patients ◽  
Vancomycin Resistant

ABSTRACT Accurate assessment of the risk factors for colonization with vancomycin-resistant enterococci (VRE) among high-risk patients is often confounded by nosocomial VRE transmission. We undertook a 15-month prospective cohort study of adults admitted to high-risk units (hematology, renal, transplant, and intensive care) in three teaching hospitals that used identical strict infection control and isolation procedures for VRE to minimize nosocomial spread. Rectal swab specimens for culture were regularly obtained, and the results were compared with patient demographic factors and antibiotic exposure data. Compliance with screening was defined as “optimal” (100% compliance) or “acceptable” (minor protocol violations were allowed, but a negative rectal swab specimen culture was required within 1 week of becoming colonized with VRE). Colonization with VRE was detected in 1.56% (66 of 4,215) of admissions (0.45% at admission and 0.83% after admission; the acquisition time was uncertain for 0.28%), representing 1.91% of patients. No patients developed infection with VRE. The subsequent rate of new acquisition of VRE was 1.4/1,000 patient days. Renal units had the highest rate (3.23/1,000 patient days; 95% confidence interval [CI], 1.54 to 6.77/1,000 patient days). vanB Enterococcus faecium was the most common species (71%), but other species included vanB Enterococcus faecalis (21%), vanA E. faecium (6%), and vanA E. faecalis (2%). The majority of isolates were nonclonal by pulsed-field gel electrophoresis analysis. Multivariate analysis of risk factors in patients with an acceptable screening suggested that being managed by a renal unit (hazard ratio [HR] compared to the results for patients managed in an intensive care unit, 4.6; 95% CI, 1.2 to 17.0 [P = 0.02]) and recent administration of either ticarcillin-clavulanic acid (HR, 3.6; 95% CI, 1.1 to 11.6 [P = 0.03]) or carbapenems (HR, 2.8; 95% CI, 1.0, 8.0 [P = 0.05]), but not vancomycin or broad-spectrum cephalosporins, were associated with acquisition of VRE. The relatively low rates of colonization with VRE, the polyclonal nature of most isolates, and the possible association with the use of broad-spectrum antibiotics are consistent with either the endogenous emergence of VRE or the amplification of previously undetectable colonization with VRE among high-risk patients managed under conditions in which the risk of nosocomial acquisition was minimized.

scholarly journals The risk-treatment paradox in acute coronary syndrome patients: insights from the FORCE-ACS registry

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
J Azzahhafi ◽  
N M R Van Der Sangen ◽  
D R P P Chan Pin Yin ◽  
J P Simao Henriques ◽  
W J Kikkert ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Mortality Risk ◽  
Recommended Care ◽  
High Risk Patients ◽  
Grace Risk Score ◽  
Risk Patients ◽  
Risk Treatment ◽  
One Year ◽  
Risk Categories

Abstract Background Acute coronary syndrome (ACS) patients at high risk might benefit most from guideline-recommended interventions. However, it is well recognized that the delivery of guideline-directed care is inversely related to the estimated mortality risk, the so called risk-treatment paradox. Purpose To assess the existence of the risk-treatment paradox in a contemporary cohort of ACS patients and its possible association with one-year mortality. Methods The study population consisted patients enrolled in the FORCE-ACS registry who survived their initial admission. All ACS patients were stratified into low, intermediate or high mortality risk based on the Global Registry of Acute Coronary Events (GRACE) risk score. Optimal guideline-recommended care was defined as undergoing coronary angiography during initial hospital admission and receiving all outpatient medications with a class I guideline recommendation (i.e. aspirin, P2Y12-inhibitor, beta-blocker, angiotensin-converting enzyme inhibitor or angiotensin receptor blocker and cholesterol-lowering drug). Aspirin and/or a P2Y12-inhibitor on top of an oral anticoagulant was also considered as optimal guideline-recommended care. The cumulative incidence of one-year mortality between optimal and suboptimal managed patients, within each GRACE risk score stratum, was estimated. Results In total, 2,524 patients who were enrolled between January 2015 and June 2018 were included. Based on the GRACE risk score, 46.9% of patients were classified as low-risk, 37.6% as intermediate-risk and 15.5% as high-risk. Overall, 49.8% of patients received optimal guideline-recommended care. Among the different risk strata, 54.9% of the low-risk, 49.1% of the intermediate-risk and 36.1% of the high-risk patients received optimal guideline-recommended care (Table 1). DAPT or DAT treatment (95.3% overall) did not differ between the risk categories. Beta-blockers were prescribed less frequently (69.6% overall), butprescription rates did not differ between the risk categories. ACE-inhibitors/ARBs were prescribed in 74.1% of all patients, but less often in high risk patients. Cholesterol lowering-drugs were prescribed in almost all patients (94.9% overall), but less frequently in high risk patients. Overall, 93.9% of patients underwent coronary angiography (CAG), high-risk patients had a statistically significant lower likelihood of undergoing CAG. In all risk categories, optimal guideline-recommended care was associated with a lower one-year mortality as compared to sub-optimal treatment (5.7% vs. 15.6% in high-risk) (Fig. 1). Conclusion Patients at higher estimated mortality risk, based on the GRACE-risk score, are less likely to receive guideline-recommended care. Although, the absolute benefit from guideline-recommended care appears to be greater in high-risk patients. Receiving guideline-recommended care was associated with a statistically significant better prognosis in intermediate- and high-risk patients. FUNDunding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): ZonMW Netherlands TopZorgSt. Antonius Research funds Figure 1. All-cause mortality

scholarly journals Noninvasive ventilation versus conventional oxygen therapy after extubation failure in high-risk patients in an intensive care unit: a pragmatic clinical trial

2021 ◽  
Vol 33 (3) ◽  
Author(s):  
Alberto Belenguer-Muncharaz ◽  
Maria-Lidón Mateu-Campos ◽  
Bárbara Vidal-Tegedor ◽  
María- Desamparados Ferrándiz-Sellés ◽  
Maria-Luisa Micó-Gómez ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
High Risk ◽  
Noninvasive Ventilation ◽  
Oxygen Therapy ◽  
Extubation Failure ◽  
Pragmatic Clinical Trial ◽  
High Risk Patients ◽  
Risk Patients
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