scholarly journals Testing the Accuracy of a Bedside Screening Tool Framework to Clinical Records for Identification of Patients at Risk of Malnutrition in a Rural Setting: An Exploratory Study

Nutrients ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 205
Author(s):  
Laura Alston ◽  
Megan Green ◽  
Melanie Nichols ◽  
Stephanie R. Partridge ◽  
Alison Buccheri ◽  
...  
Keyword(s):  
At Risk ◽  
Diagnostic Accuracy ◽  
Sensitivity And Specificity ◽  
Exploratory Study ◽  
Screening Tool ◽  
Rural Setting ◽  
Receiver Operating Curve ◽  
Specificity And Sensitivity ◽  
Patients At Risk ◽  
Clinical Records

This study aimed to explore the diagnostic accuracy of the Patient-Generated Subjective Global Assessment (PG-SGA) malnutrition risk screening tool when used to score patients based on their electronic medical records (EMR), compared to bedside screening interviews. In-patients at a rural health service were screened at the bedside (n = 50) using the PG-SGA, generating a bedside score. Clinical notes within EMRs were then independently screened by blinded researchers. The accuracy of the EMR score was assessed against the bedside score using area under the receiver operating curve (AUC), sensitivity, and specificity. Participants were 62% female and 32% had conditions associated with malnutrition, with a mean age of 70.6 years (SD 14.9). The EMR score had moderate diagnostic accuracy relative to PG-SGA bedside screen, AUC 0.74 (95% CI: 0.59–0.89). The accuracy, specificity and sensitivity of the EMR score was highest for patients with a score of 7, indicating EMR screen is more likely to detect patients at risk of malnutrition. This exploratory study showed that applying the PG-SGA screening tool to EMRs had enough sensitivity and specificity for identifying patients at risk of malnutrition to warrant further exploration in low-resource settings.

Improving the Identification of Patients at Risk of Postoperative Renal Failure after Cardiac Surgery

2006 ◽  
Vol 104 (1) ◽  
pp. 65-72 ◽  
Author(s):  
Duminda N. Wijeysundera ◽  
Keyvan Karkouti ◽  
W Scott Beattie ◽  
Vivek Rao ◽  
Joan Ivanov
Keyword(s):  
At Risk ◽  
Logistic Regression ◽  
Renal Function ◽  
Cardiac Surgery ◽  
Renal Insufficiency ◽  
Care Center ◽  
Tertiary Care ◽  
Receiver Operating Curve ◽  
Alternative Measure ◽  
Patients At Risk

Background Preoperative renal insufficiency is an important predictor of the need for postoperative renal replacement therapy (RRT). Serum creatinine (sCr) has a limited ability to identify patients with preoperative renal insufficiency because it varies with age, sex, and muscle mass. Calculated creatinine clearance (CrCl) is an alternative measure of renal function that may allow better estimation of renal reserve. Methods Data were prospectively collected for consecutive patients who underwent cardiac surgery requiring cardiopulmonary bypass at a tertiary care center. The relation between CrCl (Cockcroft-Gault equation) and RRT was initially described using descriptive statistics, logistic regression, and receiver operating curve analysis. Based on these analyses, preoperative renal insufficiency was defined as CrCl of 60 ml/min or less. Preoperative renal function was classified as moderate insufficiency (sCr > 133 microM), mild insufficiency (100 microM < sCr < or = 133 microM), occult insufficiency (sCr < or = 100 microM and CrCl < or = 60 ml/min), or normal function (sCr < or = 100 microM and CrCl > 60 ml/min). The independent association of preoperative renal function with RRT was subsequently determined using multiple logistic regression. Results Of the 10,751 patients in the sample, 137 (1.2%) required postoperative RRT. Approximately 13% of patients with normal sCr had occult renal insufficiency. Occult renal insufficiency was independently associated with RRT (odds ratio, 2.80; 95% confidence interval, 1.39-5.33). The magnitude of this risk was similar to patients with mild renal insufficiency (P = 0.73). Conclusions The inclusion of a simple CrCl-based criterion in preoperative assessments may improve identification of patients at risk of needing postoperative RRT.

scholarly journals Malnutrition and cachexia among cancer out-patients in Nairobi, Kenya

2017 ◽  
Vol 6 ◽  
Author(s):  
L. U. Kaduka ◽  
Z. N. Bukania ◽  
Y. Opanga ◽  
R. Mutisya ◽  
A. Korir ◽  
...  
Keyword(s):  
At Risk ◽  
Screening Tool ◽  
Point Of Care ◽  
Cross Sectional Study ◽  
Fat Free Mass ◽  
Assessment Tools ◽  
Correct Identification ◽  
Cross Sectional ◽  
Cancer Management ◽  
Patients At Risk

AbstractCancer is the third leading cause of death in Kenya. However, there is scarce information on the nutritional status of cancer patients to guide in decision making. The present study sought to assess the risk of malnutrition, and factors associated with malnutrition and cachexia, among cancer out-patients, with the aim of informing nutrition programmes for cancer management in Kenya and beyond. This was a facility-based cross-sectional study performed at Kenyatta National Hospital and Texas Cancer Centre in Nairobi, Kenya. The risk of malnutrition was assessed using the Malnutrition Universal Screening Tool (MUST). Diagnoses of malnutrition and cachexia were done using the European Society of Clinical Nutrition and Metabolism (ESPEN) and Fearon criteria, respectively. A total of 512 participants were assessed. Those at risk of malnutrition were 33·1 % (12·5 % at medium risk, 20·6 % at high risk). Prevalence of malnutrition was 13·4 %. The overall weight loss >5 % over 3 months was 18·2 % and low fat-free mass index was 43·1 %. Prevalence of cachexia was 14·1 % compared with 8·5 % obtained using the local criteria. Only 18·6 % participants had received any form of nutrition services. Age was a predictor of malnutrition and cachexia in addition to site of cancer for malnutrition and cigarette smoking for cachexia. The use of the MUST as a screening tool at the first point of care should be explored. The predictive value of current nutrition assessment tools, and the local diagnostic criteria for malnutrition and cachexia should be reassessed to inform the development of appropriate clinical guidelines and future capacity-building initiatives that will ensure the correct identification of patients at risk for timely care.

scholarly journals Diagnostic Accuracy of Contrast-enhanced Ultrasonography Liver Imaging Reporting and Data System in Hepatocellular Carcinoma: A Systematic Review

2021 ◽  
Author(s):  
HuiFang Li ◽  
Wei Huang ◽  
Wei Zheng ◽  
Qing Li ◽  
YunZhu Dai ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
At Risk ◽  
Sensitivity And Specificity ◽  
Web Of Science ◽  
Reporting System ◽  
Data System ◽  
Liver Imaging ◽  
Contrast Enhanced ◽  
Patients At Risk ◽  
Contrast Enhanced Ultrasonography

Abstract Background: Contrast-enhanced Ultrasonography Liver Imaging Reporting and Data System (CEUS LI-RADS) released by American College of Radiology was a widely used reporting system for patients at risk with hepatocellular carcinoma (HCC). In CEUS LI-RADS, the categories range from definitely benign (LR-1), probably begin (LR-2), intermediate probability of malignancy (LR-3), probably HCC (LR-4) to definitely HCC (LR-5), malignancy (LR-M), or definite tumor in vein (LR-TIV). Methods: We searched MEDLINE, Web of Science, Cochrane, Embase, and Chinese databases to obtain eligible studies reporting on the diagnostic performance of CEUS LI-RADS in patients at risk for HCC. Results: Twelve studies were eligible in the analysis, including 5275 patients, 5739 observations, and 4066 HCCs. The pooled sensitivity and specificity were 70% (95% Confidence Interval [CI] 65%-74%), 94% (95% CI, 91%-96%) of LR-5 category as predictors of HCC, respectively. The pooled sensitivity and specificity of LR-M category as a predictor of non-HCC malignancy were 83% (95% CI, 71%-91%), 94% (95% CI 88%-97%), respectively. The pooled proportions of HCCs were 1% (95% CI 0%-6%) for LR-2, 20% (95% CI, 9%-34%) for LR-3, 78% (95% CI, 67%-88%) for LR-4, 97% (95% CI, 94%-99%) for LR-5, 40% (95% CI, 23%–58%) for LR-M and 100% (95% CI, 93%–100%) for LR-TIV.Conclusion: CEUS LI-RADS is an important tool for the diagnosis of HCC.

scholarly journals Diagnostic accuracy of urinary latex agglutination test (KAtex) for the diagnosis of visceral leishmaniasis: A meta-analysis

2018 ◽  
Vol 12 (12) ◽  
pp. 1045-1051 ◽  
Author(s):  
Mohammad Fararouei ◽  
Bahador Sarkari ◽  
Samaneh Abdolahi Khabisi ◽  
Zahra Rezaei
Keyword(s):  
Middle East ◽  
Visceral Leishmaniasis ◽  
Diagnostic Accuracy ◽  
Sensitivity And Specificity ◽  
Meta Analysis ◽  
Latex Agglutination ◽  
Agglutination Test ◽  
Latex Agglutination Test ◽  
Receiver Operating Curve ◽  
Significant Difference

Latex agglutination test (KAtex) has been used in the last two decades for the diagnosis of visceral leishmaniasis (VL) in different VL-endemic areas. Here, we present a meta-analysis of studies which evaluated the KAtex for the diagnosis of VL to find out its overall diagnostic performance. A database search was performed on PubMed, Scopus, ISI Web of Science, Iranmedex and Google Scholar. The search of databases found 57 papers, of which 17 articles fulfilled our eligibility criteria. Meta-analysis of diagnostic accuracy (MADA) and Hierarchical Summary Receiver Operating Curve (HSROC) packages were used to do the meta-analysis and to obtain pooled estimates of sensitivity and specificity. Fixed effect bivariate analysis was conducted, using Mantel-Haenszel estimator, to measure the performance and diagnosis odds ratio (DOR) of the test. Heterogeneity of the test results was assessed by Chi-squared test. The sensitivity of individual studies ranged from 39.8 to 100%, and the specificity ranged from 64 to100%. The combined sensitivity and specificity estimates of KAtex were 77% (95% CI, 70-83%), and 97% (95% CI, 93-97%), respectively. Comparing the performance of the test by region suggests a significant difference where the lowest and highest sensitivities are reported from Nepal/Tunisia and Europe/Middle East respectively (p < 0.05). On the other hand, the lowest and highest rates of specificity were reported from Sudan and America/Middle East respectively. The overall specificity of KAtex is satisfactory. However, KAtex suffers from low sensitivity and this shortcoming should be improved. The test provides a rapid and simple diagnosis of VL and improvement of its sensitivity deserve further studies.

scholarly journals P131: Emergency department falls risk management screening tool comparison

CJEM ◽  
2016 ◽  
Vol 18 (S1) ◽  
pp. S121-S122
Author(s):  
R. Tomlinson ◽  
T. Yokota ◽  
P. Jaggi ◽  
C. Kilburn ◽  
D. Bakken ◽  
...  
Keyword(s):  
At Risk ◽  
Emergency Department ◽  
Risk Management ◽  
Fall Risk ◽  
Screening Tool ◽  
Assessment Tool ◽  
Tertiary Care ◽  
Screening Tools ◽  
Procedural Sedation ◽  
Patients At Risk

Introduction: Emergency Department (ED) fall risk screening has been newly implemented in Alberta based on Accreditation Canada requirements. Two existing inpatient tools failed to include certain ED risk conditions. One tool graded unconsciousness as no risk for falling, and neither considered intoxication or sedation. This led to the development of a new fall risk management screening tool, the FRM (Tool1). This study compared Tool1 with inpatient utilized Schmid Fall Risk Assessment Tool (Tool2) and the validated Hendrich II Fall Risk Model (Tool3). Methods: Patients (≥17 years old) in a tertiary care adult ED with any of the following; history of falling in the last 12 months, elderly/frail, incontinence, impaired gait, mobility assist device, confusion/disorientation, procedural sedation, intoxication/sedated, or unconscious were included. Forms were randomized to score patients using different paired screening tools: Tool1 paired with either Tool2 or Tool3. Percent agreement (PA) between the tools based on identification of a patient at either risk/no risk for falling; higher PA indicating more tool homogeneity. Results: A total of 928 screening forms were completed within our 8-week study period; 452 and 443 comparing Tool1 to Tool2 and Tool1 to Tool3, respectively. Thirty-two forms included only Tool1 scores, excluding them from comparative analysis. The average patient age (n=895) was 64.8±21.4 years. Tool1 identified 66.4% of patients at risk, whereas Tool2 and Tool3 identified only 19.2% and 31.4%, respectively. Tool1 and 2 had a PA of 50.2%, whereas Tool1 and Tool3 had a PA of 65.9%. Conclusion: The FRM tool had higher agreement with the validated assessment tool, identifying patients at risk for falling but better identified patients presenting with intoxication, need for procedural sedation and unconsciousness. The other tools generally miss these common ED conditions, putting these patients at risk. Validation and reliability assessments of the FRM tool are warranted.

Prediction of Maternal Hemorrhage: Using Machine Learning to Identify Patients at Risk (Preprint)

2021 ◽  
Author(s):  
Jill M Westcott ◽  
Francine Hughes ◽  
Wenke Liu ◽  
Mark Grivainis ◽  
Iffath Hoskins ◽  
...  
Keyword(s):  
Machine Learning ◽  
At Risk ◽  
Postpartum Hemorrhage ◽  
Mode Of Delivery ◽  
Receiver Operating Curve ◽  
Stage Model ◽  
Learning Methods ◽  
Second Stage ◽  
Machine Learning Methods ◽  
Patients At Risk

BACKGROUND Postpartum hemorrhage remains one of the largest causes of maternal morbidity and mortality in the United States. OBJECTIVE To utilize machine learning techniques to identify patients at risk for postpartum hemorrhage at obstetric delivery. METHODS Women aged 18 to 55 delivering at a major academic center from July 2013 to October 2018 were included for analysis (n = 30,867). A total of 497 variables were collected from the electronic medical record including demographic information, obstetric, medical, surgical, and family history, vital signs, laboratory results, labor medication exposures, and delivery outcomes. Postpartum hemorrhage was defined as a blood loss of ≥ 1000 mL at the time of delivery, regardless of delivery method, with 2179 positive cases observed (7.06%). Supervised learning with regression-, tree-, and kernel-based machine learning methods was used to create classification models based upon training (n = 21,606) and validation (n = 4,630) cohorts. Models were tuned using feature selection algorithms and domain knowledge. An independent test cohort (n = 4,631) determined final performance by assessing for accuracy, area under the receiver operating curve (AUC), and sensitivity for proper classification of postpartum hemorrhage. Separate models were created using all collected data versus limited to data available prior to the second stage of labor/at the time of decision to proceed with cesarean delivery. Additional models examined patients by mode of delivery. RESULTS Gradient boosted decision trees achieved the best discrimination in the overall model. The model including all data mildly outperformed the second stage model (AUC 0.979, 95% CI 0.971-0.986 vs. AUC 0.955, 95% CI 0.939-0.970). Optimal model accuracy was 98.1% with a sensitivity of 0.763 for positive prediction of postpartum hemorrhage. The second stage model achieved an accuracy of 98.0% with a sensitivity of 0.737. Other selected algorithms returned models that performed with decreased discrimination. Models stratified by mode of delivery achieved good to excellent discrimination, but lacked sensitivity necessary for clinical applicability. CONCLUSIONS Machine learning methods can be used to identify women at risk for postpartum hemorrhage who may benefit from individualized preventative measures. Models limited to data available prior to delivery perform nearly as well as those with more complete datasets, supporting their potential utility in the clinical setting. Further work is necessary to create successful models based upon mode of delivery. An unbiased approach to hemorrhage risk prediction may be superior to human risk assessment and represents an area for future research.

scholarly journals Sample pre-treatment determines the clinical usefulness of acid-labile subunit immunoassays in the diagnosis of growth hormone deficiency and acromegaly

2007 ◽  
Vol 156 (3) ◽  
pp. 331-339 ◽  
Author(s):  
Katherine M Morrison ◽  
Martin Bidlingmaier ◽  
Simone Stadler ◽  
Zida Wu ◽  
Lars Skriver ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Sensitivity And Specificity ◽  
Clinical Usefulness ◽  
Size Exclusion ◽  
Hormone Deficiency ◽  
Specificity And Sensitivity ◽  
Acid Labile Subunit ◽  
Pre Treatment ◽  
Acid Labile ◽  
Igfbp 3

Objective: The usefulness of measuring the GH-dependent acid-labile subunit (ALS) in the management of GH deficiency (GHD) and acromegaly remains in question and is investigated in this study, comparing several different immunoassays for ALS. Method: We compared the diagnostic accuracy of a commercially available polyclonal Ab-based ELISA with SDS pre-treatment (SDS-ELISA) with a monoclonal Ab-based immunofluorometric assay, using two unfolding methods (urea (UREA) and Glycine-HCl (Gly)). The corresponding molecular weight (MW) of ALS and IGFBP-3 immunoreactivity was determined. The clinical usefulness of each assay was examined in adult GH disorders. Results: ALS was lower in GHD and higher in acromegaly using all assays. In GHD, UREA had higher sensitivity and specificity than SDS-ELISA (59 and 69% versus 41 and 51% respectively). In acromegaly, sensitivity and specificity was 94 and 87% for UREA, 81 and 36% for Gly, and 44 and 44% for SDS-ELISA. After UREA, immunoreactivity for ALS and IGFBP-3 eluted at their predicted free MW using size-exclusion chromatography, whereas ALS immunoreactivity in SDS (300–600 kDa) and Gly (250–500 kDa) was at a high apparent MW consistent with aggregation. Conclusion: The diagnostic accuracy of ALS varies with assay choice and pre-treatment modality. UREA, which results in migration of ALS at the expected MW on a sizing column, has the highest specificity and sensitivity. Thus, if measured in an assay in which ALS is unfolded without aggregation, ALS is a clinically highly useful parameter for the assessment of GH.

scholarly journals The DOWN Questionnaire: A Novel Screening Tool for Cervical Spondylotic Myelopathy

2018 ◽  
Vol 9 (6) ◽  
pp. 607-612
Author(s):  
Kaku Barkoh ◽  
Ifije E. Ohiorhenuan ◽  
Larry Lee ◽  
Joshua Lucas ◽  
Anush Arakelyan ◽  
...  
Keyword(s):  
At Risk ◽  
Cervical Spondylotic Myelopathy ◽  
Screening Tool ◽  
Case Control Study ◽  
High Sensitivity ◽  
Case Control ◽  
Advanced Imaging ◽  
Cord Injury ◽  
Patients At Risk ◽  
Control Study

Study Design: Case-control study. Objectives: Cervical spondylotic myelopathy (CSM) is the most common cause of spinal cord injury in adults aged over 55 years. However, since the onset is typically insidious, accurately diagnosing CSM can be challenging, often requiring referral to a subspecialist and advanced imaging. To help identify patients at risk for CSM, this case-control study compared responses to a series of 4 questions (DOWN questionnaire) in myelopathic and non-myelopathic patients. Methods: Ninety-two patients, 46 with and 46 without myelopathy, were recruited for the study. Each patient answered 4 questions encompassing common symptoms associated with CSM. Responses between patient groups were compared, and Cohen’s κ was used to assess for agreement between responses and the diagnosis of myelopathy. Results: We found a sensitivity of 91% and a κ of 0.54 to 3 positive responses and a sensitivity of 72% and a κ of 0.61 to 4 positive responses. Conclusions: Positive responses to 3 or more DOWN questions has high sensitivity and moderate agreement with the diagnosis of myelopathy based on history, physical exam, and review of advanced imaging by an orthopedic or neurological surgeon. The DOWN questionnaire is a potentially useful screening tool to identify patients at risk for CSM.

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