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Systematic review of predictive performance of injury severity scoring tools.

ABSTRACT: Many injury severity scoring tools have been developed over the past few decades. These tools include the Injury Severity Score (ISS), New ISS (NISS), Trauma and Injury Severity Score (TRISS) and International Classification of Diseases (ICD)-based Injury Severity Score (ICISS). Although many studies have endeavored to determine the ability of these tools to predict the mortality of injured patients, their results have been inconsistent. We conducted a systematic review to summarize the predictive performances of these tools and explore the heterogeneity among studies. We defined a relevant article as any research article that reported the area under the Receiver Operating Characteristic curve as a measure of predictive performance. We conducted an online search using MEDLINE and Embase. We evaluated the quality of each relevant article using a quality assessment questionnaire consisting of 10 questions. The total number of positive answers was reported as the quality score of the study. Meta-analysis was not performed due to the heterogeneity among studies. We identified 64 relevant articles with 157 AUROCs of the tools. The median number of positive answers to the questionnaire was 5, ranging from 2 to 8. Less than half of the relevant studies reported the version of the Abbreviated Injury Scale (AIS) and/or ICD (37.5%). The heterogeneity among the studies could be observed in a broad distribution of crude mortality rates of study data, ranging from 1% to 38%. The NISS was mostly reported to perform better than the ISS when predicting the mortality of blunt trauma patients. The relative performance of the ICSS against the AIS-based tools was inconclusive because of the scarcity of studies. The performance of the ICISS appeared to be unstable because the performance could be altered by the type of formula and survival risk ratios used. In conclusion, high-quality studies were limited. The NISS might perform better in the mortality prediction of blunt injuries than the ISS. Additional studies are required to standardize the derivation of the ICISS and determine the relative performance of the ICISS against the AIS-based tools.

SUBMITTER: Tohira H

PROVIDER: S-EPMC3511252 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Systematic review of predictive performance of injury severity scoring tools.

Tohira Hideo H Jacobs Ian I Mountain David D Gibson Nick N Yeo Allen A

Scandinavian journal of trauma, resuscitation and emergency medicine 20120910

Many injury severity scoring tools have been developed over the past few decades. These tools include the Injury Severity Score (ISS), New ISS (NISS), Trauma and Injury Severity Score (TRISS) and International Classification of Diseases (ICD)-based Injury Severity Score (ICISS). Although many studies have endeavored to determine the ability of these tools to predict the mortality of injured patients, their results have been inconsistent. We conducted a systematic review to summarize the predicti ...[more]

PMID: 22964071

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Project description:BACKGROUND:An accurate injury severity measurement is essential for the evaluation of pediatric trauma care and outcome research. The traditional Injury Severity Score (ISS) does not consider the differential risks of the Abbreviated Injury Scale (AIS) from different body regions nor is it pediatric specific. The objective of this study was to develop a weighted ISS (wISS) system for pediatric blunt trauma patients with better predictive power than ISS. METHODS:Based on the association between mortality and AIS from each of the six ISS body regions, we generated different weights for the component AIS scores used in the calculation of ISS. The weights and wISS were generated using the National Trauma Data Bank. The Nationwide Emergency Department Sample (NEDS) was used to validate our main results. Pediatric blunt trauma patients younger than 16 years were included, and mortality was the outcome. Discrimination (areas under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, negative predictive value, concordance) and calibration (Hosmer-Lemeshow statistic) were compared between the wISS and ISS. RESULTS:The areas under the receiver operating characteristic curves from the wISS and ISS are 0.88 versus 0.86 in ISS of 1 to 74 and 0.77 versus 0.64 in ISS of 25 to 74 (p < 0.0001). The wISS showed higher specificity, positive predictive value, negative predictive value, and concordance when they were compared at similar levels of sensitivity. The wISS had better calibration (smaller Hosmer-Lemeshow statistic) than the ISS (11.6 vs. 19.7 for ISS = 1-74 and 10.9 vs. 12.6 for ISS = 25-74). The wISS showed even better discrimination with the Nationwide Emergency Department Sample. CONCLUSION:By weighting the AIS from different body regions, the wISS had significantly better predictive power for mortality than the ISS, especially in critically injured children. LEVEL OF EVIDENCE AND STUDY TYPE:Prognostic/epidemiological, level IV.

Project description:BACKGROUND:Preschool screening for developmental difficulties is increasingly becoming part of routine health service provision and yet the scope and validity of tools used within these screening assessments is variable. The aim of this review is to report on the predictive validity of preschool screening tools for language and behaviour difficulties used in a community setting. METHODS:Studies reporting the predictive validity of language or behaviour screening tools in the preschool years were identified through literature searches of Ovid Medline, Embase, EBSCO CINAHL, PsycInfo and ERIC. We selected peer-reviewed journal articles reporting the use of a screening tool for language or behaviour in a population-based sample of children aged 2-6 years of age, including a validated comparison diagnostic assessment and follow-up assessment for calculation of predictive validity. RESULTS:A total of eleven eligible studies was identified. Six studies reported language screening tools, two reported behaviour screening tools and three reported combined language & behaviour screening tools. The Language Development Survey (LDS) administered at age 2 years achieved the best predictive validity performance of the language screening tools (sens 67%, spec 94%, NPV 88% and PPV 80%). The Strengths and Difficulties Questionnaire (SDQ) administered at age 4 years achieved the best predictive validity compared to other behaviour screening tools (Sens 31%, spec 93%, NPV 84% and PPV 52%). The SDQ and Sure Start Language Measure (SSLM) administered at 2.5 years achieved the best predictive validity of the combined language & behaviour assessments (sens 87%, spec 64%, NPV 97% and PPV 31). Predictive validity data and diagnostic odds ratios identified language screening tools as more effective and achieving higher sensitivity and positive predictive value than either behaviour or combined screening tools. Screening tools with combined behaviour and language assessments were more specific and achieved higher negative predictive value than individual language or behaviour screening tools. Parent-report screening tools for language achieved higher sensitivity, specificity and negative predictive value than direct child assessment. CONCLUSIONS:Universal screening tools for language and behaviour concerns in preschool aged children used in a community setting can demonstrate excellent predictive validity, particularly when they utilise a parent-report assessment. Incorporating these tools into routine child health surveillance could improve the rate of early identification of language and behavioural difficulties, enabling more informed referrals to specialist services and facilitating access to early intervention.

Project description:BackgroundPredictive markers represent a solution for the proactive management of severe dengue. Despite the low mortality rate resulting from severe cases, dengue requires constant examination and round-the-clock nursing care due to the unpredictable progression of complications, posing a burden on clinical triage and material resources. Accordingly, identifying markers that allow for predicting disease prognosis from the initial diagnosis is needed. Given the improved pathogenesis understanding, myriad candidates have been proposed to be associated with severe dengue progression. Thus, we aim to review the relationship between the available biomarkers and severe dengue.MethodologyWe performed a systematic review and meta-analysis to compare the differences in host data collected within 72 hours of fever onset amongst the different disease severity levels. We searched nine bibliographic databases without restrictive criteria of language and publication date. We assessed risk of bias and graded robustness of evidence using NHLBI quality assessments and GRADE, respectively. This study protocol is registered in PROSPERO (CRD42018104495).Principal findingsOf 4000 records found, 40 studies for qualitative synthesis, 19 for meta-analysis. We identified 108 host and viral markers collected within 72 hours of fever onset from 6160 laboratory-confirmed dengue cases, including hematopoietic parameters, biochemical substances, clinical symptoms, immune mediators, viral particles, and host genes. Overall, inconsistent case classifications explained substantial heterogeneity, and meta-analyses lacked statistical power. Still, moderate-certainty evidence indicated significantly lower platelet counts (SMD -0.65, 95% CI -0.97 to -0.32) and higher AST levels (SMD 0.87, 95% CI 0.36 to 1.38) in severe cases when compared to non-severe dengue during this time window.ConclusionThe findings suggest that alterations of platelet count and AST level-in the first 72 hours of fever onset-are independent markers predicting the development of severe dengue.

Project description:BackgroundPrognostic models-used in critical care medicine for mortality predictions, for benchmarking and for illness stratification in clinical trials-have been validated predominantly in high-income countries. These results may not be reproducible in low or middle-income countries (LMICs), not only because of different case-mix characteristics but also because of missing predictor variables. The study objective was to systematically review literature on the use of critical care prognostic models in LMICs and assess their ability to discriminate between survivors and non-survivors at hospital discharge of those admitted to intensive care units (ICUs), their calibration, their accuracy, and the manner in which missing values were handled.MethodsThe PubMed database was searched in March 2017 to identify research articles reporting the use and performance of prognostic models in the evaluation of mortality in ICUs in LMICs. Studies carried out in ICUs in high-income countries or paediatric ICUs and studies that evaluated disease-specific scoring systems, were limited to a specific disease or single prognostic factor, were published only as abstracts, editorials, letters and systematic and narrative reviews or were not in English were excluded.ResultsOf the 2233 studies retrieved, 473 were searched and 50 articles reporting 119 models were included. Five articles described the development and evaluation of new models, whereas 114 articles externally validated Acute Physiology and Chronic Health Evaluation, the Simplified Acute Physiology Score and Mortality Probability Models or versions thereof. Missing values were only described in 34% of studies; exclusion and or imputation by normal values were used. Discrimination, calibration and accuracy were reported in 94.0%, 72.4% and 25% respectively. Good discrimination and calibration were reported in 88.9% and 58.3% respectively. However, only 10 evaluations that reported excellent discrimination also reported good calibration. Generalisability of the findings was limited by variability of inclusion and exclusion criteria, unavailability of post-ICU outcomes and missing value handling.ConclusionsRobust interpretations regarding the applicability of prognostic models are currently hampered by poor adherence to reporting guidelines, especially when reporting missing value handling. Performance of mortality risk prediction models in LMIC ICUs is at best moderate, especially with limitations in calibration. This necessitates continued efforts to develop and validate LMIC models with readily available prognostic variables, perhaps aided by medical registries.

Project description:BackgroundComputerized migraine diagnostic tools have been developed and validated since 1960. We conducted a systematic review to summarize and critically appraise the quality of all published studies involving computerized migraine diagnostic tools.MethodsWe performed a systematic literature search using PubMed, Web of Science, Scopus, snowballing, and citation searching. Cutoff date for search was 1 June 2021. Published articles in English that evaluated a computerized/automated migraine diagnostic tool were included. The following summarized each study: publication year, digital tool name, development basis, sample size, sensitivity, specificity, reference diagnosis, strength, and limitations. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool was applied to evaluate the quality of included studies in terms of risk of bias and concern of applicability.ResultsA total of 41 studies (median sample size: 288 participants, median age = 43 years; 77% women) were included. Most (60%) tools were developed based on International Classification of Headache Disorders criteria, half were self-administered, and 82% were evaluated using face-to-face interviews as reference diagnosis. Some of the automated algorithms and machine learning programs involved case-based reasoning, deep learning, classifier ensemble, ant-colony, artificial immune, random forest, white and black box combinations, and hybrid fuzzy expert systems. The median diagnostic accuracy was concordance = 89% [interquartile range (IQR) = 76-93%; range = 45-100%], sensitivity = 87% (IQR = 80-95%; range = 14-100%), and specificity = 90% (IQR = 77-96%; range = 65-100%). Lack of random patient sampling was observed in 95% of studies. Case-control designs were avoided in all studies. Most (76%) reference tests exhibited low risk of bias and low concern of applicability. Patient flow and timing showed low risk of bias in 83%.ConclusionDifferent computerized and automated migraine diagnostic tools are available with varying accuracies. Random patient sampling, head-to-head comparison among tools, and generalizability to other headache diagnoses may improve their utility.

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Systematic review of predictive performance of injury severity scoring tools.

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Systematic review of predictive performance of injury severity scoring tools.

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