A Comparison of the Abilities of Nine Scoring Algorithms in Predicting Mortality

Meredith, J. Wayne; Evans, Gregory W.; Kilgo, Patrick D.; MacKenzie, Ellen J.; Osler, Turner M.; McGwin, Gerald; Cohn, Stephen M.; Esposito, Thomas J.; Gennarelli, Thomas A.; Hawkins, Michael L.; Lucas, Charles E.; Mock, Charles; Rotondo, Michael F.; Rue, Loring W.

doi:10.1097/00005373-200210000-00001

Cited by 159 publications

(125 citation statements)

References 13 publications

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“…Using this scale, polytraumatized patients can be defined by the presence of lesions with AIS greater than or equal to 3 in at least two body regions [21][22][23][24] . The Injury Severity Score (ISS) is an anatomical index based on the AIS organic lesions scale and is one of the most frequent ways of assessing severity in trauma victims 25 . The lesions are grouped into six segments: head and neck, face, chest, abdomen, extremities and pelvis, and external.…”

Section: Methodsmentioning

confidence: 99%

Relação entre o mecanismo de trauma e lesões diagnosticadas em vítimas de trauma fechado

Parreira

Rondini

Below

et al. 2017

Rev. Col. Bras. Cir.

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Section: Methodsmentioning

confidence: 99%

Relação entre o mecanismo de trauma e lesões diagnosticadas em vítimas de trauma fechado

Parreira

Rondini

Below

et al. 2017

Rev. Col. Bras. Cir.

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“…17 The ICISS scores are derived empirically from each data set and have been shown in some studies to be more accurate than algorithm-derived ISS. [18][19][20] The accuracy of ICISS, however, may vary across data sets and may be inaccurate for rare diagnoses when derived from small data sets. 21 Because our ICD-10-to-AIS algorithm is based on consensus definitions rather than empirically derived data, algorithm performance should be minimally dependent on data sources.…”

Section: Researchmentioning

confidence: 99%

Overcoming barriers to population-based injury research: development and validation of an ICD-10–to–AIS algorithm

Xiong¹,

Brennan-Barnes²,

Gomez³

et al. 2012

Can J Surg

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Background: Hospital administrative databases are a useful source of populationlevel data on injured patients; however, these databases use the International Classification of Diseases (ICD) system, which does not provide a direct means of estimating injury severity. We created and validated a crosswalk to derive Abbreviated Injury Scale (AIS) scores from injury-related diagnostic codes in the tenth revision of the ICD (ICD-10). Methods:We assessed the validity of the crosswalk using data from the Ontario Trauma Registry Comprehensive Data Set (OTR-CDS). The AIS and Injury Severity Scores (ISS) derived using the algorithm were compared with those assigned by expert abstractors. We evaluated the ability of the algorithm to identify patients with AIS scores of 3 or greater. We used κ and intraclass correlation coefficients (ICC) as measures of concordance.Results: In total, 10 431 patients were identified in the OTR-CDS. The algorithm accurately identified patients with at least 1 AIS score of 3 or greater (κ 0.65), as well as patients with a head AIS score of 3 or greater (κ 0.78). Mapped and abstracted ISS were similar; ICC across the entire cohort was 0.83 (95% confidence interval 0.81-0.84), indicating good agreement. When comparing mapped and abstracted ISS, the difference between scores was 10 or less in 87% of patients. Concordance between mapped and abstracted ISS was similar across strata of age, mechanism of injury and mortality. Conclusion:Our ICD-10-to-AIS algorithm produces reliable estimates of injury severity from data available in administrative databases. This algorithm can facilitate the use of administrative data for population-based injury research in jurisdictions using ICD-10.Contexte : Les bases de données administratives des hôpitaux sont des sources utiles pour obtenir des données démographiques au sujet des patients victimes de blessures; ces bases de données utilisent toutefois le système de classification internationale des maladies (CIM) qui ne permet pas d'estimer directement la gravité des blessures. Nous avons créé et validé un tableau de concordance pour établir les scores de la listetype des blessures (LTB) à partir des codes de diagnostics liés aux traumatismes cités dans la dixième révision du manuel CIM (CIM-10).

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“…For trauma cases, we computed New Injury Severity Scores from hospital claim diagnosis codes (Appendix 4 of the Supplement) (22). We generated risk-adjusted hospital quality scores based on nonemergent surgical survival (Appendix 5 of the Supplement).…”

Section: Datamentioning

confidence: 99%

Outcomes of Basic Versus Advanced Life Support for Out-of-Hospital Medical Emergencies

Sanghavi¹,

Jena²,

Newhouse³

et al. 2016

Ann Intern Med

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A Comparison of the Abilities of Nine Scoring Algorithms in Predicting Mortality

Cited by 159 publications

References 13 publications

Relação entre o mecanismo de trauma e lesões diagnosticadas em vítimas de trauma fechado

Relação entre o mecanismo de trauma e lesões diagnosticadas em vítimas de trauma fechado

Overcoming barriers to population-based injury research: development and validation of an ICD-10–to–AIS algorithm

Outcomes of Basic Versus Advanced Life Support for Out-of-Hospital Medical Emergencies

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