External validation of the Simplified Acute Physiology Score (SAPS) 3 in Spain

Lopez-Caler, C.; García-Delgado, Manuel; Carpio-Sanz, J.; Álvarez-Rodríguez, Joaquín; Aguilar-Alonso, E.; Castillo-Lorente, E.; Barrueco-Francioni, J.E.; Rivera-Fernández, Ricardo

doi:10.1016/j.medine.2013.06.003

Cited by 5 publications

(6 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…0.79 (AUC). This is also less than normally registered for general ICU patients in, for example the Swedish Intensive Care Registry 24 , or in other international settings 25 , 26 where values are often in the range close to 0.85 24 , 26 . The reason for this lower value is unclear and may depend on the fact that comparatively few burns were included in the initial cohort used for the development of SAPS3 11 , 27 .…”

Section: Discussionmentioning

confidence: 70%

Addition of admission lactate levels to Baux score improves mortality prediction in severe burns

Steinvall

Elmasry

Abdelrahman

et al. 2021

Sci Rep

View full text Add to dashboard Cite

Risk adjustment and mortality prediction models are central in optimising care and for benchmarking purposes. In the burn setting, the Baux score and its derivatives have been the mainstay for predictions of mortality from burns. Other well-known measures to predict mortality stem from the ICU setting, where, for example, the Simplified Acute Physiology Score (SAPS 3) models have been found to be instrumental. Other attempts to further improve the prediction of outcome have been based on the following variables at admission: Sequential Organ Failure Assessment (aSOFA) score, determinations of aLactate or Neutrophil to Lymphocyte Ratio (aNLR). The aim of the present study was to examine if estimated mortality rate (EMR, SAPS 3), aSOFA, aLactate, and aNLR can, either alone or in conjunction with the others, improve the mortality prediction beyond that of the effects of age and percentage total body surface area (TBSA%) burned among patients with severe burns who need critical care. This is a retrospective, explorative, single centre, registry study based on prospectively gathered data. The study included 222 patients with median (25th–75th centiles) age of 55.0 (38.0 to 69.0) years, TBSA% burned was 24.5 (13.0 to 37.2) and crude mortality was 17%. As anticipated highest predicting power was obtained with age and TBSA% with an AUC at 0.906 (95% CI 0.857 to 0.955) as compared with EMR, aSOFA, aLactate and aNLR. The largest effect was seen thereafter by adding aLactate to the model, increasing AUC to 0.938 (0.898 to 0.979) (p < 0.001). Whereafter, adding EMR, aSOFA, and aNLR, separately or in combinations, only marginally improved the prediction power. This study shows that the prediction model with age and TBSA% may be improved by adding aLactate, despite the fact that aLactate levels were only moderately increased. Thereafter, adding EMR, aSOFA or aNLR only marginally affected the mortality prediction.

show abstract

Section: Discussionmentioning

confidence: 70%

Addition of admission lactate levels to Baux score improves mortality prediction in severe burns

Steinvall

Elmasry

Abdelrahman

et al. 2021

Sci Rep

View full text Add to dashboard Cite

show abstract

Section: Discussionmentioning

confidence: 99%

“…One way of improving a scoring system is to collect as many values of the proposed variables as possible, so that the model can predict the probability of a certain outcome with the desired discrimination. 31 Based on this premise, EqSAPS can be improved. The incomplete registration of values for some of the proposed variables, the small number of participant foals and few death occurrences in the studied cohort are likely the main cause of drop in performance observed in EqSAPS.…”

Section: Discussionmentioning

confidence: 99%

Equine simplified acute physiology score: Personalised medicine for the equine emergency patient

et al. 2021

View full text Add to dashboard Cite

Background: Scoring models are useful tools that guide the attending clinician in gauging the severity of disease evolution and in evaluating the efficacy of treatment. There are few tools available with this purpose for the non‐human patient, including horses. We aimed (i) to adapt the simplified acute physiology score 3 (SAPS‐3) model for the equine species, reaching a margin of accuracy greater than 75% in the calculation of the probability of survival/death and (ii) to build a decision tree that helps the attending veterinarian in assessment of the clinical evolution of the equine patient. Methods: From an initial pool of 5568 medical records from University‐based Veterinary Hospitals, a final cohort of 1000 was further mined manually for data extraction. A set of 19 variables were evaluated and tested by five machine learning data mining algorithms. Results: The final scoring model, named EqSAPS for equine simplified acute physiology score, reached 91.83% of correct estimates (post hoc) for probability of death within 24 hours upon hospitalization. The area under receiver operating characteristic curve for outcome ‘death’ was 0.742, while for ‘survival’ was 0.652. The final decision tree was able to refine prognosis of patients whose EqSAPS score suggested ‘death’. Conclusion: EqSAPS is a useful tool to gauge the severity of the clinical presentation of the equine patient.

show abstract

“…One way of improving a scoring system is to collect as many values of the proposed variables as possible, so that the model can predict the probability of death with the desired discrimination (López -Caler et al, 2014). Based on this premise, EqSAPS can be improved.…”

Section: Discussionmentioning

confidence: 99%

Equine Simplified Acute Physiology Score (EqSAPS): personalized medicine for the equine emergency patient

Barros¹,

Silva²,

Zibordi³

et al. 2020

Preprint

View full text Add to dashboard Cite

Scoring models are useful tools that guide the attending clinician in gauging the severity of disease evolution, and in evaluating the efficacy of treatment. There are few tools available with this purpose for the non-human patient, including horses. We aimed (i) to adapt the Simplified Acute Physiology Score 3 (SAPS-3) model for the equine species, reaching a margin of accuracy greater than 75% in the calculation of the probability of death, and (ii) to build a decision tree that helps the attending veterinarian in assessment of the clinical evolution of the equine patient. From an initial pool of 5 568 medical records from University-based Veterinary Hospitals, a final cohort of 1 000 was further mined manually for data extraction. A set of 19 variables were evaluated and tested by five data mining algorithms. The final scoring model, named EqSAPS for Equine Simplified Acute Physiology Score, reached 91.83% of correct estimates for probability of death within 24 hours upon hospitalization. The Area Under Receiver Operating Characteristic Curve (AUROC) for outcome “death” was 0.742, while for “survival” was 0.652. The final decision tree was able to refine prognosis of patients whose EqSAPS score suggested “death”. EqSAPS is an useful tool to gauge the severity of the clinical presentation of the equine patient.

show abstract

External validation of the Simplified Acute Physiology Score (SAPS) 3 in Spain

Cited by 5 publications

References 17 publications

Addition of admission lactate levels to Baux score improves mortality prediction in severe burns

Addition of admission lactate levels to Baux score improves mortality prediction in severe burns

Equine simplified acute physiology score: Personalised medicine for the equine emergency patient

Equine Simplified Acute Physiology Score (EqSAPS): personalized medicine for the equine emergency patient

Contact Info

Product

Resources

About