FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4280494042> ?p ?o ?g. }

• W4280494042 endingPage "264" @default.
• W4280494042 startingPage "260" @default.
• W4280494042 abstract "To investigate the value of machine learning methods for predicting in-hospital mortality in trauma patients with acute respiratory distress syndrome (ARDS).A retrospective non-intervention case-control study was performed. Trauma patients with ARDS met the Berlin definition were extracted from the the Medical Information Mart for Intensive Care III (MIMIC III) database. The basic information [including gender, age, body mass index (BMI), pH, oxygenation index, laboratory indexes, length of stay in the intensive care unit (ICU), the proportion of mechanical ventilation (MV) or continuous renal replacement therapy (CRRT), acute physiology score III (APS III), sequential organ failure score (SOFA) and simplified acute physiology score II (SAPS II)], complications (including hypertension, diabetes, infection, acute hemorrhagic anemia, sepsis, shock, acidosis and pneumonia) and prognosis data of patients were collected. Multivariate Logistic regression analysis was used to screen meaningful variables (P < 0.05). Logistic regression model, XGBoost model and artificial neural network model were constructed, and the receiver operator characteristic curve (ROC) was performed to evaluate the predictive value of the three models for in-hospital mortality in trauma patients with ARDS.A total of 760 trauma patients with ARDS were enrolled, including 346 mild cases, 301 moderate cases and 113 severe cases; 618 cases survived and 142 cases died in hospital; 736 cases received MV and 65 cases received CRRT. Multivariate Logistic regression analysis screened out significant variables, including age [odds ratio (OR) = 1.035, 95% confidence interval (95%CI) was 1.020-1.050, P < 0.001], BMI (OR = 0.949, 95%CI was 0.917-0.983, P = 0.003), blood urea nitrogen (BUN; OR = 1.019, 95%CI was 1.004-1.033, P = 0.010), lactic acid (Lac; OR = 1.213, 95%CI was 1.124-1.309, P < 0.001), red cell volume distribution width (RDW; OR = 1.249, 95%CI was 1.102-1.416, P < 0.001), hematocrit (HCT, OR = 1.057, 95%CI was 1.019-1.097, P = 0.003), hypertension (OR = 0.614, 95%CI was 0.389-0.968, P = 0.036), infection (OR = 0.463, 95%CI was 0.289-0.741, P = 0.001), acute renal failure (OR = 2.021, 95%CI was 1.267-3.224, P = 0.003) and sepsis (OR = 2.105, 95%CI was 1.265-3.502, P = 0.004). All the above variables were used to construct the model. Logistic regression model, XGBoost model and artificial neural network model predicted in-hospital mortality with area under the curve (AUC) of 0.737 (95%CI was 0.659-0.815), 0.745 (95%CI was 0.672-0.819) and 0.757 (95%CI was 0.680-0.884), respectively. There was no significant difference between any two models (all P > 0.05).Logistic regression model, XGBoost model and artificial neural network model including age, BMI, BUN, Lac, RDW, HCT, hypertension, infection, acute renal failure and sepsis have good predictive value for in-hospital mortality of trauma patients with ARDS." @default.
• W4280494042 created "2022-05-22" @default.
• W4280494042 creator A5002139784 @default.
• W4280494042 creator A5020203744 @default.
• W4280494042 creator A5048976159 @default.
• W4280494042 date "2022-03-01" @default.
• W4280494042 modified "2023-10-16" @default.
• W4280494042 title "[Predictive value of machine learning for in-hospital mortality for trauma-induced acute respiratory distress syndrome patients: an analysis using the data from MIMIC III]." @default.
• W4280494042 doi "https://doi.org/10.3760/cma.j.cn121430-20211117-01741" @default.
• W4280494042 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35574742" @default.
• W4280494042 hasPublicationYear "2022" @default.
• W4280494042 type Work @default.
• W4280494042 citedByCount "1" @default.
• W4280494042 crossrefType "journal-article" @default.
• W4280494042 hasAuthorship W4280494042A5002139784 @default.
• W4280494042 hasAuthorship W4280494042A5020203744 @default.
• W4280494042 hasAuthorship W4280494042A5048976159 @default.
• W4280494042 hasConcept C126322002 @default.
• W4280494042 hasConcept C151956035 @default.
• W4280494042 hasConcept C156957248 @default.
• W4280494042 hasConcept C2776348555 @default.
• W4280494042 hasConcept C2776376669 @default.
• W4280494042 hasConcept C2777080012 @default.
• W4280494042 hasConcept C2777371824 @default.
• W4280494042 hasConcept C2777465075 @default.
• W4280494042 hasConcept C2777714996 @default.
• W4280494042 hasConcept C2779541074 @default.
• W4280494042 hasConcept C2780221984 @default.
• W4280494042 hasConcept C2780347030 @default.
• W4280494042 hasConcept C44249647 @default.
• W4280494042 hasConcept C58471807 @default.
• W4280494042 hasConcept C71924100 @default.
• W4280494042 hasConceptScore W4280494042C126322002 @default.
• W4280494042 hasConceptScore W4280494042C151956035 @default.
• W4280494042 hasConceptScore W4280494042C156957248 @default.
• W4280494042 hasConceptScore W4280494042C2776348555 @default.
• W4280494042 hasConceptScore W4280494042C2776376669 @default.
• W4280494042 hasConceptScore W4280494042C2777080012 @default.
• W4280494042 hasConceptScore W4280494042C2777371824 @default.
• W4280494042 hasConceptScore W4280494042C2777465075 @default.
• W4280494042 hasConceptScore W4280494042C2777714996 @default.
• W4280494042 hasConceptScore W4280494042C2779541074 @default.
• W4280494042 hasConceptScore W4280494042C2780221984 @default.
• W4280494042 hasConceptScore W4280494042C2780347030 @default.
• W4280494042 hasConceptScore W4280494042C44249647 @default.
• W4280494042 hasConceptScore W4280494042C58471807 @default.
• W4280494042 hasConceptScore W4280494042C71924100 @default.
• W4280494042 hasIssue "3" @default.
• W4280494042 hasLocation W42804940421 @default.
• W4280494042 hasOpenAccess W4280494042 @default.
• W4280494042 hasPrimaryLocation W42804940421 @default.
• W4280494042 hasRelatedWork W156882 @default.
• W4280494042 hasRelatedWork W1651072 @default.
• W4280494042 hasRelatedWork W2520082 @default.
• W4280494042 hasRelatedWork W2610959 @default.
• W4280494042 hasRelatedWork W3866563 @default.
• W4280494042 hasRelatedWork W4096256 @default.
• W4280494042 hasRelatedWork W4346409 @default.
• W4280494042 hasRelatedWork W4448858 @default.
• W4280494042 hasRelatedWork W941055 @default.
• W4280494042 hasRelatedWork W4339174 @default.
• W4280494042 hasVolume "34" @default.
• W4280494042 isParatext "false" @default.
• W4280494042 isRetracted "false" @default.
• W4280494042 workType "article" @default.