6 research outputs found
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Development of a Machine Learning Model of Postoperative Acute Kidney Injury Using Non-Invasive Time-Sensitive Intraoperative Predictors.
Acute kidney injury (AKI) is a major postoperative complication that lacks established intraoperative predictors. Our objective was to develop a prediction model using preoperative and high-frequency intraoperative data for postoperative AKI. In this retrospective cohort study, we evaluated 77,428 operative cases at a single academic center between 2016 and 2022. A total of 11,212 cases with serum creatinine (sCr) data were included in the analysis. Then, 8519 cases were randomly assigned to the training set and the remainder to the validation set. Fourteen preoperative and twenty intraoperative variables were evaluated using elastic net followed by hierarchical group least absolute shrinkage and selection operator (LASSO) regression. The training set was 56% male and had a median [IQR] age of 62 (51-72) and a 6% AKI rate. Retained model variables were preoperative sCr values, the number of minutes meeting cutoffs for urine output, heart rate, perfusion index intraoperatively, and the total estimated blood loss. The area under the receiver operator characteristic curve was 0.81 (95% CI, 0.77-0.85). At a score threshold of 0.767, specificity was 77% and sensitivity was 74%. A web application that calculates the model score is available online. Our findings demonstrate the utility of intraoperative time series data for prediction problems, including a new potential use of the perfusion index. Further research is needed to evaluate the model in clinical settings
Development of a Machine Learning Model of Postoperative Acute Kidney Injury Using Non-Invasive Time-Sensitive Intraoperative Predictors
Acute kidney injury (AKI) is a major postoperative complication that lacks established intraoperative predictors. Our objective was to develop a prediction model using preoperative and high-frequency intraoperative data for postoperative AKI. In this retrospective cohort study, we evaluated 77,428 operative cases at a single academic center between 2016 and 2022. A total of 11,212 cases with serum creatinine (sCr) data were included in the analysis. Then, 8519 cases were randomly assigned to the training set and the remainder to the validation set. Fourteen preoperative and twenty intraoperative variables were evaluated using elastic net followed by hierarchical group least absolute shrinkage and selection operator (LASSO) regression. The training set was 56% male and had a median [IQR] age of 62 (51–72) and a 6% AKI rate. Retained model variables were preoperative sCr values, the number of minutes meeting cutoffs for urine output, heart rate, perfusion index intraoperatively, and the total estimated blood loss. The area under the receiver operator characteristic curve was 0.81 (95% CI, 0.77–0.85). At a score threshold of 0.767, specificity was 77% and sensitivity was 74%. A web application that calculates the model score is available online. Our findings demonstrate the utility of intraoperative time series data for prediction problems, including a new potential use of the perfusion index. Further research is needed to evaluate the model in clinical settings
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Height and body surface area versus wall stress for stratification of mid-term outcomes in ascending aortic aneurysm
ObjectivesCurrent diameter-based guidelines for ascending thoracic aortic aneurysms (aTAA) do not consistently predict risk of dissection/rupture. ATAA wall stresses may enhance risk stratification independent of diameter. The relation of wall stresses and diameter indexed to height and body surface area (BSA) is unknown. Our objective was to compare aTAA wall stresses with indexed diameters in relation to all-cause mortality at 3.75 years follow-up.MethodsFinite element analyses were performed in a veteran population with aortas ≥ 4.0 cm. Three-dimensional geometries were reconstructed from computed tomography with models accounting for pre-stress geometries. A fiber-embedded hyperelastic material model was applied to obtain wall stress distributions under systolic pressure. Peak wall stresses were compared across guideline thresholds for diameter/BSA and diameter/height. Hazard ratios for all-cause mortality and surgical aneurysm repair were estimated using cause-specific Cox proportional hazards models.ResultsOf 253 veterans, 54 (21 %) had aneurysm repair at 3.75 years. Indexed diameter alone would have prompted repair at baseline in 17/253 (6.7 %) patients, including only 4/230 (1.7 %) with diameter < 5.5 cm. Peak wall stresses did not significantly differ across guideline thresholds for diameter/BSA (circumferential: p = 0.15; longitudinal: p = 0.18), but did differ for diameter/height (circumferential: p = 0.003; longitudinal: p = 0.048). All-cause mortality was independently associated with peak longitudinal stresses (p = 0.04). Peak longitudinal stresses were best predicted by diameter (c-statistic = 0.66), followed by diameter/height (c-statistic = 0.59), and diameter/BSA (c-statistic = 0.55).ConclusionsDiameter/height improved stratification of peak wall stresses compared to diameter/BSA. Peak longitudinal stresses predicted all-cause mortality independent of age and indexed diameter and may aid risk stratification for aTAA adverse events
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Ascending thoracic aortic aneurysm elongation occurs in parallel with dilatation in a nonsurgical population.
ObjectivesRapid diameter growth is a criterion for ascending thoracic aortic aneurysm repair; however, there are sparse data on aneurysm elongation rate. The purpose of this study was to assess aortic elongation rates in nonsyndromic, nonsurgical aneurysms to understand length dynamics and correlate with aortic diameter over time.MethodsPatients with <5.5-cm aneurysms and computed tomography angiography imaging at baseline and 3-5 years follow-up underwent patient-specific three-dimensional aneurysm reconstruction using MeVisLab. Aortic length was measured along the vessel centreline between the annulus and aortic arch. Maximum aneurysm diameter was determined from imaging in a plane normal to the vessel centreline. Average rates of aneurysm growth were evaluated using the longest available follow-up.ResultsOver the follow-up period, the mean aortic length for 67 identified patients increased from 118.2 (95% confidence interval: 115.4-121.1) mm to 120.2 (117.3-123.0) mm (P = 0.02) and 15 patients (22%) experienced a change in length of ≥5% from baseline. The mean annual growth rate for length [0.38 (95% confidence interval: 0.11-0.65) mm/year] was correlated with annual growth rate for diameter [0.1 (0.03-0.2) mm/year] (rho = 0.30, P = 0.01). Additionally, annual percentage change in length [0.3 (0.1-0.5)%/year] was similar to percentage change in diameter [0.2 (0.007-0.4)%/year, P = 0.95].ConclusionsAortic length increases in parallel with aortic diameter at a similar percentage rate. Further work is needed to identify whether elongation rate is associated with dissection risk. Such studies may provide insight into why patients with aortic diameters smaller than surgical guidelines continue to experience dissection events
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Rapid Detection of Powassan Virus in a Patient With Encephalitis by Metagenomic Sequencing
Abstract We describe a patient with severe and progressive encephalitis of unknown etiology. We performed rapid metagenomic sequencing from cerebrospinal fluid and identified Powassan virus, an emerging tick-borne flavivirus that has been increasingly detected in the United States