- Pediatrics
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Early detection of bloodstream infection in critically ill children using artificial intelligence
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Hye-Ji Han, Kyunghoon Kim, June Dong Park
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Acute Crit Care. 2024;39(4):611-620. Published online November 22, 2024
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DOI: https://doi.org/10.4266/acc.2024.00752
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 Abstract
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- Background
Despite the high mortality associated with bloodstream infection (BSI), early detection of this condition is challenging in critical settings. The objective of this study was to create a machine learning tool for rapid recognition of BSI in critically ill children.
Methods
Data were extracted from a derivative cohort comprising patients who underwent at least one blood culture during hospitalization in the pediatric intensive care unit (PICU) of a tertiary hospital from January 2020 to June 2023 for model development. Data from another tertiary hospital were utilized for external validation. Variables selected for model development were age, white blood cell count with segmented neutrophil count, C-reactive protein, bilirubin, liver enzymes, glucose, body temperature, heart rate, and respiratory rate. Algorithms compared were extra trees, random forest, light gradient boosting, extreme gradient boosting, and CatBoost.
Results
We gathered 1,806 measurements and recorded 290 hospitalizations from 263 patients in the derivative cohort. Median age on admission was 43 months, with an interquartile range of 10–118.75 months, and a male predominance was observed (n=160, 55.2%). Candida albicans was the most prevalent pathogen, and median duration to confirm BSI was 3 days (range, 3–4). Patients with BSI experienced significantly higher in-hospital mortality and prolonged stays in the PICU than patients without BSI. Random forest classifier achieved the highest area under the receiver operating characteristic curve of 0.874 (0.762 for the validation set).
Conclusions
We developed a machine learning model that predicts BSI with acceptable performance. Further research is necessary to validate its effectiveness.
- Pediatrics
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A deep learning model for estimating sedation levels using heart rate variability and vital signs: a retrospective cross-sectional study at a center in South Korea
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You Sun Kim, Bongjin Lee, Wonjin Jang, Yonghyuk Jeon, June Dong Park
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Acute Crit Care. 2024;39(4):621-629. Published online November 25, 2024
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DOI: https://doi.org/10.4266/acc.2024.01200
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Abstract
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 Supplementary Material
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Optimal sedation assessment in critically ill children remains challenging due to the subjective nature of behavioral scales and intermittent evaluation schedules. This study aimed to develop a deep learning model based on heart rate variability (HRV) parameters and vital signs to predict effective and safe sedation levels in pediatric patients.
Methods
This retrospective cross-sectional study was conducted in a pediatric intensive care unit at a tertiary children’s hospital. We developed deep learning models incorporating HRV parameters extracted from electrocardiogram waveforms and vital signs to predict Richmond Agitation-Sedation Scale (RASS) scores. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC). The data were split into training, validation, and test sets (6:2:2), and the models were developed using a 1D ResNet architecture.
Results
Analysis of 4,193 feature sets from 324 patients achieved excellent discrimination ability, with AUROC values of 0.867, 0.868, 0.858, 0.851, and 0.811 for whole number RASS thresholds of −5 to −1, respectively. AUPRC values ranged from 0.928 to 0.623, showing superior performance in deeper sedation levels. The HRV metric SDANN2 showed the highest feature importance, followed by systolic blood pressure and heart rate.
Conclusions
A combination of HRV parameters and vital signs can effectively predict sedation levels in pediatric patients, offering the potential for automated and continuous sedation monitoring in pediatric intensive care settings. Future multi-center validation studies are needed to establish broader applicability.
- Epidemiology
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Pediatric septic shock estimation using deep learning and electronic medical records
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Ji Weon Lee, Bongjin Lee, June Dong Park
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Acute Crit Care. 2024;39(3):400-407. Published online August 1, 2024
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DOI: https://doi.org/10.4266/acc.2024.00031
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Abstract
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- Background
Diagnosing pediatric septic shock is difficult due to the complex and often impractical traditional criteria, such as systemic inflammatory response syndrome (SIRS), which result in delays and higher risks. This study aims to develop a deep learning-based model using SIRS data for early diagnosis in pediatric septic shock cases. Methods: The study analyzed data from pediatric patients (<18 years old) admitted to a tertiary hospital from January 2010 to July 2023. Vital signs, lab tests, and clinical information were collected. Septic shock cases were identified using SIRS criteria and inotrope use. A deep learning model was trained and evaluated using the area under the receiver operating characteristics curve (AUROC) and area under the precision-recall curve (AUPRC). Variable contributions were analyzed using the Shapley additive explanation value. Results: The analysis, involving 9,616,115 measurements, identified 34,696 septic shock cases (0.4%). Oxygen supply was crucial for 41.5% of the control group and 20.8% of the septic shock group. The final model showed strong performance, with an AUROC of 0.927 and AUPRC of 0.879. Key influencers were age, oxygen supply, sex, and partial pressure of carbon dioxide, while body temperature had minimal impact on estimation. Conclusions: The proposed deep learning model simplifies early septic shock diagnosis in pediatric patients, reducing the diagnostic workload. Its high accuracy allows timely treatment, but external validation through prospective studies is needed.
- Epidemiology
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Outcomes of extracorporeal membrane oxygenation support in pediatric hemato-oncology patients
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Hong Yul An, Hyoung Jin Kang, June Dong Park
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Acute Crit Care. 2024;39(1):108-116. Published online January 24, 2024
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DOI: https://doi.org/10.4266/acc.2023.01088
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Abstract
PDFSupplementary Material
- Background
In this study, we reviewed the outcomes of pediatric patients with malignancies who underwent hematopoietic stem cell transplantation (HSCT) and extracorporeal membrane oxygenation (ECMO). Methods: We retrospectively analyzed the records of pediatric hemato-oncology patients treated with chemotherapy or HSCT and who received ECMO in the pediatric intensive care unit (PICU) at Seoul National University Children’s Hospital from January 2012 to December 2020. Results: Over a 9-year period, 21 patients (14 males and 7 females) received ECMO at a single pediatric institute; 10 patients (48%) received veno-arterial (VA) ECMO for septic shock (n=5), acute respiratory distress syndrome (ARDS) (n=3), stress-induced myopathy (n=1), or hepatopulmonary syndrome (n=1); and 11 patients (52%) received veno-venous (VV) ECMO for ARDS due to pneumocystis pneumonia (n=1), air leak (n=3), influenza (n=1), pulmonary hemorrhage (n=1), or unknown etiology (n=5). All patients received chemotherapy; 9 received anthracycline drugs and 14 (67%) underwent HSCT. Thirteen patients (62%) were diagnosed with malignancies and 8 (38%) were diagnosed with non-malignant disease. Among the 21 patients, 6 (29%) survived ECMO in the PICU and 5 (24%) survived to hospital discharge. Among patients treated for septic shock, 3 of 5 patients (60%) who underwent ECMO and 5 of 10 patients (50%) who underwent VA ECMO survived. However, all the patients who underwent VA ECMO or VV ECMO for ARDS died. Conclusions: ECMO is a feasible treatment option for respiratory or heart failure in pediatric patients receiving chemotherapy or undergoing HSCT.
- Epidemiology
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Development of a deep learning model for predicting critical events in a pediatric intensive care unit
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In Kyung Lee, Bongjin Lee, June Dong Park
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Acute Crit Care. 2024;39(1):186-191. Published online February 20, 2024
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DOI: https://doi.org/10.4266/acc.2023.01424
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Correction in: Acute Crit Care 2024;39(2):330
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Abstract
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- Background
Identifying critically ill patients at risk of cardiac arrest is important because it offers the opportunity for early intervention and increased survival. The aim of this study was to develop a deep learning model to predict critical events, such as cardiopulmonary resuscitation or mortality. Methods: This retrospective observational study was conducted at a tertiary university hospital. All patients younger than 18 years who were admitted to the pediatric intensive care unit from January 2010 to May 2023 were included. The main outcome was prediction performance of the deep learning model at forecasting critical events. Long short-term memory was used as a deep learning algorithm. The five-fold cross validation method was employed for model learning and testing. Results: Among the vital sign measurements collected during the study period, 11,660 measurements were used to develop the model after preprocessing; 1,060 of these data points were measurements that corresponded to critical events. The prediction performance of the model was the area under the receiver operating characteristic curve (95% confidence interval) of 0.988 (0.9751.000), and the area under the precision-recall curve was 0.862 (0.700–1.000). Conclusions: The performance of the developed model at predicting critical events was excellent. However, follow-up research is needed for external validation.
- Epidemiology
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Eleven years of experience in operating a pediatric rapid response system at a children’s hospital in South Korea
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Yong Hyuk Jeon, Bongjin Lee, You Sun Kim, Won Jin Jang, June Dong Park
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Acute Crit Care. 2023;38(4):498-506. Published online November 29, 2023
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DOI: https://doi.org/10.4266/acc.2023.01354
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Abstract
PDFSupplementary Material
- Background
Various rapid response systems have been developed to detect clinical deterioration in patients. Few studies have evaluated single-parameter systems in children compared to scoring systems. Therefore, in this study we evaluated a single-parameter system called the acute response system (ARS).
Methods
This retrospective study was performed at a tertiary children’s hospital. Patients under 18 years old admitted from January 2012 to August 2023 were enrolled. ARS parameters such as systolic blood pressure, heart rate, respiratory rate, oxygen saturation, and whether the ARS was activated were collected. We divided patients into two groups according to activation status and then compared the occurrence of critical events (cardiopulmonary resuscitation or unexpected intensive care unit admission). We evaluated the ability of ARS to predict critical events and calculated compliance. We also analyzed the correlation between each parameter that activates ARS and critical events.
Results
The critical events prediction performance of ARS has a specificity of 98.5%, a sensitivity of 24.0%, a negative predictive value of 99.6%, and a positive predictive value of 8.1%. The compliance rate was 15.6%. Statistically significant increases in the risk of critical events were observed for all abnormal criteria except low heart rate. There was no significant difference in the incidence of critical events.
Conclusions
ARS, a single parameter system, had good specificity and negative predictive value for predicting critical events; however, sensitivity and positive predictive value were not good, and medical staff compliance was poor.
- Epidemiology
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Clinical implications of discrepancies in predicting pediatric mortality between Pediatric Index of Mortality 3 and Pediatric Logistic Organ Dysfunction-2
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Eui Jun Lee, Bongjin Lee, You Sun Kim, Yu Hyeon Choi, Young Ho Kwak, June Dong Park
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Acute Crit Care. 2022;37(3):454-461. Published online July 29, 2022
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DOI: https://doi.org/10.4266/acc.2021.01480
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2,946
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Abstract
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- Background
Pediatric Index of Mortality 3 (PIM 3) and Pediatric Logistic Organ Dysfunction-2 (PELOD-2) are validated tools for predicting mortality in children. Research suggests that these tools may have different predictive performance depending on patient group characteristics. Therefore, we designed this study to identify the factors that make the mortality rates predicted by the tools different.
Methods
This retrospective study included patients (<18 years) who were admitted to a pediatric intensive care unit from July 2017 to May 2019. After defining the predicted mortality of PIM 3 minus the predicted mortality rate of PELOD-2 as “difference in mortality prediction,” the clinical characteristics significantly related to this were analyzed using multivariable regression analysis. Predictive performance was analyzed through the Hosmer-Lemeshow test and area under the receiver operating characteristic curve (AUROC).
Results
In total, 945 patients (median [interquartile range] age, 3.0 [0.0–8.0] years; girls, 44.7%) were analyzed. The Hosmer-Lemeshow test revealed AUROCs of 0.889 (χ2=10.187, P=0.313) and 0.731 (χ2=6.220, P=0.183) of PIM 3 and PELOD-2, respectively. Multivariable linear regression analysis revealed that oxygen saturation, partial pressure of CO2, base excess, platelet counts, and blood urea nitrogen levels were significant factors. Patient condition-related factors such as cardiac bypass surgery, seizures, cardiomyopathy or myocarditis, necrotizing enterocolitis, cardiac arrest, leukemia or lymphoma after the first induction, bone marrow transplantation, and liver failure were significantly related (P<0.001).
Conclusions
Both tools predicted observed mortality well; however, caution is needed in interpretation as they may show different prediction results in relation to specific clinical characteristics.
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Citations
Citations to this article as recorded by  - COMPARISON OF PEDIATRIC INDEX OF MORTALITY (PIM)-3 AND PEDIATRIC SEQUENTIAL ORGAN FAILURE ASSESSMENT (pSOFA) SCORES TO PREDICT MORTALITY IN PEDIATRIC INTENSIVE CARE UNIT
ANKIT KUMAR PAWAR, GAURAV KUMAR PRAJAPATI, KANCHAN CHOUBEY, RASHMI RANDA
Asian Journal of Pharmaceutical and Clinical Research.2024; : 81. CrossRef
- Cardiology
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Percutaneous bicaval dual lumen cannula for extracorporeal life support
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Woojung Kim, Hye Won Kwon, Jooncheol Min, Sungkyu Cho, Jae Gun Kwak, June Dong Park, Woong-Han Kim
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Acute Crit Care. 2020;35(3):207-212. Published online September 23, 2019
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DOI: https://doi.org/10.4266/acc.2019.00584
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7,528
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Abstract
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- Veno-venous extracorporeal membrane oxygenation (ECMO) is a useful mechanical device for pediatric patients with severe respiratory failure. Conventional veno-venous ECMO using double cannulation, however, is not feasible due to size limitations in pediatric patients who have small femoral vessels. Recently, percutaneous bicaval dual-lumen cannula can be inserted using single cannulation via the right internal jugular vein. Herein, we report the case of a pediatric patient with severe respiratory failure who was weaned off the ECMO successfully after treatment with bicaval dual-lumen cannulation for 5 days despite the small body size and immunocompromised condition due to chemotherapy for hemophagocytic lymphohistiocytosis.
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Citations
Citations to this article as recorded by - Lipid Emulsion Treatment for Drug Toxicity Caused by Nonlocal Anesthetic Drugs in Pediatric Patients
Soo Hee Lee, Sunmin Kim, Ju-Tae Sohn
Pediatric Emergency Care.2023; 39(1): 53. CrossRef - Mechanisms underlying lipid emulsion resuscitation for drug toxicity: a narrative review
Soo Hee Lee, Ju-Tae Sohn
Korean Journal of Anesthesiology.2023; 76(3): 171. CrossRef
- Neurology/Pulmonary
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Extensive and Progressive Cerebral Infarction after Mycoplasma pneumoniae Infection
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Yu Hyeon Choi, Hyung Joo Jeong, Bongjin Lee, Hong Yul An, Eui Jun Lee, June Dong Park
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Korean J Crit Care Med. 2017;32(2):211-217. Published online December 29, 2016
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DOI: https://doi.org/10.4266/kjccm.2016.00283
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7,745
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Abstract
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- Acute cerebral infarctions are rare in children; however they can occur as a complication of a Mycoplasma pneumoniae (MP) infection due to direct invasion, vasculitis, or a hypercoagulable state. We report on the case of a 5-year-old boy who had an extensive stroke in multiple cerebrovascular territories 10 days after the diagnosis of MP infection. Based on the suspicion that the cerebral infarction was associated with a macrolide-resistant MP infection, the patient was treated with levofloxacin, methyl-prednisolone, intravenous immunoglobulin, and enoxaparin. Despite this medical management, cerebral vascular narrowing progressed and a decompressive craniectomy became necessary for the patient’s survival. According to laboratory tests, brain magnetic resonance imaging, and clinical manifestations, the cerebral infarction in this case appeared to be due to the combined effects of hypercoagulability and cytokine-induced vascular inflammation.
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Citations
Citations to this article as recorded by - Stroke associated with Mycoplasma hominis infection: a case report
Anthoula C. Tsolaki, Galaktion Konstantinidis, Stavroula Koukou, Fotini Michali, Despina Georgiadou, Thomas Tegos, Nikolaos D. Michalis
Journal of Medical Case Reports.2021;[Epub] CrossRef - Thrombosis associated with mycoplasma pneumoniae infection (Review)
Jingwei Liu, Yumei Li
Experimental and Therapeutic Medicine.2021;[Epub] CrossRef - Multiple anatomic sites of infarction in a pediatric patient with M. pneumoniae infection, a case report
Devon W. Hahn, Claire E. Atkinson, Matthew Le
BMC Pediatrics.2021;[Epub] CrossRef
- Neurosurgery
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Severe Rhabdomyolysis in Phacomatosis Pigmentovascularis Type IIb associated with Sturge-Weber Syndrome
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Bongjin Lee, Hyung Joo Jeong, Yu Hyeon Choi, Chong Won Choi, June Dong Park
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Korean J Crit Care Med. 2015;30(4):329-335. Published online November 30, 2015
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DOI: https://doi.org/10.4266/kjccm.2015.30.4.329
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7,720
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Abstract
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- Phacomatosis pigmentovascularis (PPV) is a rare syndrome characterized by concurrent nevus flammeus (capillary malformation) and pigmentary nevus. According to current research, the major pathophysiologic mechanism in PPV is venous dysplasia with resultant compensatory collateral channels and venous hypertension. Arterial involvement is rare. We herein report our experience on renovascular hypertension, intermittent claudication, and severe rhabdomyolysis due to diffuse stenosis of multiple arteries in a patient with PPV type IIb associated with SWS.
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Citations
Citations to this article as recorded by - Oral healthcare management of a child with phakomatosis pigmentovascularis associated with bilateral Sturge‐Weber syndrome
Mariana Leonel Martins, Aline Dos Santos Letieri, Michele Machado Lenzi, Michelle Agostini, Gloria Fernanda Castro
Special Care in Dentistry.2019; 39(3): 324. CrossRef
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