Acute and Critical Care

Original Article

Pediatrics
Pediatric septic shock estimation using deep learning and electronic medical records: Ji Weon Lee, Bongjin Lee, June Dong Park; Acute Crit Care. 2024;39(3):400-407. Published online August 1, 2024; DOI: https://doi.org/10.4266/acc.2024.00031

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Abstract PDF: 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.

Corrigendum

Pediatrics
Corrigendum to: Development of a deep learning model for predicting critical events in a pediatric intensive care unit: In Kyung Lee, Bongjin Lee, June Dong Park; Acute Crit Care. 2024;39(2):330-330. Published online April 1, 2024; DOI: https://doi.org/10.4266/acc.2023.01424.e1; Corrects: Acute Crit Care 2024;39(1):186

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Original Articles

Pediatrics
Development of a deep learning model for predicting critical events in a pediatric intensive care unit: In Kyung Lee, Bongjin Lee, June Dong Park; Acute Crit Care. 2024;39(1):186-191. Published online February 20, 2024; DOI: https://doi.org/10.4266/acc.2023.01424; Correction in: Acute Crit Care 2024;39(2):330

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Abstract PDF: 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.

Pediatrics
Eleven years of experience in operating a pediatric rapid response system at a children’s hospital in South Korea: Yong Hyuk Jeon, Bongjin Lee, You Sun Kim, Won Jin Jang, June Dong Park; Acute Crit Care. 2023;38(4):498-506. Published online November 29, 2023; DOI: https://doi.org/10.4266/acc.2023.01354

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Abstract PDF Supplementary 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.

Pediatrics
Clinical implications of discrepancies in predicting pediatric mortality between Pediatric Index of Mortality 3 and Pediatric Logistic Organ Dysfunction-2: Eui Jun Lee, Bongjin Lee, You Sun Kim, Yu Hyeon Choi, Young Ho Kwak, June Dong Park; Acute Crit Care. 2022;37(3):454-461. Published online July 29, 2022; DOI: https://doi.org/10.4266/acc.2021.01480

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Abstract PDF

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.

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

Case Reports

Neurology/Pulmonary
Extensive and Progressive Cerebral Infarction after Mycoplasma pneumoniae Infection: Yu Hyeon Choi, Hyung Joo Jeong, Bongjin Lee, Hong Yul An, Eui Jun Lee, June Dong Park; Korean J Crit Care Med. 2017;32(2):211-217. Published online December 29, 2016; DOI: https://doi.org/10.4266/kjccm.2016.00283

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3 Web of Science
3 Crossref

Abstract PDF

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.

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
Severe Rhabdomyolysis in Phacomatosis Pigmentovascularis Type IIb associated with Sturge-Weber Syndrome: Bongjin Lee, Hyung Joo Jeong, Yu Hyeon Choi, Chong Won Choi, June Dong Park; Korean J Crit Care Med. 2015;30(4):329-335. Published online November 30, 2015; DOI: https://doi.org/10.4266/kjccm.2015.30.4.329

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Abstract PDF

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.

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

Disseminated Neonatal Herpes Simplex Virus Infection: Bongjin Lee, Jinsol Hwang, Yu Hyeon Choi, Young Joo Han, Young Hun Choi, June Dong Park; Korean J Crit Care Med. 2013;28(4):331-335.; DOI: https://doi.org/10.4266/kjccm.2013.28.4.331

3,288 View
53 Download
1 Crossref

Abstract PDF

Disseminated neonatal herpes simplex virus (HSV) infection is one of the most severe neonatal infections, and can have devastating consequences without early proper treatment. However, the administration of acyclovir can often be delayed because the symptoms and signs of HSV infection are non-specific and because HSV polymerase chain reaction (PCR) results may be negative early in the course of HSV infection. We report a case of disseminated neonatal HSV infection that was diagnosed by type 1 HSV PCR on day 8 of admission. Despite delayed administration of acyclovir, the patient was cured and subsequently discharged after 30 days of admission. Fortunately, this patient was treated successfully, but delayed administration of acyclovir has the potential to lead to significant problems. Considering the seriousness of neonatal HSV infection, empirical acyclovir therapy should be considered if HSV infection is suspected.

Citations

Citations to this article as recorded by

A Case of Herpes Simplex Virus Type 2 Encephalitis of a Newborn Delivered by a Mother without Prenatal Screening
Eun Seob Lee, Joon Young Kim, Kon Hee Lee, Jung Won Lee, Yong Ju Lee, Yeon Joung Oh, Ji Seok Bang, Tae-Jung Sung
Korean Journal of Perinatology.2014; 25(3): 195. CrossRef

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