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1.
Pediatr Crit Care Med ; 24(6): e292-e296, 2023 06 01.
Article in English | MEDLINE | ID: mdl-37036203

ABSTRACT

OBJECTIVES: To examine whether escalating antimicrobial treatment in pediatric oncology and hematopoietic cell transplantation (HSCT) patients admitted to the PICU is supported by culture data or affects patient outcomes. DESIGN: Retrospective cross-sectional study. SETTING: Quaternary care PICU. PATIENTS: Patients younger than 18 years old who were admitted to the PICU at Boston Children's Hospital from 2012 to 2017 with a diagnosis of cancer or who had received HSCT and who had suspected sepsis at the time of PICU admission. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 791 PICU admissions for 544 patients that met inclusion criteria, 71 (9%) had escalation of antimicrobial therapy. Median Pediatric Logistic Organ Dysfunction (PELOD) score was higher in the escalation group (4 vs 3; p = 0.01). There were 14 admissions (20%) with a positive culture in the escalation group and 110 (15%) in the no escalation group ( p = 0.31). In the escalation group, there were only 2 (3%) cultures with organisms resistant to the initial antimicrobial regimen, compared with 28 (4%) cultures with resistant organisms in the no escalation group ( p = 1). Mortality in the escalation group was higher (17%) compared with the nonescalation group (5%; p < 0.001). The escalation group had more acute kidney injury (AKI) (25%) during treatment compared with the no escalation group (15%; p = 0.04), although this difference was not statistically significant when controlling for age, neutropenia, and PELOD-2 score (odds ratio, 1.75; 95% CI, 0.95-3.08; p = 0.06). CONCLUSIONS: Few patients who had escalation of antimicrobials proved on culture data to have an organism resistant to the initial antimicrobials, and more patients developed AKI during escalated treatment. While the escalation group likely represents a sicker population, whether some of these patients would be safer without escalation of antimicrobial therapy warrants further study.


Subject(s)
Acute Kidney Injury , Anti-Infective Agents , Hematopoietic Stem Cell Transplantation , Neoplasms , Child , Humans , Infant , Adolescent , Retrospective Studies , Cross-Sectional Studies , Neoplasms/drug therapy , Anti-Infective Agents/therapeutic use , Hematopoietic Stem Cell Transplantation/adverse effects , Intensive Care Units, Pediatric
2.
Crit Care Explor ; 3(5): e0426, 2021 May.
Article in English | MEDLINE | ID: mdl-34036277

ABSTRACT

OBJECTIVES: To determine whether machine learning algorithms can better predict PICU mortality than the Pediatric Logistic Organ Dysfunction-2 score. DESIGN: Retrospective study. SETTING: Quaternary care medical-surgical PICU. PATIENTS: All patients admitted to the PICU from 2013 to 2019. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We investigated the performance of various machine learning algorithms using the same variables used to calculate the Pediatric Logistic Organ Dysfunction-2 score to predict PICU mortality. We used 10,194 patient records from 2013 to 2017 for training and 4,043 patient records from 2018 to 2019 as a holdout validation cohort. Mortality rate was 3.0% in the training cohort and 3.4% in the validation cohort. The best performing algorithm was a random forest model (area under the receiver operating characteristic curve, 0.867 [95% CI, 0.863-0.895]; area under the precision-recall curve, 0.327 [95% CI, 0.246-0.414]; F1, 0.396 [95% CI, 0.321-0.468]) and significantly outperformed the Pediatric Logistic Organ Dysfunction-2 score (area under the receiver operating characteristic curve, 0.761 [95% CI, 0.713-0.810]; area under the precision-recall curve (0.239 [95% CI, 0.165-0.316]; F1, 0.284 [95% CI, 0.209-0.360]), although this difference was reduced after retraining the Pediatric Logistic Organ Dysfunction-2 logistic regression model at the study institution. The random forest model also showed better calibration than the Pediatric Logistic Organ Dysfunction-2 score, and calibration of the random forest model remained superior to the retrained Pediatric Logistic Organ Dysfunction-2 model. CONCLUSIONS: A machine learning model achieved better performance than a logistic regression-based score for predicting ICU mortality. Better estimation of mortality risk can improve our ability to adjust for severity of illness in future studies, although external validation is required before this method can be widely deployed.

3.
Diabetes ; 69(7): 1503-1517, 2020 07.
Article in English | MEDLINE | ID: mdl-32321760

ABSTRACT

Diabetic retinopathy is a potentially blinding eye disease that threatens the vision of one-ninth of patients with diabetes. Progression of the disease has long been attributed to an initial dropout of pericytes that enwrap the retinal microvasculature. Revealed through retinal vascular digests, a subsequent increase in basement membrane bridges was also observed. Using cell-specific markers, we demonstrate that pericytes rather than endothelial cells colocalize with these bridges. We show that the density of bridges transiently increases with elevation of Ang-2, PDGF-BB, and blood glucose; is rapidly reversed on a timescale of days; and is often associated with a pericyte cell body located off vessel. Cell-specific knockout of KLF4 in pericytes fully replicates this phenotype. In vivo imaging of limbal vessels demonstrates pericyte migration off vessel, with rapid pericyte filopodial-like process formation between adjacent vessels. Accounting for off-vessel and on-vessel pericytes, we observed no pericyte loss relative to nondiabetic control retina. These findings reveal the possibility that pericyte perturbations in location and process formation may play a role in the development of pathological vascular remodeling in diabetic retinopathy.


Subject(s)
Diabetic Retinopathy/etiology , Homeostasis , Hyperglycemia/pathology , Pericytes/physiology , Animals , Antigens/analysis , Becaplermin/physiology , Collagen Type IV/analysis , Diabetes Mellitus, Experimental/drug therapy , Insulin/therapeutic use , Kruppel-Like Factor 4 , Kruppel-Like Transcription Factors/physiology , Mice , Mice, Inbred C57BL , Myosin Heavy Chains/analysis , Pericytes/drug effects , Platelet Endothelial Cell Adhesion Molecule-1/analysis , Proteoglycans/analysis , Ribonuclease, Pancreatic/physiology , Streptozocin
4.
Biol Blood Marrow Transplant ; 24(2): 324-329, 2018 02.
Article in English | MEDLINE | ID: mdl-29074373

ABSTRACT

To ensure optimal clinical outcomes for patients while retaining adequate protection for donors, the National Marrow Donor Program developed guidelines specifying that up to 20 mL/kg of bone marrow can be harvested from donors. These guidelines, originally developed for unrelated adult donors, are followed in children as well. We studied the impact of granulocyte colony-stimulating factor (G-CSF) priming on the cellular composition of harvested bone marrow, sought to develop an algorithm to optimize bone marrow harvest volume from pediatric matched sibling donors, and studied the impact of CD34+ cell dose on clinical outcomes. We analyzed data from 92 bone marrow harvests and clinical outcomes for 69 sibling recipient-donor duos, The mean age of recipients was 9.85 ± 5.90 years, and that of donors was 11.85 ± 6.36 years. G-CSF priming was not associated with higher yield of CD34+ cells/µL. The median CD34+ cell count obtained from donors was 700 cells/µL (range, 400-1700 cells/µL) in donors age <6 years, 360 cells/µL (range, 100-1100 cells/µL) in donors age 6 to 12 years, and 300 cells/µL (range, 80-800 cells/µL) in donors age >12 years (P < .001). The number of CD34+ cells infused had no impact on traditional clinical outcomes; however, it was significantly related to graft-versus-host disease/relapse/rejection-free survival. Our investigation revealed that ultimately, a CD34+ cell count of approximately 3 to 5 × 106/kg was a threshold beyond which increasing CD34+ cell dose did not impact outcome. In this study, we addressed the broad question of whether harvesting up to 20 mL/kg of bone marrow from a child donor is truly necessary for optimal outcomes in every pediatric case.


Subject(s)
Antigens, CD34/analysis , Bone Marrow Transplantation/methods , Granulocyte Colony-Stimulating Factor/pharmacology , Practice Guidelines as Topic/standards , Adolescent , Child , Child, Preschool , Humans , Siblings , Tissue Donors
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