Impact of the COVID-19 Outbreak on Disease Spectrum of Pediatric Intensive Care Units

The characteristics of new-onset myasthenia gravis after COVID-19 outbreak: a cross-sectional study

BACKGROUND

Little research has been conducted on new-onset myasthenia gravis (MG) patients following the coronavirus disease 2019 (COVID-19) pandemic. COVID-19 surged in China on December 7th, 2022. This study aimed to explore the clinical characteristics of new-onset MG patients after COVID-19 and analyze factors affecting their disease improvement.

METHODS

All new-onset MG patients before (December 1st, 2021 to December 7th, 2022) and after COVID-19 outbreak (December 8th, 2022 to November 30th, 2023) were included in this study. Data was collected through the electronic medical record system and follow-up. Multivariate logistic regression was used to identify independent predictors of clinical improvement in patients with new-onset MG.

RESULTS

359 new-onset MG patients (165 before COVID-19 outbreak and 194 after COVID-19 outbreak) were enrolled in this study. After COVID-19 outbreak, there was an increase in new-onset MG patients, with more cases occurring within the first three months. The rates of pulmonary inflammation (40.28%), COVID-19 vaccination (88.14%), and treatment with tacrolimus (15.98%) and MG duration (15 weeks, IQR: 5.75, 32) were higher, while rates of thymectomy (13.92%), baseline MG-ADL (3, IQR: 3, 6), and QMGS (7, IQR: 5,8) were lower compared to new-onset MG patients before COVID-19 outbreak. Multivariate logistic regression analysis showed that age at onset (OR 0.964, p < 0.001), baseline MG-ADL (OR 1.611, p < 0.001), and ocular MG (OR 0.401, p = 0.041) were independent predictors of clinical improvement in new-onset MG after the COVID-19 outbreak.

CONCLUSION

In this single-center cross-sectional study, new-onset MG patients following the COVID-19 outbreak showed altered seasonal onset patterns, milder disease severity, and higher OMG onset age. Age at onset is an independently negative predictor of improvement in new-onset MG patients after the COVID-19 outbreak. Whereas baseline MG-ADL is an independently positive predictor.

Implementation of an Innovative Palliative Care Screening Tool in the Pediatric Intensive Care Unit: A Pilot Study

Background: Pediatric palliative care (PPC) can improve the quality of care provided to critically ill children with a high risk of morbidity and mortality. Early identification of patients admitted to the pediatric intensive care unit (PICU) who may benefit from PPC involvement is essential. Objectives: To create a brief screening tool, the Pediatric Intensive Care-Pediatric Palliative Care Screen, identifying PICU patients most likely to benefit from PPC involvement and to assess if weekly screening with this screening tool increases the number of PPC consults placed in the PICU. Methods: This is a prospective investigational single-center study in a 24-bed PICU at a U.S. tertiary care children's hospital. Weekly screening was completed by two clinicians for a six-month period between April and October 2022. Results: A total of 162 screens were completed on 124 individual patients; 47 screens were positive (29%), and 115 were negative (71%). Fourteen new PPC consults were placed from the PICU with one PPC consult for every 36.7 compared with one PPC for every 41.4 admissions the previous year. Of the positive screens, 68% had two or more comorbidities at the time of PICU admission versus 26% of negative screens (p < 0.001). Technology dependence (57% vs. 5%, p < 0.001) and presence of congenital defects (26% vs. 10%, p = 0.013) were significantly more common among positive screens. Conclusions: Weekly screening with a short, 7-question screening tool can identify PICU patients most likely to benefit from a PPC consult. Patients with chronic illnesses and baseline comorbidities are most likely to screen positive.

Etiological and clinical characteristics of severe pneumonia in pediatric intensive care unit (PICU)

OBJECTIVE

To analyze the etiological distribution characteristics of pediatric patients with severe pneumonia admitted to the Pediatric Intensive Care Unit (PICU), in order to provide a reference for the rational use of clinical antimicrobial drugs.

METHODS

A retrospective analysis of pediatric patients admitted to PICU with a diagnosis of severe pneumonia from January 2018 to December 2021 was performed and statistical analysis of pathogenic characteristics was performed.

RESULTS

A total of 649 pathogens were detected in 515 children, with a positive detection rate of 77.48%. Bacteria were detected at the highest rate (40.52%), followed by viruses (34.35%), atypical pathogens (19.72%) and fungal (4.31%). Gram-positive infections were dominated by Staphylococcus aureus (39.56%) and Streptococcus pneumoniae (32.97%), and Gram-negative infections were dominated by Acinetobacter Bahmani (16.28%) and Haemophilus influenzae (15.12%), followed by Klebsiella pneumoniae (13.95%) and Pseudomonas aeruginosa (12.21%). Viral infections were dominated by respiratory syncytial virus (25.65%) and EB virus (20.43%), fungal infections were dominated by Candida albicans (50.0%). The proportion of children infected with single pathogen (49.62%) was comparable to that of those with mixed infections (50.38%). There were statistically significant differences in the distribution of children with single pathogen infection by gender (P < 0.05). The age distribution of children with single bacterial, single viral and single fungal infections was statistically different (P < 0.05). There was no significant difference in the distribution of onset season in children with single pathogen infections (P > 0.05), but the number of children with single viral infections was significantly higher in winter and spring than that in summer and autumn, and the difference was statistically significant (P < 0.05). A mixture of 2 pathogens (77.61%) accounted for the majority of mixed infections, there were statistical differences in the distribution of bacterial + viral infection in terms of gender, age, and onset season (P < 0.05), children with viral + mycoplasma infection in terms of gender and age (P < 0.05), and children with viral + fungal infection in terms of gender (P < 0.05), and children with bacterial + mycoplasma infection in terms of age and onset season (P < 0.05). Among the children infected with 3 pathogens, there were statistically significant differences in the distribution of bacterial + viral + fungal and viral + mycoplasma + fungal infections in terms of gender (P < 0.05), and children with bacterial + viral + mycoplasma infection in terms of age (P < 0.05), while there was no significant difference in the distribution of onset season (P > 0.05). There were no significant differences in the distribution of children infected with 4 pathogens in terms of gender, age and onset season (P > 0.05).

CONCLUSION

The pathogens of pediatric patients with severe pneumonia in PICU commonly involves bacteria and viruses. As the age of children grows, the detection rate of bacteria shows a decreasing trend, and the pathogenic spectrum gradually changes from bacteria to mycoplasma and viruses, and the number of mixed infections gradually increase. Rational selection of antimicrobial drugs needs to consider pathogenic characteristics of different age, gender, and onset season in clinical practice.