Facemasks are recommended to reduce the spread of SARS-CoV-2, but concern about inadequate gas exchange is an often cited reason for non-compliance.
Among adult volunteers, do either cloth masks or ...surgical masks impair oxygenation or ventilation either at rest or during physical activity?
With IRB approval and informed consent, we measured heart rate (HR), transcutaneous carbon dioxide (CO2) tension and oxygen levels (SpO2) at the conclusion of six 10-minute phases: sitting quietly and walking briskly without a mask, sitting quietly and walking briskly while wearing a cloth mask, and sitting quietly and walking briskly while wearing a surgical mask. Brisk walking required at least a 10bpm increase in heart rate. Occurrences of hypoxemia (decrease in SpO2 of ≥3% from baseline to a value of ≤94%) and hypercarbia (increase in CO2 tension of ≥5 mmHg from baseline to a value of ≥46 mmHg) in individual subjects were collected. Wilcoxon signed-rank was used for pairwise comparisons among values for the whole cohort (e.g. walking without a mask versus walking with a cloth mask).
Among 50 adult volunteers (median age 33 years; 32% with a co-morbidity), there were no episodes of hypoxemia or hypercarbia (0%; 95% confidence interval 0-1.9%). In paired comparisons, there were no statistically significant differences in either CO2 or SpO2 between baseline measurements without a mask and those while wearing either kind of mask mask, both at rest and after walking briskly for ten minutes.
The risk of pathologic gas exchange impairment with cloth masks and surgical masks is near-zero in the general adult population.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
In their pragmatic trial in 15 paediatric intensive care units (PICUs) in the UK, invasively ventilated children older than 38 weeks corrected gestational age and younger than 16 years without ...cyanotic heart disease, pulmonary hypertension, or acute brain injury who were admitted to PICUs as an emergency were randomly allocated to a conservative (peripheral oxygen saturation SpO2 88–92%) or liberal (SpO2 >94%) target for bedside clinician-driven ventilator titration. A meta-analysis of five neonatal trials, including nearly 5000 infants, found that aiming for SpO2 of 85–89% versus 91–95% increased mortality while reducing severe retinopathy, although only one individual trial showed increased mortality overall.3,4 Similarly, several trials of heterogeneous cohorts of critically ill adults have been done, and except for one single centre study comparing universal supplemental oxygen to drive SpO2 to 97% or greater versus as-needed oxygen targeting SpO2 94–98%, no large trial has shown improvement in mortality or other major outcomes with lower oxygen targets; one study of adults with acute respiratory distress syndrome even suggests harm.5–11 Overall, meta-analysis of 17 studies including more than 10 000 critically ill adults shows no effect of oxygenation targets on mortality, serious adverse events, or quality of life. 12 While critically ill children should not be considered either small adults or overgrown neonates, the lack of consistent benefit across trials limits enthusiasm for declaring SpO2 of 88–92% the new standard of PICU care based on one trial. ...as in other trials, the conservative group was often above-range, with only a quarter of SpO2 values in goal range, and many children having deviations of 3 h or more out-of-range without ventilator adjustment. 6–9 Thus, it is impossible to conclude if achieving an SpO2 of 88–92% improves outcomes. ...the risk that setting an aspirational goal of SpO2 88–92%—but really just wanting to avoid hyperoxia—could result in lax implementation of other patient goals (ie, targeted temperature management, chest compression rate, etc) must be considered.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Children have been less affected by the COVID-19 pandemic, but its repercussions on pediatric illnesses may have been significant. This study examines the indirect impact of the pandemic on a ...population of critically ill children in the United States.
Were there significantly fewer critically ill children admitted to PICUs during the second quarter of 2020, and were there significant changes in the types of diseases admitted?
This retrospective observational cohort study used the Virtual Pediatric Systems database. Participants were 160,295 children admitted to the PICU at 77 sites in the United States during quarters 1 (Q1) and 2 (Q2) of 2017 to 2019 (pre-COVID-19) and 2020 (COVID-19).
The average number of admissions was similar between pre-COVID-19 Q1 and COVID-19 Q1 but decreased by 32% from pre-COVID-19 Q2 to COVID-19 Q2 (20,157 to 13,627 admissions per quarter). The largest decreases were in respiratory conditions, including asthma (1,327 subjects in pre-COVID-19 Q2 (6.6% of patients) vs 241 subjects in COVID-19 Q2 (1.8%; P < .001) and bronchiolitis (1,299 6.5% vs 121 0.9%; P < .001). The percentage of trauma admissions increased, although the raw number of trauma admissions decreased. Admissions for diabetes mellitus and poisoning/ingestion also increased. In the multivariable model, illness severity-adjusted odds of ICU mortality for PICU patients during COVID-19 Q2 increased compared with pre-COVID-19 Q2 (OR, 1.165; 95% CI, 1.00-1.357; P = .049).
Pediatric critical illness admissions decreased substantially during the second quarter of 2020, with significant changes in the types of diseases seen in PICUs in the United States. There was an increase in mortality in children admitted to the PICU during this period.
To evaluate the contribution of PICU care to increasing hospital charges for patients with bronchiolitis over a 10-year study period.
In this retrospective multicenter study, changes in annual ...hospital charges (adjusted for inflation) were analyzed using linear regression for subjects admitted to the PICU with invasive mechanical ventilation (PICU + IMV) and without IMV (PICU - IMV), and for children not requiring PICU care.
Free-standing children's hospitals contributing to the Pediatric Health Information System (PHIS) database.
Children less than 2 years with bronchiolitis discharged from a PHIS hospital between July 2009 and June 2019. Subjects were categorized as high risk if they were born prematurely or had a chronic complex condition.
None.
PICU patients were 26.5% of the 283,006 included subjects but accrued 66% of the total $14.83 billion in charges. Annual charges increased from $1.01 billion in 2009-2010 to $2.07 billion in 2018-2019, and PICU patients accounted for 83% of this increase. PICU + IMV patients were 22% of all PICU patients and accrued 64% of all PICU charges, but PICU - IMV patients without a high-risk condition had the highest relative increase in annual charges, increasing from $76.7 million in 2009-2010 to $377.9 million in 2018-2019 (374% increase, ptrend < 0.001).
In a multicenter cohort study of children hospitalized with bronchiolitis, PICU patients, especially low-risk children without the need for IMV, were the highest driver of increased hospital charges over a 10-year study period.
The field of pediatric critical care has been hampered in the era of precision medicine by our inability to accurately define and subclassify disease phenotypes. This has been caused by heterogeneity ...across age groups that further challenges the ability to perform randomized controlled trials in pediatrics. One approach to overcome these inherent challenges include the use of machine learning algorithms that can assist in generating more meaningful interpretations from clinical data. This review summarizes machine learning and artificial intelligence techniques that are currently in use for clinical data modeling with relevance to pediatric critical care. Focus has been placed on the differences between techniques and the role of each in the clinical arena. The various forms of clinical decision support that utilize machine learning are also described. We review the applications and limitations of machine learning techniques to empower clinicians to make informed decisions at the bedside. IMPACT: Critical care units generate large amounts of under-utilized data that can be processed through artificial intelligence. This review summarizes the machine learning and artificial intelligence techniques currently being used to process clinical data. The review highlights the applications and limitations of these techniques within a clinical context to aid providers in making more informed decisions at the bedside.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Shein and Rotta discuss the long-term neurocognitive morbidity after a single episode of respiratory failure in children. The fact that most children treated in the pediatric intensive care unit ...(PICU) survive to hospital discharge is causing a shift from mortality to long-term morbidity as the outcome of interest in pediatric critical illness. Collectively termed pediatric post-intensive care syndrome (P/CS-p), the physical, emotional, social, and cognitive sequelae of critical illness can adversely affect surviving children and their families well beyond hospitalization. Although studies that include children with direct neurologic injury, whether acute or chronic, may be less suitable for identifying modifiable risk factors for PICS-p, generally healthy children with acute respiratory failure treated with mechanical ventilation-with improved gas exchange at the cost of exposure to sedative and analgesic agents and other possibly injurious PICU therapies-comprise an optimal cohort to assess the association between critical care and long-term outcomes.
Characteristics of children with impaired development who have acute appendicitis are not well described in the literature.
We reviewed the National Surgical Quality Improvement Program-Pediatric and ...the multicenter Pediatric Health Information System for patients with acute appendicitis. Comparisons for demographics, clinical outcomes, and hospital charges between children with impaired development versus neurotypical children were made using independent t test or Wilcoxon rank sum tests. The multivariable logistic regression model estimated the odds of complicated acute appendicitis in impaired development patients. Based on correlation analyses, hierarchical linear modeling was used to examine the extent to which impaired development influenced resource use.
Patients with impaired development were younger, had higher comorbidities, and were more commonly male sex. In the National Surgical Quality Improvement Program-Pediatric database, impaired development was associated with higher rates of complicated acute appendicitis (33.6% vs 27.5, P < .001), particularly in older children, and higher usage of computed tomography at National Surgical Quality Improvement Program-Pediatric hospitals (23.1% vs 15.1%, P < .001). In the Pediatric Health Information System database, the adjusted odds of complicated acute appendicitis were significantly higher in patients with impaired development (1.20 1.09–1.31), low childhood opportunity level (1.39 95% confidence interval: 1.31–1.47), and Black race (1.25 1.17–1.33). Hierarchical adjusted linear modeling showed that impaired development was associated with significantly higher hospital charges (9% increase).
Management of acute appendicitis in children with impaired development remains a challenge to clinicians, as evidenced by the higher rate of perforated appendicitis in older children, diagnostic computed tomography use at National Surgical Quality Improvement Program-Pediatric hospitals, postoperative computed tomography use, and increased costs.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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Pediatric Critical Care and COVID-19 González-Dambrauskas, Sebastián; Vásquez-Hoyos, Pablo; Camporesi, Anna ...
Pediatrics (Evanston),
09/2020, Volume:
146, Issue:
3
Journal Article
PDF
