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7/26/2019 1 Recent Thought-Provoking Articles in Pediatric Medicine Matthew Garber MD, FAAP, FHM Professor of Pediatrics University of Florida COM Jacksonville Division Chief UF Hospitalists Wolfson CH and UF Health Medical Director, Value in Inpatient Pediatrics Network I have nothing to disclose. I do not plan to discuss any off-label medication use. 1 2

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Page 1: Recent Thought-Provoking Articles in Pediatric Medicine...7/26/2019 1 Recent Thought-Provoking Articles in Pediatric Medicine Matthew Garber MD, FAAP, FHM Professor of Pediatrics University

7/26/2019

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Recent Thought-Provoking Articles in Pediatric

Medicine

Matthew Garber MD, FAAP, FHM

Professor of Pediatrics University of Florida COM Jacksonville

Division Chief UF Hospitalists Wolfson CH and UF Health

Medical Director, Value in Inpatient Pediatrics Network

I have nothing to disclose.

I do not plan to discuss any off-label medication use.

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Page 2: Recent Thought-Provoking Articles in Pediatric Medicine...7/26/2019 1 Recent Thought-Provoking Articles in Pediatric Medicine Matthew Garber MD, FAAP, FHM Professor of Pediatrics University

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Learning Objectives

1)Discuss findings from recent

scientific articles in pediatric

medicine

2)Critically appraise articles using

statistics

3)List several potential practice

changes based on recent literature

Fairly Common Things…

Antibiotic duration for

GBS

Hyperbilirubinemia

testing

Probiotics

Solids and sleep

Gastric residuals

Acid Suppressive

Therapy

New directions

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Coon et al, Pediatrics November 2018

Multicenter retrospective cohort study

Infants 7 days to 4 months in PHIS with GBS

bacteremia 2000 to 2015

Short = discharged <=8days without a PICC

Outcome -readmission GBS bacteremia,

meningitis, osteo by 1 yoa

Propensity-adjusted, inverse probability–weighted

regression models.

Shortened IV Antibiotic Course for

Uncomplicated, Late-Onset Group B

Streptococcal Bacteremia

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Statistical interlude (X 3 maybe 4)

Hospital-level prescribing variation in lieu of RCT – a form of

instrumental variable

Inverse probability–weighting/propensity scores

NNT = 100/ARR, ARR = 2.5% then NNT = 40

NNT – using the upper end of the 95% CI −0.2% (−3.0% to

2.5%) – we can calculate an NNT assuming longer course

prevents recurrence

But what’s the risk if we take the lower bound of the CI?

Is it 100/-3.0% = -33

The authors used the point prevalence – 0.2% and ignored

the minus sign, calculating 100/0.2 = 500

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Probiotics – the tale of 3 trials

Multicenter Trial of a Combination Probiotic for

Children with Gastroenteritis

Freedman et al, N Engl J Med, Nov 2018

Lactobacillus rhamnosus GG versus Placebo for

Acute Gastroenteritis in Children

Schnadower et al, N Engl J Med, Nov 2018

Post-Antibiotic Gut Mucosal Microbiome

Reconstitution Is Impaired by Probiotics and

Improved by Autologous FMT

Suez et al, Cell, Sept 2018

oink

Multicenter Trial of a Combination Probiotic

for Children with Gastroenteritis

RCT double blinded, 886 pts 3 to 48 months, AGE <

72 hours, 6 peds EDs Canada

5-day probiotic containing Lactobacillus rhamnosus

R0011 and L. helveticus R0052, at 4.0×109 CFU BID

or placebo

Primary outcome mod-severe GE (score), Secondary

duration V/D, % pts with unscheduled visits, adverse

events

Power calc: 670 provide 90% power to detect 10%

difference (assuming 25% outcome in placebo group,

alpha .05 two tailed)

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And no difference in tertiary outcomes – extra visits, day care/work missed

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Lactobacillus rhamnosus GG versus Placebo

for Acute Gastroenteritis in Children

RCT double blinded, 971 pts 3 to 48

months, AGE < 72 hours, 10 peds EDs US

5-day Lactobacillus rhamnosus GG at

1×1010 CFU BID or placebo

Outcome and power calculations basically

the same (also looked for household

transmission)

No difference in other outcomes except repeat health care

visits which became insignificant when adjusted for multiple

comparisons

Note the incidence of mod-severe diarrhea less than

predicted in power calc

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Post-Antibiotic Gut Mucosal Microbiome

Reconstitution Is Impaired by Probiotics and

Improved by Autologous FMT

Probiotics perturb rather than aid inmicrobiota recovery back to baseline after antibiotic treatment in humans.

Statistical Interlude

Power or Sample Size calculation

What goes into it?

Alpha, baseline probability of the

outcome, effect size, power, scatter of

data, estimate for drop out/cross overs

etc.

Especially important for negative studies

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Effect of Gastric Residual Evaluation on

Enteral Intake in Extremely Preterm Infants

A Randomized Clinical Trial

Parker et al, JAMA Pediatrics, June 2019

RCT, not blinded (feeding decisions per protocol),

143 infants, <= 32 weeks GA, <=1250 grams, feeding

by 72 hours, only human milk

Primary outcome weekly enteral nutrition in mL/kg

for 6 weeks after birth

Secondary outcomes days to full feeds, PN/CVL

days, growth, LOS, feeding intolerance, presumed

sepsis, >= stage 2 NEC, VAP

Feed me

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No residuals

checked (95%CI)

Residuals

checked (95% CI)

P value

Mean weekly food

increase

20.7 mL/kg/d 17.9 mL/kg/d 0.02

Week 5 137.2 (128.6 to

145.8)

123.9 (115.2 to

132.6)

0.03

Week 6 141.6 (133.2 to

150.0)

128.4 (119.9 to

136.9)

0.03

Mean estimated

log weights

7.01 (6.99-7.02) 6.98 (6.97-7.00) 0.03

Abd distension

episodes

0.59 (0.34-1.01) 1.79 (1.27-2.53) 0.001

Discharged 8 days

earlier

4.21 (4.14-4.28)

Days to discharge

4.28 (4.19-4.36) 0.01

NEC 0.058 (0.018-

0.190)

0.026 (0.006-

0.109)

0.60

Death 0.004 (0.0003-

0.046)

0.012 (0.001-

0.131)

0.06

Late-Onset Sepsis 0.97 (0.67-1.40) 1.38 (0.97-1.94) 0.08

But not powered for safety,

e.g NEC!!!

Statistical Interlude

Generalized Linear Models allow the dependent

variable (response variable) to have distributions

other than normal (log-normal, binomial, Poisson)

The response doesn’t vary linearly but some

function (link function) of the response does vary

linearly

For example, if a constant change in a predictor

(independent) variable causes a constant change in

the RATE (an increase of 10 degrees F causes TWICE

as many people to go to the beach) of the response

variable, then the LOG of the response variable is

predicted to vary linearly.

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A Novel Icterometer for Hyperbilirubinemia

Screening in Low-Resource Settings

Lee et al, Pediatrics, May 2019

Limited access to screening/tx of hyperbili in low

resource settings

An estimated 6 million infants who need phototherapy do

not receive it

Icterometer using advanced digital color processing

technology and an enhanced visual design to simplify

color matching

Test the validity of Bili-ruler to detect clinically

significant thresholds of hyperbilirubinemia and

Interrater reliability of icterometer scoring

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Study design

Infants from Boston and Bangladesh <28 days old

No knowledge of TcB/TSB

Compare strips to blanched skin

Natural light, near window, without fluorescent lighting as possible

Forehead, nose, abdomen, palms, and soles X 2, avg for each area

Random subset had 2 examiners measure at nose for IRR

TcB obtained within 2 hours (serum bili included if obtained w/in 2 hours)

Spearman correlation coefficients

Clinical thresholds of hyperbilirubinemia (>=11, 13, 15, 17, 20 mg/dL)

It Works!!!

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Statistical Interlude

We learn sensitivity and specificity in

medical school - sensitivity TP/ (TP +FN),

Sensitivity TN / (TN + FP)

Some of us learn PPV and NPV in

residency/practice - clinically useful

PPV = TP/(TP +FP), NPV = (TN/TN +FN) – if

my patient tested +(-) what is the chance

she has (doesn’t have) the dz?

Requires knowing the prevalence of disease

Likelihood ratios

Likelihood ratios do not require knowing

the prevalence of a disease and can give

you a sense of the “value” of a test

LR+ = Prob test is + in dz/Prob is + in nondz

Sensitivity/(1-specificity)

LR- = Prob test is – in diseased person/Prob

test is – in nondiseased person

(1-sensitivity)/specificity

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+LR-LR

Estimate the pretest probability of disease using H&P, literature

Previous testing, whatever is at your disposal

So that’s pretty cool, but we live in the US -

Screening for Neonatal Hyperbilirubinemia—

First Do No Harm? Grosse SD, JAMA Peds 5/19 Phototx decreases bili, but does it prevent acute/chronic bilirubin

encephalopathy? Do the benefits exceed the harms?

Childhood Seizures After Phototherapy, Newman et al, Pediatrics 10/18

The adjusted 10-year excess risks per 1000 were 2.4 (95% CI: 0.6 to

4.1) overall, 3.7 (95% CI: 1.2 to 6.1) in boys, and 0.8 (95% CI: −1.7 to

3.2) in girls.

Similar findings in Denmark Maimburg RD et al, Epilepsy Res, 2016

The USPSTF and the AAFP concluded there was insufficient evidence to

warrant universal screening of term or near-term infants for NHB

NHB not recommended for NBN screening based on lack of direct evidence

that it reduces CBE

Risk for cerebral palsy in infants with total serum bilirubin levels at or

above the exchange transfusion threshold: a population-based study. Wu et

al, JAMA Peds, 2015, limit tx to much higher levels/with RF

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And hot off the presses….

A Simpler Prediction Rule for Rebound

Hyperbilirubinemia – Chang, Newman, Pediatrics,

July 2019

Rebound hyperbilirubinemia -TSB reaching or PTX

threshold within 72 hours of discontinuing PTX

Infants >= 38 weeks GA stopping at 2mg/dl below

threshold at initiation has a 2.5% risk of rebound,

but 10.2% for infants <= 38 weeks GA

Infants < 38 weeks GA stopping at 5.5mg/dl below

AAP phototx threshold at initiation has a 2.6% risk of

rebound

“Starting solid foods won’t make your baby

any more likely to sleep through the night” UK National Health Service

Association of Early Introduction of Solids With

Infant Sleep A Secondary Analysis of a Randomized

Clinical Trial, Perkin et al, JAMA Pediatrics, July 18

The Enquiring About Tolerance (EAT) study, RCT

Introduction of 6 allergenic (and nonallergenic)

foods from age 3 months compared to exclusive

breastfeeding until 6 months

Detailed validated sleep questionnaire on 15

occasions between ages 3 months and 3 years

An Intention to Treat (ITT) analysis supplemented by

a per-protocol analysis

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All findings significant with ITT and enhanced with per-protocol analysis

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Statistical Interlude

Intention to treat vs

Per-protocol

If non-compliance has any

association with the outcome than

per-protocol is biased

If you get disparate conclusions from

these analyses the results are

ambiguous

Early Acid Suppression Therapy Exposure

and Fracture in Young Children

Malchodi et al, Pediatrics, July 2019

We know that AST is frequently prescribed despite

lack of evidence of efficacy in infants and young

children

We already know that AST increases the risk of CAP,

AGE, and Cdiff

PPIs increase fractures in adults

The relationship between AST use in the 1st year of

life and childhood fracture (up to 14), accounting

for duration of exposure and age at initiation

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Methods

A retrospective cohort of children

born in the Military Healthcare

System 1-5yoa

Primary analysis children started on

AST before 1 yoa

Secondary analysis children started

on AST between 1-2yoa

Compared to children 1-5 without

any AST

11.4%

3% on PPIs

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Hazard Ratios

The hazard is the slope of the survival curve

Proportional hazards assumption –

The ratio of the 2 slopes all along the curve is the same

Then the HR is similar to a RR

Patients in the dotted line are dying at twice the rate

at any given time during the study

The hazard of being caught

skipping this stats lesson compared

to the enjoyment I’ll have

elsewhere…

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In summary

Consider completing ABX for uncomplicated GBS

bacteremia orally

Don’t prescribe probiotics for AGE

Don’t check gastric residuals in the NICU

Don’t screen for neonatal hyperbilirubinemia; consider a

higher threshold for PTX and stop PTX when bili is 2mg/dl

under the AAP initiation threshold (or 5.5mg/dl if GA < 38

weeks)

Tell moms you are sorry that you said solids won’t help

their young infants sleep through the night and that they

were right all along

Don’t prescribe acid suppressive therapy, especially PPI’s,

to infants, even if your brother-in-law is a pediatric

orthopedist who really needs the business

Questions???

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