OBJECTIVES:

The Finnegan Neonatal Abstinence Score (FNAS) monitors infants with neonatal abstinence syndrome (NAS), but it has been criticized for being time consuming and subjective. Many institutions have transitioned to a more straightforward screening tool, Eat, Sleep, Console (ESC), an assessment based on 3 simple observations with a focus on maximizing nonpharmacologic therapies. We aimed to compare the sensitivity and specificity of the ESC with that of the FNAS to determine if infants who needed pharmacologic therapy could potentially be missed when assessed by using ESC.

METHODS:

A retrospective cohort study of infants identified by International Classification of Diseases, Ninth Revision and International Classification of Diseases, 10th Revision billing codes for NAS. FNAS scores were recorded every 4 hours for the entire hospitalization. ESC proxy scores were created by using components of the FNAS that referenced eating, sleeping, and consoling. Detailed demographic and clinical data were manually extracted regarding opioid exposures and pharmacologic treatment of NAS.

RESULTS:

From 2013 to 2016, 423 infants ≥37 weeks’ gestation had a total of 33 115 FNAS scores over 921 days of observation. In total, 287 (68%) were exposed to buprenorphine, 100 (23.7%) were exposed to methadone, and 165 (39%) were pharmacologically treated. The FNAS was 94.8% sensitive and 63.5% specific for pharmacologic treatment, and the ESC proxy variables were 99.4% sensitive and 40.2% specific (P < .01).

CONCLUSIONS:

ESC proxy variables have slightly higher sensitivity compared with FNAS, suggesting that ESC use is unlikely to miss infants requiring treatment who would have been identified by FNAS. Transitioning from FNAS to ESC is not likely to impair the care of infants with NAS.

Neonatal abstinence syndrome (NAS) is characterized by symptoms of withdrawal that occur in a newborn after fetal exposure to maternal opioids. NAS symptoms manifest clinically as neurologic, gastrointestinal, and autonomic dysregulation. From 2000 to 2009, the incidence of NAS tripled as a result of a nearly five-fold increase in the incidence of maternal opioid use during pregnancy.1  Hospital length of stay,2  and thus the cost associated with treating NAS,13  has also dramatically risen. The state of Maine is particularly affected, with an incidence of NAS being >30 cases per 1000 live births.4 

NAS symptom severity is often assessed by using the Modified Finnegan Neonatal Abstinence Score (FNAS),5  a 21-point scoring system that has been criticized for both its complexity and subjectivity. FNAS scoring is used in determining if an infant’s symptoms are severe enough to require pharmacologic therapy with medications such as morphine, methadone, or phenobarbital. There is significant variability between institutions regarding the specific FNAS score used as a threshold for initiating pharmacologic treatment of infants with NAS or for prompting a clinical assessment. Some institutions treat infants on the basis of their exposure to any opioids in utero without accounting for symptom severity.69  Thus, there is a growing gap between FNAS scoring and clinical decision-making.1013 

Clinicians have worked to optimize nonpharmacologic management and streamline clinical protocols for assessment of NAS symptoms.1419  Most efforts to improve the FNAS scoring system have been focused on creating shorter versions of the FNAS tool to simplify the evaluation. Several other tools and simplified FNAS scoring tools exist but have not been widely used because they are less studied than the FNAS tool or have no designated scoring cutoff for treatment.20 

Yale New Haven Children’s Hospital developed a novel assessment strategy that included observation from only 3 clinical features: (1) the ability to eat, (2) the ability to sleep undisturbed for 1 hour after feeding, and (3) the level of irritability as defined by the ability to be consoled within 10 minutes.21,22  One of the critical aspects of this new paradigm is a strong emphasis on nonpharmacologic care with the increased use of breastfeeding when appropriate, swaddling, and holding and creation of a low-stimulation environment and support for the maternal-child dyad. Implementation of this Eat, Sleep, Console (ESC) protocol scoring system has significantly decreased hospital length of stay and the number of infants requiring pharmacologic intervention.21  In only 1 study have researchers directly compared the FNAS to ESC assessment in 50 infants,19,21  but no comparisons of larger cohorts have been performed. We aimed to compare the sensitivity and specificity of FNAS and ESC elements using a subset of components of the FNAS as a proxy for ESC protocol assessment in a large retrospective cohort. Our goal was to determine if cases requiring pharmacologic treatment, defined in this cohort by actual treatment status, would have been missed if the ESC assessment alone were used.

This was a retrospective cohort study of neonates with NAS at a single institution, in which patients were assessed clinically by using the FNAS. Our institution is a 116-bed children’s hospital embedded within a tertiary medical center in New England.

Cases of infants with NAS were identified in the electronic medical record (EMR) by the presence of an International Classification of Diseases, Ninth Revision (779.5) or an International Classification of Diseases, 10th Revision (P96.1) billing code indicating NAS and documentation in the maternal record of opioid use during pregnancy. Infants were also identified if FNAS scoring was performed during the hospitalization but were excluded if FNAS scoring was performed to assess symptoms related to iatrogenic opioid exposure. An additional exclusion criterion was gestational age <37 weeks.

FNAS scores were assigned and recorded by nursing staff in the EMR every 4 hours for a minimum of 5 to 7 days per hospital protocol and continued throughout the infant’s entire hospitalization by using the standard 21-symptom scoring system. Nurses recorded the individual component scores in the EMR, and the component scores were totaled (total FNAS score) by the EMR. All component and total scores for every infant in the cohort during the infant’s entire hospitalization at our institution were extracted from the EMR. At our institution, infants with 3 consecutive scores ≥8 or 2 consecutive scores ≥12 were clinically assessed for pharmacologic treatment. If indicated, pharmacologic treatment was initiated in the NICU for infants after the assessment by the attending neonatologist. Not all infants who met the FNAS threshold received pharmacologic treatment.

The dependent outcome was the infant’s pharmacologic treatment status: treated or untreated. A manual chart review was used to determine if the infant received pharmacologic therapy with morphine, phenobarbital, or both.

Component scores of the FNAS similar to the 3 ESC protocol assessment elements were identified.

The FNAS score for “feeding” has 2 levels (a score of 0 or 2). The ESC protocol assessment asks, “Can the infant eat 1 ounce per feed or breastfeed well?” to assess feeding. Infants scoring 0 for “poor feeding” were considered Eat− (because this is feeding normally); those scoring a 2 on FNAS were designated as Eat+.

The FNAS score (ranging from 0 to 3, with higher scores indicating more difficulties with sleep) for sleep has 4 levels: sleeps <1 hour after feeding (a score of 3 per the FNAS), sleeps <2 hours after feeding (a score of 2), sleeps <3 hours after feeding (a score of 1), or sleeps >3 hours after feeding (score of 0). The ESC protocol assessment asks, “Can the infant sleep more than 1 hour after feeding?” The FNAS score of 3 for sleep was the ESC proxy chosen for poor sleeping; infants scoring 3 were designated as Sleep+. Infants scoring 0, 1, or 2 for sleep in FNAS were considered Sleep−.

The FNAS variable for cry is the closest proxy to the ESC variable. The FNAS score for cry has 3 levels: normal or no crying (a score of 0 per the FNAS), “excessive high-pitched cry” (a score of 2), or “continuous high-pitched cry” (a score of 3). The ESC protocol assessment asks, “Can the infant be consoled within 10 minutes?” The FNAS score of 2 or 3 for “cry” was considered the equivalent of the ESC protocol parameter for inconsolability, and infants scoring 2 or 3 were designated as Console+. Infants scoring a 0 for cry were considered Console−.

According to the ESC protocol assessment guidelines, infants are eligible for pharmacologic intervention if 1 of the 3 parameters (Eat, Sleep, or Console) remains positive after nonpharmacologic therapy is maximized. Infants were designated ESC proxy− if they were Eat−, Sleep−, and Console−, and these infants would not require pharmacologic treatment. Because of the retrospective nature of the study and the absence of nonpharmacologic intervention data, we designated infants as “ESC proxy+” if they were Eat+, Sleep+, or Console+ more than once in the FNAS data (to correlate with the clinical protocol of first implementing nonpharmacologic treatment). These infants would have met the criteria for pharmacologic treatment in our ESC protocol, assuming nonpharmacologic treatment had been maximized.

Clinical, demographic, opioid, and other exposures were analyzed by using descriptive statistics. Sensitivity and specificity of FNAS were calculated on the basis of the threshold (scores ≥8 in 3 consecutive scores or ≥12 in 2 consecutive scores) and treatment status; similar calculations were repeated for the ESC proxy. These were calculated by using the actual treatment status of the infant as the indicator of disease. Using only the treated infants, we compared the ESC proxy scores to the FNAS scores’ determination of infant status. We compared them using the McNemar comparison with Yates correction for tests with expected values <10. The initial analysis was done in Excel 2016 and in R version 3.6.1. The institutional review board deemed this project institutional review board exempt.

From February 2013 to August 2016, a total of 480 infants were opioid exposed and had FNAS scoring, and 423 of these met inclusion criteria by gestational age. The majority of infants were delivered vaginally to multiparous mothers (Table 1). The most common opioid exposure was buprenorphine (67.8%). The majority of infants had pharmacologic coexposures, with tobacco being the most common. For the cohort as a whole, 33 115 FNAS total scores were recorded over 921 days of observation. Although 256 infants (60.5% of the overall cohort) met the FNAS criteria for pharmacologic treatment (3 consecutive FNAS scores ≥8 or 2 FNAS scores ≥12), only 165 (39% of the overall cohort) of these infants were true-positives and were treated pharmacologically (Table 2). In total, 9 infants, false-negatives, did not meet the FNAS screening threshold yet received pharmacologic treatment (Tables 2 and 3). An additional 91 infants, the false-positives, scored above the FNAS screening threshold but were not treated, and 158 were untreated and scored below the threshold.

TABLE 1

Demographic Characteristics of Infants Scored for NAS (Including Maternal and Infant Characteristics) and Pharmacologic Treatment Status

Total, n = 423Treated, n = 174Untreated, n = 249
Boys, n (%) 218 (51.5) 95 (54.6) 123 (49.4) 
Born at our facility, n (%) 378 (89.4) 140 (80.5) 238 (95.6) 
Transfer from another hospital, n (%) 44 (10.4) 33 (19.0) 11 (4.4) 
Other,a n (%) 1 (0.2) 1 (0.6) 0 (0.0) 
Delivery type, n (%)    
 Cesarean delivery 140 (33.1) 55 (31.6) 85 (34.1) 
 Vaginal 280 (66.2) 118 (67.8) 162 (65.1) 
 Unknown 3 (0.7) 3 (1.7) 3 (1.2) 
Birth weight, g, mean ± SD 3156.2 ± 543.8 3136.3 ± 565.7 3170.1 ± 527.6 
 <2500, n (%) 50 (11.8) 21 (12.1) 29 (11.6) 
 2500–4000, n (%) 353 (83.5) 146 (83.9) 207 (83.1) 
 >4000, n (%) 20 (4.7) 7 (4.0) 13 (5.2) 
Maternal age, y, mean ± SD 28.3 ± 4.7 28.4 ± 4.6 28.2 ± 4.7 
 <18, n (%) 0 (0.0) 0 (0.0) 0 (0.0) 
 18–35, n (%) 376 (88.9) 154 (88.5) 222 (89.2) 
 >35, n (%) 44 (10.4) 17 (9.8) 27 (10.8) 
 Unknown 3 (0.7) 3 (1.7) 0 (0.0) 
Maternal marital status, n (%)    
 Significant other 175 (41.4) 68 (39.1) 107 (43.0) 
 Single 161 (38.1) 82 (47.1) 79 (31.7) 
 Married 67 (15.8) 17 (9.8) 50 (20.1) 
 Divorced 14 (3.3) 4 (2.3) 10 (4.0) 
 Legally separated 4 (0.9) 1 (0.6) 3 (1.2) 
 Unknown 2 (0.5) 2 (1.1) 0 (0.0) 
Maternal parity, mean ± SD 2.4 ± 1.4 2.5 ± 1.5 2.3 ± 1.3 
 1, n (%) 120 (28.4) 46 (26.4) 74 (29.7) 
 2–5, n (%) 271 (64.1) 116 (66.7) 155 (62.2) 
 >5, n (%) 15 (3.5) 7 (4.0) 8 (3.2) 
 Unknown, n (%) 10 (2.4) 2 (1.1) 8 (3.2) 
Total, n = 423Treated, n = 174Untreated, n = 249
Boys, n (%) 218 (51.5) 95 (54.6) 123 (49.4) 
Born at our facility, n (%) 378 (89.4) 140 (80.5) 238 (95.6) 
Transfer from another hospital, n (%) 44 (10.4) 33 (19.0) 11 (4.4) 
Other,a n (%) 1 (0.2) 1 (0.6) 0 (0.0) 
Delivery type, n (%)    
 Cesarean delivery 140 (33.1) 55 (31.6) 85 (34.1) 
 Vaginal 280 (66.2) 118 (67.8) 162 (65.1) 
 Unknown 3 (0.7) 3 (1.7) 3 (1.2) 
Birth weight, g, mean ± SD 3156.2 ± 543.8 3136.3 ± 565.7 3170.1 ± 527.6 
 <2500, n (%) 50 (11.8) 21 (12.1) 29 (11.6) 
 2500–4000, n (%) 353 (83.5) 146 (83.9) 207 (83.1) 
 >4000, n (%) 20 (4.7) 7 (4.0) 13 (5.2) 
Maternal age, y, mean ± SD 28.3 ± 4.7 28.4 ± 4.6 28.2 ± 4.7 
 <18, n (%) 0 (0.0) 0 (0.0) 0 (0.0) 
 18–35, n (%) 376 (88.9) 154 (88.5) 222 (89.2) 
 >35, n (%) 44 (10.4) 17 (9.8) 27 (10.8) 
 Unknown 3 (0.7) 3 (1.7) 0 (0.0) 
Maternal marital status, n (%)    
 Significant other 175 (41.4) 68 (39.1) 107 (43.0) 
 Single 161 (38.1) 82 (47.1) 79 (31.7) 
 Married 67 (15.8) 17 (9.8) 50 (20.1) 
 Divorced 14 (3.3) 4 (2.3) 10 (4.0) 
 Legally separated 4 (0.9) 1 (0.6) 3 (1.2) 
 Unknown 2 (0.5) 2 (1.1) 0 (0.0) 
Maternal parity, mean ± SD 2.4 ± 1.4 2.5 ± 1.5 2.3 ± 1.3 
 1, n (%) 120 (28.4) 46 (26.4) 74 (29.7) 
 2–5, n (%) 271 (64.1) 116 (66.7) 155 (62.2) 
 >5, n (%) 15 (3.5) 7 (4.0) 8 (3.2) 
 Unknown, n (%) 10 (2.4) 2 (1.1) 8 (3.2) 
a

Born precipitously in ambulance by emergency medical services.

TABLE 2

Number of Subjects Exceeding Screening Threshold Using FNAS or ESC Proxy by Treatment Status

Treated, n = 174Untreated, n = 249
FNAS status   
 Above threshold, n = 256 165 91 
 Below threshold, n = 167 158 
ESC proxy status   
 ESC proxy+, n = 322 173 149 
 ESC proxy–, n = 101 100 
Treated, n = 174Untreated, n = 249
FNAS status   
 Above threshold, n = 256 165 91 
 Below threshold, n = 167 158 
ESC proxy status   
 ESC proxy+, n = 322 173 149 
 ESC proxy–, n = 101 100 
TABLE 3

Comparing FNAS Threshold Scoring Status and ESC Proxy Status (2 Screening Tests) in 174 Patients Treated Pharmacologically

ESC Proxy+, n (%)ESC Proxy–, n (%)
Above FNAS threshold 165 (94.0) 0 (0.0) 
Below FNAS threshold 8 (4.6) 1 (0.6) 
ESC Proxy+, n (%)ESC Proxy–, n (%)
Above FNAS threshold 165 (94.0) 0 (0.0) 
Below FNAS threshold 8 (4.6) 1 (0.6) 

More infants were above the screening threshold when using the ESC proxy assessment (322 vs 256). However, there were fewer false-negatives with the ESC proxy assessment: only 1 (0.6%) treated infant was ESC proxy− versus 9 (5.2%) false-negatives according to the FNAS assessment. There were 149 infants who scored ESC proxy+ but who were not treated. A single infant was ESC proxy− and ultimately received treatment (of note, this infant also did not meet the FNAS screening threshold).

We then compared the ESC and FNAS methods as screening tests to detect the underlying need for pharmacologic treatment using the receipt of pharmacologic care as the marker of the presence of the disease (Table 4). Both tests had similar sensitivity for detection of disease (FNAS was 94.8% and ESC proxy was 99.4%). The ESC proxy had 40.2% specificity for infants requiring intervention for NAS compared with the full FNAS scoring system (63.5%).

TABLE 4

Test Characteristics of the FNAS Threshold and ESC Proxy Scores Using Ultimate Treatment Status as Indication of Presence of Disease (P < .01)

FNAS, %ESC Proxy Components, %
Sensitivity 94.8 99.4 
Specificity 63.5 40.2 
Negative predictive value 94.6 99.1 
Positive predictive value 64.5 53.7 
FNAS, %ESC Proxy Components, %
Sensitivity 94.8 99.4 
Specificity 63.5 40.2 
Negative predictive value 94.6 99.1 
Positive predictive value 64.5 53.7 

Our goal for this project was to determine if transitioning from FNAS to the ESC assessment tool would inappropriately screen out infants who had been clinically assessed as needing pharmacologic treatment of NAS. We found that the ESC proxy had slightly higher sensitivity (99.4% vs 94.8%), and this was encouraging, yet there was a sizeable decrease in specificity (40.2% vs 63.5%), suggesting that more infants from the untreated category would be assessed for pharmacologic treatment by using ESC than FNAS. This does not mean more infants would be pharmacologically treated because clinician judgment has historically superseded scoring thresholds within our institution, as evidenced by the discrepancy between those who scored above the FNAS threshold for treatment versus those who actually received treatment. Our finding of high sensitivity of ESC proxy scores in the treated infants provides reassurance to those institutions that have made the transition to ESC from FNAS that this transition will not miss infants who have been traditionally viewed as requiring pharmacologic therapy for NAS.

Because one-third of the infants who exceeded the FNAS screening threshold were not treated pharmacologically, this work supports the concept that clinical judgment and unmeasured factors in addition to the screening assessment tools are used to determine appropriate treatment. Although we cannot exclude other reasons to employ the FNAS screening method, our analysis gives us confidence that the added work of such comprehensive observations in the setting of infants at risk for NAS does not directly contribute to more appropriate intervention than using just the ESC proxies. Our hospital has chosen to redirect the clinical care efforts from the FNAS scores to the more attentive bedside evaluations and provision of direct care required in the ESC evaluation practices. Our results reveal that these criteria will not miss infants who would ultimately be deemed in need of pharmacologic treatment. However, given the lower specificity of the ESC proxy scores compared with FNAS, there is a risk of overintervening on infants when using the ESC proxy score instead of FNAS, although, given the strong focus on nonpharmacologic care with ESC, there is a low likelihood of excess pharmacologic treatment.

Although the FNAS was developed as a diagnostic tool, our work reveals that, in practice, it is being used as a way to identify infants who may need treatment and not as a strict indication for treatment despite exceeding the FNAS thresholds. The ESC is designed as a screening tool, and our work reveals that by limiting the FNAS just to the ESC proxy components, institutions will not underidentify infants potentially requiring intervention for NAS.

One strength of our project is that at the time of this study, our institution, as part of a national randomized control trial for methadone versus morphine treatment of NAS,23  had been trained in techniques for consistent scoring of the FNAS. As such, we are confident that the scoring of variables was as uniform as possible given the recent review of format, schedule, and subtleties of the tool.24  Additionally, we reviewed data before ESC was proposed, so there were unlikely to be assessment changes by the nursing staff due to a desire to streamline the scoring process to record fewer elements or from the implementation of the many nonpharmacologic management options that came along with true adherence to the ESC protocols. A strength of our study is the mixed primary opioid exposure (many other studies only allow for a single opioid exposure).

There are also several important limitations of this study. These have to do with assumptions about the equivalence of the FNAS components to the ESC, which, although similar, are not identical. In addition, we chose to assume proxy+ treatment status on the basis of ≥2 occurrences of being proxy+, assuming this would be the equivalent of maximizing nonpharmacologic therapy after the first proxy+. This may be the reason for the lower specificity of the ESC proxy. An additional limitation of this study is a lack of data regarding at what time point an infant was pharmacologically treated. Therefore, we do not know at which time point FNAS scores might have changed because of pharmacologic or nonpharmacologic intervention. We also did not have information regarding age at transfer for infants coming from outside facilities, which may account for the 9 infants who were treated but did not exceed the FNAS threshold (because our data set only included scores from our institution). For example, it is possible an infant was transferred after scoring well above the threshold at the outside hospital but only had a single excessive score here; they would have been classified as below threshold on the basis of our data, but, in reality, they would have been above the threshold when looking at their entire clinical history. An additional limitation is that the retrospective nature of this study does not allow for assessment of the increased nonpharmacologic measures that come with ESC protocols. Finally, we were unable to analyze the potential association of maternal coexposures, many of which are known to increase the likelihood of receiving pharmacologic treatment of NAS.

Providing adequate care for NAS is a critical part of our clinical mission. Our study reveals that, within our system, transitioning to the ESC method would not miss infants requiring intervention who would have been otherwise identified by the FNAS. Potential benefits to the infants, families, and caregivers by reducing the observational burden of the FNAS system to the more straightforward ESC process would be unlikely to result in missing opportunities for care, delaying the detection of highly symptomatic infants or adding to the workload for the staff or families. As institutions move away from the FNAS to the ESC method, they can feel confident the more limited screening will not miss infants who would have been identified by the more conservative FNAS screening protocol.

Deidentified individual participant data will not be made available.

Dr Curran conceptualized and designed the study, conducted initial analysis of data, and drafted the initial manuscript; Dr Holt assisted with conceptualization and design of the study and reviewed and revised the manuscript; Drs Arciero and Quinlan conducted and confirmed analysis and reviewed and revised the initial manuscript; Drs Cox and Craig supervised collection of initial data and demographics of the cohort and reviewed and revised the initial manuscript; and all authors approved the final manuscript as submitted.

FUNDING: No external funding.

1
Patrick
SW
,
Dudley
J
,
Martin
PR
, et al
.
Prescription opioid epidemic and infant outcomes
.
Pediatrics
.
2015
;
135
(
5
):
842
850
2
Tolia
VN
,
Patrick
SW
,
Bennett
MM
, et al
.
Increasing incidence of the neonatal abstinence syndrome in U.S. neonatal ICUs
.
N Engl J Med
.
2015
;
372
(
22
):
2118
2126
3
Kocherlakota
P
.
Neonatal abstinence syndrome
.
Pediatrics
.
2014
;
134
(
2
).
4
Ko
JY PS
,
Tong
VT
,
Patel
R
,
Lind
JN
,
Barfield
WD
.
Incidence of neonatal abstinence syndrome – 28 states, 1999–2013
.
MMWR Morb Mortal Wkly Rep
.
2016
;
65
(
31
):
799
802
5
Johnson
K
,
Gerada
C
,
Greenough
A
.
Treatment of neonatal abstinence syndrome
.
Arch Dis Child Fetal Neonatal Ed
.
2003
;
88
(
1
):
F2
F5
6
Westgate
PM
,
Gomez-Pomar
E
.
Judging the neonatal abstinence syndrome assessment tools to guide future tool development: the use of clinimetrics as opposed to psychometrics
.
Front Pediatr
.
2017
;
5
:
204
7
Gaalema
DE
,
Scott
TL
,
Heil
SH
, et al
.
Differences in the profile of neonatal abstinence syndrome signs in methadone- versus buprenorphine-exposed neonates
.
Addiction
.
2012
;
107
(
suppl 1
):
53
62
8
Orlando
S
.
An overview of clinical tools used to assess neonatal abstinence syndrome
.
J Perinat Neonatal Nurs
.
2014
;
28
(
3
):
212
219
9
Gaalema
DE
,
Heil
SH
,
Badger
GJ
,
Metayer
JS
,
Johnston
AM
.
Time to initiation of treatment for neonatal abstinence syndrome in neonates exposed in utero to buprenorphine or methadone
.
Drug Alcohol Depend
.
2013
;
133
(
1
):
266
269
10
Kaltenbach
K
,
Finnegan
LP
.
Neonatal abstinence syndrome, pharmacotherapy and developmental outcome
.
Neurobehav Toxicol Teratol
.
1986
;
8
(
4
):
353
355
11
Grossman
M
,
Seashore
C
,
Holmes
AV
.
Neonatal abstinence syndrome management: a review of recent evidence
.
Rev Recent Clin Trials
.
2017
;
12
(
4
):
226
232
12
Jones
HE
,
Kaltenbach
K
,
Heil
SH
, et al
.
Neonatal abstinence syndrome after methadone or buprenorphine exposure
.
N Engl J Med
.
2010
;
363
(
24
):
2320
2331
13
Pritham
UA
,
Troese
M
,
Stetson
A
.
Methadone and buprenorphine treatment during pregnancy: what are the effects on infants?
Nurs Womens Health
.
2007
;
11
(
6
):
558
567
14
Gomez Pomar
E
,
Finnegan
LP
,
Devlin
L
, et al
.
Simplification of the Finnegan Neonatal Abstinence Scoring System: retrospective study of two institutions in the USA
.
BMJ Open
.
2017
;
7
(
9
):
e016176
15
Brandt
L
,
Finnegan
LP
.
Neonatal abstinence syndrome: where are we, and where do we go from here?
Curr Opin Psychiatry
.
2017
;
30
(
4
):
268
274
16
Shirel
T
,
Hubler
CP
,
Shah
R
, et al
.
Maternal opioid dose is associated with neonatal abstinence syndrome in children born to women with sickle cell disease
.
Am J Hematol
.
2016
;
91
(
4
):
416
419
17
Kelly
LE
,
Jansson
LM
,
Moulsdale
W
, et al
.
A core outcome set for neonatal abstinence syndrome: study protocol for a systematic review, parent interviews and a Delphi survey
.
Trials
.
2016
;
17
(
1
):
536
18
Jones
HE
,
Seashore
C
,
Johnson
E
, et al
.
Psychometric assessment of the Neonatal Abstinence Scoring System and the MOTHER NAS Scale
.
Am J Addict
.
2016
;
25
(
5
):
370
373
19
Bagley
SM
,
Wachman
EM
,
Holland
E
,
Brogly
SB
.
Review of the assessment and management of neonatal abstinence syndrome
.
Addict Sci Clin Pract
.
2014
;
9
(
1
):
19
20
Jansson
LM
,
Velez
M
,
Harrow
C
.
The opioid-exposed newborn: assessment and pharmacologic management
.
J Opioid Manag
. 2009
;
5
(
1
):
47
21
Grossman
MR
,
Lipshaw
MJ
,
Osborn
RR
,
Berkwitt
AK
.
A novel approach to assessing infants with neonatal abstinence syndrome
.
Hosp Pediatr
.
2018
;
8
(
1
):
1
6
22
Grossman
MR
,
Berkwitt
AK
,
Osborn
RR
, et al
.
An initiative to improve the quality of care of infants with neonatal abstinence syndrome
.
Pediatrics
.
2017
;
139
(
6
):
e20163360
23
Davis
JM
,
Shenberger
J
,
Terrin
N
, et al
.
Comparison of safety and efficacy of methadone vs morphine for treatment of neonatal abstinence syndrome: a randomized clinical trial
.
JAMA Pediatr
.
2018
;
172
(
8
):
741
748
24
Lucas
K
,
Knobel
RB
.
Implementing practice guidelines and education to improve care of infants with neonatal abstinence syndrome
.
Adv Neonatal Care
.
2012
;
12
(
1
):
40
45

Competing Interests

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.