Assessment of Pain in Newborns and Older Infants (Infant Pain Assessment Study =
| Status: | Enrolling by invitation |
|---|---|
| Healthy: | No |
| Age Range: | Any |
| Updated: | 10/13/2018 |
| Start Date: | October 30, 2017 |
| End Date: | December 2026 |
Using Machine-learning Algorithms to Assess Acute Pain in Nonverbal Infants
Pain assessments in non-verbal, critically ill infants represent an important clinical
challenge. Older children or adults can easily express their pain, but infants lack that
capability. They frequently experience repetitive acute pain during routine ICU care, but
their analgesic management flounders on the horns of a dilemma: (a) failure to treat infant
pain leads to immediate clinical instability and potentially long-term physical, behavioral,
and cognitive sequelae, vs. (b) strong analgesics may increase risks for medical
complications and/or impaired brain growth. Bedside nurses currently assess pain using pain
scores, before taking action to ameliorate pain. Pain scores increase nursing workload and
provide subjective assessments, rather than objective data for evaluating infant pain.
Consequently, infants exposed to skin-breaking procedures, surgery, or other painful
conditions often receive variable and inconsistent pain management in the ICU. The
investigators aim to develop a multimodal pain assessment system, using sensor fusion and
novel machine learning algorithms to provide an objective measure of pain that is
context-dependent and rater-independent. This will enhance the quality of pain management in
ICUs and allow continuous pain monitoring in real-time.
challenge. Older children or adults can easily express their pain, but infants lack that
capability. They frequently experience repetitive acute pain during routine ICU care, but
their analgesic management flounders on the horns of a dilemma: (a) failure to treat infant
pain leads to immediate clinical instability and potentially long-term physical, behavioral,
and cognitive sequelae, vs. (b) strong analgesics may increase risks for medical
complications and/or impaired brain growth. Bedside nurses currently assess pain using pain
scores, before taking action to ameliorate pain. Pain scores increase nursing workload and
provide subjective assessments, rather than objective data for evaluating infant pain.
Consequently, infants exposed to skin-breaking procedures, surgery, or other painful
conditions often receive variable and inconsistent pain management in the ICU. The
investigators aim to develop a multimodal pain assessment system, using sensor fusion and
novel machine learning algorithms to provide an objective measure of pain that is
context-dependent and rater-independent. This will enhance the quality of pain management in
ICUs and allow continuous pain monitoring in real-time.
Inclusion Criteria:
- 1. All infants less than 6 months of corrected chronological age. 2. Infants admitted
to the participating ICUs at LPCH (NICU, PICU, CVICU). 3. Require an acute painful
procedure for routine clinical care.
Exclusion Criteria:
1. Newborns with birth trauma, intrapartum asphyxia (5-minute Apgar Score <4 or cord pH <
7.01), fetal growth restriction (birth weight < 5th percentile for gestation),
congenital anomalies or metabolic disorders, or any kind of brain injury.
2. Newborns born to mothers with a history of heavy smoking or drug abuse (alcohol,
cocaine, ketamine, heroin/other opiates) or psychiatric drugs used during this
pregnancy.
3. Newborns and infants requiring positive pressure ventilation using a face mask (BiPAP)
or endotracheal tube (conventional or high-frequency ventilators).
4. Newborns and infants receiving continuous infusions of opioid drugs (morphine,
fentanyl, others) and nerve blocks or neuraxial analgesia affecting the site of the
invasive procedure during the 24 hours prior to study entry. (Note: Infants receiving
intermittent opioids or non-opioid analgesics (acetaminophen, ibuprofen, ketorolac,
others) WILL NOT be excluded).
5. Newborns and infants with facial anomalies, injuries or other pathologies affecting
the facial area.
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