Pecarn Head Ct Calculator
Determine if a child with minor head trauma needs a CT scan using PECARN decision rules. Enter values for instant results with step-by-step formulas.
Calculator
Adjust values & calculateNo high-risk or intermediate-risk predictors present. Risk of ciTBI is less than 0.02%. CT is not recommended. The negative predictive value of PECARN in this group is 100%.
Formula
For children < 2 years: High-risk predictors are GCS < 15, altered mental status, and palpable skull fracture. Intermediate predictors are occipital/parietal/temporal scalp hematoma, LOC >= 5 seconds, severe mechanism, and not acting normally. For children >= 2 years: High-risk predictors are GCS < 15, altered mental status, and basilar skull fracture signs. Intermediate predictors are vomiting, LOC, severe headache, and severe mechanism.
Last reviewed: January 2026
Worked Examples
Example 1: Infant Fall from Changing Table
Example 2: School-Age Child with No Risk Factors
Background & Theory
The Pecarn Head Ct Calculator applies the following established principles and formulas. Health and medicine calculators are grounded in validated physiological measurement methods established through decades of clinical research. Body Mass Index, or BMI, is calculated by dividing weight in kilograms by height in meters squared (kg/m²), a formula originating from Adolphe Quetelet's 19th-century statistical work and later codified by the WHO into standard classifications: underweight below 18.5, normal weight 18.5 to 24.9, overweight 25 to 29.9, and obese at 30 and above. Basal Metabolic Rate quantifies the minimum energy required to sustain life at rest. The Mifflin-St Jeor equation, published in 1990 and widely regarded as the most accurate for most adults, calculates BMR as (10 × weight in kg) + (6.25 × height in cm) − (5 × age) ± sex adjustment. The older Harris-Benedict equations, revised in 1984 by Roza and Shizgal, remain in common use. Total Daily Energy Expenditure is derived by multiplying BMR by a physical activity factor ranging from 1.2 for sedentary individuals to 1.9 for extremely active ones, following the methodology validated by doubly labeled water studies. Body fat percentage can be estimated without laboratory equipment using the U.S. Navy circumference method, which uses neck, waist, and hip measurements, or via BMI-derived equations adjusted for age and sex. The Jackson-Pollock skinfold method offers higher precision with calipers. Blood pressure classification, according to the American College of Cardiology and the 2017 ACC/AHA guidelines, defines normal as below 120/80 mmHg, elevated as 120 to 129 systolic, and hypertension stage 1 as 130 to 139 systolic or 80 to 89 diastolic. Target heart rate zones for aerobic exercise are derived from maximum heart rate estimates, most commonly using the formula 220 minus age in years, with moderate-intensity training typically defined as 50 to 70 percent of maximum heart rate and vigorous intensity at 70 to 85 percent, consistent with CDC and American Heart Association guidelines. These thresholds guide safe and effective cardiovascular conditioning.
History
The history behind the Pecarn Head Ct Calculator traces back through the following developments. The history of health measurement stretches back to ancient Greece, where Hippocrates around 400 BCE laid the foundation for observational medicine by systematically recording patient symptoms, diet, and environment. His humoral theory, though scientifically superseded, established the principle that the body operates as an interconnected system subject to measurable imbalance. The transformation toward modern medicine accelerated in the 19th century. Louis Pasteur and Robert Koch developed germ theory in the 1860s and 1870s, identifying microorganisms as disease agents and enabling targeted interventions. Florence Nightingale, working during the Crimean War in the 1850s, introduced statistical analysis to nursing practice, demonstrating through data visualization that sanitation reduced mortality. Her work is foundational to evidence-based health measurement. The discovery of vitamins in the early 20th century, beginning with Casimir Funk's coinage of the term in 1912 and culminating in the isolation of vitamins A through K, created the field of nutritional science and gave rise to dietary reference intake frameworks. The World Health Organization, founded in 1948, subsequently established global standards for health metrics, disease classification through the International Classification of Diseases, and recommended daily allowances. The BMI as a clinical screening tool gained traction in the 1970s through Ancel Keys' large-scale epidemiological work, which validated Quetelet's index as a population-level obesity indicator. Through the 1980s and 1990s, the Framingham Heart Study produced landmark data linking cholesterol, blood pressure, and lifestyle factors to cardiovascular disease risk, directly shaping the numeric thresholds still used in health calculators. The evidence-based medicine movement, formalized by Gordon Guyatt and colleagues at McMaster University in the early 1990s, demanded that all health recommendations derive from systematically graded clinical evidence. The digital health era beginning in the 2000s brought these formulas to consumer devices, wearable sensors, and smartphone applications, expanding access to health self-monitoring on a global scale and enabling population-level data collection that continues to refine clinical reference ranges.
Frequently Asked Questions
Formula
PECARN Risk = High / Intermediate / Very Low based on age-specific clinical predictors
For children < 2 years: High-risk predictors are GCS < 15, altered mental status, and palpable skull fracture. Intermediate predictors are occipital/parietal/temporal scalp hematoma, LOC >= 5 seconds, severe mechanism, and not acting normally. For children >= 2 years: High-risk predictors are GCS < 15, altered mental status, and basilar skull fracture signs. Intermediate predictors are vomiting, LOC, severe headache, and severe mechanism.
Worked Examples
Example 1: Infant Fall from Changing Table
Problem: An 8-month-old fell from a changing table (approximately 3.5 feet). The child cried immediately, has a large occipital scalp hematoma, GCS is 15, no altered mental status, no palpable skull fracture, and the parent says the child seems slightly fussier than normal.
Solution: PECARN Algorithm (< 2 years):\nGCS < 15: No\nAltered Mental Status: No\nPalpable Skull Fracture: No\n=> Not High Risk\n\nIntermediate Predictors:\nOccipital Scalp Hematoma: YES\nLOC: No\nSevere Mechanism: YES (fall > 3 feet for < 2 yr)\nActing Normally: Questionable (fussier)\n=> Intermediate Risk (ciTBI risk ~0.9%)
Result: INTERMEDIATE RISK | ciTBI ~0.9% | Observation 4-6 hours vs CT (shared decision-making)
Example 2: School-Age Child with No Risk Factors
Problem: A 7-year-old tripped and hit their forehead on the ground at school. No loss of consciousness. GCS 15. No vomiting, no headache, acting normally. Ground-level fall.
Solution: PECARN Algorithm (>= 2 years):\nGCS < 15: No\nAltered Mental Status: No\nBasilar Skull Fracture Signs: No\n=> Not High Risk\n\nIntermediate Predictors:\nVomiting: No\nLOC: No\nSevere Headache: No\nSevere Mechanism: No (ground-level fall)\n=> Very Low Risk (ciTBI risk <0.05%)
Result: VERY LOW RISK | ciTBI <0.05% | CT NOT recommended | Discharge with return precautions
Frequently Asked Questions
What is the PECARN head injury decision rule?
The PECARN (Pediatric Emergency Care Applied Research Network) head injury prediction rule is an evidence-based clinical decision tool developed to identify children at very low risk for clinically important traumatic brain injury (ciTBI) after minor head trauma, thereby reducing unnecessary CT scans. Published by Kuppermann and colleagues in The Lancet in 2009, it was derived from the largest prospective pediatric head injury study ever conducted, enrolling over 42,000 children across 25 emergency departments in North America. The rule uses separate algorithms for children under 2 years and those aged 2 years and older, because the clinical predictors of brain injury differ between these age groups. The rule has been externally validated in multiple international studies with consistently high negative predictive value.
Why are there separate PECARN algorithms for children under 2 and over 2 years?
The PECARN study identified different clinical predictors of ciTBI for children under 2 years compared to those 2 years and older, necessitating separate algorithms. In children under 2, palpable skull fractures and non-frontal scalp hematomas are important predictors because infants have thinner, more deformable skulls and cannot verbalize symptoms like headache. The parent observation that the child is not acting normally carries significant weight in this age group because it serves as a proxy for altered mental status that cannot be reliably assessed in preverbal children. In children 2 years and older, clinical signs of basilar skull fracture, vomiting, and severe headache replace the infant-specific criteria because older children can communicate symptoms and their skull anatomy more closely resembles adults.
How accurate is the PECARN rule at identifying children who need CT scans?
The PECARN prediction rule demonstrates exceptional accuracy for identifying children at very low risk for ciTBI. In the validation cohort, the rule had a sensitivity of 100 percent for ciTBI in children under 2 years and 96.8 percent in children 2 years and older, meaning it correctly identified virtually all children with clinically significant brain injuries. The negative predictive value exceeds 99.95 percent for children classified as very low risk. If applied consistently, the PECARN rule could potentially reduce CT use by 20 to 25 percent in children presenting with minor head trauma. The very high sensitivity comes at the cost of moderate specificity (approximately 50 to 60 percent), meaning that many children classified as intermediate or high risk will not have ciTBI, but the rule reliably identifies who does NOT need imaging.
What constitutes a severe mechanism of injury in the PECARN criteria?
The PECARN rule defines severe mechanism of injury as motor vehicle crash with patient ejection, death of another passenger in the same vehicle, or rollover. For pedestrians or cyclists, severe mechanism includes being struck by a motor vehicle without a helmet. Falls are classified as severe if the distance exceeds 5 feet for children 2 years and older, or exceeds 3 feet for children under 2 years. Head struck by a high-impact projectile is also considered severe. Notably, common mechanisms such as ground-level falls, falls from beds or couches (typically less than 3 feet), walking into objects, and being struck by soft objects are NOT considered severe mechanisms. The mechanism of injury serves as an intermediate-risk predictor in both age-group algorithms and helps guide the observation versus CT decision.
What are the limitations of the PECARN head injury prediction rule?
The PECARN rule has several important limitations that clinicians should understand. First, it was designed only for minor head trauma with initial GCS of 14 or 15 and should not be applied to children with GCS less than 14, penetrating injuries, or known bleeding disorders. Second, the rule was validated primarily in North American emergency departments and may perform differently in other healthcare settings or populations. Third, the intermediate-risk category includes a wide range of ciTBI probabilities (0.8 to 0.9 percent), and clinical judgment remains essential for deciding between observation and CT in these patients. Fourth, the rule does not account for non-accidental trauma (child abuse), which requires a different diagnostic approach. Finally, the rule addresses only ciTBI and may miss isolated skull fractures or minor intracranial findings that, while not requiring intervention, may be clinically relevant in certain contexts.
How accurate are the results from Pecarn Head Ct Calculator?
All calculations use established mathematical formulas and are performed with high-precision arithmetic. Results are accurate to the precision shown. For critical decisions in finance, medicine, or engineering, always verify results with a qualified professional.
References
Reviewed by Rahul Singh, Health & Wellness Specialist · Editorial policy