Postmenstrual Age Versus Postnatal Age

Two Clocks for Describing Development

In neonatal pharmacokinetics, “age” can refer to more than one elapsed-time scale. Two infants who are both 14 days old after birth may have experienced very different durations of development before birth. A model that uses only time since birth does not represent that prenatal interval directly; a model that uses postmenstrual age includes it in the age scale.

These measures are related by a simple calculation, but they answer different questions. The choice matters when age is used to represent developmental change in a PK model: the same infant has a larger postmenstrual age than postnatal age, and infants born at different gestational ages can have different postmenstrual ages despite the same time since birth.

Definition: Postnatal age (PNA) is elapsed time since birth. Gestational age at birth (GA at birth) is the estimated duration of gestation when the infant was born. Postmenstrual age (PMA) is gestational age at birth plus postnatal age. For ages expressed in weeks and days, add the elapsed times using 7 days per week.

Gestational age is commonly recorded as completed weeks plus additional days. For example, 31 weeks and 5 days is written as 31+5. The “+5” means five days beyond 31 completed weeks; it is not a decimal fraction. Thus, 31+5 is not 31.5 weeks. When a model requires age in decimal weeks, convert the days by dividing by 7: 31+5 corresponds to \(31+5/7 \approx 31.71\) weeks.

PNA is zero at birth and increases with elapsed time after birth. PMA at birth equals GA at birth, and PMA increases by the same amount as PNA. These calculations assume that GA at birth and the elapsed time since birth are recorded on compatible time scales. In practice, age may be recorded in days, weeks and days, or decimal weeks; conversions should be explicit and consistent.

Calculating Both Ages

Worked Example: A Premature Infant at Follow-Up

A hypothetical infant is born at 28 weeks and 4 days of gestation. The infant is assessed 6 weeks and 3 days after birth. Calculate PNA and PMA at assessment.

Postnatal age. The time elapsed since birth is \(6\) weeks and \(3\) days, so PNA is \(6+3\), or \(45\) days.

Postmenstrual age. Add the gestational age at birth to the postnatal age:

\begin{aligned} \text{PMA} &= (28\text{ weeks }+4\text{ days})+(6\text{ weeks }+3\text{ days})\\ &=34\text{ weeks }+7\text{ days}\\ &=35\text{ weeks }+0\text{ days}. \end{aligned}

The infant is therefore 6 weeks and 3 days postnatal, but 35 weeks postmenstrual. The 35-week value is the developmental time coordinate that includes the estimated gestational interval before birth; it does not mean the infant has spent 35 weeks outside the womb.

Worked Example: A Term-Born Infant

A hypothetical infant is born at 39 weeks and 2 days of gestation and is assessed 14 days later. Calculate PNA and PMA.

Postnatal age. Fourteen days is exactly 2 weeks, so PNA is 2 weeks and 0 days.

Postmenstrual age. Add the 2 postnatal weeks to the gestational age at birth:

39\text{ weeks }+2\text{ days}+2\text{ weeks} =41\text{ weeks }+2\text{ days}.

At assessment, this infant is 2 weeks postnatal and 41 weeks and 2 days postmenstrual. “Term-born” does not mean that every infant should be assigned a gestational age of 40 weeks. The calculation uses the infant’s recorded GA at birth, not a rounded term value.

It is useful to check calculations in days as well as weeks and days. In the premature-infant example, GA at birth is \(28\times7+4=200\) days and PNA is \(6\times7+3=45\) days. Their sum is \(245\) days, which is \(35\times7\), confirming PMA of 35 weeks. This check helps catch errors when adding a total of 7 or more days.

What the Choice Means in a PK Model

An age covariate provides a time coordinate for representing development. Choosing PNA places birth at the origin: infants with the same time since birth receive the same PNA, even if they were born at different gestational ages. Choosing PMA places an infant’s age coordinate at GA at birth on the day of birth and then advances it by PNA. Infants born at different gestational ages can therefore have different PMAs at the same PNA.

For example, a generic age-dependent component of a population PK model might be written as \(g(A_i)\), where \(A_i\) is the selected age measure for infant \(i\). If \(A_i\) is PNA, the component describes change along time since birth. If \(A_i\) is PMA, it describes change along the age scale that includes both gestation and time after birth. This notation does not specify the shape of \(g\); the age scale and the functional form are separate modeling decisions.

The identity relating the two measures also shows why they cannot always be substituted without changing a model. Let \(G_i\) be infant \(i\)’s GA at birth and \(T_i\) be that infant’s PNA, measured in the same units. Then:

\text{PMA}_i=G_i+T_i.

Suppose, only for illustration, that a model includes a linear age term \(\beta_A A_i\) in a predictor. With PMA as the age measure, this term is:

\beta_A\text{PMA}_i =\beta_A(T_i+G_i) =\beta_A T_i+\beta_A G_i.

This derivation shows that replacing PMA by PNA alone omits the contribution of GA at birth unless that difference is otherwise represented. If every infant had the same GA at birth, the added term would be constant and could be absorbed into an intercept. When GA at birth varies, it is not generally one common constant. The same issue arises for nonlinear age functions: in general, \(g(T_i+G_i)\) is not equal to \(g(T_i)\) plus a single shared constant.

Worked Example: Same PNA, Different PMA

Consider two hypothetical infants assessed at 4 weeks PNA. Infant A was born at 28 weeks gestation; Infant B was born at 32 weeks gestation. Calculate their PMAs and compare their age coordinates.

For Infant A, \(\text{PMA}=28+4=32\) weeks. For Infant B, \(\text{PMA}=32+4=36\) weeks. Both have PNA of 4 weeks, but their PMAs differ by \(36-32=4\) weeks.

To make the consequence for model inputs concrete, suppose a purely illustrative linear age term has coefficient \(0.08\) per week and uses PMA. Holding all other model terms equal, the difference in the age contribution is:

0.08\frac{1}{\text{week}}\times(36-32)\text{ weeks}=0.32.

If this term is on the log scale, the corresponding ratio of the modeled quantities is \(\exp(0.32)\approx1.377\). This is a calculation under the stated hypothetical model, not evidence that the infants’ PK parameters actually differ by that amount. With PNA as the age input, both infants would instead receive the same age value of 4 weeks. The example isolates how the selected clock changes the covariate input; it does not establish which clock is preferable for a particular drug or data set.

Choosing and Checking an Age Scale

PMA and PNA are not competing measurements of the same elapsed interval. Each defines a different time origin and can be appropriate for a different developmental question. A PK analysis should state which is used, give its units, and describe how it was calculated. The interpretation of an estimated age relationship is conditional on that definition.

Age measure	Time origin	What equal values mean	Key limitation
PNA	Birth	The same elapsed time since birth	Does not itself include differences in gestational age at birth
PMA	Gestational age at birth, continued after birth	The same combined gestational and postnatal age coordinate	Does not imply identical developmental history or environment
GA at birth	Birth	The same estimated gestational duration at delivery	Is a birth characteristic, not an age that continues to increase after birth

Several checks can reveal an age-scale problem before or during model development:

Verify the arithmetic and units. Confirm that weeks-and-days values are normalized, that days are converted consistently, and that assessment dates produce plausible PNA values.
Check the age origin. Confirm whether a field labeled “age” means PNA, PMA, or another convention. A variable name alone is not enough to establish its meaning.
Inspect the birth-age range. If GA at birth varies substantially, PNA and PMA can rank infants differently in age at a given assessment. That difference is relevant to interpretation.
Look for systematic patterns by age definition. Compare observed data and model residuals across the age range and, where relevant, across GA-at-birth groups. A trend may indicate an inadequate representation, but it does not by itself identify the cause.
Check whether the data support the distinction. If PNA and GA at birth have limited independent variation, their contributions may be difficult to separate. A more elaborate age specification cannot recover information the data do not contain.

These checks are diagnostics, not automatic rules for selecting PMA. Residual patterns can reflect model misspecification, sparse sampling, measurement error, or other covariates as well as an age-scale choice. Similarly, close agreement between results under two age definitions does not prove that the definitions are interchangeable; it may reflect the particular distribution of ages in the data.

Common Pitfall and Practical Limitations

A frequent mistake is to report “the infant is 35 weeks old” without saying whether this means 35 weeks PNA or PMA. In the premature-infant example, these are very different statements: PNA is 6 weeks and 3 days, while PMA is 35 weeks. Always name the measure and, when useful, state both.

Another mistake is to assume that infants with the same PMA have identical maturation because their age coordinates match. PMA aligns their total gestational-plus-postnatal age, but does not encode whether some of that time was spent in utero or after birth. These histories may differ in ways relevant to development and clinical care. Conversely, equal PNA establishes equal elapsed time since birth, not equal prenatal developmental duration.

In PK modeling, choosing an age scale does not establish a biological mechanism or guarantee an adequate model. It defines how development is indexed. The data, the scientific question, and model diagnostics must support the resulting interpretation. The choice should be documented clearly enough that another analyst can reproduce the age covariate from GA at birth and assessment timing.

Key takeaway: PNA is time since birth; PMA is GA at birth plus PNA. Both describe an infant’s age, but they use different time origins. A population PK model’s developmental interpretation therefore depends on which measure supplies its age coordinate.

Check Your Understanding

Answer each question, then check the solutions below.

An infant is born at 30 weeks and 6 days and is assessed 3 weeks and 2 days later. What are the infant’s PNA and PMA?
An infant is born at 40 weeks and 1 day and is assessed 21 days later. What are the infant’s PNA and PMA?
Two infants each have 5 weeks PNA. One was born at 27 weeks and the other at 34 weeks. Calculate both PMAs and explain why their PNA values are equal.
In one sentence, state what is lost if a model uses PNA alone when GA at birth varies, relative to using PMA.

Solutions. (1) PNA is 3 weeks and 2 days. PMA is \(30\text{ weeks }+6\text{ days}+3\text{ weeks }+2\text{ days}=33\text{ weeks }+8\text{ days}=34\text{ weeks }+1\text{ day}\). (2) PNA is 21 days, or 3 weeks. PMA is \(40\text{ weeks }+1\text{ day}+3\text{ weeks}=43\text{ weeks }+1\text{ day}\). (3) The PMAs are \(27+5=32\) weeks and \(34+5=39\) weeks. Their PNA values are equal because both have spent the same elapsed time since birth; their PMAs differ because their GA at birth differs. (4) PNA alone does not include the variation in gestational age at birth that contributes to PMA, so it places infants with equal time since birth at the same age coordinate even when their PMAs differ.