DOI: 10.5061/dryad.1c59zw44t
title: Pregnancy and postpartum dynamics revealed by millions of lab tests

description: Pregnancy and delivery involve dynamic alterations in many physiological
 systems. However, the physiological dynamics during pregnancy and after
 delivery have not been systematically analyzed at high temporal resolution
 in a large human population. Here we present the dynamics of 76 lab tests
 based on a cross-sectional analysis of roughly 41 million measurements
 from over 300,000 pregnancies. We analyzed each test at weekly intervals
 from 20 weeks preconception to 80 weeks postpartum, providing detailed
 temporal profiles. About half of the tests take three months to a year to
 return to baseline during postpartum, highlighting the physiologic load of
 childbirth. The precision of the data revealed the effects of
 preconception supplements, overshoots after delivery, and intricate
 temporal responses to changes in blood volume and renal filtration rate.
 Pregnancy complications – gestational diabetes, pre-eclampsia, and
 postpartum hemorrhage – showed distinct dynamical changes. These results
 provide a comprehensive dynamic portrait of the systems physiology of
 pregnancy.
description: Study Population The study population
 consisted of individuals from the Clalit healthcare database,
 Israel's largest health maintenance organization (HMO). We considered
 all pregnancies of females aged 20 to 35 between 2003 and 2020.
 Information about pregnancies before 2003 is not available. We estimated
 the fraction of first pregnancies for the years 2010-2020 to reduce the
 influence of first pregnancies before 2003 which we cannot account for.
 For more information, see “stats.csv”. Data
 Collection Medical records were pseudonymized by
 hashing of personal identifiers and randomization of dates by a random
 number of weeks uniformly sampled between 0 and 13 weeks for each patient
 and adding it to all dates in the patient diagnoses, laboratory, and
 medication records. This randomization does not affect timing relative to
 delivery.  We examined the timeframe of 60 weeks before
 delivery to 80 weeks after delivery for all documented labours within our
 study population. 0 is denoted as the week of delivery. We identified
 deliveries by ICD9 code V27 and confirmed a childbirth record for the
 individual. We excluded preterm deliveries (≤37 gestational weeks, ICD9
 code 644) stillbirths, and labors with more than one newborn. Nonetheless,
 12% of deliveries were at the ≤37 gestational weeks and missing the 644
 code. To mitigate ascertainment bias of the test
 results, for each test, we removed data from individuals with chronic
 disease that affected the test if the onset of the disease was up to 6
 months after the test. We also removed data from individuals who purchased
 drugs that affected the tests in the 6 months before the tests. Chronic
 diseases are defined as non-pediatric ICD9 codes with a Kaplan−Meyer
 survival drop of &gt;10% over 5 years and are assigned above a minimal
 average drop of 1/3 per y. Drugs that affect a test were defined as drugs
 with significant effect on the test (false discovery rate &lt; 0.01).
 This step allowed us to focus on a relatively healthy subset of the
 pregnant population, reducing the confounding effects associated with
 specific health conditions listed above or medication usage.
 To exclude the potential effect of follow-up pregnancies in the
 80 weeks following delivery, we excluded lab values from individuals with
 another delivery within 40 weeks following the measurement.
 For each pregnancy, we gathered all available test values
 including standard blood count, kidney and liver function tests, blood
 coagulation tests, lipid panel, inflammation markers, and hormones. We
 then discretized test values into time points relative to the time of
 birth in weekly intervals for each test. In addition to test values, we
 also extracted data on patients including age (at measurement, mean, and
 interquartile range) and BMI (the most proximal BMI measurement in medical
 records outside pregnancy, mean and interquartile range, if
 available). Privacy concerns
 Retrospective test results were aggregated and only statistical
 information was kept. Our ethical agreement with Clalit does not require
 informed consent for the publication of this aggregated data. Weekly
 intervals with a single measurement per test were removed. Mean values
 were kept for weekly intervals (per test) with 10 measurements or less and
 other values (percentiles, standard deviation) were removed, ensuring
 individual measurements cannot be interpreted from the aggregated
 data.
description: # Pregnancy and postpartum dynamics revealed by millions of lab tests
 [https://doi.org/10.5061/dryad.1c59zw44t](https://doi.org/10.5061/dryad.1c59zw44t) [![DOI](https://zenodo.org/badge/822709739.svg)](https://doi.org/10.5281/zenodo.13996864) The dataset contains summary statistics on lab tests from &gt;300K pregnancies in Israel in the period 2003-2020 who are members of "Clalit Healthcare", Israel's largest HMO. It spans 110 different tests at weekly resolution. Where BMI information was available, the measurements were grouped into three: 15-18.5, 18.5-25, and 25-30. These test results are also included in the ungrouped dataset. In addition, the dataset contains the same information for 3 common complications: Postpartum hemorrhage (PPH), gestational diabetes mellitus (GDM), and pre-eclampsia. The dataset of these pregnancies is brought at a 4-week resolution due to a lower number of measurements. See *Methods* for more details on dataset curation. # Description of the data and file structure Each individual test result was computed as a quantile score from a reference of a healthy, non-pregnant same-aged female population. We retained the participant's age and BMI information if available (before pregnancy). The queried results were binned into weekly intervals starting 60 weeks before delivery until 80 weeks postpartum.\ For the BMI-grouped dataset, the data is further binned (see above). For each such bin with properties (test_name, week [bmi_group]), summary statistics were computed including mean, standard deviation, and the (5,10,25,50,75,90, and 95) percentiles. The dataset consists of CSV files in the following structure: ``` - pregnancy.1w/ # Results at 1w resolution, no BMI groups - 17_HYDROXY_PROGESTERONE.csv # Summary statistics on 17α-OHP - ACTH_ADRENOCORTICOTROPIC_HORMONE.csv # Summary statistics on ACTH - ⋮ - pregnancy.2w/ # Results at 2w resolution, no BMI groups - ⋮ - pregnancy.1w.bmi/ # Results at 1w resolution with BMI groups - ⋮ - pregnancy.gdm.4w/ # Pregnancies with a gestational diabetes diagnosis, 4-week resolution - ⋮ - pregnancy.postpartum_hemorrhage.4w/ # Pregnancies with a postpartum hemorrhage diagnosis, 4-week resolution - ⋮ - pregnancy.pre-eclampsia.4w/ # Pregnancies with a pre-eclampsia diagnosis, 4-week resolution - ⋮ - stats.csv # Meta-statistics on each lab test, see below - complications.csv # Number of pregnancies per complication - excluded_icd9_codes.csv # ICD9 codes of all medical diagnoses excluded, "Chronic disease" as discussed in the methods. - Metadata.csv # Table of units and test names - LabNorm.csv # Reference values from a healthy, non-pregnant female population. ``` ## Lab test files Each CSV file in the directories with the "pregnancy" prefix has the following structure: | week | val\_n | val\_mean | val\_sd | val\_5 | val\_10 | val\_25 | val\_50 | val\_75 | val\_90 | val\_95 | qval\_mean | qval\_sd | qval\_5 | qval\_10 | qval\_25 | qval\_50 | qval\_75 | qval\_90 | qval\_95 | … | bmi\_n | … | | ---------- | ------ | --------- | -------- | ----------- | ----------- | ----------- | ----------- | ------- | ----------- | ----------- | ---------- | -------- | -------- | -------- | -------- | -------- | -------- | -------- | -------- | - | ------ | - | | \[-60,-56) | 4668 | 4.274635 | 0.356050 | 3.700000048 | 3.900000095 | 4.099999905 | 4.300000191 | 4.5 | 4.699999809 | 4.800000191 | 0.517748 | 0.300543 | 0.035977 | 0.081233 | 0.279392 | 0.554869 | 0.793191 | 0.924205 | 0.962102 | … | 1376 | … | *First row from `pregnancy.4w/Albumin.csv` Where: * week: Week of the test relative to delivery (=0). * val_n: Number of lab tests in the weekly interval. * val_mean: The mean of all test values in the interval. Units are industry standard and be found in `Metadata.xlsx` * val_sd: Standard deviation of the test values in the interval. * val_(5···95) - The (5···95)th percentiles of the test values in the interval, the 50th percentile being the median. * qval columns: Same as the above for the quantile score of the test results in the interval. * bmi_n: Number of test results that had a valid BMI measurement. Other columns (not shown) are age and BMI columns with the same summary statistics. ### Missing Values Some files are missing some rows where weekly intervals have a single measurement (or None). Where 110 are not identifiable at the individual level, protecting participants' privacy. The same policy applies to the BMI columns. ## Other files The file `stats.csv` provides some metadata statistics about the dataset: * `gw_X` column names are the `X`th percentile of delivery time, unit is gestational week. * Fraction of first pregnancies was calculated based on the records after 2010 only, since pregnancies before 2002 are not included and therefore we cannot know about earlier pregnancies. * Preterm pregnancies are those with delivery at or before the 37th gestational week. `Metadata.csv` maps test names to the file names, and includes other metadata such as physiological system and unit of measurement. `LabNorm.csv` is stratified to ages and lab tests, each with a reference sampled at 13 points in the distribution. The reference is a healthy (see *Methods* for the definition of healthy), same-aged, and non-pregnant female population. # Sharing/Access information Dataset and Juptyer notebooks for analysis are available on GitHub: * [![GitHub](https://img.icons8.com/ios-glyphs/30/000000/github.png)Pregnancy and postpartum dynamics revealed by millions of lab tests](https://github.com/AlonLabWIS/PregnancyMillions) * A frozen repository is available on [Zenodo](https://doi.org/10.5281/zenodo.13996864). Data was curated using the following sources: * Clalit Healthcare * [LabNorm R package](https://cran.r-project.org/package=labNorm)