Abstract
Rationale & Objective:
Preeclampsia is a pregnancy-related complication characterized by acute hypertension and end-organ dysfunction. We evaluated the long-term association between preeclampsia and the risk of developing chronic hypertension and kidney disease.
Study Design:
Observational cohort study.
Setting & Participants:
27,800 adults with deliveries in the Geisinger Health System between 1996 and 2019.
Exposure:
Preeclampsia.
Outcomes:
Hypertension, reduced estimated glomerular filtration rate (eGFR; <60 mL/min/1.73 m2), and albuminuria > 300 mg/g.
Analytical Approach:
Propensity-score matching and Cox proportional hazards models to evaluate the association between preeclampsia and incident hypertension, reduced eGFR, and albuminuria.
Results:
Of 27,800 adults with pregnancies during the study period (mean age, 28 years; 3% Black race), 2,977 (10.7%) had at least one pregnancy complicated by preeclampsia. After matching for multiple characteristics, individuals with preeclampsia had a higher risk of developing chronic hypertension (HR, 1.77; 95% CI 1.45 – 2.16), eGFR < 60 mL/min/1.73 m2 (HR, 3.23; 95% CI 1.64 – 6.36), albuminuria (HR, 3.60; 95% CI 2.38 – 5.44), and a subsequent episode of preeclampsia (HR, 24.76; 95% CI 12.47–48.36), compared to matched controls without preeclampsia. Overall, postpartum follow-up testing was low. In the first six months after delivery, 31% vs. 14% of individuals with and without preeclampsia had serum creatinine tests, respectively, and testing for urine protein was the same in both groups, with only 26% having follow-up testing.
Limitations:
Primarily White study population, observational study, reliance on ICD codes for medical diagnosis.
Conclusions:
Individuals with a pregnancy complicated by preeclampsia had a higher risk of hypertension, reduced eGFR, and albuminuria compared to individuals without preeclampsia.
Plain Language Summary
Preeclampsia is a significant contributor to perinatal and maternal morbidity and is marked by new-onset hypertension and end-organ damage, including acute kidney injury or proteinuria. To gain insight into the long-term kidney effects of the disease, we compared adults with deliveries complicated by preeclampsia to those without in the Geisinger Health System, while also assessing post-partum testing rates. Our results demonstrate that pregnant individuals with preeclampsia are at a heightened risk for future hypertension, reduced eGFR, and albuminuria, with overall low rates of post-partum testing among both individuals with and without preeclampsia. These findings underscore the need to consider preeclampsia as an important risk factor for the development of chronic kidney disease. Further studies are required to determine optimal post-preeclampsia monitoring strategies.
Introduction
Preeclampsia affects 3–5% of all pregnancies in the United States (US) and is a major cause of maternal and perinatal mortality1. Diagnosed by de-novo hypertension with concurrent new-onset organ dysfunction (as evidenced by proteinuria, acute kidney injury, impaired liver function, pulmonary edema, thrombocytopenia, visual disturbances, right upper quadrant abdominal pain or neurological symptoms) after 20 weeks gestation, preeclampsia by definition is a systemic disease2.
The broader entity of hypertension in pregnancy - which encompasses preeclampsia as well as gestational hypertension- is a risk factor for hypertension, cardiac disease, and cerebrovascular events later in life, with a dose-dependent effect with greater severity and earlier onset of hypertension3–5. However, less is understood about the long-term prognosis of preeclampsia with regard to kidney function. In the acute phase, preeclampsia affects the kidney with podocyte loss and glomerular endotheliosis, and a study has also linked preeclampsia to the development of end-stage kidney disease6,7. Optimal kidney-related follow-up practices for individuals with preeclampsia have not been set forth in the American College of Obstetricians and Gynecologists (ACOG) practice bulletin 2. Quantifying the associations with adverse kidney outcomes is therefore important to identify early risk factors for kidney disease and the future development of strategies for risk reduction.
The goal of this study was to assess the risk of hypertension and kidney disease following a preeclampsia event and to assess the frequency of monitoring vascular and kidney health in the post-preeclampsia period. Using medical records from a large tertiary health system, we evaluated the long-term risk of developing hypertension, reduced estimated glomerular filtration rate (eGFR), or severe albuminuria after an episode of preeclampsia, comparing risk to that observed in individuals with a pregnancy that was not complicated by preeclampsia. We also evaluated the risk of future preeclampsia in individuals with a pregnancy complicated by preeclampsia and assessed postpartum testing rates.
Methods
Study Population
The study population was drawn from the Geisinger Health System, a large tertiary healthcare system serving 45 counties in central and northeastern Pennsylvania. We utilized the Geisinger electronic health record (EHR) data which contains information on all inpatient and outpatient encounters, prescriptions, vitals, laboratory measurements, and billing codes. Geisinger provides care for a remarkably stable population (with the exception of two counties, the estimated out-migration rate is <1% per year)8. Adults aged 18 to 45 years with an obstetric delivery in Geisinger during 1996–2019 were included. Deliveries were identified based on evidence for a vaginal delivery or cesarean delivery using (1) International Classification of Diseases (ICD) Ninth and Tenth Revision diagnosis codes (ICD9: 644.2, 649.81, 649.82, 650, 669.71; ICD10: O60.1, O60.2 O75.82, O80, O82, Z37) or (2) Current Procedural Terminology codes (59400, 59409, 59510, 59610, 59618). Individuals who had a history of cardiovascular disease, diabetes mellitus, albuminuria, eGFR < 60 ml/min/1.73 m2, or hypertension at any point prior to 20 weeks of gestation were excluded (Figure S1). Pre-existing hypertension was defined based on ICD-9 and ICD-10 billing codes (ICD9: 401, 402, 403, 404, 405; ICD10: I10, I11, I12, I13, I15) for hypertension or use of antihypertensive medications as per previously validated algorithm9. Albuminuria was defined as urine albumin-to-creatinine ratio (UACR) >300 mg/g, the equivalent urine protein-to-creatinine ratio based (UPCR) on prior conversion equations10, or a urine dipstick >2+. The study was reviewed and approved by the Johns Hopkins University Bloomberg School of Public Health and Geisinger Medical Center Institutional Review Boards. Individual-level informed consent was not obtained for this secondary analysis of an established database with privacy protection.
Exposure
The primary exposure of interest was preeclampsia, including preeclampsia with severe features and eclampsia, and identified by (1) inpatient record with an ICD 9 or 10 diagnosis codes for preeclampsia (ICD9: 642.4, 642.5, 642.6; ICD10: O14, O15) or (2) outpatient laboratory results significant for albuminuria after 20 weeks of gestation, but before delivery. Prior research has confirmed the validity of ICD-based diagnosis of preeclampsia and demonstrated high positive predictive value, negative predictive value, and specificity11. Albuminuria was defined as UACR >300 mg/g, the equivalent UPCR based on prior conversion equations10, or a urine dipstick >2+.
Outcomes
We examined three outcomes in the postpartum period. The first was the development of chronic hypertension, identified by ICD-9 and ICD-10 billing codes or the start of antihypertensive medication as per a previously validated algorithm9. The second was eGFR <60 ml/min/1.73 m2 as estimated using outpatient serum creatinine and the CKD-EPI 2021 equation12. The third was the presence of albuminuria, defined as outpatient UACR >300 mg/g or urine dipstick >2+. UPCR was also included using >660mg/g as the equivalent value based on prior conversion equations10. Both eGFR and albuminuria outcomes were confirmed based on a second measure within 2 years. We additionally examined a secondary outcome of the development of a subsequent episode of preeclampsia.
Covariates
Collected covariates included age at delivery, race (as recorded in the EHR and coded as Black, White, or other), the number of prior deliveries, year of delivery, body mass index (BMI; kg/m2), prenatal systolic blood pressure (SBP; mmHg), prenatal diastolic blood pressure (DBP; mmHg), prenatal eGFR (ml/min/1.73m2, estimated using the CKD-EPI 2021 equation12) and smoking status at delivery (i.e., current smoker, ever smoker or never smoker). Prenatal blood pressure variables, BMI, and eGFR were captured between 40 and 20 weeks before delivery.
Statistical Analysis
Study participants were described according to preeclampsia status using mean ± standard deviation (SD), frequency by number (percentage), or median (interquartile range) as applicable. Five variables were missing in more than 20% of the population (Table S1), with prenatal eGFR (80%) and smoking status (82%) being the most commonly missed. For smoking, a missing value was imputed as a never-smoker given the plausibility that most women are unlikely to smoke during pregnancy. Additionally, rates of smoking were extremely high among those with non-missing smoking status, suggesting that this variable is noted only when there is an affirmative response. Multiple imputations by chained equations were performed to account for missingness in the rest of the variables, imputing 10 datasets. Within each imputed dataset, we constructed a propensity-matched cohort. Pregnant individuals with a first episode of preeclampsia were matched with individuals with a delivery uncomplicated by preeclampsia (and without previous history of preeclampsia) based on age, race, the number of prior deliveries, year of delivery, smoking status at the time of delivery, prenatal measures of eGFR, BMI, systolic and diastolic blood pressures. The cases were matched one-to-one with controls with the closest propensity score (nearest neighbor matching) without replacement. Pregnant individuals with a preeclampsia episode could serve as controls until their first preeclampsia event. Balance in the covariates was assessed by comparing the standardized mean differences before and after matching, with a threshold of 0.1 indicating a successful balance of covariates. For baseline characteristics and characterization of incidence rates, we selected for display the matched cohort with the median sample size.
To assess the risk of the study outcomes associated with preeclampsia, Cox proportional hazards regression was performed in each propensity score-matched cohort to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs). Hazard ratios estimated in each imputed dataset were pooled using Rubin’s rules after logarithmic transformation. The time at which risk began (t0) was designated to be 12 weeks postpartum for both cases and controls. Follow-up for outcomes continued until the time of the last encounter within the Geisinger system. The risk of subsequent preeclampsia (the second episode for individuals with preeclampsia, the first episode for matched controls) was determined using Cox proportional hazard models. Only individuals who had at least one subsequent pregnancy were included in this analysis.
Follow up rates of blood pressure, serum creatinine, and albuminuria (UACR, UPCR, or dipstick) testing were assessed in cases and controls at varying postpartum periods until time of the last encounter in the Geisinger Health System. Individuals with a subsequent pregnancy were censored 9 months before next delivery in this analysis so as not to inadvertently include prenatal monitoring. Additional sensitivity analyses included restricting the preeclampsia exposure to those diagnosed by ICD code only and, to prevent the possibility of including gestational disease, by censoring participants at next delivery, and separately by excluding measures obtained during subsequent pregnancies. A two-sided p-value <0.05 was considered statistically significant. All statistical analyses were performed using STATA software (version 17; Stata Corporation, College Station, TX).
Results
Participant Characteristics
Of the 27,800 adults with a delivery between 1996 and 2019 who met the inclusion criteria (Figure S1), 2,977 (10.7%) had a pregnancy complicated by preeclampsia. The overall average age at delivery was 28 years, 3% of the study population was identified as Black, and the average previous deliveries was 0.2 (Table S1). Before matching, individuals with preeclampsia had a higher prenatal BMI (31.5 vs. 28.6 kg/m2), SBP (116 vs. 110 mmHg), and DBP (69 vs. 65 mmHg) when compared to individuals without preeclampsia (Table S1). Prenatal eGFR was similar among both groups with an average eGFR of 125 ml/min/1.73 m2. During an overall follow up of 21 years, 1588 (5.7%) patients had incident hypertension, 189 (0.7%) had eGFR < 60 ml/min/1.73 m2, and 456 (1.6%) had proteinuria (Table S2). After propensity score matching, all covariates were well balanced between the cases and controls in each of the ten imputed datasets (Table 1; Figure 1). The number of cases and controls varied from 4552 to 4582.
Table 1.
Maternal Characteristics of Individuals With And Without Preeclampsia After Propensity Score Matching.
| Variable | No Preeclampsia (N = 2276) | Preeclampsia (N = 2276) |
|---|---|---|
| Age at Delivery (years) | 28 ± 6 | 28 ± 6 |
| Black | 74 (3%) | 72 (3%) |
| Previous Deliveries | 0.2 ± 0.5 | 0.2 ± 0.5 |
| Year of Delivery | 2009 [2005 – 2015] | 2010 [2005 – 2014] |
| Prenatal BMI (kg/m2) | 32 ± 8 | 32 ± 8 |
| Prenatal SBP (mmHg) | 116 ± 12 | 116 ± 13 |
| Prenatal DBP (mmHg) | 69 ± 9 | 69 ± 9 |
| Prenatal eGFR (mL/min/1.73m2) | 125 ± 10 | 124 ± 11 |
| Smoking Status | ||
| Current Smoker | 402 (18%) | 403 (18%) |
| Former Smoker | 578 (25%) | 617 (27%) |
| Never Smoker | 1296 (57%) | 1256 (55%) |
Characteristics are presented as mean ± standard deviation, median [interquartile range], or number (%).
BMI=body mass index; eGFR=estimated glomerular filtration rate; SBP=systolic blood pressure; DBP=diastolic blood pressure. The cohort shown was the median in terms of the sample size of the 10 multiply imputed and then propensity-matched cohorts.
Figure 1. Covariate Balance Before And After Propensity Matching.
SBP=systolic blood pressure; DBP=diastolic blood pressure. BMI=body mass index; eGFR=estimated glomerular filtration rate.
Risk of Adverse Outcomes
In the propensity-matched analysis, individuals who experienced preeclampsia in their pregnancy had higher incidence of hypertension (15.3 vs. 8.6 per 1,000-person-years) eGFR <60 ml/min/m2 (1.9 vs. 0.7 per 1,000 person-years), and albuminuria (5.3 vs. 1.6 per 1,000 person-years) in individuals with preeclampsia (Table 2). Findings were similar in the unmatched cohort (Table S2). Higher risks of future hypertension (HR 1.77, 95% CI: 1.45 – 2.16), eGFR <60 mL/min/1.73 m2 (HR 3.23, 95% CI: 1.64 – 6.36), and albuminuria (HR 3.60, 95% CI: 2.38 – 5.44 ) were observed in individuals with preeclampsia compared to controls (Table 3, Figure 2). A sensitivity analysis evaluating the association of preeclampsia defined by ICD code only showed similar results, with a higher risk of hypertension (HR 1.88, 95% CI: 1.52 – 2.32, eGFR < 60 mL/min/1.73 m2 (HR 3.16, 95% CI: 1.51 – 6.60), and albuminuria (HR 2.74, 95% CI: 1.74 – 4.33) (Table S3). The associations remained consistent, with higher risks of hypertension, eGFR < 60 mL/min/1.73 m2, and albuminuria when participants were censored at the last measure within the Geisinger cohort, at the next delivery, and when subsequent pregnancy measures were omitted (Table S3).
Table 2.
Incident Outcomes By Preeclampsia Exposure In The Matched Cohort.
| No Preeclampsia (N = 2276) |
Preeclampsia (N = 2276) |
|
|---|---|---|
| Incident Hypertension | ||
| N events | 157 (6.9%) | 252 (11.1%) |
| Follow-Up Time, mean (SD), years | 8.0 (6.1) | 7.2 (5.6) |
| Incidence Rate | 8.6 (7.3 – 10.0) | 15.3 (13.6 − 17.4) |
| Incident eGFR <60 ml/min/1.73 m2 | ||
| N events | 13 (0.6%) | 35 (1.5%) |
| Follow-Up Time, mean (SD), years | 8.4 (6.2) | 8.1 (5.7) |
| Incidence Rate | 0.7 (0.4 – 1.2) | 1.9 (1.4 − 2.6) |
| Incident Albuminuria | ||
| N events | 31 (1.4%) | 96 (4.2%) |
| Follow-Up Time, mean (SD), years | 8.4 (6.2) | 7.9 (5.7) |
| Incidence Rate | 1.6 (1.1 – 2.3) | 5.3 (4.4 − 6.5) |
The Incidence Rate is displayed per 1000 person-years. Ranges in parenthesis refer to 95% confidence intervals.
Table 3.
Hazard Ratios (95% Confidence Intervals) For Adverse Outcomes For Preeclampsia Cases In Matched Cohort.
| Outcome | Hazard Ratio (95% CI) | p-value |
|---|---|---|
| Incident Hypertension | 1.77 (1.45 – 2.16) | < 0.001 |
| Incident eGFR< 60ml/min/1.73m 2 | 3.23 (1.64 – 6.36) | < 0.001 |
| Incident Albuminuria | 3.60 (2.38 – 5.44) | < 0.001 |
| Preeclampsia in Subsequent Pregnancy* | 24.56 (12.47–48.36) | < 0.001 |
This analysis was limited to only those individuals with a subsequent pregnancy.
Figure 2.
Cumulative Incidence of (A) Hypertension, (B) eGFR < 60 mL/min/m2, (C) Albuminuria in the Matched Cohorts.
Risk of Subsequent Preeclampsia
Adults who had a previous episode of preeclampsia were found to have a higher risk of a subsequent episode of preeclampsia (HR 24.56, 95% CI: 12.47–48.36) (Table 3).
Postpartum Testing and Monitoring
Assessment of postpartum testing in the propensity matched cohort produced showed marginally higher annual rates of testing of systolic blood pressure (2.96 vs. 2.72 measurement per person-year, p<0.001), serum creatinine (0.50 vs. 0.38 measurement per person-year, p<0.001), and albuminuria (0.29 vs. 0.24 measurement per person-year, p<0.001) in individuals with preeclampsia compared to individuals without preeclampsia (Table 4). Findings were similar in the unmatched cohort (Table S4). In the first six months after delivery, 31% vs. 14% had serum creatinine tests among individuals with and without preeclampsia, respectively and 26% in both groups had follow-up urine protein tests.
Table 4.
Testing of Systolic Blood Pressure, Serum Creatinine, And Urine Protein In Individuals With And Without Preeclampsia Across Varying Postpartum Periods In The Matched Cohort*
| Incidence Rate Measurement per person-year |
||
|---|---|---|
| Postpartum Period | No Preeclampsia (N = 2276) |
Preeclampsia (N = 2276) |
| Systolic Blood Pressure (mmHg) | ||
| Overall | 2.72 (2.69 – 2.75) | 2.96 (2.93 – 2.99) |
| < 6 months | 4.54 (4.42 – 4.67) | 5.28 (5.15 – 5.42) |
| 6–12 months | 2.19 (2.11 – 2.28) | 2.57 (2.47 – 2.67) |
| > 12 months | 2.60 (2.57 – 2.63) | 2.78 (2.75 – 2.81) |
| Serum Creatinine (mg/dL) | ||
| Overall | 0.38 (0.37 – 0.39) | 0.50 (0.48 – 0.51) |
| < 6 months | 0.28 (0.25 – 0.31) | 0.64 (0.59 – 0.69) |
| 6–12 months | 0.26 (0.23 – 0.30) | 0.33 (0.30 – 0.37) |
| > 12 months | 0.40 (0.39 – 0.41) | 0.50 (0.48 – 0.51) |
| Urine protein (UACR, UPCR, or Dipstick) | ||
| Overall | 0.24 (0.23 – 0.25) | 0.29 (0.28 – 0.30) |
| < 6 months | 0.53 (0.49 – 0.57) | 0.53 (0.49 – 0.57) |
| 6–12 months | 0.20 (0.18 – 0.23) | 0.26 (0.23 – 0.29) |
| > 12 months | 0.22 (0.21 – 0.23) | 0.27 (0.26 – 0.28) |
Ranges in parenthesis refer to 95% confidence intervals. UACR, Urine albumin-creatinine ratio; UPCR, Urine protein-creatinine ratio;
84 individuals with and without preeclampsia did not have any encounters within the Geisinger System after Index Date
Discussion
In this study of individuals with deliveries complicated by preeclampsia in the Geisinger Health system, we examined the association of preeclampsia in pregnancy on the future risk of vascular and kidney function, specifically by assessing hypertension, reduced eGFR, and albuminuria. We observed that individuals with a pregnancy complicated by preeclampsia were at a higher risk of long-term hypertension, reduced eGFR, and albuminuria than those with normotensive pregnancies. Individuals with a prior history of preeclampsia also had a significantly higher risk of a future pregnancy complicated by preeclampsia. Postpartum screening for hypertension and kidney disease was low overall, and without large differences observed between the cases and controls. Taken together, our findings suggest that individuals who develop preeclampsia during pregnancy constitute a high-risk population for kidney disease and merit closer monitoring for early prevention of long-term consequences.
Literature on the association of adverse pregnancy outcomes with the development of kidney disease has focused mainly on hypertensive disorders of pregnancy, and few studies have evaluated associations in the United States (US) population. Studies on the repercussions of preeclampsia for subsequent reduced eGFR or high albuminuria have provided disparate results. In a meta-analysis of seven studies (located in Israel, Jordan, Finland, Sweden) with 273 individuals with preeclampsia and 333 individuals without preeclampsia, a history of preeclampsia was associated with a four-fold increased risk of microalbuminuria but not associated with reduced eGFR at an average follow up of 7 years postpartum13. A larger meta-analysis involving 110,803 cases with and 2,680,929 controls (predominantly in the Scandinavian countries, and to lesser extent in Netherlands, Israel, and Australia) without preeclampsia did not find a significant association between preeclampsia and chronic kidney disease (CKD) or albuminuria over a follow-up period of 5–20 years14. A more recent systematic review included one study performed in the US and demonstrated an association between preeclampsia and CKD (defined using eGFR, albuminuria, or hospital records), but did not specifically report on albuminuria15. Our study adds to the expanding evidence by demonstrating the significant association of preeclampsia with future risk of both albuminuria and reduced eGFR in otherwise healthy adults of reproductive age in the US. The variability in the findings across studies may be explained by the heterogeneity in preeclampsia diagnosis, differences in the length of follow-up for outcomes, or baseline characteristics of the study population.
Guidelines acknowledge the increased cardiovascular risk after hypertensive pregnancy disorders, but specific recommendations on screening, interval follow-up, and prevention after a preeclamptic pregnancy are inconsistent and not clearly established. ACOG suggests following individuals with any hypertensive disorder of pregnancy with a blood pressure check 7–10 days postpartum with additional follow-up at the traditional 4–6-week postpartum visit and subsequent visits if necessary but does not mention kidney assessment16. The American Heart Association recognizes preeclampsia as a substantial cardiovascular risk factor and emphasizes the need for appropriate postpartum screening and control of risk factors, but without specific recommendations for action17. In contrast, the National Institute for Health and Care Excellence (NICE) in the United Kingdom (UK) advises follow up urine protein measurement 6–8 weeks after delivery in individuals with preeclampsia and suggests further review with primary care or specialist at 3 months after birth to assess kidney function in those with persistent proteinuria18.
Follow-up rates after hypertensive pregnancies remain limited in the US with prior studies demonstrating rates ranging from 20–60%19–21. Even when visits do occur, testing among high-risk patients is limited. A 2004 UK study of 257 individuals with preeclampsia and a 6-week postpartum visit reported that 6% did not have blood pressure measured and 68% did not have albuminuria testing22. Our results also demonstrate low overall follow-up testing in individuals with preeclampsia in the postpartum period, especially after 6 months. This is perhaps not surprising given albuminuria screening for conditions known to be at risk for CKD (i.e. hypertension and diabetes) is also suboptimal23. Greater screening and follow-up after a preeclampsia episode may uncover additional incident cases of albuminuria, eGFR <60 ml/min/1.73m2, and hypertension with opportunities for treatment.
In contrast to preeclampsia, ACOG has explicit screening protocols for gestational diabetes for the prevention of adverse long-term outcomes. ACOG recommends screening with glucose tolerance test, HbA1c, or fasting plasma glucose at 4–12 weeks postpartum, a referral to preventive or medical therapy for those with an abnormal test, and repeat testing every 1–3 years for those with a normal test24. Although the absolute risk of adverse outcomes after preeclampsia is not as high as that in gestational diabetes, where nearly 20% of patients develop diabetes by 9 years25, the present study suggests a strong association between preeclampsia and future hypertension and kidney disease. Our estimates of incident albuminuria and CKD are likely underestimates given the low rate of follow-up eGFR and ACR monitoring. The effectiveness of close monitoring of individuals with preeclampsia, as with gestational diabetes, in detecting early, asymptomatic disease deserves further evaluation.
Studies on trends in hypertensive pregnancy disorders indicate that preeclampsia cases are rising. Possible contributing factors include more advanced maternal age, the rising prevalence of obesity, and expanded use of assistive reproductive technologies 26–28. In contrast, outcomes after hypertensive disorders of pregnancy are improving, likely due to advances in medical intervention and increased attention to maternal health29. In line with these trends, identifying and counseling individuals at high risk for persistent hypertension or recurrence of preeclampsia is extremely important. Qualitative studies have demonstrated that few individuals with preeclampsia understand their future risk of cardiovascular disease,30,31 and studies assessing knowledge of the link between preeclampsia and kidney disease are lacking. The postnatal period therefore offers a unique opportunity for healthcare providers to educate individuals about their risk for future kidney disease or hypertension, alter modifiable risk factors, and improve follow-up rates.
Our study has certain limitations that are important to acknowledge. Diagnoses relied on ICD codes, which leaves the potential for misclassification although we used laboratory values for CKD outcomes which is a strength. We defined hypertension in our study based on the presence of an ICD diagnosis or the use of antihypertensive medication rather than actual ambulatory blood pressure readings. A large proportion of our study population was White, and they received care from a single health system, limiting the generalizability of our results. Data were missing for several covariates, although this was expected given that pregnant individuals are by and large young and healthy. In addition, individuals who underwent laboratory testing may have been tested due to clinician concern or other non-random factors, rather than routine screening. It may also be possible that some patients have received care outside of the Geisinger system, and data from these visits may not be captured in our study. However, we only included patients receiving primary care at Geisinger. We also used rigorous statistical methods such as multiple imputations and propensity score matching to minimize the effects of potential selection bias introduced by missing data and confounding by indication, respectively. As with all observational studies, residual confounding is a possibility, and causality cannot be inferred. Despite these limitations, our study contributes to the published data by further expanding the literature on the adverse effects of preeclampsia on chronic kidney disease. Major strengths of our study include our focus pregnant individuals without major risk factors, adjustment of potential confounders such as race, obesity, smoking, diabetes that were unexplored in several prior studies, and a lengthy observation period.
In conclusion, individuals with a pregnancy complicated by preeclampsia are at substantially increased risk of future hypertension, reduced eGFR, and albuminuria as well as substantially higher risk for a subsequent episode of preeclampsia. Postpartum screening for hypertension and CKD in this high-risk population remains low. This study highlights the importance of obtaining a thorough obstetric history for risk assessment, identifying preeclampsia as an independent risk factor for future hypertension and CKD, and emphasizes the need for appropriate postpartum monitoring and control of modifiable risk factors.
Supplementary Material
Figure S1. Derivation of study cohort.
Table S1. Maternal characteristics of individuals with and without preeclampsia before propensity score matching.
Table S2. Incident outcomes overall and by preeclampsia exposure in the unmatched cohort.
Table S3. Hazard ratios (95% Confidence Interval) for adverse outcomes: preeclampsia cases defined by diagnosis code; censoring at last measure; censoring at next delivery; excluding subsequent pregnancy measures.
Table S4. Testing of systolic blood pressure, serum creatinine, and urine protein in individuals with and without preeclampsia across varying postpartum periods in the unmatched cohort
Support:
Dr. Srialluri is supported by NIH/NIDDK under award number T32DK007732–27. Dr. Grams is supported by K24HL1555861 and R01DK115534. The funders had no role in the study design, data analysis, interpretation, writing, or decision to submit for publication.
Footnotes
Financial Disclosure: The authors declare that they have no relevant financial interests.
Peer Review: Received November 14, 2022. Evaluated by 2 external peer reviewers, with direct editorial input from a Statistics/Methods Editor, an Associate Editor, and a Deputy Editor who served as Acting Editor-in-Chief. Accepted in revised form April 22, 2023. The involvement of an Acting Editor-in-Chief was to comply with AJKD’s procedures for potential conflicts of interest for editors, described in the Information for Authors & Journal Policies.
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Figure S1. Derivation of study cohort.
Table S1. Maternal characteristics of individuals with and without preeclampsia before propensity score matching.
Table S2. Incident outcomes overall and by preeclampsia exposure in the unmatched cohort.
Table S3. Hazard ratios (95% Confidence Interval) for adverse outcomes: preeclampsia cases defined by diagnosis code; censoring at last measure; censoring at next delivery; excluding subsequent pregnancy measures.
Table S4. Testing of systolic blood pressure, serum creatinine, and urine protein in individuals with and without preeclampsia across varying postpartum periods in the unmatched cohort