Background: Preeclampsia has been suggested to increase the risk of end-stage kidney disease (ESKD); however, most studies were unable to adjust for potential confounders including pre-existing comorbidities such as renal disease and cardiovascular disease (CVD). We aimed to examine the association between preeclampsia and the risk of ESKD in healthy women, while taking into account pre-existing comorbidity and potential confounders. Methods and findings: Using data from the Swedish Medical Birth Register (MBR), women who had singleton live births in Sweden between 1982 and 2012, including those who had preeclampsia, were identified. Women with a diagnosis of chronic kidney disease (CKD), CVD, hypertension, or diabetes prior to the first pregnancy were excluded. The outcome was a diagnosis of ESKD, identified from the Swedish Renal Registry (SRR) from January 1, 1991, onwards along with the specified cause of renal disease. We conducted Cox proportional hazards regression analysis to examine the association between preeclampsia and ESKD adjusting for several potential confounders: maternal age, body mass index (BMI), education, native country, and smoking. This analysis accounts for differential follow-up among women because women had different lengths of follow-up time. We performed subgroup analyses according to preterm preeclampsia, small for gestational age (SGA), and women who had 2 pregnancies with preeclampsia in both. The cohort consisted of 1,366,441 healthy women who had 2,665,320 singleton live births in Sweden between 1982 and 2012. At the first pregnancy, women's mean (SD) age and BMI were 27.8 (5.13) and 23.4 (4.03), respectively, 15.2% were smokers, and 80.7% were native Swedish. The overall median (interquartile range [IQR]) follow-up was 7.4 years (3.2–17.4) and 16.4 years (10.3–22.0) among women with ESKD diagnosis. During the study period, 67,273 (4.9%) women having 74,648 (2.8% of all pregnancies) singleton live births had preeclampsia, and 410 women developed ESKD with an incidence rate of 1.85 per 100,000 person-years. There was an association between preeclampsia and ESKD in the unadjusted analysis (hazard ratio [HR] = 4.99, 95% confidence interval [CI] 3.93–6.33; p < 0.001), which remained in the extensively adjusted (HR = 4.96, 95% CI 3.89–6.32, p < 0.001) models. Women who had preterm preeclampsia (adjusted HR = 9.19; 95% CI 5.16–15.61, p < 0.001) and women who had preeclampsia in 2 pregnancies (adjusted HR = 7.13, 95% CI 3.12–16.31, p < 0.001) had the highest risk of ESKD compared with women with no preeclampsia. Considering this was an observational cohort study, and although we accounted for several potential confounders, residual confounding cannot be ruled out. Conclusions: The present findings suggest that women with preeclampsia and no major comorbidities before their first pregnancy are at a 5-fold increased risk of ESKD compared with parous women with no preeclampsia; however, the absolute risk of ESKD among women with preeclampsia remains small. Preeclampsia should be considered as an important risk factor for subsequent ESKD. Whether screening and/or preventive strategies will reduce the risk of ESKD in women with adverse pregnancy outcomes is worthy of further investigation.
Ali S Khashan and colleagues reveal an increased risk for kidney disease in women who had pre-eclampsia during pregnancy.
Author summary: Why was this study done?: A large number of studies reported an increased risk of cardiovascular disease (CVD) among women who had preeclampsia compared with women who had no preeclampsia. Only few studies reported such as association between preeclampsia and the risk of developing end-stage kidney disease (ESKD). Some of these studies did not adjust for key potential confounders and may have lacked high-quality data. What did the researchers do and find?: We performed this study to examine the association between preeclampsia and ESKD using a large cohort from the Swedish national registers (N = 1,366,441 healthy women who had 2,665,320 singleton live births). We found that women who had preeclampsia in at least one pregnancy, were 5 times more likely to have ESKD compared with parous women who had never had preeclampsia (hazard ratio [HR] = 4.96, 95% confidence interval [CI] 3.89–6.32). This association was independent of several sociodemographic factors such as maternal age and education and prepregnancy comorbidity such as renal disease and CVD. What do these findings mean?: These results highlight the importance of preeclampsia as a risk marker for developing ESKD. These findings need to be investigated further to see whether preventive strategies would reduce the risk of ESKD.
The prevalence of chronic kidney disease (CKD) is estimated at 10% to 12% of the global population [[
Preeclampsia—defined as hypertension and the coexistence of one or more of the following new-onset conditions: proteinuria, maternal organ dysfunction (including renal insufficiency), or evidence of uteroplacental dysfunction indicated by fetal growth restriction [[
Whether the association between preeclampsia and the risk of ESKD is confounded by prepregnancy CKD, diabetes, and CVD is unknown[[
Using data from the Swedish Medical Birth Register (MBR), which contains data on >99% of all births in Sweden, we identified all women who had singleton live births between January 1, 1982, and December 31, 2012. Data from the Swedish National Patient Register (NPR), the Swedish Multi-Generation Register [[
We identified and excluded women with prior CKD, CVD, hypertension, or diabetes through a linkage with the NPR using the international classification of diseases (ICD) codes (S1 Table). Preexisting diabetes and hypertension were readily available in the MBR. This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 STROBE Checklist).
Preeclampsia is recorded at the time of discharge from the hospital, using ICD-8, ICD-9, and ICD-10 (8th, 9th, and 10th revisions). Preeclampsia is defined in Sweden as a diastolic blood pressure of >90 mmHg accompanied by proteinuria (≥0.3 g/day or ≥1 on a urine dipstick). Eclampsia is defined as the occurrence of preeclampsia with seizures (S1 Table). The preeclampsia records in the MBR have previously been found to accurately reflect medical records [[
Women who had no preeclampsia contributed follow-up time to the unexposed category from the day after the first delivery until first ESKD diagnosis, death, migration, or October 31, 2013—whichever came first. Women who had preeclampsia in the first pregnancy contributed follow-up time to the exposed category from the day after the first delivery until first ESKD diagnosis, death, migration, or October 31, 2013—whichever came first. Women who had no preeclampsia in the first pregnancy but had preeclampsia in subsequent pregnancies contributed follow-up time to the unexposed category from the first day after the first delivery until they had preeclampsia and contributed follow-up time to the exposed category from the first day after the delivery with preeclampsia until first ESKD diagnosis, death, migration, or October 31, 2013—whichever came first.
The outcome measure was ESKD. We used data from the SRR to identify women who initiated dialysis or kidney transplantation during follow-up. In addition, we used data from the Swedish Cause of Death Registry to identify women with renal disease cause of death. We used data from the SRR on all persons in Sweden who were diagnosed with ESKD from January 1, 1991, until October 31, 2013.
We had data on maternal age, number of births, body mass index (BMI), highest education level, native country, and smoking. Gestational age and small for gestational age (SGA) could have potential confounding or mediating effect on the association between preeclampsia and ESKD; therefore, they were analysed separately in stratified analyses. SGA was defined as a birth weight of 2 SDs below the mean of the sex-specific and gestational age distributions [[
Maternal and birth characteristics are presented according to preeclampsia status using frequency and percentages. According to a prespecified analysis plan, we used Cox proportional hazards regression to estimate the hazard ratio (HR) and 95% CIs. A Cox analysis allows the underlying risk to vary over time. It also accounts for differential follow-up time during the study period, which is very important because women had different lengths of follow-up time during the study period. The main exposure variable was any preeclampsia diagnosis in any pregnancy between 1982 and 2012 represented in the analysis as a time-dependent variable. This means that a woman with preeclampsia was considered exposed to preeclampsia from the date of delivery that was affected by preeclampsia until the end of follow-up. Considering that women who gave birth between 1982 and 1990 did not have records of ESKD until 1991 onwards, their entry was delayed until January 1991; i.e., they were not included in the analysis until registration of ESKD started in January 1991. We performed partially adjusted analyses adjusting for year of delivery. Fully adjusted models included maternal age, BMI, smoking, number of births, native country, and education. The above variables were included in the models as categorical variables, as presented in Table 1. Maternal age, BMI, smoking, and number of births were included in the models as time-dependent variables because they may potentially change across pregnancies, whereas highest education level and native country were time-fixed variables. The results of the association between each sociodemographic variable and the risk of ESKD from the main model are presented in S1 Text. The following subgroup and sensitivity analyses were prespecified.
Graph
Table 1 Maternal characteristics and pregnancy outcomes among healthy women at the first delivery.
Characteristic No preeclampsia, Preeclampsia, Age (years) <20 60,482 (4.7) 3,272 (4.7) 20–29 816,752 (63.2) 41,756 (63.5) 30–39 395,997 (30.6) 19,546 (29.6) ≥40 19,561 (1.5) 1,177 (1.8) BMI in early pregnancy (kg/m2) Underweight: <18.5 45,287 (3.5) 1,451 (2.2) Normal: 18.5–24.9 694,802 (53.7) 29,152 (44.3) Overweight: 25–29.9 183,448 (14.2) 12,801 (19.5) Obese: ≥30 63,195 (4.9) 7,236 (11.0) Missing 306,060 (23.7) 15,111 (23.0) Native country Sweden 1,038,664 (80.3) 56,742 (86.3) Other Scandinavian 39,179 (3.0) 1,932 (2.9) Non-Scandinavian 214,949 (16.6) 7,077 (10.8) Education level Pre–high school 121,962 (9.4) 5,796 (8.8) High school 568,755 (44.0) 31,624 (48.1) University level 586,564 (45.4) 27,855 (42.4) Missing 15,511 (1.2) 476 (0.7) Maternal smoking Nonsmoker 1,001,890 (77.5) 53,512 (81.4) 0–9 cigarettes per day 135,540 (10.5) 5,367 (8.2) ≥10 cigarettes per day 62,462 (4.8) 2,363 (3.6) Missing 92,900 (7.2) 4,509 (6.9) Gestational diabetes No 1,287,825 (99.6) 65,146 (99.1) Yes 4,967 (0.4) 605 (0.9) Preterm birth Term (≥37 weeks) 1,219,161 (94.3) 53,104 (80.8) Preterm (34–36 weeks) 53,566 (4.1) 7,535 (11.5) Very preterm (<34 weeks) 17,613 (1.4) 4,956 (7.5) Missing 2,452 (0.2) 156 (0.2) SGA No 1,244,054 (96.2) 57,224 (87.0) Yes 39,864 (3.1) 7,788 (11.8) Missing 8,874 (0.7) 739 (1.1) Year of first birth 1982–1989 326,185 (25.2) 16,881 (25.7) 1990–1999 409,967 (31.7) 22,236 (33.8) 2000–2012 556,640 (43.1) 26,634 (40.5)
1 A healthy woman was defined as a woman who had no recorded kidney disease, CVD, diabetes, or hypertension before the first pregnancy.
2 Abbreviations: BMI, body mass index; CVD, cardiovascular disease; SGA, small for gestational age
We analysed data separately for those women who had only 1 pregnancy and those who had 2 pregnancies only. We categorised women as follows: (
To examine the potential effect of SGA on the association between preeclampsia and ESKD, we created a 3-category variable: (
Further analyses were performed by including statistical interaction terms between the preeclampsia variable and (
The population attributable risk (PAR) of ESKD is an estimate of the fraction of the total number of cases of ESKD in the population that can be attributed to a particular exposure. The estimation was carried out as described by Last [[
Graph
where p is the proportion of the total population exposed to preeclampsia. The adjusted HR of ESKD in relation to exposure to preeclampsia was used.
Post hoc analyses were performed to (
The statistical analysis was performed in Stata version 13.1 (StataCorp, College Station, TX). All tests were two-sided with 5% significance level.
The study cohort consisted of 1,366,441 women (2,665,320 singleton live births) with no CKD, CVD, hypertension, or diabetes before the first pregnancy. During the study period, 4.9% of women (67,273/1,366,441) had at least 1 preeclampsia diagnosis (Fig 1). ESKD was diagnosed in 410 women.
Graph: CKD, chronic kidney disease; CVD, cardiovascular disease.
The overall median (interquartile range [IQR]) follow-up was 7.4 years (3.2–17.4) and 16.4 years (10.3–22.0) among women with ESKD diagnosis, i.e., the longer the follow-up, the more likely a woman was to develop ESKD. Women who had preeclampsia were older on average and had higher BMI. Among women with no preeclampsia in the first pregnancy, 14.2% were overweight, and 4.9% were obese compared with 20.1% and 11.8% overweight and obese, respectively, among women with preeclampsia. Women who had preeclampsia were more likely to be native Swedish (80.3% versus 86.3%) and nonsmokers (77.5% versus 81.4%). Details are summarised in Table 1.
The incidence rate of ESKD per 100,000 person-years was 1.85 (95% CI 1.66–2.05) among women with no preeclampsia and 12.35 (95% CI 9.61–15.88) among women who had preeclampsia. There was an association between preeclampsia and the risk of end-stage renal disease (ESRD) in the crude analysis (HR = 4.99, 95% CI 3.93–6.33, p < 0.001), which remained largely unchanged in the adjusted model (HR = 4.96, 95% CI 3.89–6.32, p < 0.001). The associations between each potential confounder included in this model and the risk of ESKD are presented in S1 Text and S2 Table. When the analysis was restricted to women who had their first birth from 1991 onwards, the results supported the same conclusion, although the HR was higher (HR = 6.88; 95% CI 4.77–9.92, p < 0.001; Fig 2 and Table 2).
Graph: The cumulative hazard plot was based on a cohort of 1,358,543 women with 2,654,641 births. Black: women with no preeclampsia; blue: women with at least one preeclampsia diagnosis; 95% CIs in dashed lines. CI, confidence interval; ESKD, end-stage kidney disease.
Graph
Table 2 HRs of the association between preeclampsia and ESKD among healthy women.
Exposure variable Number of women with ESRD Partially adjusted HR Adjusted HR Entire study cohort No preeclampsia 325 Reference [ Reference [ Preeclampsia 85 4.99 (3.93–6.33) 4.96 (3.89–6.32) Preterm preeclampsia No preeclampsia 325 Reference [ Reference [ Term preeclampsia 73 4.68 (3.63–6.04) 4.67 (3.60–6.04) Preterm preeclampsia 12 9.19 (5.16–16.35) 8.76 (4.91–15.61) Preeclampsia and SGA No preeclampsia 325 Reference [ Reference [ Preeclampsia only 72 4.89 (3.79–6.31) 4.89 (3.77–6.34) Preeclampsia and SGA 13 6.04 (3.47–10.51) 5.71 (3.28–9.96) Term preeclampsia with no SGA No preeclampsia 325 Reference [ Reference [ Preeclampsia 65 4.71 (3.60–6.15) 4.73 (3.60–6.21) After 2 pregnancies (women with 2 pregnancies only) No preeclampsia 128 Reference [ Reference [ Preeclampsia in 1 pregnancy 28 4.70 (3.12–7.08) 4.43 (2.92–6.70) Preeclampsia in both pregnancies 6 8.24 (3.63–18.70) 7.13 (3.12–16.31) Entire study cohort (after 1991) No preeclampsia 111 Reference [ Reference [ Preeclampsia 45 6.90 (4.83–9.86) 6.88 (4.77–9.92) Women with 1 pregnancy only No preeclampsia 162 Reference [ Reference [ Preeclampsia 34 4.40 (3.04–6.38) 4.42 (3.03–6.46)
- 3 A healthy woman was defined as a woman who had no recorded kidney disease, CVD, diabetes, or hypertension before the first pregnancy.
- 4 *p < 0.001
- 5
a Model included year of delivery. - 6
b Adjusted for maternal age, BMI, smoking, education, native country, year of delivery, and parity. - 7 Abbreviations: CI, confidence interval; CVD, cardiovascular disease; ESKD, end-stage kidney disease; ESRD, end-stage renal disease; HR, hazard ratio; SGA, small for gestational age
Women who had 2 pregnancies complicated with preeclampsia had more than 7-fold increased risk of ESKD (HR = 7.13; 95% CI 3.12–16.31, p < 0.001), whereas women who had preeclampsia in 1 pregnancy had a more than 4-fold increased risk of ESKD (HR = 4.43; 95% CI 2.92–6.70, p < 0.001; Fig 3 and Table 2). The association between term preeclampsia and ESKD was more than 4-fold (HR = 4.67; 95% CI 3.60–6.04, p < 0.001), whereas the association between preterm preeclampsia and the risk of ESKD was almost 9-fold (HR = 8.76; 95% CI 4.91–15.61, p < 0.001). The association between preeclampsia without SGA and ESKD was almost 5-fold (HR = 4.89; 95% CI 3.77–6.34, p < 0.001), whereas the HR was slightly larger for preeclampsia and SGA (HR = 5.71; 95% CI 3.28–9.96, p < 0.001).
Graph: The cumulative hazard plot was based on the cohort of 650,455 women who had 2 pregnancies recorded in the Swedish MBR during the study period; N = 1,291,179. Black: women with no preeclampsia; blue: women who had preeclampsia in 1 pregnancy; green: women who had preeclampsia in 2 pregnancies. 95% CIs in dashed lines. CI, confidence interval; ESKD, end-stage kidney disease; MBR, Medical Birth Register.
There was no statistically significant interaction between preeclampsia and maternal age, BMI, or smoking at the first pregnancy (Table 3). Of the 410 women with ESKD in the study cohort, 96 (23.5%) were diagnosed as glomerulonephritis, 20 (4.9%) as interstitial nephritis, 51 (12.5%) as diabetic nephropathy, 16 (3.9%) as nephrosclerosis due to hypertension, 79 (19.3%) as ADPKD, 112 (27.3%) as other specified renal diseases, and 36 (8.8%) as unknown renal disease. Excluding women who developed ESKD as a result of ADPKD from the analysis resulted in a slightly smaller association (HR = 4.50; 95% CI 3.37–5.93; p < 0.001).
Graph
Table 3 The association between preeclampsia and ESKD based on subgroup analyses.
Subgroup variable ESKD partially adjusted HR (95% CI) Interaction ESKD adjusted HR (95% CI) Interaction Maternal age <30 years at the first pregnancy 0.40 0.35 No preeclampsia Reference [ Reference [ Preeclampsia 5.57 (3.92–7.90) 5.63 (3.95–8.01) Maternal age ≥30 years at the first pregnancy No preeclampsia Reference [ Reference [ Preeclampsia 4.54 (3.27–6.29) 4.48(3.22–6.23) BMI 0.84 0.77 No preeclampsia Reference [ Reference [ Preeclampsia 4.51 (2.96–6.89) 4.92 (3.22–7.52) Normal BMI at the first pregnancy No preeclampsia Reference [ Reference [ Preeclampsia 4.23 (2.74–6.56) 4.50 (2.91–6.97) Nonsmokers 0.79 0.73 No preeclampsia Reference [ Reference [ Preeclampsia 4.95 (3.70–6.63) 4.87 (3.63–6.54) Smokers No preeclampsia Reference [ Reference [ Preeclampsia 4.61 (2.71–7.85) 4.37 (2.57–7.45) Women born in Sweden No preeclampsia Reference [ Reference [ Preeclampsia 5.20 (3.97–6.81) 4.93 (3.75–6.48) Women with no gestational diabetes NA No preeclampsia Reference [ Reference [ Preeclampsia 4.69 (3.65–6.03) 4.69 (3.63–6.05)
- 8
a Model included year of delivery. - 9
b Adjusted for maternal age, BMI, smoking, education, native country, year of delivery, and parity. The variable that was included in the interaction term with preeclampsia was not adjusted for. The analysis was restricted to 1 subgroup of women. - 10
c The models that included interaction terms between preeclampsia and BMI excluded women with missing BMI data, and the model that included an interaction term between preeclampsia and smoking excluded women with missing smoking data. - 11 Abbreviations: BMI, body mass index; CI, confidence interval; ESKD, end-stage kidney disease; HR, hazard ratio; NA, none applicable
The association between preeclampsia and ESKD due to diabetes nephropathy was 9-fold (HR = 9.60; 95% CI 5.27–17.51, p < 0.001]) due to interstitial nephritis was 10-fold (HR = 10.54; 95% CI 4.09–27.13, p < 0.001), whereas it was 3-fold for glomerulonephritis (HR = 3.44; 95% CI 1.93–6.11, p < 0.001) and other causes (HR = 3.29; 95% CI 2.08–5.21, p < 0.001; Table 4). However, these results should be interpreted with caution because the number of events was small in the specific models. The numbers did not allow us to calculate the association due to hypertension.
Graph
Table 4 The association between preeclampsia and ESKD according to specific causes.
Cause of ESKD Number of exposed/unexposed cases Median follow-up (IQR) among ESKD women, years Partially adjusted HR Adjusted HR Glomerulonephritis 14/82 13.87 (9.34–20.16) 3.29 (1.86–5.80) 3.44 (1.93–6.11) Interstitial nephritis 7/13 14.27 (8.90–20.67) 10.29 (4.09–25.84) 10.54 (4.09–27.13) Diabetic nephropathy 17/34 15.12 (8.69–23.62) 10.29 (5.73–18.46) 9.60 (5.27–17.51) Other specified and unknown CKD 29/119 15.3 (8.46–19.62) 3.27 (2.08–5.14) 3.29 (2.08–5.21)
- 12
a Model included year of delivery. - 13
b Adjusted for maternal age, BMI, smoking, education, native country, year of delivery, and parity. - 14 *All p < 0.001
- 15 Abbreviations: BMI, body mass index; CI, confidence interval; CKD, chronic kidney disease; ESKD, end-stage kidney disease; HR, hazard ratio; IQR, interquartile range
The proportion of women who had preeclampsia in the cohort was 0.048, and the adjusted HR was 4.50 (excluding women who had ESKD caused by ADPKD); therefore, the population attributable fraction associated with preeclampsia was 0.14. Thus, in our study, exposure to preeclampsia accounted for 14% of all ESKD in the studied population.
The results of the association between preeclampsia and ESKD among women who had CKD, CVD, hypertension, or diabetes before the first pregnancy (S2 Text and S3 Table) and among all women combined (S3 Text and S4 Table) are presented in Supporting information. The associations between preeclampsia and the risk of ESKD at 5, 10, and 20 years are also presented in Supporting information (S4 Text and S5 Table).
This large, nationwide cohort study of healthy women followed up to 30 years after their first pregnancy suggests that women who have preeclampsia are at almost 5-fold increased risk to develop ESKD. The association is independent of a number of key potential confounders, including pre-existing CKD, CVD, diabetes, and hypertension. The highest risk of ESKD was observed among women with preterm preeclampsia, preeclampsia and SGA in the same pregnancy, and women who had preeclampsia in 2 pregnancies. The highest risk was associated with development of diabetic nephropathy. The population attributable fraction suggested that preeclampsia was responsible for 14% of all ESKD cases in parous women, although this estimate is based on the assumption that the association between preeclampsia and ESKD is causal. Restricting the analysis to women who had their first delivery from 1991 onwards resulted in a higher HR. Our results suggested that the risk of ESKD was increased in relation to preeclampsia in the first 5 years and the first 10-year follow-up (S5 Table), which may suggest that the increased HR could be due to missed ESKD diagnoses between 1982 and 1990 and that the true HR is likely to be larger than 5.
The present findings are consistent with a population-based study from Norway, which included about 570,000 women compared with our 1.36 million [[
Two other studies using insurance claims data on approximately 240,000 and 940,000 women, respectively, both from Taiwan, reported an increased risk of ESKD in relation to hypertensive disorders in pregnancy, including gestational hypertension and preeclampsia [[
The precise pathophysiological mechanisms linking preeclampsia and ESKD are not clear. CKD and preeclampsia have common risk factors (e.g., obesity, hypertension, and insulin resistance), indicating a shared aetiology most likely through the widespread endothelial dysfunction that has been shown to be present in both preeclampsia and ESKD [[
Previous studies have shown that women with a history of preeclampsia have an increased incidence of microalbuminuria, a marker for renal disease [[
Changes in renal haemodynamics postpartum in women with preeclampsia have also been suggested to contribute to an increased risk of ESKD. However, the few studies that assessed renal function and haemodynamics after preeclamptic pregnancy [[
Our study has several strengths. First, it is the largest study on preeclampsia and ESKD to date using one of the best available epidemiological data sources worldwide. The MBR contains data on more than 99% of all births in Sweden, which rules out selection bias due to nonparticipation. Furthermore, the data were collected prospectively, and the preeclampsia diagnoses were ascertained by obstetricians and registered during follow-up in the MBR, which minimised the risk of misclassification. Linkage to the national and validated SRR confirmed the ESKD diagnosis directly and reduced the risk of misclassification of outcome commonly seen when using only administrative databases. We were able to identify the primary renal diagnosis made by the nephrologist. Our access to data on maternal comorbidity before the first pregnancy and during the reproductive period is a significant strength, which allowed us to address the potential confounding of CKD, diabetes, hypertension, and CVD by excluding them from the main analysis. In addition, due to the prospectively collected information in the MBR, we were able to adjust for key sociodemographic variables, including age, BMI, smoking, education, and native country. The size of the cohort allowed us to perform several subgroup and sensitivity analyses.
The study has some limitations that should be considered when interpreting the results. Although we excluded women who had a recorded prepregnancy diagnosis of a major related comorbidity, we cannot rule out that some women may have had undiagnosed or unknown disease leading to residual confounding. Although the study is population based, the results are not generalisable to women who had stillbirth or twins because these were not included in the cohort. However, the percentage of women who may have had stillbirth or twins is very small. Also, we did not have data on miscarriages during the study period; however, this is unlikely to influence the reported results because these women would not have had preeclampsia. We cannot rule out potential confounding by environmental factors related to diet and physical activity and genetic factors, which we did not have access to. Finally, data on BMI were missing in 23% of the population; however, this was similar between exposed and unexposed groups, and maternal characteristics did not appear to confound the association between preeclampsia and ESKD.
We report that healthy women with preeclampsia are at a 5-fold increased risk of ESKD compared with parous women with no preeclampsia. This shows that preeclampsia is a sex-specific, independent risk factor for the subsequent development of ESKD. However, it should be noted that the overall ESKD risk remains small. Whether screening and/or preventative strategies will reduce the risk of ESKD in women with adverse pregnancy outcomes is worthy of further investigation.
S1 STROBE Checklist
(DOC)
S1 Text
The HRs and 95% CIs of the sociodemographic factors and the risk of ESKD.
CI, confidence interval; ESKD, end-stage kidney disease; HR, hazard ratio.(DOCX)
S2 Text
The association between preeclampsia and ESKD among women with prepregnancy comorbidity.
ESKD, end-stage kidney disease.(DOCX)
S3 Text
The association between preeclampsia and ESKD among all women regardless of prepregnancy comorbidity.
ESKD, end-stage kidney disease.(DOCX)
S4 Text
The association between preeclampsia and ESKD at 5-, 10-, and 20-year follow-up.
ESKD, end-stage kidney disease.(DOCX)
S1 Table
ICD codes.
ICD, international classification of diseases.(XLSX)
S2 Table
The HRs of the association between each potential confounder, included in the main analysis, and ESKD among healthy women.
ESKD, end-stage kidney disease; HR, hazard ratio.(XLSX)
S3 Table
HRs of the association between preeclampsia and ESKD among women with prepregnancy comorbidity.
ESKD, end-stage kidney disease; HR, hazard ratio.(XLSX)
S4 Table
HRs of the association between preeclampsia and ESKD among all women regardless of prepregnancy medical history.
ESKD, end-stage kidney disease; HR, hazard ratio.(XLSX)
S5 Table
The HRs of the association between preeclampsia and ESKD among healthy women, women with prepregnancy comorbidity, and all women at 5-, 10-, and 20-year follow-up.
All HRs are based on comparing women who had preeclampsia in at least 1 pregnancy with women who never had preeclampsia during the follow-up period. ESKD, end-stage kidney disease; HR, hazard ratio.(XLSX)
• ADPKD
- adult polycystic kidney disease
• BMI
- body mass index
• CI
- confidence interval
• CKD
- chronic kidney disease
• CVD
- cardiovascular disease
• eGFR
- estimated glomerular filtration rate
• ESKD
- end-stage kidney disease
• ESRD
- end-stage renal disease
• GFR
- glomerular filtration rate
• HR
- hazard ratio
• ICD
- international classification of diseases
• IQR
- interquartile range
• KEAP1
- Kelch-like erythroid cell-derived protein with CNC homology (ESH)-associated protein 1
• MBR
- Medical Birth Register
• NPR
- National Patient Register
• Nrf2
- nuclear factor erythroid 2(NF-E2)-related factor 2
• PAR
- population attributable risk
• PREVEND
- Prevention of Renal and Vascular Endstage Disease Study
• SGA
- small for gestational age
• SRR
- Swedish Renal Registry
• STROBE
- Strengthening the Reporting of Observational Studies in Epidemiology
By Ali S. Khashan; Marie Evans; Marius Kublickas; Fergus P. McCarthy; Louise C. Kenny; Peter Stenvinkel; Tony Fitzgerald and Karolina Kublickiene
Reported by Author; Author; Author; Author; Author; Author; Author; Author