Pregnancy outcomes after living kidney donation from a nationwide population-based cohort study from Korea

Data sources and study participants

This national survey is based on the claims database of the Korean National Health Insurance (NHI). South Korea’s NHI system is a national health insurance system run by the South Korean government and covers up to 98% of South Korea’s population. The South Korean NHI claims database includes patient sociodemographic information, patient inpatient and outpatient service use, diagnosis, and treatment. International Classification of Diseases, Tenth Revision (ICD-10) codes were used to record diagnoses in this database. This database has been shown to provide reliable estimates of the prevalence of certain diseases in South Korea.20,21,22.

This study included women aged 19 years and older who had given birth at least once between 2007 and 2018 (ICD-10: R4351, R4335, R4356, R4358, R3131, R3138, R3141, R3143, R3146, R3148, R4361, R4362, R4370, R4376, R4376, R4376, R4379, R7380, R4514, R4516, R4507, R4508, R4509, R4510, R4514, R4516, R4517, R4518, R5002, R5002) Among them, we excluded women who had a diagnostic code of hypertension or diabetes mellitus in the last 5 years. We identified donors who provided kidneys between 2007 and her 2016 by searching standardized codes for donor nephrectomy (R3272) and healthy kidney donors (Z52.4). Donors with multiple pregnancies (more than one fetus at a time) or a history of organ transplantation (ICD-10: O30, O31, O632, O661, O663, and O692 for multiple pregnancies; R3280, Q8040-Q8050) were excluded. , Q8140-Q8150, Q8061, Q8062, Q8080, Q8101, Q8102, Q8103, Q8121, Q8122, Q8123 history of organ transplantation). Each donor’s nephrectomy date served as her cohort enrollment date.

A control group was selected among pregnant women with no history of hypertension, diabetes mellitus, or organ donation during the same period. We also excluded women with multiple pregnancies or a history of organ transplantation. All women were randomly assigned cohort enrollment dates according to the distribution of donor cohort enrollment dates (from 1 January 2007 to her 31 December 2017). Six controls were then matched per donor based on age at entry, year of cohort entry, place of residence, income, number of pregnancies, and time to first pregnancy after cohort entry.

This study was approved by the Institutional Review Board of Ilsan Hospital, National Health Insurance Agency (2021-04-009). The need for written informed consent was waived by the Board due to the retrospective nature of the study. All methods were performed in accordance with relevant guidelines and regulations.

Definition and study endpoints

The study’s primary endpoint was gestational hypertension or pre-eclampsia. Secondary endpoints were severe gestational hypertension or pre-eclampsia, delivery, low birth weight (<2500 g), stillbirth, ectopic pregnancy, and maternal death. Women were followed until death, immigration from South Korea, or the end of the study period (December 31, 2019).

ICD-10 code and Korean NHI claims database (ICD-10: O10, O13, O16 for gestational hypertension; O11 and O14 for pre-eclampsia; O15 for eclampsia; O365) prescribing data (< 2500 g); O364 for stillbirth; O00 for ectopic pregnancy; O03, O04, O05, O06 for maternal death; O07). Gestational hypertension was defined as new-onset hypertension (blood pressure ≥ 140/90) after 20 weeks of gestation without proteinuria. Preeclampsia was defined as gestational hypertension (≥0.3 g per day or ≥+1 on a standard urinalysis strip) with proteinuria. The operational definition of severe gestational hypertension or pre-eclampsia is defined as a diagnostic code with a history of antihypertensive medication. A drug was considered to be used if one or more prescriptions were received during the study period (10 months before delivery date until delivery date).

confounding variable

We investigated the age of admission, the time from admission to childbirth, the number of births, place of residence, and income. Each insured person’s income quintile represents their financial status and is based on their health insurance payments. Patient’s comorbidities were assessed based on her claim code within 5 years prior to cohort enrollment using the Charlson Comorbidity Index.twenty three.

statistical analysis

To compare pregnancy outcomes in living kidney donors and non-donors, propensity score matching was performed to adjust for differences in patient characteristics. Propensity scores were estimated using multiple logistic regression analysis. Regression analyzes predicted each patient’s likelihood of receiving treatment based on age at admission, total number of pregnancies, place of residence, and income. The discriminating and calibrating ability of the propensity score model was evaluated with the C statistic and the Hosmer-Lemeshow statistic. After propensity score-matched samples were formed, we assessed the balance of baseline variables between her two propensity-matched cohort groups.

Continuous variables were compared using the paired t-test or Wilcoxon signed-rank test, as appropriate, and categorical variables were compared with the McNemar test or marginal homogeneity test, as appropriate.twenty fourThe Mann–Whitney U and Wilcoxon signed-rank tests were used to compare continuous variables between subject groups, and the chi-square test was used to compare categorical variables. Cox proportional hazards analysis was used to compare pregnancy outcomes and risk factors for gestational hypertension or pre-eclampsia between donors and non-donors. Patients were adjusted for comorbidities using the Charlson Comorbidity Index. All statistical analyzes were performed using SAS 9.2 (SAS Institute Inc., Cary, NC, USA) and RStudio v1.1.463 (RStudio Inc., Boston, MA, USA). P. Values ​​less than 0.05 were considered statistically significant.

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