Abstract
Abstract
Objective
To examine the association between clinical severity features, laboratory biomarkers and adverse maternal outcomes in women diagnosed with pre-eclampsia–eclampsia syndrome.
Design
A retrospective cohort study design.
Setting
Ayder Comprehensive Specialized Hospital, a tertiary care hospital in Tigray, Ethiopia.
Participants
A total of 1095 women diagnosed with pre-eclampsia–eclampsia syndrome between 2015 and 2021 were consecutively included.
Outcomes
Adverse maternal outcomes, defined as a composite of intensive care unit (ICU) admission, need for haemodialysis, pulmonary oedema or death.
Methods
A multivariable binary logistic regression model was used to assess the association between pre-eclampsia severity features, laboratory biomarkers and adverse maternal outcomes. Adjusted odds ratios (AORs) were estimated with 95% CIs.
Results
Adverse maternal outcomes occurred in 100 (9.1%) of cases. Eclampsia (AOR=8.85, 95% CI 4.08 to 19.20), lower extremity oedema (AOR=2.28, 95% CI 1.06 to 4.90) and elevated creatinine levels (AOR=5.07, 95% CI 2.21 to 11.61) were significant predictors. Additionally, increasing maternal age was associated with a higher risk (AOR=1.07, 95% CI 1.00 to 1.13).
Conclusions
Clinical severity features (eclampsia and lower extremity oedema), laboratory biomarkers (elevated creatinine) and increasing maternal age were associated with unfavourable maternal outcomes. These findings highlight the importance of integrating clinical signs and laboratory biomarkers into risk assessment for pre-eclampsia patients.
Keywords: Pregnancy, Maternal medicine, Retrospective Studies, PUBLIC HEALTH
STRENGTHS AND LIMITATIONS OF THIS STUDY.
This study integrates laboratory tests and severity characteristics of pre-eclampsia–eclampsia syndrome in a single analysis, enhancing robustness by controlling both laboratory findings and maternal clinical symptoms.
The majority of laboratory biomarkers have incomplete data, affecting the study’s comprehensiveness.
This study relies on existing medical records, restricting the availability of certain variables and potentially introducing unmeasured confounders.
Background
Hypertensive disorders of pregnancy, including pre-eclampsia–eclampsia syndrome, affect 5%–10% of all pregnancies and can lead to life-threatening complications if not properly managed.1 This condition can affect multiorgan systems, increasing the risk of severe complications during delivery and post partum.2 3 Laboratory parameters coupled with pre-eclampsia severity features serve as crucial tools to classify the type of pregnancy-induced hypertension and determine appropriate management strategies.4 5
Prior research in high-income countries has explored the association between maternal pre-eclampsia severity features, such as headache, blurred vision, nausea, vomiting, epigastric pain and chest pain, and laboratory biomarkers, including alanine aminotransferase (ALT), aspartate aminotransferase (AST), creatinine, platelet count and blood urea nitrogen (BUN).6,11 However, findings have been inconsistent. Some studies have reported a significant correlation between these factors and severe maternal outcomes,6,9 whereas others did not.10 11
In resource-limited settings, most studies have focused on demographic and pregnancy-related factors influencing maternal outcomes, often overlooking the role of severity features and laboratory markers. Additionally, their scope has been limited to solely perinatal outcomes without considering maternal endpoints12,14 or has not accounted for critical variables such as laboratory markers or pre-eclampsia symptoms.15,18 Evidence from Ethiopia is similarly scarce; studies have either examined only outcomes within the first 24 hours post partum, limiting insights into long-term complications,19 failed to account for potential confounders20 or did not consider pre-eclampsia severity features.21
Thus, a comprehensive investigation into the association between pre-eclampsia severity features, laboratory biomarkers and adverse maternal outcomes is needed. The prompt identification of high-risk pre-eclampsia–eclampsia patients would allow healthcare providers to personalise treatment strategies for optimal management. This study aimed to establish the association between pre-eclampsia severity characteristics, laboratory tests and adverse maternal outcomes in women diagnosed with pre-eclampsia–eclampsia syndrome.
Methods
Study design and setting
A retrospective cohort design was employed to investigate the association between laboratory tests and maternal clinical symptoms with adverse maternal outcomes. The study was conducted at Ayder Comprehensive Specialized Hospital, a tertiary care hospital located in Tigray, Ethiopia. The hospital is the largest referral hospital in the Tigray region. This study includes a record of consecutive data for a 7-year period (2015–2021).
Participants
This study used secondary data extracted from patient charts. The study population included all women diagnosed with pre-eclampsia–eclampsia syndrome, including atypical pre-eclampsia, who were admitted during the antenatal, intrapartum or postnatal period at Ayder Hospital. A total of 27 350 gestating individuals were included, among whom 1095 had pre-eclampsia. Participants were retrospectively followed until discharge or death. All charts had complete records for the outcome variable.
Variables
The independent variables of interest included pre-eclampsia–eclampsia severity features and laboratory biomarkers. Pre-eclampsia severity features encompassed symptoms such as headache, blurred vision, epigastric pain, right upper quadrant pain, nausea/vomiting and nasal bleeding, which were recorded based on patient reports. Clinically assessed signs included hand swelling, facial swelling, abdominal wall oedema, lower extremity oedema and vulvar oedema. Laboratory biomarkers included platelet count, haemoglobin, ALT, AST, BUN, creatinine and urine protein. These tests were conducted either at the time of pre-eclampsia diagnosis or on the patient’s initial arrival at the hospital for referred cases, with abnormal values determined using hospital laboratory reference ranges. Details of these references and the limit of detection are provided in online supplemental table 1.
Baseline sociodemographic, clinical and obstetric characteristics were included as covariates, including age, residence, gravidity, parity, antenatal care (ANC) follow-up, plurality, history of pre-eclampsia, thyroid disorder, body mass index and history of gestational diabetes mellitus. Additionally, the use of antihypertensive and anticonvulsant medications for the management of pre-eclampsia during the current pregnancy was included.
Outcomes
The composite outcome was adverse maternal outcomes, defined as the occurrence of any of the following: intensive care unit (ICU) admission, need for haemodialysis, pulmonary oedema or death. Reasons for ICU admissions were exclusively for mechanical ventilation. These outcomes were selected based on their clinical severity and relevance in pre-eclampsia–eclampsia syndrome.
Power and sample size
The power calculation for logistic regression was performed using Cohen’s h effect size approach using R software,22 with creatinine as the exposure variable. First, Cohen’s h was computed using the composite adverse maternal outcome probabilities in the reference group (8.9%) and the exposed group (41.7%), yielding a value of 0.798. Next, a power analysis for two independent proportions, with unequal sample sizes, was conducted to estimate the statistical power needed to detect this difference. The analysis was performed at a significance level of 0.05 with a two-sided alternative hypothesis. The results indicated a statistical power of 0.99. A similar power estimation was conducted using AST and ALT as predictors, yielding the same statistical power, confirming the robustness of the sample size in detecting significant associations.
Data analysis
Data were initially entered into EpiData V.4.6 and subsequently transferred to R V.4.3.0 for analysis.23 Before conducting statistical analyses, missing data assessment was performed for explanatory variables with incomplete values (creatinine, platelet count, haemoglobin, ALT, AST, BUN and qualitative urine protein). The χ2 test was used to evaluate whether the mechanism of missingness followed a missing completely at random (MCAR) pattern by examining associations between missingness and the composite outcome (online supplemental table 2). Since no significant associations were found, a complete case analysis was conducted.
For descriptive statistics, frequencies and percentages were calculated for categorical variables, while means with SD were used for continuous variables.
A binary logistic regression model was used to assess the association between pre-eclampsia severity features, laboratory tests and adverse maternal outcomes. Crude odds ratios and adjusted odds ratios (AORs) were calculated along with their 95% CIs. Variables were included in the final model based on their clinical relevance. Before we ran the final model, we checked multicollinearity among the covariates. A history of pre-eclampsia was excluded due to distribution imbalance. Several variables exhibited strong correlations to each other: diastolic blood pressure ≥110 mm Hg with systolic blood pressure ≥160 mm Hg, ALT with AST, facial swelling with hand swelling, blurred vision with headache and right upper quadrant pain with epigastric pain. To address multicollinearity while preserving relevant clinical information, we included each correlated variable one at a time in separate versions of the model rather than incorporating them simultaneously.
The final multivariable model included age, gravidity, antenatal care (ANC), plurality, use of anticonvulsants and antihypertensives, eclampsia, headache, epigastric pain, hand swelling, abdominal wall oedema, lower extremity oedema, systolic blood pressure >160 mm Hg, creatinine, platelet count, haemoglobin, AST, BUN and urine protein.
Patient and public involvement
Neither the patients nor the public were involved in the design, conduct, reporting or dissemination plans of this research.
Results
Demographic, clinical and obstetric characteristics
For over 7 years, our study hospital served 27 350 gestating individuals, of whom 1095 were diagnosed with pre-eclampsia–eclampsia syndrome. The participants had a mean age of 27.6 years (SD=6.5), and the majority (58.5%) resided in urban areas. Nearly half (42.8%) of the women were primigravida (range, 1–12). The majority (88.9%) had received ANC follow-up. Out of the total 1095 individuals in the study, 80 had an abortion during the current pregnancy, and 1015 proceeded to delivery. Of those who gave birth, 414 (40.8%) had a caesarean section. Additionally, more than half (59.3%) received antihypertensive medication during the current pregnancy, and 442 (40.4%) used anticonvulsants during this period. Table 1 presents further details on the obstetric and clinical characteristics of the participants.
Table 1. Demographic, clinical and obstetric characteristics of the study participants, Ayder Comprehensive Specialized Hospital, Mekelle, Northern Ethiopia, 2015–2021 (n=1095).
| Characteristic | Total (n=1095) | Composite endpoint | |
| Yes (n=100) | No (n=995) | ||
| Age in years (mean (SD)) | 27.6 (6.5) | 27.4 (6.5) | 27.6 (6.5) |
| Residence, n (%) | |||
| Urban | 641 (58.5) | 55 (55.0) | 586 (58.9) |
| Rural | 454 (41.5) | 45 (45.0) | 409 (41.1) |
| Gravidity, n (%) (range, 1–12) | |||
| One | 469 (42.8) | 49 (49.0) | 420 (42.1) |
| Two | 209 (19.1) | 13 (13.0) | 196 (19.7) |
| Three | 127 (11.6) | 16 (16.0) | 111 (11.2) |
| Four and above | 290 (26.5) | 22 (22.0) | 268 (27.0) |
| Parity, n (%) (range, 0–11) | |||
| ANC follow-up, n (%) | 973 (88.9) | 83 (83.0) | 890 (89.5) |
| Abortion (current), n (%) | 80 (7.3%) | 11 (11.0) | 69 (6.9) |
| Mode of delivery, n (%) (n=1015) | |||
| Spontaneous vaginal delivery | 575 (56.6) | 52 (58.4) | 523 (56.5) |
| Operative vaginal delivery | 26 (2.6) | 4 (4.5) | 22 (2.4) |
| Caesarean section | 414 (40.8) | 33 (37.1) | 381 (41.1) |
| Multiple pregnancy, n (%) | 99 (9.0) | 6 (6.0) | 93 (9.3) |
| History of pre-eclampsia, n (%) | 68 (6.2) | 4 (4.0) | 64 (6.4) |
| Chronic hypertension, n (%) | 45 (4.1) | 5 (5.0) | 40 (4.0) |
| Thyroid disorder, n (%) | 16 (1.5) | 2 (2.0) | 14 (1.4) |
| BMI >30 kg/m2, n (%) | 17 (1.6) | 3 (3.0) | 14 (1.4) |
| History of GDM, n (%) | 10 (0.9) | 3 (3.0) | 7 (0.7) |
| Antihypertensive drug use, n (%) | 649 (59.3) | 64 (64.0) | 585 (58.8) |
| Anticonvulsant drug use, n (%) | 442 (40.4) | 31 (31.0) | 411 (41.3) |
The composite endpoint includes admission to intensive care unit (ICU), the need for haemodialysis, pulmonary oedema or death.
GDMgestational diabetes mellitusSDstandard deviation
Severity features and laboratory test results
Most of the study participants (67.1%) were diagnosed with pre-eclampsia with severity features. Of the participants, 202 (18.4%) were diagnosed with eclampsia. Nearly half (46.8%) of the participants reported headaches, and 322 (29.3%) of them reported blurred vision. Epigastric pain was another commonly reported symptom, with 309 (28.2%) of the participants experiencing it. In the laboratory analyses, 123 (12.6%) of the participants had a creatinine level >1.3 mg/dL, whereas 207 (20.0%) had a platelet count <1 00 000 /µL. Higher levels of ALT and AST were observed in 177 (20.0%) and 252 (25.8%) of the participants, respectively (table 2).
Table 2. Severity features of pre-eclampsia–eclampsia syndrome by the outcome, Ayder Comprehensive Specialized Hospital, Mekelle, Northern Ethiopia, 2015–2021 (n=1095).
| Characteristic | Total (n=1095) | Composite endpoint | |
| Yes (n=100) | No (n=995) | ||
| Pre-eclampsia with severity features, n (%) | 735 (67.1) | 74 (74.0) | 661 (67.1) |
| Eclampsia, n (%) | 202 (18.4) | 45 (45.0) | 157 (15.8) |
| Headache, n (%) | 512 (46.8) | 55 (55.0) | 457 (46.8) |
| Blurred vision, n (%) | 322 (29.4) | 42 (42.0) | 280 (28.0) |
| Blindness, n (%) | 11 (1.00) | 2 (2.0) | 9 (0.9) |
| Epigastric pain, n (%) | 309 (28.2) | 30 (30.0) | 279 (28.0) |
| Right upper quadrant pain, n (%) | 176 (16.1) | 19 (19.0) | 157 (15.8) |
| Vomiting, n (%) | 90 (8.2) | 16 (16.0) | 74 (7.4) |
| Hand swelling, n (%) | 66 (6.0) | 9 (9.0) | 57 (5.7) |
| Facial swelling, n (%) | 99 (9.0) | 9 (9.0) | 90 (9.0) |
| Abdominal wall oedema, (%) | 70 (6.4) | 10 (10.0) | 60 (6.0) |
| Nasal bleeding, (%) | 25 (2.3) | 1 (1.0) | 24 (2.4) |
| Lower extremity oedema, (%) | 277 (25.3) | 36 (36.0) | 241 (24.2) |
| Vulvar oedema, (%) | 46 (4.2) | 7 (7.0) | 39 (3.9) |
| SBP >160, n (%) | 574 (52.4) | 49 (49.0) | 525 (52.4) |
| DBP >110, n (%) | 467 (42.6) | 40 (40.0) | 427 (42.9) |
| Creatinine >1.3, n (%) (n=977) | 115 (11.8) | 34 (36.6) | 81 (9.2) |
| Platelets < 100,000, n (%) (n=1036) | 207 (20.0) | 26 (27.1) | 181 (19.3) |
| Haemoglobin level <11, n (%) (n=1061) | 206 (19.4) | 31 (31.6) | 175 (18.2) |
| ALT >64, n (%) (n=884) | 177 (20.0) | 30 (36.1) | 147 (18.3) |
| AST >62, n (%) (n=978) | 252 (25.8) | 38 (42.2) | 214 (24.1) |
| BUN >20, n (%) (n=789) | 358 (45.4) | 45 (64.3) | 313 (43.5) |
| Positive qualitative urine protein, n (%) (n=942) | 659 (70.0) | 59 (71.9) | 600 (69.8) |
The composite endpoint includes admission to the intensive care unit (ICU), the need for haemodialysis, pulmonary oedema or death.
ALT, alanine aminotransferase; AST, aspartate aminotransferase; BUNblood urea nitrogenDBP, diastolic blood pressure; SBP, systolic blood pressure
Magnitude of adverse maternal outcomes
The composite outcome included 13 (1.2%) women who underwent haemodialysis and admitted to the ICU: 24 (2.2%) pulmonary oedema patients, 33 (3.0%) deaths and 69 (6.3%) maternal ICU admissions. Collectively, these adverse maternal outcomes accounted for 100 (9.1%) of the cohort (figure 1).
Figure 1. Adverse maternal outcomes of pre-eclampsia–eclampsia syndrome, Ayder Comprehensive Specialized Hospital, Mekelle, Northern Ethiopia, 2017–2021 (n=1095).
Clinical and laboratory predictors of severe adverse maternal outcomes
The factors associated with severe adverse maternal outcomes are summarised in table 3. Mothers diagnosed with eclampsia had significantly higher odds of experiencing an adverse maternal outcome than those without eclampsia (AOR=8.85, 95% CI 4.08 to 19.20, p<0.001). Similarly, mothers with lower extremity oedema had more than twice the likelihood of experiencing an adverse outcome (AOR=2.28, 95% CI 1.06 to 4.90, p=0.035). Elevated creatinine levels (>1.3 mg/dL) were significantly associated with adverse outcomes (AOR=5.07, 95% CI 2.21 to 11.61, p<0.001). Increasing maternal age was found to be significantly associated with adverse maternal outcomes, with each 1-year increase in age raising the odds of experiencing an adverse outcome by 7.0% (AOR=1.07, 95% CI 1.00 to 1.13, p=0.042).
Table 3. Multivariable logistic regression model for predictors of adverse maternal outcomes among mothers with pre-eclampsia–eclampsia syndrome, Ayder Comprehensive Specialized Hospital, Mekelle, Northern Ethiopia, 2015–2021 (n = 1095).
| Characteristic | COR (95% CI) | AOR (95% CI) | P value |
| Age | 0.99 (0.96–1.02) | 1.07 (1.00–1.13) | 0.042* |
| Gravidity | |||
| One | ref | ref | |
| Two | 0.57 (0.30–1.07) | 0.73 (0.28–1.91) | 0.521 |
| Three | 1.23 (0.68–2.25) | 2.27 (0.86–6.00) | 0.099 |
| Four and above | 0.70 (0.41–1.19) | 0.54 (0.20–1.48) | 0.234 |
| ANC visits | |||
| Yes | ref | ref | |
| No | 1.74 (0.99–3.04) | 1.75 (0.74–4.12) | 0.202 |
| Multiple pregnancies | |||
| No | ref | ref | |
| Yes | 0.62 (0.26–1.45) | 0.33 (0.07–1.53) | 0.156 |
| Anticonvulsant use | |||
| No | ref | ref | |
| Yes | 0.64 (0.41–0.99) | 0.74 (0.37–1.45) | 0.380 |
| Antihypertensive use | |||
| No | ref | ref | |
| Yes | 1.24 (0.81–1.91) | 1.26 (0.56–2.89) | 0.590 |
| Eclampsia | |||
| No | ref | ref | |
| Yes | 4.37 (2.84–6.71) | 8.85 (4.08–19.20) | <0.001* |
| Headache | |||
| No | ref | ref | |
| Yes | 1.44 (0.95–2.17) | 0.56 (0.27–1.28) | 0.129 |
| Epigastric pain | |||
| No | ref | ref | |
| Yes | 1.10 (0.70–1.72) | 1.40 (0.64–3.05) | 0.402 |
| Hand swelling | |||
| No | ref | ref | |
| Yes | 1.63 (0.78–3.39) | 1.14 (0.31–4.19) | 0.847 |
| Abdominal wall oedema | |||
| No | ref | ref | |
| Yes | 1.73 (0.86–3.50) | 0.93 (0.27–3.24) | 0.913 |
| Lower extremity oedema | |||
| No | ref | ref | |
| Yes | 1.76 (1.14–2.71) | 2.28 (1.06–4.90) | 0.035* |
| SBP >160 mm Hg | |||
| No | ref | ref | |
| Yes | 0.86 (0.57–1.30) | 0.80 (0.36–1.80) | 0.598 |
| Creatinine | |||
| ≤1.3 | ref | ref | |
| >1.3 | 5.71 (3.53–9.23) | 5.07 (2.21–11.61) | <0.001* |
| Platelet | |||
| ≥1 00 000 | ref | ref | |
| <1 00 000 | 1.56 (0.96–2.51) | 1.08 (0.48–2.47) | 0.845 |
| Haemoglobin | |||
| ≥11 | ref | ref | |
| <11 | 2.08 (1.32–3.29) | 1.10 (0.50–2.41) | 0.815 |
| AST | |||
| ≤62 | ref | ref | |
| >62 | 2.30 (1.47–3.59) | 0.94 (0.43–2.09) | 0.889 |
| BUN | |||
| ≤20 | ref | ref | |
| >20 | 2.33 (1.40–3.89) | 1.00 (0.49–2.06) | 0.992 |
| Urine protein | |||
| Negative | ref | ref | |
| Positive | 1.11 (0.67–1.84) | 0.90 (0.42–1.91) | 0.786 |
The composite endpoint includes admission to the intensive care unit (ICU), the need for haemodialysis, pulmonary oedema or death. To address multicollinearity, highly correlated variables (diastolic blood pressure ≥110 mm Hg with systolic blood pressure ≥160 mm Hg, ALT with AST, facial swelling with hand swelling, blurred vision with headache and right upper quadrant pain with epigastric pain) were included in the model one at a time, replacing their respective correlated variable. However, none of the five substituted variables, namely, diastolic blood pressure ≥110 mm Hg, ALT, facial swelling, blurred vision and right upper quadrant pain were statistically significant predictors of adverse maternal outcomes.
Statistically significant at p < 0.05
ALTalanine aminotransferaseASTaspartate aminotransferaseBUNblood urea nitrogen
Discussion
This study investigated the association between pre-eclampsia severity features, laboratory biomarkers and adverse maternal outcomes. Our findings indicate that eclampsia, the presence of lower extremity oedema and elevated creatinine levels were significantly associated with severe maternal outcomes. Additionally, maternal age was identified as an important risk factor for adverse maternal outcomes.
Maternal outcomes of early-onset versus late-onset pre-eclampsia–eclampsia syndrome are reported elsewhere in previous publications.24 This study found that eclamptic mothers are at an increased risk of serious maternal outcomes compared with their counterparts. This may be partly because severe pre-eclampsia can progress to eclampsia,25 which can then lead to life-threatening complications. Similarly, the presence of lower extremity oedema was found to be a significant predictor of adverse maternal outcomes. Although existing literature on this specific association is scarce, oedema among pre-eclampsia patients is linked to adverse maternal outcomes. For example, a study reported that both pure interstitial oedema and simple cavity gap oedema were associated with complications.26 Another study further found that oedema could serve as a predictor of adverse maternal outcomes,27 reinforcing its clinical significance.
Most of the pre-eclampsia severity features included in our model were not significant predictors of adverse maternal outcomes. A prospective cohort study from the Preeclampsia Integrated Estimate of RiSk study discovered that maternal symptoms of pre-eclampsia do not have independent predictive value for adverse maternal outcomes.11 Conversely, different studies have shown that nausea and vomiting or epigastric pain9 and chest pain or dyspnoea6 28 were found to be predictors of maternal adverse outcomes. This discrepancy could be due to a number of reasons: first, the timing of the outcome was different between the studies; second, there was a huge sample size difference between the studies; third, the composite outcome did not have the same criteria. For example, one of the studies considered placenta abruption as an outcome of interest,11 whereas the other study included abruption as an outcome.9
In addition to severity features, laboratory biomarkers such as creatinine provide further insight into adverse maternal outcomes; those whose creatinine level was >1.3 mg/dL had more than five times higher odds of adverse maternal outcomes. Supporting our findings, a study from Australia, which focused on adverse maternal outcomes in pre-eclampsia at term, and several other reports,6 28 29 including one from Ethiopia,21 have found that elevated serum creatinine level was associated with severe disease progression and adverse maternal outcomes.
However, not all laboratory biomarkers were associated with the outcome. For example, AST and ALT did not demonstrate significant association. In line with our findings, Greiner et al did not find a significant association between AST and ALT with adverse maternal outcomes.10 In contrast, several studies, mostly from developed countries, have reported that women with any abnormal liver function test were at higher risk of experiencing an adverse maternal outcome compared with women with normal results.6 8 9 27 28 This discrepancy may be due to differences in composite outcome definitions. Most of the comparative studies6 8 9 28 included hepatic-related morbidities in their composite adverse maternal outcome measure, which might have inflated the predictive value of liver function tests for adverse maternal outcomes.
Similarly, we did not find an association between platelet count and unfavourable maternal outcomes. Previous studies have reported mixed findings on this association. Some studies have found strong associations between platelet count and poor maternal outcome,6 7 30 31 whereas others, consistent with our study, have not found any significant association.29 This discrepancy may be attributed to inconsistencies in the definition and components of adverse outcomes across studies, variations in baseline characteristics and differences in covariate adjustment. For example, one of the studies included blood transfusion as part of the outcome measure,7 which could overestimate the association, because a lower platelet count could lead to a higher risk of excessive bleeding, increasing the likelihood of requiring a blood transfusion. Another study31 defined the outcome as a composite of major organ morbidity but did not specify which organs were considered. Additionally, one study was adjusted for only a limited number of potential confounders,30 which may have influenced its findings.
In this study, the odds of adverse maternal outcomes increased with age. Previous studies have also shown that older women were more likely to experience adverse maternal outcomes related to pre-eclampsia.32 33 This may be because pre-eclampsia is more common among older women,34 and even in the absence of pre-eclampsia, older women are at a higher risk of adverse maternal outcomes.35 36
This study did not assess these markers, and evidence suggests that uric acid and triglycerides may also contribute to the risk of pre-eclampsia complications. Triglycerides are associated with an increased risk of pre-eclampsia.37,39 Similarly, uric acid has been linked to pre-eclampsia risk prediction40,43; however, some studies, including a systematic review, have found no association between uric acid levels and pre-eclampsia.44 45 A more recently introduced parameter, the uric acid-to-creatinine ratio, has also been used as a predictor of pre-eclampsia development.46
One of the strengths of this study is that, unlike many previous studies,7 8 11 it included both laboratory tests and severity characteristics of pre-eclampsia–eclampsia syndrome in a single analysis, making it robust, as it controls both laboratory findings and maternal clinical symptoms. This study has several limitations. First, as a retrospective study, it relies on existing medical records, which limits the availability of certain variables and may introduce potential unmeasured confounders. For example, the absence of educational level in patient charts could influence the association of interest. Second, although we tried to establish that the missingness was MCAR, the high proportion of incomplete laboratory biomarker data remains a limitation. Third, variability in clinical assessments, laboratory tests and medical record documentation may introduce measurement misclassification in both predictors and outcomes. Finally, the findings may not be generalisable to the general population.
Conclusions
This study found that eclampsia, lower extremity oedema, high creatinine levels and increasing maternal age were significantly associated with adverse maternal outcomes, whereas liver function tests (AST and ALT) and platelet count were not. These findings suggest that incorporating clinical signs such as lower extremity oedema, biomarkers like creatinine levels and maternal age into risk assessment strategies may improve early identification of high-risk pre-eclamptic patients. However, given the study’s retrospective nature and potential measurement errors, future prospective studies are needed to strengthen the evidence base and provide a more thorough understanding of these associations.
supplementary material
Acknowledgements
We extend our heartfelt appreciation to the senior physicians at the study hospital for their invaluable assistance in conducting the data extraction.
Footnotes
Funding: The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Prepublication history and additional supplemental material for this paper are available online. To view these files, please visit the journal online (https://doi.org/10.1136/bmjopen-2024-089935).
Provenance and peer review: Not commissioned; externally peer reviewed.
Patient consent for publication: Not applicable.
Data availability free text: The data used in these analyses are available upon reasonable request. The data involve patient chart extraction of a tertiary care hospital and are stored in the hospital administration’s secure database. The authors do not have the privilege to access and share the data directly, but the hospital administration will share upon a reasonable request.
Patient and public involvement: Patients or the public were not involved in the design, conduct, reporting, or dissemination plans of this study.
Ethics approval: Ethical approval was obtained from the Institutional Review Board (IRB) of Mekelle University, College of Health Sciences (#MU-IRB 2016/2022). Ethical principles adhered to the Declaration of Helsinki. Given that secondary data were analysed, the IRB of Mekelle University, College of Health Sciences, waived the need for informed consent. Data were de-identified during the data extraction process from patient charts.
Data availability statement
Data are available upon reasonable request.
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