Risk Factors for Maternal and Fetal Mortality in Acute Fatty Liver of Pregnancy and New Predictive Models

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A better understanding of the risk factors of AFLP is required. Methods: We analyzed demographic characteristics, clinical symptoms, and laboratory findings of 106 patients with acute fatty liver of pregnancy. Risk factors for maternal and fetal mortality were analyzed by univariate and multivariate logistic regression analysis. The new models based on the multivariate logistic regression analysis and model for end-stage liver disease were tested for all patients with acute fatty liver of pregnancy. The receiver operating characteristic curve was applied to compare the prediction efficiency, sensitivity, and specificity of the two models. Results: Prenatal nausea (p = 0.037), prolonged prothrombin time (p = 0.003), and elevated serum creatinine (p = 0.003) were independent risk factors for maternal mortality in patients with acute fatty liver of pregnancy. The receiver operating characteristic curve showed that the area under the curve of the model for end-stage liver disease was 0.948, with a sensitivity of 100% and a specificity of 83.3%. The area under the curve of new model was 0.926, with a sensitivity of 90% and a specificity of 94.8%. Hepatic encephalopathy (p = 0.016) and thrombocytopenia (p = 0.001) were independent risk factors for fetal mortality. Using receiver operating characteristic curve, the area under the curve of the model for end-stage liver disease was 0.694, yielding a sensitivity of 68.8% and a specificity of 64.4%. The area under the curve of the new model was 0.893, yielding a sensitivity of 100% and a specificity of 73.3%. Conclusion: Both the new predictive model for maternal mortality and the model for end-stage liver disease showed good predictive efficacy for maternal mortality in patients with acute fatty liver of pregnancy (the area under the curve = 0.948 and 0.926, respectively), and the new predictive model for fetal mortality was superior to the model for end-stage liver disease in predicting fetal mortality (the area under the curve = 0.893 and 0.694, respectively) with better sensitivity and specificity. Maternal & Fetal Medicine AFLP Maternal mortality Fetal mortality Risk factor Prognostic model Figures Figure 1 Figure 2 Background Acute fatty liver of pregnancy (AFLP) is a rare but potentially life-threatening hepatic disorder that occurs during the third trimester or early postpartum period. It is defined as severe hepatic synthetic dysfunction due to microvascular steatosis. Although the reported incidence of AFLP was 1 in 7,000 to 1 in 15,000 pregnancies ( 1 ), it could progress rapidly to serious complications such as disseminated intravascular coagulation (DIC), postpartum hemorrhage, multiple organ dysfunction syndrome (MODS), acute hepatic failure (AHF), and maternal or fetal mortality. The pathogenesis of AFLP remains unclear, and most of the literature supports that it is secondary to mitochondrial defects in the fetal long-chain 3-hydroxyacyl-coenzyme A dehydrogenase, as well as other enzymes potentially involved in fatty oxidation, leading to excessive accumulation of fatty acids in maternal hepatocytes, which, in turn, leads to lipotoxicity, oxidative damage, inflammation, and hepatocyte necrosis ( 2 ). Early recognition and diagnosis of AFLP with prompt termination of pregnancy and intensive supportive care are essential for both maternal and fetal survival. With advances in multidisciplinary supportive management of patients with AFLP, maternal and fetal mortality rates have decreased significantly to 7–18% and 9–23%, respectively ( 3 ). Early assessment of the prognosis of patients with AFLP may play an important role in improving maternal and fetal survival ( 4 ). Previous clinical studies on AFLP, largely based on a small number of patients owing to its low prevalence, have found significant differences in its epidemiology ( 1 , 5 ), symptoms ( 6 ), complications ( 6 ), and outcomes ( 1 , 7 , 8 ). The model for end-stage liver disease (MELD) founded in 2000 by Malinchoc and Kamath of Mayo Clinic, the largest liver disease center in the United States, was a grading method for assessing the severity of end-stage liver disease. It was originally created to predict the survival of 231 patients with cirrhosis and portal hypertension after transjugular intrahepatic portosystemic shunt. The statistical model obtained by Cox proportional hazard regression identified four laboratory and clinical indicators that can be used to better assess the three-month survival of patients ( 9 ). Thereafter, Kamath et al . improved the scoring system to R = 3.8 ln (bilirubin) + 11.2 ln (INR) + 9.6 ln (creatinine ) + 6.4 ( 10 ), which made the MELD one of the most widely used scoring systems for evaluating the prognosis of liver disease. Thus far, many studies have reported the ability of the MELD to predict the short-term prognosis of patients with acute liver failure and pregnancy-specific liver diseases ( 11 , 12 ). However, large-sample studies have rarely investigated the efficacy of the MELD in predicting maternal and fetal outcome of AFLP, owing to the rarity of this condition. The existing literature predominantly consists of small hospital-based case series or historical cohorts identified retrospectively over a number of years. Therefore, there is an urgent need for clinical studies on AFLP, especially large-sample and multicenter prospective studies, to help clinicians make prognostic judgments. Our study included 106 patients with AFLP who were admitted to our hospital during the past 10 years. We aimed to explore the independent risk factors for maternal and fetal mortality, and develop new models for predicting the poor prognosis of patients with AFLP. Methods Patients and clinical data We retrospectively analyzed the data of 119 patients who were admitted to Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University and diagnosed with AFLP from September 2011 to November 2020. The diagnosis of all selected patients was reassessed using the Swansea criteria (wherein the diagnosis of AFLP requires the satisfaction of six or more criteria), as detailed in Table 1 . Ten patients who also had a comorbid disease such as viral hepatitis, intrahepatic cholestasis during pregnancy; hemolysis, elevated liver enzymes, and low platelet (HELLP) syndrome; and drug-induced hepatitis, and three patients with incomplete prenatal data were excluded. A total of 106 patients with AFLP were finally enrolled in the study. All patients were prenatally diagnosed with AFLP. Information regarding their laboratory findings, imaging data, and clinical symptoms was collected from the electronic medical records, and they were followed up within 1 month after discharge. The study was approved by the institutional review board of our hospital (approval no. SWYX: NO.2021-052). The ethics committee waived the need for obtaining informed consent from the patients, because the study was an observational, retrospective study using a database from which the patients’ identification information had been removed. Data extracted from these medical records included demographic characteristics, clinical symptoms, laboratory findings, clinical course, and maternal and perinatal outcomes. Demographic characteristics included age, gestational weeks, parity, mode of delivery, single or twin fetus, fetal sex, admission to ICU or not, and days from the first symptom to delivery. Clinical symptoms included abdominal pain, anorexia, nausea, vomiting, polyuria, jaundice, encephalopathy, and high blood pressure. Laboratory findings included prothrombin time (PT), activated partial thromboplastin time (APTT), international normalized ratio (INR), fibrinogen, white blood cell count, hemoglobin, percentage of neutrophils, neutrophils (N), platelet count (PLT), procalcitonin, blood urea nitrogen (BUN), blood creatinine (Cr), blood glucose, uric acid, aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transpeptidase (GGT), alkaline phosphatase (ALP), total bilirubin (TBIL), direct bilirubin (DBIL), and albumin (Alb). Primary prognostic outcomes included maternal and fetal mortality. Swansea criteria for diagnosis of AFLP The international diagnostic criteria for AFLP were based on the Swansea diagnostic standards, as shown in Table 1 ( 8 , 13 ). Six or more criteria are required to diagnose AFLP. The exclusion criteria were as follows: viral hepatitis, intrahepatic cholestasis of pregnancy, HELLP syndrome, drug-induced hepatitis, autoimmune hepatitis, and other diseases. Table 1 Swansea criteria for diagnosis of AFLP Variable Finding Vomiting Positive Abdominal pain Positive Polydipsia or polyuria Positive Hepatic encephalopathy Positive Bilirubin > 14 µmol/L Hypoglycemia 340 µmol/L Leukocytosis > 11 × 10 9 /L Ascites or ultrasound shows bright liver Positive ALT > 42 U/L Serum ammonia > 47 µmol/L Serum creatinine > 150 µmol/L Coagulopathy PT > 14 s APTT 34 s Liver biopsy Diffuse micro vesicular steatosis in hepatocytes ALT: alanine aminotransferase; PT: prothrombin time; APTT: activated partial thromboplastin time Statistical analysis Continuous variables were expressed as mean and standard deviation, and categorical variables were expressed as count and percentages. Continuous variables were tested using Student’s t test, t test with Welch correction, or Mann–Whitey U test, depending on normal distribution and homogeneity in variance. The counting data were tested using the chi-square test. Multiple logistic regression analysis was used to determine the independent risk factors for different outcomes and build prognostic prediction models. The new models and the MELD were used to assess all patients with AFLP. The receiver operating characteristic (ROC) curve was applied to compare the predictive efficiency, sensitivity, and specificity of the two models in evaluating the prognosis of patients with AFLP. Results Clinical characteristics of AFLP patients A total of 106 patients with AFLP were enrolled in this study. Their demographic characteristics and clinical symptoms are shown in Table 2 . Laboratory findings and prognostic outcomes are shown in Tables 3 and 4 , respectively. The average maternal age was 29.8 ± 4.8 years, and the average gestational age was 35.8 ± 2.9 weeks. The median duration from the first symptom to delivery was 7.9 ± 7.9 days. In total, 43 (40.6%) patients were primigravida and 63 (59.4%) were multigravida; 98 (92.5%) patients delivered by cesarean section and 8 (7.5%) patients delivered vaginally. A total of 91 (76.5%) male and 28 (23.5%) female infants were born. Among all patients with AFLP, 96 (90.6%) were admitted to the intensive care unit (ICU) after delivery. The common clinical symptoms included abdominal pain (30.2%), anorexia (56.6%), nausea (46.2%), vomiting (48.1%), polydipsia and polyuria (9.4%), jaundice (23.6%), hepatic encephalopathy (7.5%), and hypertension (15.1%). Table 2 Demographic characteristics and clinical symptoms of patients with AFLP (n = 106) Variable Mean ± SD/No. (%) Demographic characteristics Maternal age (year) 29.8 ± 4.8 Gravidity 1 31 (29.2) 2 29 (27.4) ≥ 3 46 (43.4) Parity 1 43 (40.6) 2 54 (50.9) 3 9 (8.5) Delivery Cesarean section 98 (92.5) Vaginal 8 (7.5) Number of fetuses Single 93 (87.7) Twins 13 (12.3) Gender of baby Female 24 (22.6) Male 69 (65.1) Female/male 2 (1.9) Female/female 1 (0.9) Male/male 10 (9.4) Admitted to ICU 96 (90.6) Days from the first symptom to delivery 7.9 ± 7.9 Days of pregnancy when the first symptom occurred 250.5 ± 20.2 Symptoms Abdominal pain 32 (30.2) Anorexia 60 (56.6) Nausea 49 (46.2) Vomiting 51 (48.1) Polydipsia/polyuria 10 (9.4) Jaundice 25 (23.6) Hepatic encephalopathy 8 (7.5) Hypertension 16 (15.1) Coagulation tests yielded obviously abnormal results, including prolonged PT (22.5 ± 15.9 s), APTT (53.8 ± 27.4 s), and INR (2.1 ± 2.1), and decreased fibrinogen levels (1.6 ± 1.3 g/L). The results of blood routine tests showed increased leukocyte (15.1 ± 5.6 × 10 9 /L) and neutrophil (11.5 ± 4.8 × 10 9 /L) counts, decreased hemoglobin (111.2 ± 24.4 g/L), and normal PLT count (150.3 ± 7.4 × 10 9 /L). PCT was significantly increased (4.6 ± 11.3 ng/mL). Liver function tests revealed increased levels of ALT (292.2 ± 281.6 U/L), AST (289.2 ± 270.8 U/L), GGT (97.2 ± 63.9 U/L), ALP (414.0 ± 220.4 U/L), TBIL (134.1 ± 102.8 µmol/L), and DBIL (82.5 ± 60.9 µmol/L). Renal function was impaired, as evident from increased BUN (8.0 ± 5.5 mmol/L) and Cr (169.9 ± 95.7 µmol/L) levels. Abdominal ultrasound was performed for 71 patients, out of which 42 (59.2%) patients showed positive results. However, 35 patients did not undergo prenatal abdominal ultrasound. The maternal mortality rate was 9.4% (10/106) and the fetal mortality rate was 15.1% (16/106). The common severe complications included acute kidney injury (AKI; 67.0%), DIC (28.3%), postpartum hemorrhage/wound seroma (27.4%), sepsis (26.4%), MODS (28.3%), and AHF (22.6%). Table 3 Laboratory findings of patients with AFLP (n = 106) Variable Mean ± SD Reference range Prothrombin time (s) 22.5 ± 15.9 10.7–14 Activated partial thromboplastin time (s) 53.8 ± 27.4 28–45 International normalized ratio (INR) 2.1 ± 2.1 0.8–1.2 Fibrinogen (g/L) 1.6 ± 1.3 1.75–4.35 Leukocyte (× 10 9 /L) 15.1 ± 5.6 3.5–9.5 Hemoglobin (g/L) 111.2 ± 24.4 130–175 Neutrophil% (%) 75.3 ± 8.5 40–75 Neutrophil (× 10 9 /L) 11.5 ± 4.8 1.8–6.3 Platelets (× 10 9 /L) 150.3 ± 7.4 125–350 Procalcitonin (ng/mL) 4.6 ± 11.3 0–0.05 Blood urea nitrogen (mmol/L) 8.0 ± 5.5 2.8–7.14 Creatinine (µmol/L) 169.9 ± 95.7 40–135 Glucose (mmol/L) 4.4 ± 2.0 3.9–6.3 Uric acid (µmol/L) 495.3 ± 157.5 208–428 Aspartate aminotransferase (U/L) 289.2 ± 270.8 15–40 Alanine aminotransferase (U/L) 292.2 ± 281.6 9–50 Glutamyl transpeptidase (U/L) 97.2 ± 63.9 10–60 Alkaline phosphatase (U/L) 414.0 ± 220.4 45–125 Total bilirubin (µmol/L) 134.1 ± 102.8 3.5–23.5 Direct bilirubin (µmol/L) 82.5 ± 60.9 0.5–6.5 Albumin (g/L) 28.2 ± 5.7 40–55 Table 4 Complications and outcomes of patients with AFLP (n = 106) Variable No. (%) Maternal complications Acute kidney injury 71 (67.0) Disseminated intravascular coagulation 30 (28.3) Postpartum hemorrhage/wound seroma 29 (27.4) Sepsis 28 (26.4) Multiple organ dysfunction syndrome 30 (28.3) Acute hepatic failure 24 (22.6) Maternal outcome Death 10 (9.4) Fetal outcome Death 16 (15.1) Risk factors for maternal mortality, and the new predictive model The distinction in demographic and clinical characteristics and laboratory findings between survivors and non-survivors is summarized in Table 5 . Univariate analyses showed that maternal mortality was significantly related to nausea (p = 0.042), hepatic encephalopathy (p = 0.027), prolonged PT (p < 0.0001), prolonged APTT (p = 0.0009), increased INR (p < 0.0001), decreased fibrinogen (p = 0.004), increased leukocytes (p = 0.018), increased neutrophils (p = 0.012), thrombocytopenia (p = 0.0003), increased Cr (p = 0.002), increased TBIL (p = 0.006), increased DBIL (p = 0.024) and decreased Alb (p = 0.017). Table 5 Comparison of demographic, clinical, and laboratory characteristics between maternal survivors and non-survivors Variable No. (%) Alive (n = 96) Dead (n = 10) P- value Demographic characteristics Maternal age (year) 29.7 ± 4.8 31.5 ± 4.7 0.245 Gravidity 0.307 1 29 (30.2) 2 (20.0) 2 27(28.1%) 2 (20.0) ≥ 3 40 (41.7) 6 (60.0) Parity 0.239 1 40 (41.7) 3 (30.0) 2 49 (51.0) 5 (50.0) 3 7 (7.3) 2 (20.0) Delivery 0.560 Cesarean section 89 (92.7) 9 (90.0) Vaginal 7 (7.3) 1 (10.0) Number of fetuses 0.608 Single 83 (86.5) 10 (100.0) Twins 13 (13.5) 0 Gender of baby 0.531 Female 20 (20.8) 4 (40.0) Male 63 (65.6) 6 (60.0) Female/male 2 (2.1) 0 Female/female 1 (1.0) 0 Male/male 10 (10.4) 0 Delivery in other hospital 0.219 Yes 19 (19.8) 4 (40.0) No 77 (80.2) 6 (60.0) Admitted to ICU 86 (89.6) 10 (100.0) 0.593 Symptoms Abdominal pain 29 (30.2) 3 (30.0) > 0.9999 Anorexia 54 (56.3) 6 (60.0) > 0.9999 Nausea 41 (42.7) 8 (80.0) 0.042* Vomiting 44 (45.8) 7 (70.0) 0.191 Polydipsia/polyuria 9 (9.4) 1 (10.0) > 0.9999 Jaundice 24 (25.0) 1 (10.0) 0.446 Encephalopathy 5 (5.2) 3 (30.0) 0.027* Hypertension 14 (14.6) 2 (20.0) 0.645 Days from the first symptom to delivery 7.7 ± 7.9 9.1 ± 8.3 0.375 Days of pregnancy when the first symptom occurred 250.8 ± 20.9 247.4 ± 8.8 0.273 Laboratory findings PT (s) 20.7 ± 14.8 39.4 ± 16.8 < 0.0001**** APTT (s) 50.8 ± 23.5 82.8 ± 43.3 0.0009*** INR 1.9 ± 2.0 4.1 ± 2.1 < 0.0001**** Fibrinogen (g/L) 1.6 ± 1.3 0.8 ± 0.5 0.004** Leukocyte (× 10 9 /L) 14.6 ± 5.1 19.6 ± 7.6 0.018* Hemoglobin (g/L) 111.1 ± 24.7 111.7 ± 22.0 0.776 N% 75.1 ± 8.7 77.0 ± 5.5 0.500 N (× 10 9 /L) 11.2 ± 4.5 15.3 ± 5.9 0.012* Platelets (× 10 9 /L) 157.7 ± 72.6 79.2 ± 32.0 0.0003*** PCT (ng/mL) 4.8 ± 12.0 3.6 ± 3.5 0.985 BUN (mmol/L) 7.7 ± 5.3 10.8 ± 6.1 0.077 Cr (mg/dL) 156.6 ± 76.1 297.1 ± 160.6 0.002** GLU (mmol/L) 4.3 ± 1.4 5.2 ± 5.0 0.182 Uric acid (µmol/L) 490.6 ± 151.6 540 ± 210.8 0.611 AST (U/L) 295.5 ± 275.2 229.2 ± 227.5 0.308 ALT (U/L) 301.5 ± 287.9 203.2 ± 201.3 0.237 GGT (U/L) 97.51 ± 62.7 93.8 ± 78.1 0.545 ALP (U/L) 416.6 ± 223.2 388.5 ± 199.6 0.979 TBIL (µmol/L) 124.7 ± 92.7 224.1 ± 150.5 0.006** DBIL (µmol/L) 78.1 ± 58.3 124.5 ± 72.3 0.024* Alb (g/L) 28.6 ± 5.7 24.2 ± 5.1 0.017* The above significant variables and BUN (p = 0.077) were included in the logistic regression analysis performed using the forward selection approach, in order to avoid missing important risk factors. The results of logistic regression analysis showed that nausea (p = 0.037), prolonged PT (p = 0.003), and increased Cr (p = 0.003) were independent risk factors for maternal mortality, as shown in Table 6 . Based on these three variables, a new predictive model for maternal mortality was established using the following formula: 2.911 × Nausea + 0.07 × Prothrombin time + 0.011 × Creatinine − 8.86. Table 6 Analysis of independent risk factors for maternal death Variable B S.E. OR 95%CI P-value Nausea 2.911 1.398 18.376 1.186–284.707 0.037* Prothrombin time 0.07 0.024 1.073 1.024–1.124 0.003** Creatinine 0.011 0.004 1.012 1.004–1.019 0.003** Constant −8.86 2.218 The ROC curve was used to evaluate the predictive efficiency of the new model and the MELD with regard to the prognosis of maternal death (Fig. 1 , Table 7 ). The threshold of the MELD was 29.835 and the area under the curve( AUC) was 0.948, with a sensitivity of 100% and a specificity of 83.3%. The threshold of the new model was 0.186 and the AUC was 0.926, with a sensitivity of 90% and a specificity of 94.8%. Both the new model and the MELD showed good predictive efficacy for maternal mortality in patients with acute fatty liver of pregnancy and the new model was superior to the MELD in terms of specificity. Table 7 Comparison of the two models for predicting maternal mortality Model Threshold Sensitivity (%) Specificity (%) AUC 95%CI MELD 29.835 100 83.3 0.948 0.904–0.992 New model 0.186 90 94.8 0.926 0.825–1 Risk factors for fetal mortality, and the new predictive model As shown in Table 8 , univariate analysis showed that fetal mortality was significantly related to encephalopathy (p = 0.017), prolonged PT (p = 0.0005), prolonged APTT (p < 0.0001), increased INR (p = 0.0008), decreased fibrinogen (p = 0.016), elevated leukocyte (p = 0.043), thrombocytopenia (p < 0.0001), decreased GGT (p = 0.019), increased TBIL (p = 0.007), increased DBIL (p = 0.018), and decreased Alb (p = 0.006). Table 8 Comparison of demographic, clinical, and laboratory characteristics between fetal survivors and non-survivors Variable No. (%) Alive (n = 90) Dead (n = 16) P- value Demographic characteristics Maternal age (year) 29.6 ± 4.7 31.1 ± 5.6 0.275 Gravidity 0.258 1 28 (31.1) 3 (18.7) 2 22 (24.4) 7 (43.8) ≥ 3 40 (44.5) 6 (37.5) Parity 0.299 1 39 (43.3) 4 (25.0) 2 43 (47.8) 11 (68.8) 3 8 (8.9) 1 (6.2) Delivery 0.099 Cesarean section 85 (94.4) 13 (81.3) Vaginal 5 (5.6) 3 (18.7) Number of fetuses 0.411 Single 80 (88.9) 13 (81.3) Twins 10 (11.1) 3 (18.7) Gender of baby 0.531 Female 22 (24.4) 11 (68.8) Male 58 (64.4) 2 (12.5) Female/male 2 (2.2) 0 Female/female 7 (7.8) 3 (18.7) Male/male 1 (1.1) 0 Admitted to ICU 81 (90.0) 15 (93.8) > 0.999 Symptoms Abdominal pain 28 (31.1) 4 (25.0) 0.772 Anorexia 50 (55.6) 10 (62.5) 0.785 Nausea 41 (45.6) 8 (50.0) 0.790 Vomiting 43 (47.8) 8 (50.0) > 0.999 Polydipsia/polyuria 10 (11.1) 0 0.353 Jaundice 21 (23.3) 4 (25.0) > 0.999 Encephalopathy 4 (4.4) 4 (25.0) 0.017* Hypertension 14 (15.2) 2 (12.5) > 0.999 Days from the first symptom to delivery 7.4 ± 7.2 10.8 ± 10.7 0.394 Days of pregnancy when the first symptom occurred 251.0 ± 19.5 242.6 ± 19.2 0.051 Laboratory findings PT (s) 20.8 ± 13.0 31.9 ± 25.3 0.0005*** APTT (s) 48.9 ± 19.7 81.4 ± 44.6 < 0.0001**** INR 1.9 ± 1.5 3.3 ± 4.1 0.0008*** Fibrinogen (g/L) 1.7 ± 1.3 1.1 ± 1.0 0.016* Leukocyte (× 10 9 /L) 14.8 ± 5.7 17.0 ± 4.2 0.043* Hemoglobin (g/L) 112.6 ± 24.1 102.9 ± 25.0 0.141 N% 75.0 ± 8.6 76.9 ± 7.5 0.419 N (× 10 9 /L) 11.3 ± 4.9 13.0 ± 3.9 0.087 Platelets (× 10 9 /L) 164.2 ± 70.3 72.2 ± 28.1 < 0.0001**** PCT (ng/mL) 3.2 ± 2.9 10.8 ± 24.9 0.074 BUN (mmol/L) 7.7 ± 4.5 10.0 ± 9.1 0.422 Cr (mg/dL) 163.3 ± 83.9 206.4 ± 143.7 0.259 GLU (mmol/L) 4.4 ± 2.0 4.3 ± 1.8 0.778 Uric acid (µmol/L) 496.4 ± 141.6 488.7 ± 233.5 0.463 AST (U/L) 254.9 ± 183.2 309.5 ± 232.1 0.468 ALT (U/L) 299.1 ± 289.8 253.7 ± 234.5 0.485 GGT (U/L) 101.4 ± 63.0 73.1 ± 65.6 0.019* ALP (U/L) 428.3 ± 226.6 333.1 ± 164.8 0.131 TBIL (µmol/L) 122.2 ± 91.5 201.3 ± 136.4 0.007** DBIL (µmol/L) 76.1 ± 56.2 118.1 ± 75.0 0.018* Alb (g/L) 28.9 ± 5.5 24.6 ± 5.5 0.006** Multivariate logistic regression analysis showed that encephalopathy (p = 0.016) and thrombocytopenia (p = 0.001) were independent risk factors for fetal mortality (Table 9 ). Thereafter, a new predictive model for fetal mortality was established using the following formula: 2.411 × encephalopathy − 0.44 × platelets + 2.506 Table 9 Analysis of independent risk factors for fetal mortality Variable B S.E. OR 95%CI P-value Encephalopathy 2.411 0.999 11.141 1.574–78.87 0.016* Platelets −0.44 0.013 0.957 0.933–0.981 0.001** Constant 2.506 1.087 SE: standard error; CI: confidence interval In predicting fetal mortality, the threshold of the MELD was 25.124 and the AUC was 0.694, with a sensitivity of 68.8% and a specificity of 64.4%. The threshold of the new model was − 45.234 and the AUC was 0.893, with a sensitivity of 100% and a specificity of 73.3%. Thus, compared with the MELD, the new model could more accurately predict fetal death, with a higher sensitivity and specificity (Fig. 2 , Table 10 ). Table 10 Comparison of the two models for predicting fetal mortality Model Threshold Sensitivity (%) Specificity (%) AUC 95%CI MELD 25.124 68.8 64.4 0.694 0.543–0.846 New model −45.234 100 73.3 0.893 0.832–0.955 MELD: model for end-stage liver disease; AUC: area under the curve; CI: confidence interval Discussion AFLP is a rare and fatal obstetric emergency that occurs in the second and third trimester of pregnancy or in the early postpartum period. It can lead to acute liver failure, AKI, multiple organ failure, and even maternal and fetal mortality. Many studies have analyzed the high-risk factors for the morbidity associated with AFLP, fatal complications, and perinatal death. Recent studies have shown that being a primigravida, multiple pregnancies, carrying a male fetus, other liver diseases during pregnancy, previous history of AFLP, and preeclampsia are the potential risk factors for AFLP( 1 , 14 – 16 ). The recognition of high-risk factors is helpful for the prevention and treatment of AFLP, and can consequently improve the prognosis of the mother and the child. Early diagnosis; prompt delivery; and multidisciplinary supportive care from the departments of obstetrics, blood transfusion, and the ICU have resulted in improved maternal mortality ( 3 ). Although liver biopsy is the gold standard for the diagnosis of AFLP, it is rarely performed owing to its invasive nature and owing to the fact that it can cause complications in the presence of coagulopathy. In addition, liver biopsy is just a diagnostic method and does not contribute significantly to the treatment of AFLP. Therefore, none of the patients with AFLP in this study underwent liver biopsy. The 106 patients with AFLP who were enrolled in this study delivered 119 fetuses, including 13 twin pregnancies and 93 single pregnancies. The incidence of twin pregnancy was 12.3% (13/106), which occurred only in the surviving group; however, there was no statistically significant difference in the incidence of twin pregnancy between the survivor and non-survivor groups (13.5% vs. 0, p = 0.608). This finding is similar to the results of another retrospective study conducted in China by Cheng et al . ( 17 ) that showed that the incidence of twin pregnancy among patients with AFLP was 28.1%; however, there was a statistically significant difference between the survivor and non-survivor groups (44.4% vs. 7.1%, p = 0.02). This indicated that twin pregnancy may be a potential protective factor for patients with AFLP; however, this is contrary to the results of the prospective study conducted by Knight et al . ( 1 ). Although our study enrolled the largest number of patients among the three studies (n = 106), it was still not a sufficiently large sample. Because of the rarity of AFLP, our study does not have the power to determine whether this is a statistically significant relationship or just a chance finding. A previous study by Gao et al . showed that male fetus, intrauterine death, postpartum diagnosis of AFLP, DIC, and prolonged PT and APTT were potential risk factors for maternal mortality in AFLP, whereas a history of legal termination of pregnancy, and increased TBIL and serum Cr were independent risk factors ( 18 ). In this study, male fetuses (p = 0.580) and a history of legal termination of pregnancy (p = 0.239) showed no statistically significant difference between the two groups and were not included in the potential risk factors for maternal mortality in AFLP. Previous studies have rarely included a prediction model for fetal mortality. In this study, a new model for predicting fetal mortality was established and the predictive value of the MELD for fetal mortality was also verified. The results of multivariate logistic regression analysis indicated that hepatic encephalopathy (p = 0.016) and thrombocytopenia (p = 0.001) were independent risk factors for fetal mortality in patients with AFLP. Hepatic encephalopathy is a comprehensive disorder of central nervous system dysfunction caused by severe liver disease. As the most direct complication of liver damage in patients with acute liver failure, it is one of the causes of death in patients with liver disease. Its occurrence suggests that patients with AFLP have had acute liver failure before delivery and the fetus has a high incidence of intrauterine distress and stillbirth. In patients with preeclampsia and HELLP syndrome, thrombocytopenia is an independent risk factor for postpartum complications such as infection, thromboembolism, and DIC, and these complications are also common in patients with AFLP ( 19 ). The retrospective study by Cheng et al . showed that carrying a male fetus and vaginal delivery were risk factors for fetal mortality; however, these two variables did not show significant positive predictive value in our study ( 17 ). Gao et al . found that fetal distress and prolonged APTT were risk factors for fetal mortality ( 18 ). The univariate analysis in our study showed that prolonged APTT was a risk factor for fetal mortality (p < 0.0001), but multivariate analysis showed no positive predictive value. The new model based on hepatic encephalopathy and thrombocytopenia was compared with the MELD with regard to the prediction of fetal mortality. The threshold of the MELD was 25.124 and the AUC was 0.694, with a sensitivity of 68.8% and a specificity of 64.4%. The threshold of the new model was 45.234 and the AUC was 0.893, with a sensitivity of 100% and a specificity of 73.3%. Thus, compared with the MELD, the new model could more accurately predict fetal mortality, with a higher sensitivity and specificity. In this study, the common clinical symptoms of patients with AFLP were anorexia (56.6%), vomiting (48.1%), nausea (46.2%), abdominal pain (30.2%), jaundice (23.6%), hypertension (15.1%), polydipsia and polyuria (9.4%), and cerebral encephalopathy (7.5%), which was similar to the results of a national prospective study on AFLP conducted in the UK. This study, conducted between February 2005 and August 2006, reported that 60% of the patients with AFLP experienced vomiting, 56% experienced abdominal pain, 12% experienced polydipsia, and 9% had encephalopathy ( 1 ). In the present study, the common severe complications besides death were AKI (67.0%), DIC(30%), MODS(30%), postpartum hemorrhage(29%), sepsis(28%) and AHF(22.6%), which is consistent with the results of the study by Chen et al . ( 20 ). In their study, the most common maternal complication was acute renal dysfunction (79.5%), followed by DIC (47.7%) and MODS (38.6%). Maternal and fetal mortality rates attributable to AFLP vary greatly among studies, with the maternal mortality rate ranging from 12–18% and the fetal mortality rate ranging from 7–58% ( 21 ). Our previous clinical study showed that the maternal and fetal mortality rates of 52 patients with AFLP admitted to our hospital from January 2001 to December 2011 were 8% and 23%, respectively ( 22 ). In this study, a total of 106 patients with AFLP were admitted to our hospital from September 2011 to November 2020, and 119 fetuses were delivered. The maternal and fetal mortality rates were 9.4% (10/106) and 15.1% (18/119) respectively, both of which were lower than those reported in other studies. Compared with the last decade, the maternal mortality rate has declined slightly and the fetal mortality rate has decreased significantly in our hospital. This may be related to the loosening of the two-child policy, leading to an increasing number of older mothers and, consequently, more complications during pregnancy, causing a slight increase in maternal mortality. However, with the development of multidisciplinary supportive management in our hospital, especially pediatric intensive care, the level of comprehensive treatment of the fetus has been greatly improved, leading to a significant decline in the fetal mortality rate. In this study, prenatal nausea (p = 0.037), prolonged PT (p = 0.003), and elevated serum Cr (p = 0.003) were independent risk factors for maternal mortality in patients with AFLP. Another study reported that ascites, thrombocytopenia, and serum Cr were independent risk factors for postpartum complications in pre-eclampsia and HELLP syndrome ( 23 ). The clinical symptoms of AFLP are similar to those of HELLP syndrome, and both are pregnancy-specific liver diseases. The predictive model for AFLP also included one clinical symptom and two laboratory findings, and elevated serum Cr was an independent risk factor for both AFLP and HELLP syndrome. However, the difference between the PLT count in AFLP was statistically significant in univariate analysis (p = 0.0003) and was eliminated in multivariate logistic regression analysis. This suggests that thrombocytopenia is a potential risk factor for maternal mortality in AFLP, which needs to be verified by a larger-sample study. Transaminase levels have not been shown to be important across most disease models in liver disease, including our model for AFLP (p > 0.05). A single-center retrospective study with 130 cases (AFLP = 32; HELLP = 81; pre-eclampsia and liver disease = 17) showed that both the MELD and the new model with two objective variables, namely serum TBIL and INR, were reliable for predicting the short-term mortality in patients with pregnancy-specific liver disease (followed up until 3 months after delivery or until death) ( 12 ). In the present study, TBIL and INR were statistically significant in univariate analysis (p = 0.006 and p < 0.0001, respectively), but they were eliminated in multivariate logistic regression analysis, which also suggested that increased TBIL and prolonged INR are potential risk factors for maternal mortality in AFLP; further prospective studies with larger sample sizes are warranted to explore the risk factors for maternal mortality in patients with AFLP. Previous clinical studies have shown that the MELD based on TBIL, Cr, and INR shows good predictive efficacy for acute liver failure and pregnancy-specific liver disease ( 11 , 12 ). A study conducted in China showed that the MELD was a good predictor of all complications of AFLP, including ascites, hepatic encephalopathy, sepsis, and renal insufficiency (all AUCs > 0.8), and the optimal cut-off values were close to 30 ( 24 ). Our study also verified that both the MELD and the new model show good predictive efficacy in predicting maternal mortality in AFLP (AUC = 0.948 and 0.926, respectively). Overall, compared with previous models based on only laboratory findings, the new predictive model for maternal mortality included one clinical symptom and two laboratory findings, which was more readily available, less expensive and easier to implement clinically. To the best of our knowledge, the symptom of nausea that we identified as an independent risk factor for AFLP has not been previously described. This study had a long duration of almost 10 years, and is the largest single-center clinical study on AFLP so far. The number of patients with AFLP enrolled in this study is only second to that in the multicenter study by Gao et al ., in which our hospital has participated in the past ( 18 ). As all patients with AFLP came from one single center, they received similar obstetric and multidisciplinary treatments after hospitalization, and some limitations of different medical levels were counter-balanced. There are some limitations to our research. Firstly, we did not evaluate the morbidity of AFLP owing to the deficiency of data on total pregnant women during the study period. Secondly, this was a single-center and small-sample study because of the rarity of AFLP, which might reduce the general applicability of our findings, although we had extended the study period to one decade and our study was a retrospective study. Thirdly, as Shandong Provincial Hospital is a tertiary referral center for critical patients in China, some patients with AFLP were referred to our hospital after severe postpartum complications, and their condition was relatively critical. The manner and timing of medical intervention during their prenatal treatment differed, which directly affected the prognosis of the patients. Conclusions We identified a group of risk factors for maternal and fetal mortality among patients with AFLP and developed two new prognostic models. Both the new predictive model for maternal mortality and the MELD showed good predictive efficacy for maternal mortality in patients with acute fatty liver of pregnancy (the area under the curve = 0.948 and 0.926, respectively), while the new predictive model for fetal mortality was superior to the model for end-stage liver disease in predicting fetal mortality (the area under the curve = 0.893 and 0.694, respectively) with better sensitivity and specificity. Abbreviations AFLP: acute fatty liver of pregnancy; MELD: model for end-stage liver disease; ALT: alanine aminotransferase; PT: prothrombin time; APTT: activated partial thromboplastin time; ROC: receiver operating characteristic; ICU: intensive care unit; INR: International normalized ratio; N: neutrophils; PLT: platelet count; BUN: blood urea nitrogen; Cr: blood creatinine; GLU: Glucose; AST: aspartate aminotransferase; GGT: gamma-glutamyl transpeptidase; ALK: Alkaline phosphatase; TBIL: total bilirubin; DBIL: direct bilirubin; Alb: albumin; DIC: disseminated intravascular coagulation. Declarations Ethics approval and consent to participate The study has been performed in accordance with the Declaration of Helsinki and has been approved by Biomedical Research Committee of Shandong Provincial Hospital (approval no. SWYX: NO.2021-052), which waived the need for obtaining informed consent from the patients, because the study was an observational, retrospective study using a database from which the patients’ identification information had been removed. Consent for publication Not applicable. Availability of data and materials The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation. Competing interests The authors declare that they have no competing interests. Funding This work was supported by the National Natural Science Foundation of China (no. 81903086); the National Natural Science Foundation of Shandong Province (no. ZR2019QH014); Shanghai Shenkang Hospital Development Center (no.SHDC12019125). Authors’ contributions CW, MC and ZM contributed to conception and design of the study. CW and WF organized the database. MC performed the statistical analysis. ZM wrote the first draft of the manuscript. MM, JZ, QW and GQ revised sections of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version. Acknowledgments This study was funded by the National Natural Science Foundation of China (no. 81903086) and the National Natural Science Foundation of Shandong Province (no. ZR2019QH014), which was received by Dr. Man Chen, and Shanghai Shenkang Hospital Development Center (no. SHDC12019125), which was received by Dr. Mei Meng. References Knight M, Nelson-Piercy C, Kurinczuk JJ, Spark P, Brocklehurst P. A prospective national study of acute fatty liver of pregnancy in the UK. Gut. 2008;57(7):951-6. Natarajan SK, Ibdah JA. Role of 3-Hydroxy Fatty Acid-Induced Hepatic Lipotoxicity in Acute Fatty Liver of Pregnancy. International journal of molecular sciences. 2018;19(1). Hay JE. Liver disease in pregnancy. Hepatology (Baltimore, Md). 2008;47(3):1067-76. Knox TA, Olans LB. Liver disease in pregnancy. The New England journal of medicine. 1996;335(8):569-76. Nelson DB, Yost NP, Cunningham FG. Acute fatty liver of pregnancy: clinical outcomes and expected duration of recovery. American journal of obstetrics and gynecology. 2013;209(5):456.e1-7. Minakami H, Morikawa M, Yamada T, Yamada T, Akaishi R, Nishida R. Differentiation of acute fatty liver of pregnancy from syndrome of hemolysis, elevated liver enzymes and low platelet counts. The journal of obstetrics and gynaecology research. 2014;40(3):641-9. Xiong HF, Liu JY, Guo LM, Li XW. Acute fatty liver of pregnancy: over six months follow-up study of twenty-five patients. World journal of gastroenterology. 2015;21(6):1927-31. Goel A, Ramakrishna B, Zachariah U, Ramachandran J, Eapen CE, Kurian G, et al. How accurate are the Swansea criteria to diagnose acute fatty liver of pregnancy in predicting hepatic microvesicular steatosis? Gut. 2011;60(1):138-9; author reply 9-40. Malinchoc M, Kamath PS, Gordon FD, Peine CJ, Rank J, ter Borg PC. A model to predict poor survival in patients undergoing transjugular intrahepatic portosystemic shunts. Hepatology (Baltimore, Md). 2000;31(4):864-71. Kamath PS, Wiesner RH, Malinchoc M, Kremers W, Therneau TM, Kosberg CL, et al. A model to predict survival in patients with end-stage liver disease. Hepatology (Baltimore, Md). 2001;33(2):464-70. McPhail MJ. Improving MELD for use in acute liver failure. Journal of hepatology. 2011;54(6):1320; author reply -1. Murali AR, Devarbhavi H, Venkatachala PR, Singh R, Sheth KA. Factors that predict 1-month mortality in patients with pregnancy-specific liver disease. Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association. 2014;12(1):109-13. Ch'ng CL, Morgan M, Hainsworth I, Kingham JG. Prospective study of liver dysfunction in pregnancy in Southwest Wales. Gut. 2002;51(6):876-80. Davidson KM, Simpson LL, Knox TA, D'Alton ME. Acute fatty liver of pregnancy in triplet gestation. Obstetrics and gynecology. 1998;91(5 Pt 2):806-8. Wei Q, Zhang L, Liu X. Clinical diagnosis and treatment of acute fatty liver of pregnancy: a literature review and 11 new cases. The journal of obstetrics and gynaecology research. 2010;36(4):751-6. Lee NM, Brady CW. Liver disease in pregnancy. World journal of gastroenterology. 2009;15(8):897-906. Cheng N, Xiang T, Wu X, Li M, Xie Y, Zhang L. Acute fatty liver of pregnancy: a retrospective study of 32 cases in South China. The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstet. 2014;27(16):1693-7. Gao Q, Qu X, Chen X, Zhang J, Liu F, Tian S, et al. Outcomes and risk factors of patients with acute fatty liver of pregnancy: a multicentre retrospective study. Singapore medical journal. 2018;59(8):425-30. Bernal W, Hall C, Karvellas CJ, Auzinger G, Sizer E, Wendon J. Arterial ammonia and clinical risk factors for encephalopathy and intracranial hypertension in acute liver failure. Hepatology (Baltimore, Md). 2007;46(6):1844-52. Chen G, Huang K, Ji B, Chen C, Liu C, Wang X, et al. Acute fatty liver of pregnancy in a Chinese Tertiary Care Center: a retrospective study. Archives of gynecology and obstetrics. 2019;300(4):897-901. Rajasri AG, Srestha R, Mitchell J. Acute fatty liver of pregnancy (AFLP)--an overview. Journal of obstetrics and gynaecology : the journal of the Institute of Obstetrics and Gynaecology. 2007;27(3):237-40. Wang S, Li SL, Cao YX, Li YP, Meng JL, Wang XT. Noninvasive Swansea criteria are valuable alternatives for diagnosing acute fatty liver of pregnancy in a Chinese population. The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstet. 2017;30(24):2951-5. Deruelle P, Coudoux E, Ego A, Houfflin-Debarge V, Codaccioni X, Subtil D. Risk factors for post-partum complications occurring after preeclampsia and HELLP syndrome. A study in 453 consecutive pregnancies. European journal of obstetrics, gynecology, and reproductive biology. 2006;125(1):59-65. Li P, Lin S, Li L, Cui J, Wang Q, Zhou S, et al. Utility of MELD scoring system for assessing the prognosis of acute fatty liver of pregnancy. European journal of obstetrics, gynecology, and reproductive biology. 2019;240:161-6. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-590345","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":32593777,"identity":"f6da40eb-0a9d-4072-a832-0b0f9070f556","order_by":0,"name":"Zhaoli Meng","email":"","orcid":"","institution":"Shandong Provincial Hospital, Shandong University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhaoli","middleName":"","lastName":"Meng","suffix":""},{"id":32593778,"identity":"6ce70e91-2ac4-478f-ad5d-a289bf156c23","order_by":1,"name":"Wei Fang","email":"","orcid":"","institution":"Shandong Provincial Hospital affiliated to Shandong First Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Fang","suffix":""},{"id":32593779,"identity":"415d257b-ce44-441a-9305-c2d0927c7e6b","order_by":2,"name":"Jicheng Zhang","email":"","orcid":"","institution":"Shandong Provincial Hospital, Shandong University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jicheng","middleName":"","lastName":"Zhang","suffix":""},{"id":32593780,"identity":"7c8247c1-e2d7-4453-8bdc-e7094889a66f","order_by":3,"name":"Mei Meng","email":"","orcid":"","institution":"Ruijin Hospital, Shanghai Jiao Tong University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mei","middleName":"","lastName":"Meng","suffix":""},{"id":32593781,"identity":"3810f4e0-aea5-45b9-a54e-bd7eb18139b1","order_by":4,"name":"Qizhi Wang","email":"","orcid":"","institution":"Shandong Provincial Hospital affiliated to Shandong First Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qizhi","middleName":"","lastName":"Wang","suffix":""},{"id":32593782,"identity":"012c4747-af37-4ed9-8ba4-3a0d117273a2","order_by":5,"name":"Guoqiang Qie","email":"","orcid":"","institution":"Shandong Provincial Hospital affiliated to Shandong First Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Guoqiang","middleName":"","lastName":"Qie","suffix":""},{"id":32593783,"identity":"1cfad6c6-0461-48bf-a246-ad9376c49295","order_by":6,"name":"Man Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIiWNgGAWjYDACCSht397Y+CChwoYELQY8h5sNHpxJI0WLRHqb5MO2Q4R18M9uPvboRs0dBnOGxLaKBLYDDPzt3Qn4LblzLN0459gzBsuGg203EnjuMEicObsBrxYDiRwz6Ry2wwwMBxuBWiSeAUVyCWnJ/yad8w+o5TBjW0GCwWFitOSwSee2AVUeY2xjSEggQovEjTQz6dy+wwySPYzNEgkH0ngI+oV/RvIz6Zxvhxn45Z8//Pjzn40cf3svfi0wUN8AZfAQpXwUjIJRMApGAX4AAF9+S0LJGAJkAAAAAElFTkSuQmCC","orcid":"","institution":"Shandong Provincial Hospital, Shandong University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Man","middleName":"","lastName":"Chen","suffix":""},{"id":32593784,"identity":"b254a235-db44-4d0f-88ef-9e8baa686ae9","order_by":7,"name":"Chunting Wang","email":"","orcid":"","institution":"Shandong Provincial Hospital, Shandong University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Chunting","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2021-06-04 08:14:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-590345/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-590345/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":10389694,"identity":"150fc2e2-852b-4c3b-bd1b-39e20866fbf6","added_by":"auto","created_at":"2021-06-15 14:41:01","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":58075,"visible":true,"origin":"","legend":"Receiver operating characteristic curve of the model for end-stage liver disease scoring system and the new model in predicting maternal death","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-590345/v1/15da5ad87e1d6eb45c26b0ab.jpg"},{"id":10389279,"identity":"abb42cf5-e977-4818-a052-9ba8be24c9e7","added_by":"auto","created_at":"2021-06-15 14:38:01","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":60805,"visible":true,"origin":"","legend":"Receiver operating characteristic curve of the model for end-stage liver disease scoring system and the new model in predicting fetal death.","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-590345/v1/e9baa5e1b71df0b4d8d1458c.jpg"},{"id":13698642,"identity":"4f80fa4a-00ad-4b8d-96a8-788cedbc8223","added_by":"auto","created_at":"2021-09-17 13:15:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":608497,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-590345/v1/894042b0-23d3-43a4-884e-bc96de510792.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eRisk Factors for Maternal and Fetal Mortality in Acute Fatty Liver of Pregnancy and New Predictive Models\u003c/p\u003e","fulltext":[{"header":"Background","content":" \u003cp\u003eAcute fatty liver of pregnancy (AFLP) is a rare but potentially life-threatening hepatic disorder that occurs during the third trimester or early postpartum period. It is defined as severe hepatic synthetic dysfunction due to microvascular steatosis. Although the reported incidence of AFLP was 1 in 7,000 to 1 in 15,000 pregnancies (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), it could progress rapidly to serious complications such as disseminated intravascular coagulation (DIC), postpartum hemorrhage, multiple organ dysfunction syndrome (MODS), acute hepatic failure (AHF), and maternal or fetal mortality. The pathogenesis of AFLP remains unclear, and most of the literature supports that it is secondary to mitochondrial defects in the fetal long-chain 3-hydroxyacyl-coenzyme A dehydrogenase, as well as other enzymes potentially involved in fatty oxidation, leading to excessive accumulation of fatty acids in maternal hepatocytes, which, in turn, leads to lipotoxicity, oxidative damage, inflammation, and hepatocyte necrosis (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Early recognition and diagnosis of AFLP with prompt termination of pregnancy and intensive supportive care are essential for both maternal and fetal survival. With advances in multidisciplinary supportive management of patients with AFLP, maternal and fetal mortality rates have decreased significantly to 7\u0026ndash;18% and 9\u0026ndash;23%, respectively (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEarly assessment of the prognosis of patients with AFLP may play an important role in improving maternal and fetal survival (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Previous clinical studies on AFLP, largely based on a small number of patients owing to its low prevalence, have found significant differences in its epidemiology (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), symptoms (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), complications (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), and outcomes (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). The model for end-stage liver disease (MELD) founded in 2000 by Malinchoc and Kamath of Mayo Clinic, the largest liver disease center in the United States, was a grading method for assessing the severity of end-stage liver disease. It was originally created to predict the survival of 231 patients with cirrhosis and portal hypertension after transjugular intrahepatic portosystemic shunt. The statistical model obtained by Cox proportional hazard regression identified four laboratory and clinical indicators that can be used to better assess the three-month survival of patients (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Thereafter, Kamath \u003cem\u003eet al\u003c/em\u003e. improved the scoring system to R\u0026thinsp;=\u0026thinsp;3.8 ln (bilirubin)\u0026thinsp;+\u0026thinsp;11.2 ln (INR)\u0026thinsp;+\u0026thinsp;9.6 ln (creatinine )\u0026thinsp;+\u0026thinsp;6.4 (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), which made the MELD one of the most widely used scoring systems for evaluating the prognosis of liver disease. Thus far, many studies have reported the ability of the MELD to predict the short-term prognosis of patients with acute liver failure and pregnancy-specific liver diseases (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). However, large-sample studies have rarely investigated the efficacy of the MELD in predicting maternal and fetal outcome of AFLP, owing to the rarity of this condition. The existing literature predominantly consists of small hospital-based case series or historical cohorts identified retrospectively over a number of years. Therefore, there is an urgent need for clinical studies on AFLP, especially large-sample and multicenter prospective studies, to help clinicians make prognostic judgments.\u003c/p\u003e \u003cp\u003eOur study included 106 patients with AFLP who were admitted to our hospital during the past 10 years. We aimed to explore the independent risk factors for maternal and fetal mortality, and develop new models for predicting the poor prognosis of patients with AFLP.\u003c/p\u003e "},{"header":"Methods","content":"\u003cdiv class=\"Section2\" id=\"Sec3\"\u003e\n \u003ch2\u003ePatients and clinical data\u003c/h2\u003e\n \u003cp\u003eWe retrospectively analyzed the data of 119 patients who were admitted to Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University and diagnosed with AFLP from September 2011 to November 2020. The diagnosis of all selected patients was reassessed using the Swansea criteria (wherein the diagnosis of AFLP requires the satisfaction of six or more criteria), as detailed in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. Ten patients who also had a comorbid disease such as viral hepatitis, intrahepatic cholestasis during pregnancy; hemolysis, elevated liver enzymes, and low platelet (HELLP) syndrome; and drug-induced hepatitis, and three patients with incomplete prenatal data were excluded. A total of 106 patients with AFLP were finally enrolled in the study.\u003c/p\u003e\n \u003cp\u003eAll patients were prenatally diagnosed with AFLP. Information regarding their laboratory findings, imaging data, and clinical symptoms was collected from the electronic medical records, and they were followed up within 1 month after discharge. The study was approved by the institutional review board of our hospital (approval no. SWYX: NO.2021-052). The ethics committee waived the need for obtaining informed consent from the patients, because the study was an observational, retrospective study using a database from which the patients\u0026rsquo; identification information had been removed. Data extracted from these medical records included demographic characteristics, clinical symptoms, laboratory findings, clinical course, and maternal and perinatal outcomes.\u003c/p\u003e\n \u003cp\u003eDemographic characteristics included age, gestational weeks, parity, mode of delivery, single or twin fetus, fetal sex, admission to ICU or not, and days from the first symptom to delivery. Clinical symptoms included abdominal pain, anorexia, nausea, vomiting, polyuria, jaundice, encephalopathy, and high blood pressure. Laboratory findings included prothrombin time (PT), activated partial thromboplastin time (APTT), international normalized ratio (INR), fibrinogen, white blood cell count, hemoglobin, percentage of neutrophils, neutrophils (N), platelet count (PLT), procalcitonin, blood urea nitrogen (BUN), blood creatinine (Cr), blood glucose, uric acid, aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transpeptidase (GGT), alkaline phosphatase (ALP), total bilirubin (TBIL), direct bilirubin (DBIL), and albumin (Alb). Primary prognostic outcomes included maternal and fetal mortality.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec4\"\u003e\n \u003ch2\u003eSwansea criteria for diagnosis of AFLP\u003c/h2\u003e\n \u003cp\u003eThe international diagnostic criteria for AFLP were based on the Swansea diagnostic standards, as shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e (\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e). Six or more criteria are required to diagnose AFLP. The exclusion criteria were as follows: viral hepatitis, intrahepatic cholestasis of pregnancy, HELLP syndrome, drug-induced hepatitis, autoimmune hepatitis, and other diseases.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSwansea criteria for diagnosis of AFLP\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFinding\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVomiting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbdominal pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePolydipsia or polyuria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHepatic encephalopathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBilirubin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;14 \u0026micro;mol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypoglycemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;4 mmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUric acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;340 \u0026micro;mol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeukocytosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;11 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAscites or ultrasound shows bright liver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eALT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;42 U/L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSerum ammonia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;47 \u0026micro;mol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSerum creatinine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;150 \u0026micro;mol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCoagulopathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;14 s\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAPTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 s\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLiver biopsy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiffuse micro vesicular steatosis in hepatocytes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003eALT: alanine aminotransferase; PT: prothrombin time; APTT: activated partial thromboplastin time\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec5\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cp\u003eContinuous variables were expressed as mean and standard deviation, and categorical variables were expressed as count and percentages. Continuous variables were tested using Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e test, \u003cem\u003et\u003c/em\u003e test with Welch correction, or Mann\u0026ndash;Whitey \u003cem\u003eU\u003c/em\u003e test, depending on normal distribution and homogeneity in variance. The counting data were tested using the chi-square test. Multiple logistic regression analysis was used to determine the independent risk factors for different outcomes and build prognostic prediction models. The new models and the MELD were used to assess all patients with AFLP. The receiver operating characteristic (ROC) curve was applied to compare the predictive efficiency, sensitivity, and specificity of the two models in evaluating the prognosis of patients with AFLP.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv class=\"Section2\" id=\"Sec7\"\u003e\n \u003ch2\u003eClinical characteristics of AFLP patients\u003c/h2\u003e\n \u003cp\u003eA total of 106 patients with AFLP were enrolled in this study. Their demographic characteristics and clinical symptoms are shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. Laboratory findings and prognostic outcomes are shown in Tables\u0026nbsp;3 and \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, respectively. The average maternal age was 29.8\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8 years, and the average gestational age was 35.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9 weeks. The median duration from the first symptom to delivery was 7.9\u0026thinsp;\u0026plusmn;\u0026thinsp;7.9 days. In total, 43 (40.6%) patients were primigravida and 63 (59.4%) were multigravida; 98 (92.5%) patients delivered by cesarean section and 8 (7.5%) patients delivered vaginally. A total of 91 (76.5%) male and 28 (23.5%) female infants were born. Among all patients with AFLP, 96 (90.6%) were admitted to the intensive care unit (ICU) after delivery. The common clinical symptoms included abdominal pain (30.2%), anorexia (56.6%), nausea (46.2%), vomiting (48.1%), polydipsia and polyuria (9.4%), jaundice (23.6%), hepatic encephalopathy (7.5%), and hypertension (15.1%).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDemographic characteristics and clinical symptoms of patients with AFLP (n\u0026thinsp;=\u0026thinsp;106)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD/No. (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographic characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaternal age (year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.8\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGravidity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31 (29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (27.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46 (43.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eParity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (40.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54 (50.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDelivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCesarean section\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e98 (92.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVaginal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber of fetuses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93 (87.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTwins\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (12.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender of baby\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (22.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69 (65.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale/male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale/female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale/male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (9.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdmitted to ICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96 (90.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDays from the first symptom to delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.9\u0026thinsp;\u0026plusmn;\u0026thinsp;7.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDays of pregnancy when the first symptom occurred\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e250.5\u0026thinsp;\u0026plusmn;\u0026thinsp;20.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSymptoms\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbdominal pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (30.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnorexia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60 (56.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNausea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 (46.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVomiting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51 (48.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePolydipsia/polyuria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (9.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJaundice\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (23.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHepatic encephalopathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eCoagulation tests yielded obviously abnormal results, including prolonged PT (22.5\u0026thinsp;\u0026plusmn;\u0026thinsp;15.9 s), APTT (53.8\u0026thinsp;\u0026plusmn;\u0026thinsp;27.4 s), and INR (2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1), and decreased fibrinogen levels (1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3 g/L). The results of blood routine tests showed increased leukocyte (15.1\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L) and neutrophil (11.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L) counts, decreased hemoglobin (111.2\u0026thinsp;\u0026plusmn;\u0026thinsp;24.4 g/L), and normal PLT count (150.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.4 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L). PCT was significantly increased (4.6\u0026thinsp;\u0026plusmn;\u0026thinsp;11.3 ng/mL). Liver function tests revealed increased levels of ALT (292.2\u0026thinsp;\u0026plusmn;\u0026thinsp;281.6 U/L), AST (289.2\u0026thinsp;\u0026plusmn;\u0026thinsp;270.8 U/L), GGT (97.2\u0026thinsp;\u0026plusmn;\u0026thinsp;63.9 U/L), ALP (414.0\u0026thinsp;\u0026plusmn;\u0026thinsp;220.4 U/L), TBIL (134.1\u0026thinsp;\u0026plusmn;\u0026thinsp;102.8 \u0026micro;mol/L), and DBIL (82.5\u0026thinsp;\u0026plusmn;\u0026thinsp;60.9 \u0026micro;mol/L). Renal function was impaired, as evident from increased BUN (8.0\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5 mmol/L) and Cr (169.9\u0026thinsp;\u0026plusmn;\u0026thinsp;95.7 \u0026micro;mol/L) levels. Abdominal ultrasound was performed for 71 patients, out of which 42 (59.2%) patients showed positive results. However, 35 patients did not undergo prenatal abdominal ultrasound. The maternal mortality rate was 9.4% (10/106) and the fetal mortality rate was 15.1% (16/106). The common severe complications included acute kidney injury (AKI; 67.0%), DIC (28.3%), postpartum hemorrhage/wound seroma (27.4%), sepsis (26.4%), MODS (28.3%), and AHF (22.6%).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab3\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLaboratory findings of patients with AFLP (n = 106)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference range\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProthrombin time (s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.5\u0026thinsp;\u0026plusmn;\u0026thinsp;15.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.7\u0026ndash;14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eActivated partial thromboplastin time (s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53.8\u0026thinsp;\u0026plusmn;\u0026thinsp;27.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u0026ndash;45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInternational normalized ratio (INR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8\u0026ndash;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFibrinogen (g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.75\u0026ndash;4.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeukocyte (\u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.1\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.5\u0026ndash;9.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHemoglobin (g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e111.2\u0026thinsp;\u0026plusmn;\u0026thinsp;24.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e130\u0026ndash;175\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeutrophil% (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75.3\u0026thinsp;\u0026plusmn;\u0026thinsp;8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026ndash;75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeutrophil (\u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.8\u0026ndash;6.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlatelets (\u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e150.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e125\u0026ndash;350\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProcalcitonin (ng/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.6\u0026thinsp;\u0026plusmn;\u0026thinsp;11.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u0026ndash;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlood urea nitrogen (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.0\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.8\u0026ndash;7.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCreatinine (\u0026micro;mol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e169.9\u0026thinsp;\u0026plusmn;\u0026thinsp;95.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026ndash;135\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGlucose (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.9\u0026ndash;6.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUric acid (\u0026micro;mol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e495.3\u0026thinsp;\u0026plusmn;\u0026thinsp;157.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e208\u0026ndash;428\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAspartate aminotransferase (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e289.2\u0026thinsp;\u0026plusmn;\u0026thinsp;270.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u0026ndash;40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlanine aminotransferase (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e292.2\u0026thinsp;\u0026plusmn;\u0026thinsp;281.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u0026ndash;50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGlutamyl transpeptidase (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e97.2\u0026thinsp;\u0026plusmn;\u0026thinsp;63.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u0026ndash;60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlkaline phosphatase (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e414.0\u0026thinsp;\u0026plusmn;\u0026thinsp;220.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026ndash;125\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal bilirubin (\u0026micro;mol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e134.1\u0026thinsp;\u0026plusmn;\u0026thinsp;102.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.5\u0026ndash;23.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDirect bilirubin (\u0026micro;mol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82.5\u0026thinsp;\u0026plusmn;\u0026thinsp;60.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u0026ndash;6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlbumin (g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026ndash;55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Taba\"\u003e\n \u003ccaption\u003e\n \u003cp\u003eTable 4\u003c/p\u003e\n \u003cp\u003eComplications and outcomes of patients with AFLP (n = 106)\u003c/p\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo. (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaternal complications\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAcute kidney injury\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71 (67.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDisseminated intravascular coagulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (28.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePostpartum hemorrhage/wound seroma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (27.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSepsis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (26.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMultiple organ dysfunction syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (28.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAcute hepatic failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (22.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaternal outcome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDeath\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (9.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFetal outcome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDeath\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec8\"\u003e\n \u003ch2\u003eRisk factors for maternal mortality, and the new predictive model\u003c/h2\u003e\n \u003cp\u003eThe distinction in demographic and clinical characteristics and laboratory findings between survivors and non-survivors is summarized in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e. Univariate analyses showed that maternal mortality was significantly related to nausea (p\u0026thinsp;=\u0026thinsp;0.042), hepatic encephalopathy (p\u0026thinsp;=\u0026thinsp;0.027), prolonged PT (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), prolonged APTT (p\u0026thinsp;=\u0026thinsp;0.0009), increased INR (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), decreased fibrinogen (p\u0026thinsp;=\u0026thinsp;0.004), increased leukocytes (p\u0026thinsp;=\u0026thinsp;0.018), increased neutrophils (p\u0026thinsp;=\u0026thinsp;0.012), thrombocytopenia (p\u0026thinsp;=\u0026thinsp;0.0003), increased Cr (p\u0026thinsp;=\u0026thinsp;0.002), increased TBIL (p\u0026thinsp;=\u0026thinsp;0.006), increased DBIL (p\u0026thinsp;=\u0026thinsp;0.024) and decreased Alb (p\u0026thinsp;=\u0026thinsp;0.017).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab4\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of demographic, clinical, and laboratory characteristics between maternal survivors and non-survivors\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo. (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlive (n\u0026thinsp;=\u0026thinsp;96)\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDead (n\u0026thinsp;=\u0026thinsp;10)\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldItalic\"\u003eP-\u003c/span\u003e\u003cstrong\u003evalue\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographic characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaternal age (year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.245\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGravidity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.307\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (30.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27(28.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (41.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eParity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.239\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (41.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 (51.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDelivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.560\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCesarean section\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89 (92.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (90.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVaginal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber of fetuses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.608\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83 (86.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTwins\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender of baby\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.531\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (20.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63 (65.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale/male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale/female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale/male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (10.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDelivery in other hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.219\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (19.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77 (80.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdmitted to ICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86 (89.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.593\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSymptoms\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbdominal pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (30.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.9999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnorexia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54 (56.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.9999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNausea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (42.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (80.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.042*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVomiting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44 (45.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (70.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.191\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePolydipsia/polyuria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (9.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.9999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJaundice\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.446\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEncephalopathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.027*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (14.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.645\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDays from the first symptom to delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.7\u0026thinsp;\u0026plusmn;\u0026thinsp;7.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.1\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.375\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDays of pregnancy when the first symptom occurred\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e250.8\u0026thinsp;\u0026plusmn;\u0026thinsp;20.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e247.4\u0026thinsp;\u0026plusmn;\u0026thinsp;8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.273\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLaboratory findings\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePT (s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.7\u0026thinsp;\u0026plusmn;\u0026thinsp;14.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39.4\u0026thinsp;\u0026plusmn;\u0026thinsp;16.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001****\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAPTT (s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.8\u0026thinsp;\u0026plusmn;\u0026thinsp;23.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82.8\u0026thinsp;\u0026plusmn;\u0026thinsp;43.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0009***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eINR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001****\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFibrinogen (g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.004**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeukocyte (\u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.018*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHemoglobin (g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e111.1\u0026thinsp;\u0026plusmn;\u0026thinsp;24.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e111.7\u0026thinsp;\u0026plusmn;\u0026thinsp;22.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75.1\u0026thinsp;\u0026plusmn;\u0026thinsp;8.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77.0\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN (\u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.012*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlatelets (\u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e157.7\u0026thinsp;\u0026plusmn;\u0026thinsp;72.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79.2\u0026thinsp;\u0026plusmn;\u0026thinsp;32.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0003***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePCT (ng/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.8\u0026thinsp;\u0026plusmn;\u0026thinsp;12.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.985\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBUN (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.7\u0026thinsp;\u0026plusmn;\u0026thinsp;5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCr (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e156.6\u0026thinsp;\u0026plusmn;\u0026thinsp;76.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e297.1\u0026thinsp;\u0026plusmn;\u0026thinsp;160.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGLU (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.182\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUric acid (\u0026micro;mol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e490.6\u0026thinsp;\u0026plusmn;\u0026thinsp;151.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e540\u0026thinsp;\u0026plusmn;\u0026thinsp;210.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.611\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAST (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e295.5\u0026thinsp;\u0026plusmn;\u0026thinsp;275.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e229.2\u0026thinsp;\u0026plusmn;\u0026thinsp;227.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.308\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eALT (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e301.5\u0026thinsp;\u0026plusmn;\u0026thinsp;287.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e203.2\u0026thinsp;\u0026plusmn;\u0026thinsp;201.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.237\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGGT (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e97.51\u0026thinsp;\u0026plusmn;\u0026thinsp;62.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93.8\u0026thinsp;\u0026plusmn;\u0026thinsp;78.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.545\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eALP (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e416.6\u0026thinsp;\u0026plusmn;\u0026thinsp;223.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e388.5\u0026thinsp;\u0026plusmn;\u0026thinsp;199.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.979\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTBIL (\u0026micro;mol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e124.7\u0026thinsp;\u0026plusmn;\u0026thinsp;92.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e224.1\u0026thinsp;\u0026plusmn;\u0026thinsp;150.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.006**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDBIL (\u0026micro;mol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78.1\u0026thinsp;\u0026plusmn;\u0026thinsp;58.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e124.5\u0026thinsp;\u0026plusmn;\u0026thinsp;72.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.024*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlb (g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.017*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eThe above significant variables and BUN (p\u0026thinsp;=\u0026thinsp;0.077) were included in the logistic regression analysis performed using the forward selection approach, in order to avoid missing important risk factors. The results of logistic regression analysis showed that nausea (p\u0026thinsp;=\u0026thinsp;0.037), prolonged PT (p\u0026thinsp;=\u0026thinsp;0.003), and increased Cr (p\u0026thinsp;=\u0026thinsp;0.003) were independent risk factors for maternal mortality, as shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e. Based on these three variables, a new predictive model for maternal mortality was established using the following formula: 2.911 \u0026times; Nausea\u0026thinsp;+\u0026thinsp;0.07 \u0026times; Prothrombin time\u0026thinsp;+\u0026thinsp;0.011 \u0026times; Creatinine\u0026thinsp;\u0026minus;\u0026thinsp;8.86.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab5\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAnalysis of independent risk factors for maternal death\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eS.E.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNausea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.911\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.398\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.376\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.186\u0026ndash;284.707\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.037*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProthrombin time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.024\u0026ndash;1.124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCreatinine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.004\u0026ndash;1.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConstant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;8.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eThe ROC curve was used to evaluate the predictive efficiency of the new model and the MELD with regard to the prognosis of maternal death (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e). The threshold of the MELD was 29.835 and the area under the curve( AUC) was 0.948, with a sensitivity of 100% and a specificity of 83.3%. The threshold of the new model was 0.186 and the AUC was 0.926, with a sensitivity of 90% and a specificity of 94.8%. Both the new model and the MELD showed good predictive efficacy for maternal mortality in patients with acute fatty liver of pregnancy and the new model was superior to the MELD in terms of specificity.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab6\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of the two models for predicting maternal mortality\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eThreshold\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSensitivity (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecificity (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAUC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMELD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.835\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.948\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.904\u0026ndash;0.992\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNew model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.926\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.825\u0026ndash;1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec9\"\u003e\n \u003ch2\u003eRisk factors for fetal mortality, and the new predictive model\u003c/h2\u003e\n \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e, univariate analysis showed that fetal mortality was significantly related to encephalopathy (p\u0026thinsp;=\u0026thinsp;0.017), prolonged PT (p\u0026thinsp;=\u0026thinsp;0.0005), prolonged APTT (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), increased INR (p\u0026thinsp;=\u0026thinsp;0.0008), decreased fibrinogen (p\u0026thinsp;=\u0026thinsp;0.016), elevated leukocyte (p\u0026thinsp;=\u0026thinsp;0.043), thrombocytopenia (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), decreased GGT (p\u0026thinsp;=\u0026thinsp;0.019), increased TBIL (p\u0026thinsp;=\u0026thinsp;0.007), increased DBIL (p\u0026thinsp;=\u0026thinsp;0.018), and decreased Alb (p\u0026thinsp;=\u0026thinsp;0.006).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab7\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of demographic, clinical, and laboratory characteristics between fetal survivors and non-survivors\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo. (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlive (n\u0026thinsp;=\u0026thinsp;90)\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDead (n\u0026thinsp;=\u0026thinsp;16)\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldItalic\"\u003eP-\u003c/span\u003e\u003cstrong\u003evalue\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographic characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaternal age (year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.6\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.1\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.275\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGravidity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.258\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (31.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (18.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (24.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (43.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (44.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eParity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.299\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39 (43.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (47.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (68.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDelivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.099\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCesarean section\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85 (94.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (81.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVaginal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (18.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber of fetuses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.411\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 (88.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (81.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTwins\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (18.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender of baby\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.531\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (24.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (68.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58 (64.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale/male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale/female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (18.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale/male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdmitted to ICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e81 (90.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (93.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSymptoms\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbdominal pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (31.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.772\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnorexia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50 (55.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (62.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.785\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNausea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (45.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.790\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVomiting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (47.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePolydipsia/polyuria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.353\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJaundice\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (23.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEncephalopathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.017*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDays from the first symptom to delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.4\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.394\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDays of pregnancy when the first symptom occurred\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e251.0\u0026thinsp;\u0026plusmn;\u0026thinsp;19.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e242.6\u0026thinsp;\u0026plusmn;\u0026thinsp;19.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLaboratory findings\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePT (s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.8\u0026thinsp;\u0026plusmn;\u0026thinsp;13.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.9\u0026thinsp;\u0026plusmn;\u0026thinsp;25.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0005***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAPTT (s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.9\u0026thinsp;\u0026plusmn;\u0026thinsp;19.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e81.4\u0026thinsp;\u0026plusmn;\u0026thinsp;44.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001****\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eINR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0008***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFibrinogen (g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.016*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeukocyte (\u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.0\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.043*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHemoglobin (g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e112.6\u0026thinsp;\u0026plusmn;\u0026thinsp;24.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e102.9\u0026thinsp;\u0026plusmn;\u0026thinsp;25.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.141\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75.0\u0026thinsp;\u0026plusmn;\u0026thinsp;8.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76.9\u0026thinsp;\u0026plusmn;\u0026thinsp;7.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.419\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN (\u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlatelets (\u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e164.2\u0026thinsp;\u0026plusmn;\u0026thinsp;70.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72.2\u0026thinsp;\u0026plusmn;\u0026thinsp;28.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001****\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePCT (ng/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.8\u0026thinsp;\u0026plusmn;\u0026thinsp;24.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBUN (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.0\u0026thinsp;\u0026plusmn;\u0026thinsp;9.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.422\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCr (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e163.3\u0026thinsp;\u0026plusmn;\u0026thinsp;83.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e206.4\u0026thinsp;\u0026plusmn;\u0026thinsp;143.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.259\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGLU (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.778\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUric acid (\u0026micro;mol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e496.4\u0026thinsp;\u0026plusmn;\u0026thinsp;141.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e488.7\u0026thinsp;\u0026plusmn;\u0026thinsp;233.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.463\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAST (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e254.9\u0026thinsp;\u0026plusmn;\u0026thinsp;183.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e309.5\u0026thinsp;\u0026plusmn;\u0026thinsp;232.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.468\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eALT (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e299.1\u0026thinsp;\u0026plusmn;\u0026thinsp;289.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e253.7\u0026thinsp;\u0026plusmn;\u0026thinsp;234.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.485\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGGT (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e101.4\u0026thinsp;\u0026plusmn;\u0026thinsp;63.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73.1\u0026thinsp;\u0026plusmn;\u0026thinsp;65.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.019*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eALP (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e428.3\u0026thinsp;\u0026plusmn;\u0026thinsp;226.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e333.1\u0026thinsp;\u0026plusmn;\u0026thinsp;164.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTBIL (\u0026micro;mol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122.2\u0026thinsp;\u0026plusmn;\u0026thinsp;91.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e201.3\u0026thinsp;\u0026plusmn;\u0026thinsp;136.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.007**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDBIL (\u0026micro;mol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76.1\u0026thinsp;\u0026plusmn;\u0026thinsp;56.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e118.1\u0026thinsp;\u0026plusmn;\u0026thinsp;75.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.018*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlb (g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.006**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eMultivariate logistic regression analysis showed that encephalopathy (p\u0026thinsp;=\u0026thinsp;0.016) and thrombocytopenia (p\u0026thinsp;=\u0026thinsp;0.001) were independent risk factors for fetal mortality (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e). Thereafter, a new predictive model for fetal mortality was established using the following formula: 2.411 \u0026times; encephalopathy \u0026minus;\u0026thinsp;0.44 \u0026times; platelets\u0026thinsp;+\u0026thinsp;2.506\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab8\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAnalysis of independent risk factors for fetal mortality\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eS.E.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEncephalopathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.411\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.574\u0026ndash;78.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.016*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlatelets\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.957\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.933\u0026ndash;0.981\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConstant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eSE: standard error; CI: confidence interval\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIn predicting fetal mortality, the threshold of the MELD was 25.124 and the AUC was 0.694, with a sensitivity of 68.8% and a specificity of 64.4%. The threshold of the new model was \u0026minus;\u0026thinsp;45.234 and the AUC was 0.893, with a sensitivity of 100% and a specificity of 73.3%. Thus, compared with the MELD, the new model could more accurately predict fetal death, with a higher sensitivity and specificity (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, Table \u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab9\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of the two models for predicting fetal mortality\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eThreshold\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSensitivity (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecificity (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAUC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMELD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.694\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.543\u0026ndash;0.846\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNew model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;45.234\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.893\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.832\u0026ndash;0.955\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eMELD: model for end-stage liver disease; AUC: area under the curve; CI: confidence interval\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":" \u003cp\u003eAFLP is a rare and fatal obstetric emergency that occurs in the second and third trimester of pregnancy or in the early postpartum period. It can lead to acute liver failure, AKI, multiple organ failure, and even maternal and fetal mortality. Many studies have analyzed the high-risk factors for the morbidity associated with AFLP, fatal complications, and perinatal death. Recent studies have shown that being a primigravida, multiple pregnancies, carrying a male fetus, other liver diseases during pregnancy, previous history of AFLP, and preeclampsia are the potential risk factors for AFLP(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). The recognition of high-risk factors is helpful for the prevention and treatment of AFLP, and can consequently improve the prognosis of the mother and the child. Early diagnosis; prompt delivery; and multidisciplinary supportive care from the departments of obstetrics, blood transfusion, and the ICU have resulted in improved maternal mortality (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Although liver biopsy is the gold standard for the diagnosis of AFLP, it is rarely performed owing to its invasive nature and owing to the fact that it can cause complications in the presence of coagulopathy. In addition, liver biopsy is just a diagnostic method and does not contribute significantly to the treatment of AFLP. Therefore, none of the patients with AFLP in this study underwent liver biopsy.\u003c/p\u003e \u003cp\u003eThe 106 patients with AFLP who were enrolled in this study delivered 119 fetuses, including 13 twin pregnancies and 93 single pregnancies. The incidence of twin pregnancy was 12.3% (13/106), which occurred only in the surviving group; however, there was no statistically significant difference in the incidence of twin pregnancy between the survivor and non-survivor groups (13.5% vs. 0, p\u0026thinsp;=\u0026thinsp;0.608). This finding is similar to the results of another retrospective study conducted in China by Cheng \u003cem\u003eet al\u003c/em\u003e. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) that showed that the incidence of twin pregnancy among patients with AFLP was 28.1%; however, there was a statistically significant difference between the survivor and non-survivor groups (44.4% vs. 7.1%, p\u0026thinsp;=\u0026thinsp;0.02). This indicated that twin pregnancy may be a potential protective factor for patients with AFLP; however, this is contrary to the results of the prospective study conducted by Knight \u003cem\u003eet al\u003c/em\u003e. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Although our study enrolled the largest number of patients among the three studies (n\u0026thinsp;=\u0026thinsp;106), it was still not a sufficiently large sample. Because of the rarity of AFLP, our study does not have the power to determine whether this is a statistically significant relationship or just a chance finding. A previous study by Gao \u003cem\u003eet al\u003c/em\u003e. showed that male fetus, intrauterine death, postpartum diagnosis of AFLP, DIC, and prolonged PT and APTT were potential risk factors for maternal mortality in AFLP, whereas a history of legal termination of pregnancy, and increased TBIL and serum Cr were independent risk factors (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). In this study, male fetuses (p\u0026thinsp;=\u0026thinsp;0.580) and a history of legal termination of pregnancy (p\u0026thinsp;=\u0026thinsp;0.239) showed no statistically significant difference between the two groups and were not included in the potential risk factors for maternal mortality in AFLP.\u003c/p\u003e \u003cp\u003ePrevious studies have rarely included a prediction model for fetal mortality. In this study, a new model for predicting fetal mortality was established and the predictive value of the MELD for fetal mortality was also verified. The results of multivariate logistic regression analysis indicated that hepatic encephalopathy (p\u0026thinsp;=\u0026thinsp;0.016) and thrombocytopenia (p\u0026thinsp;=\u0026thinsp;0.001) were independent risk factors for fetal mortality in patients with AFLP. Hepatic encephalopathy is a comprehensive disorder of central nervous system dysfunction caused by severe liver disease. As the most direct complication of liver damage in patients with acute liver failure, it is one of the causes of death in patients with liver disease. Its occurrence suggests that patients with AFLP have had acute liver failure before delivery and the fetus has a high incidence of intrauterine distress and stillbirth. In patients with preeclampsia and HELLP syndrome, thrombocytopenia is an independent risk factor for postpartum complications such as infection, thromboembolism, and DIC, and these complications are also common in patients with AFLP (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). The retrospective study by Cheng \u003cem\u003eet al\u003c/em\u003e. showed that carrying a male fetus and vaginal delivery were risk factors for fetal mortality; however, these two variables did not show significant positive predictive value in our study (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Gao \u003cem\u003eet al\u003c/em\u003e. found that fetal distress and prolonged APTT were risk factors for fetal mortality (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). The univariate analysis in our study showed that prolonged APTT was a risk factor for fetal mortality (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), but multivariate analysis showed no positive predictive value. The new model based on hepatic encephalopathy and thrombocytopenia was compared with the MELD with regard to the prediction of fetal mortality. The threshold of the MELD was 25.124 and the AUC was 0.694, with a sensitivity of 68.8% and a specificity of 64.4%. The threshold of the new model was 45.234 and the AUC was 0.893, with a sensitivity of 100% and a specificity of 73.3%. Thus, compared with the MELD, the new model could more accurately predict fetal mortality, with a higher sensitivity and specificity.\u003c/p\u003e \u003cp\u003eIn this study, the common clinical symptoms of patients with AFLP were anorexia (56.6%), vomiting (48.1%), nausea (46.2%), abdominal pain (30.2%), jaundice (23.6%), hypertension (15.1%), polydipsia and polyuria (9.4%), and cerebral encephalopathy (7.5%), which was similar to the results of a national prospective study on AFLP conducted in the UK. This study, conducted between February 2005 and August 2006, reported that 60% of the patients with AFLP experienced vomiting, 56% experienced abdominal pain, 12% experienced polydipsia, and 9% had encephalopathy (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). In the present study, the common severe complications besides death were AKI (67.0%), DIC(30%), MODS(30%), postpartum hemorrhage(29%), sepsis(28%) and AHF(22.6%), which is consistent with the results of the study by Chen \u003cem\u003eet al\u003c/em\u003e. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). In their study, the most common maternal complication was acute renal dysfunction (79.5%), followed by DIC (47.7%) and MODS (38.6%).\u003c/p\u003e \u003cp\u003eMaternal and fetal mortality rates attributable to AFLP vary greatly among studies, with the maternal mortality rate ranging from 12\u0026ndash;18% and the fetal mortality rate ranging from 7\u0026ndash;58% (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Our previous clinical study showed that the maternal and fetal mortality rates of 52 patients with AFLP admitted to our hospital from January 2001 to December 2011 were 8% and 23%, respectively (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). In this study, a total of 106 patients with AFLP were admitted to our hospital from September 2011 to November 2020, and 119 fetuses were delivered. The maternal and fetal mortality rates were 9.4% (10/106) and 15.1% (18/119) respectively, both of which were lower than those reported in other studies. Compared with the last decade, the maternal mortality rate has declined slightly and the fetal mortality rate has decreased significantly in our hospital. This may be related to the loosening of the two-child policy, leading to an increasing number of older mothers and, consequently, more complications during pregnancy, causing a slight increase in maternal mortality. However, with the development of multidisciplinary supportive management in our hospital, especially pediatric intensive care, the level of comprehensive treatment of the fetus has been greatly improved, leading to a significant decline in the fetal mortality rate.\u003c/p\u003e \u003cp\u003eIn this study, prenatal nausea (p\u0026thinsp;=\u0026thinsp;0.037), prolonged PT (p\u0026thinsp;=\u0026thinsp;0.003), and elevated serum Cr (p\u0026thinsp;=\u0026thinsp;0.003) were independent risk factors for maternal mortality in patients with AFLP. Another study reported that ascites, thrombocytopenia, and serum Cr were independent risk factors for postpartum complications in pre-eclampsia and HELLP syndrome (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). The clinical symptoms of AFLP are similar to those of HELLP syndrome, and both are pregnancy-specific liver diseases. The predictive model for AFLP also included one clinical symptom and two laboratory findings, and elevated serum Cr was an independent risk factor for both AFLP and HELLP syndrome. However, the difference between the PLT count in AFLP was statistically significant in univariate analysis (p\u0026thinsp;=\u0026thinsp;0.0003) and was eliminated in multivariate logistic regression analysis. This suggests that thrombocytopenia is a potential risk factor for maternal mortality in AFLP, which needs to be verified by a larger-sample study. Transaminase levels have not been shown to be important across most disease models in liver disease, including our model for AFLP (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). A single-center retrospective study with 130 cases (AFLP\u0026thinsp;=\u0026thinsp;32; HELLP\u0026thinsp;=\u0026thinsp;81; pre-eclampsia and liver disease\u0026thinsp;=\u0026thinsp;17) showed that both the MELD and the new model with two objective variables, namely serum TBIL and INR, were reliable for predicting the short-term mortality in patients with pregnancy-specific liver disease (followed up until 3 months after delivery or until death) (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). In the present study, TBIL and INR were statistically significant in univariate analysis (p\u0026thinsp;=\u0026thinsp;0.006 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, respectively), but they were eliminated in multivariate logistic regression analysis, which also suggested that increased TBIL and prolonged INR are potential risk factors for maternal mortality in AFLP; further prospective studies with larger sample sizes are warranted to explore the risk factors for maternal mortality in patients with AFLP.\u003c/p\u003e \u003cp\u003ePrevious clinical studies have shown that the MELD based on TBIL, Cr, and INR shows good predictive efficacy for acute liver failure and pregnancy-specific liver disease (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). A study conducted in China showed that the MELD was a good predictor of all complications of AFLP, including ascites, hepatic encephalopathy, sepsis, and renal insufficiency (all AUCs\u0026thinsp;\u0026gt;\u0026thinsp;0.8), and the optimal cut-off values were close to 30 (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Our study also verified that both the MELD and the new model show good predictive efficacy in predicting maternal mortality in AFLP (AUC\u0026thinsp;=\u0026thinsp;0.948 and 0.926, respectively).\u003c/p\u003e \u003cp\u003eOverall, compared with previous models based on only laboratory findings, the new predictive model for maternal mortality included one clinical symptom and two laboratory findings, which was more readily available, less expensive and easier to implement clinically. To the best of our knowledge, the symptom of nausea that we identified as an independent risk factor for AFLP has not been previously described.\u003c/p\u003e \u003cp\u003eThis study had a long duration of almost 10 years, and is the largest single-center clinical study on AFLP so far. The number of patients with AFLP enrolled in this study is only second to that in the multicenter study by Gao \u003cem\u003eet al\u003c/em\u003e., in which our hospital has participated in the past (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). As all patients with AFLP came from one single center, they received similar obstetric and multidisciplinary treatments after hospitalization, and some limitations of different medical levels were counter-balanced.\u003c/p\u003e \u003cp\u003eThere are some limitations to our research. Firstly, we did not evaluate the morbidity of AFLP owing to the deficiency of data on total pregnant women during the study period. Secondly, this was a single-center and small-sample study because of the rarity of AFLP, which might reduce the general applicability of our findings, although we had extended the study period to one decade and our study was a retrospective study. Thirdly, as Shandong Provincial Hospital is a tertiary referral center for critical patients in China, some patients with AFLP were referred to our hospital after severe postpartum complications, and their condition was relatively critical. The manner and timing of medical intervention during their prenatal treatment differed, which directly affected the prognosis of the patients.\u003c/p\u003e "},{"header":"Conclusions","content":" \u003cp\u003eWe identified a group of risk factors for maternal and fetal mortality among patients with AFLP and developed two new prognostic models. Both the new predictive model for maternal mortality and the MELD showed good predictive efficacy for maternal mortality in patients with acute fatty liver of pregnancy (the area under the curve\u0026thinsp;=\u0026thinsp;0.948 and 0.926, respectively), while the new predictive model for fetal mortality was superior to the model for end-stage liver disease in predicting fetal mortality (the area under the curve\u0026thinsp;=\u0026thinsp;0.893 and 0.694, respectively) with better sensitivity and specificity.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cp\u003eAFLP: acute fatty liver of pregnancy; MELD: model for end-stage liver disease; ALT: alanine aminotransferase; PT: prothrombin time; APTT: activated partial thromboplastin time; ROC: receiver operating characteristic; ICU: intensive care unit; INR: International normalized ratio; N: neutrophils; PLT: platelet count; BUN: blood urea nitrogen; Cr: blood creatinine; GLU: Glucose; AST: aspartate aminotransferase; GGT: gamma-glutamyl transpeptidase; ALK: Alkaline phosphatase; TBIL: total bilirubin; DBIL: direct bilirubin; Alb: albumin; DIC: disseminated intravascular coagulation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study has been performed in accordance with the Declaration of Helsinki and has been approved by Biomedical Research Committee of Shandong Provincial Hospital (approval no. SWYX: NO.2021-052), which waived the need for obtaining informed consent from the patients, because the study was an observational, retrospective study using a database from which the patients\u0026rsquo; identification information had been removed.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (no. 81903086); the National Natural Science Foundation of Shandong Province (no. ZR2019QH014); Shanghai Shenkang Hospital Development Center (no.SHDC12019125).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCW, MC and ZM contributed to conception and design of the study. CW and WF organized the database. MC performed the statistical analysis. ZM wrote the first draft of the manuscript. MM, JZ, QW and GQ revised sections of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the National Natural Science Foundation of China (no. 81903086) and the National Natural Science Foundation of Shandong Province (no. ZR2019QH014), which was received by Dr. Man Chen, and Shanghai Shenkang Hospital Development Center (no. SHDC12019125), which was received by Dr. Mei Meng.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKnight M, Nelson-Piercy C, Kurinczuk JJ, Spark P, Brocklehurst P. A prospective national study of acute fatty liver of pregnancy in the UK. Gut. 2008;57(7):951-6.\u003c/li\u003e\n\u003cli\u003eNatarajan SK, Ibdah JA. Role of 3-Hydroxy Fatty Acid-Induced Hepatic Lipotoxicity in Acute Fatty Liver of Pregnancy. International journal of molecular sciences. 2018;19(1).\u003c/li\u003e\n\u003cli\u003eHay JE. Liver disease in pregnancy. Hepatology (Baltimore, Md). 2008;47(3):1067-76.\u003c/li\u003e\n\u003cli\u003eKnox TA, Olans LB. Liver disease in pregnancy. The New England journal of medicine. 1996;335(8):569-76.\u003c/li\u003e\n\u003cli\u003eNelson DB, Yost NP, Cunningham FG. Acute fatty liver of pregnancy: clinical outcomes and expected duration of recovery. American journal of obstetrics and gynecology. 2013;209(5):456.e1-7.\u003c/li\u003e\n\u003cli\u003eMinakami H, Morikawa M, Yamada T, Yamada T, Akaishi R, Nishida R. Differentiation of acute fatty liver of pregnancy from syndrome of hemolysis, elevated liver enzymes and low platelet counts. The journal of obstetrics and gynaecology research. 2014;40(3):641-9.\u003c/li\u003e\n\u003cli\u003eXiong HF, Liu JY, Guo LM, Li XW. Acute fatty liver of pregnancy: over six months follow-up study of twenty-five patients. World journal of gastroenterology. 2015;21(6):1927-31.\u003c/li\u003e\n\u003cli\u003eGoel A, Ramakrishna B, Zachariah U, Ramachandran J, Eapen CE, Kurian G, et al. How accurate are the Swansea criteria to diagnose acute fatty liver of pregnancy in predicting hepatic microvesicular steatosis? Gut. 2011;60(1):138-9; author reply 9-40.\u003c/li\u003e\n\u003cli\u003eMalinchoc M, Kamath PS, Gordon FD, Peine CJ, Rank J, ter Borg PC. A model to predict poor survival in patients undergoing transjugular intrahepatic portosystemic shunts. Hepatology (Baltimore, Md). 2000;31(4):864-71.\u003c/li\u003e\n\u003cli\u003eKamath PS, Wiesner RH, Malinchoc M, Kremers W, Therneau TM, Kosberg CL, et al. A model to predict survival in patients with end-stage liver disease. Hepatology (Baltimore, Md). 2001;33(2):464-70.\u003c/li\u003e\n\u003cli\u003eMcPhail MJ. Improving MELD for use in acute liver failure. Journal of hepatology. 2011;54(6):1320; author reply -1.\u003c/li\u003e\n\u003cli\u003eMurali AR, Devarbhavi H, Venkatachala PR, Singh R, Sheth KA. Factors that predict 1-month mortality in patients with pregnancy-specific liver disease. Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association. 2014;12(1):109-13.\u003c/li\u003e\n\u003cli\u003eCh'ng CL, Morgan M, Hainsworth I, Kingham JG. Prospective study of liver dysfunction in pregnancy in Southwest Wales. Gut. 2002;51(6):876-80.\u003c/li\u003e\n\u003cli\u003eDavidson KM, Simpson LL, Knox TA, D'Alton ME. Acute fatty liver of pregnancy in triplet gestation. Obstetrics and gynecology. 1998;91(5 Pt 2):806-8.\u003c/li\u003e\n\u003cli\u003eWei Q, Zhang L, Liu X. Clinical diagnosis and treatment of acute fatty liver of pregnancy: a literature review and 11 new cases. The journal of obstetrics and gynaecology research. 2010;36(4):751-6.\u003c/li\u003e\n\u003cli\u003eLee NM, Brady CW. Liver disease in pregnancy. World journal of gastroenterology. 2009;15(8):897-906.\u003c/li\u003e\n\u003cli\u003eCheng N, Xiang T, Wu X, Li M, Xie Y, Zhang L. Acute fatty liver of pregnancy: a retrospective study of 32 cases in South China. The journal of maternal-fetal \u0026amp; neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstet. 2014;27(16):1693-7.\u003c/li\u003e\n\u003cli\u003eGao Q, Qu X, Chen X, Zhang J, Liu F, Tian S, et al. Outcomes and risk factors of patients with acute fatty liver of pregnancy: a multicentre retrospective study. Singapore medical journal. 2018;59(8):425-30.\u003c/li\u003e\n\u003cli\u003eBernal W, Hall C, Karvellas CJ, Auzinger G, Sizer E, Wendon J. Arterial ammonia and clinical risk factors for encephalopathy and intracranial hypertension in acute liver failure. Hepatology (Baltimore, Md). 2007;46(6):1844-52.\u003c/li\u003e\n\u003cli\u003eChen G, Huang K, Ji B, Chen C, Liu C, Wang X, et al. Acute fatty liver of pregnancy in a Chinese Tertiary Care Center: a retrospective study. Archives of gynecology and obstetrics. 2019;300(4):897-901.\u003c/li\u003e\n\u003cli\u003eRajasri AG, Srestha R, Mitchell J. Acute fatty liver of pregnancy (AFLP)--an overview. Journal of obstetrics and gynaecology : the journal of the Institute of Obstetrics and Gynaecology. 2007;27(3):237-40.\u003c/li\u003e\n\u003cli\u003eWang S, Li SL, Cao YX, Li YP, Meng JL, Wang XT. Noninvasive Swansea criteria are valuable alternatives for diagnosing acute fatty liver of pregnancy in a Chinese population. The journal of maternal-fetal \u0026amp; neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstet. 2017;30(24):2951-5.\u003c/li\u003e\n\u003cli\u003eDeruelle P, Coudoux E, Ego A, Houfflin-Debarge V, Codaccioni X, Subtil D. Risk factors for post-partum complications occurring after preeclampsia and HELLP syndrome. A study in 453 consecutive pregnancies. European journal of obstetrics, gynecology, and reproductive biology. 2006;125(1):59-65.\u003c/li\u003e\n\u003cli\u003eLi P, Lin S, Li L, Cui J, Wang Q, Zhou S, et al. Utility of MELD scoring system for assessing the prognosis of acute fatty liver of pregnancy. European journal of obstetrics, gynecology, and reproductive biology. 2019;240:161-6.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"AFLP, Maternal mortality, Fetal mortality, Risk factor, Prognostic model","lastPublishedDoi":"10.21203/rs.3.rs-590345/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-590345/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eAcute fatty liver of pregnancy (AFLP) is a rare but potentially life-threatening hepatic disorder that leads to considerable maternal and fetal mortality. A better understanding of the risk factors of AFLP is required.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We analyzed demographic characteristics, clinical symptoms, and laboratory findings of 106 patients with acute fatty liver of pregnancy. Risk factors for maternal and fetal mortality were analyzed by univariate and multivariate logistic regression analysis. The new models based on the multivariate logistic regression analysis and model for end-stage liver disease were tested for all patients with acute fatty liver of pregnancy. The receiver operating characteristic curve was applied to compare the prediction efficiency, sensitivity, and specificity of the two models.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003ePrenatal nausea (p = 0.037), prolonged prothrombin time (p = 0.003), and elevated serum creatinine (p = 0.003) were independent risk factors for maternal mortality in patients with acute fatty liver of pregnancy. The receiver operating characteristic curve showed that the area under the curve of the model for end-stage liver disease was 0.948, with a sensitivity of 100% and a specificity of 83.3%. The area under the curve of new model was 0.926, with a sensitivity of 90% and a specificity of\u0026nbsp;94.8%. Hepatic encephalopathy (p = 0.016) and thrombocytopenia (p = 0.001) were independent risk factors for fetal mortality. Using receiver operating characteristic curve, the area under the curve of the model for end-stage liver disease was 0.694, yielding a sensitivity of 68.8% and a specificity of 64.4%. The area under the curve of the new model was 0.893, yielding a sensitivity of 100% and a specificity of 73.3%. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eBoth the new predictive model for maternal mortality and the model for end-stage liver disease showed good predictive efficacy for maternal mortality in patients with acute fatty liver of pregnancy (the area under the curve = 0.948 and 0.926, respectively), and the new predictive model for fetal mortality was superior to the model for end-stage liver disease in predicting fetal mortality (the area under the curve = 0.893 and 0.694, respectively) with better sensitivity and specificity.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"Risk Factors for Maternal and Fetal Mortality in Acute Fatty Liver of Pregnancy and New Predictive Models","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-06-15 14:37:59","doi":"10.21203/rs.3.rs-590345/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3a8754fb-b9e5-48be-b0d3-c2d9373c254a","owner":[],"postedDate":"June 15th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":5018420,"name":"Maternal \u0026 Fetal Medicine"}],"tags":[],"updatedAt":"2021-06-29T03:59:11+00:00","versionOfRecord":[],"versionCreatedAt":"2021-06-15 14:37:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-590345","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-590345","identity":"rs-590345","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}