Risk factors for periventricular-intraventricular haemorrhage severity in preterm infants: A propensity score-matched analysis

Risk factors for periventricular-intraventricular haemorrhage severity in preterm infants: A propensity score-matched analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Risk factors for periventricular-intraventricular haemorrhage severity in preterm infants: A propensity score-matched analysis Jinglan Huang, Yan Wang, Tian Tian, Tingting Zhu, Jun Tang, Tao Xiong This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1937668/v2 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Jul, 2023 Read the published version in BMC Pediatrics → Version 2 posted 10 You are reading this latest preprint version Show more versions Abstract Background: Most previous studies comparing etiological studies in infants with and without periventricular-intraventricular haemorrhage (PV-IVH) concluded that younger gestational age (GA) was associated with a higher prevalence rate of PV-IVH. However, only few studies have examined the risk factors associated with the severity of PV-IVH after removing the influence of GA. Therefore, we investigated the risk factors apart from GA for PV-IVH severity in preterm infants less than 32 weeks. Methods: This was a retrospective case-control study of preterm infants born in West China Second Hospital with PV-IVH between 2009 and 2018. PV-IVH was defined using cranial ultrasound screening. Preterm infants with PV-IVH were divided into mild and severe groups. Both groups were matched in a 1:1 ratio using propensity score calculated from GA. Variables were collected from infant–mother pairs. A stepwise forward multivariate logistic regression model was adopted to select factors that affected the severity of PV-IVH in preterm infants. Results: A total of 3,783 preterm infants with PV-IVH were included. The total incidence of PV-IVH in preterm infants was 15.58%, and the incidence of PV-IVH of grades I, II, III, and IV was 2.50%, 9.52%, 3.13%, and 0.42%, respectively. The mortality of mild and severe PV-IVH was 0.33% and 3.25%, respectively. We matched 315 infants with severe PV-IVH with 315 infants with mild PV-IVH. The results suggested that early-onset sepsis (odds ratio [OR] 2.50, 95% confidence interval [CI]: 1.50–4.16), thrombocytopenia (OR 2.37, 95% CI: 1.39–4.04), multiple gestations (OR 1.69, 95% CI: 1.15–2.49), invasive mechanical ventilation (OR 1.59, 95% CI: 1.10–2.31), and magnesium sulphate use (OR 1.46, 95% CI: 1.01–2.10) were associated with severe PV-IVH. Female sex (OR 0.65, 95% CI: 0.46–0.91) was a protective factor against severe PV-IVH. Conclusions : Early-onset sepsis, thrombocytopenia, multiple gestations, invasive mechanical ventilation, magnesium sulphate use, and male sex contributed to severe PV-IVH in preterm infants regardless of GA, these risk factors may combine to predict the incidence of PV-IVH in preterm infants. preterm infants periventricular-intraventricular haemorrhage gestational age propensity score risk factor Figures Figure 1 Background Premature births and their consequences are significant clinical and social problems. Periventricular-intraventricular haemorrhage (PV-IVH) is a typical intracranial lesion in preterm infants[ 1 ], and the prognosis is mainly dependent on its severity[ 2 ]. A previous study suggests that preterm infants with mild PV-IVH are at a higher risk of cerebral palsy compared to preterm infants without PV-IVH[ 2 ]. As the grade of PV-IVH increases, the degree of neurological damage also increases; consequently severe PV-IVH (grades III and IV) is an independent risk factor for death and neurological sequelae[ 2 , 3 ]. Survivors of severe PV-IVH often experience cognitive, language, and motor deficits, requiring extensive and early rehabilitation interventions to improve neurological outcomes[ 4 ]. Severe PV-IVH results in a heavy burden on the affected infants, their families, and society. Therefore, identifying the risk factors for different degrees of PV-IVH is essential and may facilitate a better understanding of the PV-IVH aetiology. PV-IVH occurrence, particularly severe PV-IVH, is inversely related to gestational age (GA)[ 5 – 7 ]. The reasons include poor coagulation, fragile microvasculature in the germinal matrix, lack of autoregulatory mechanisms in cerebral blood flow, and increased complications and treatments associated with the small size of preterm infants[ 8 ]. GA, the most influential and immutable factor, has been considered routinely in previous PV-IVH studies, which may have eliminated the effects of other factors. Therefore, exploring the other adjustable factors for PV-IVH is essential. Furthermore, current studies have only compared infants with and without PV-IVH in aetiology research. Only few studies have examined the different risk factors between severe and mild PV-IVH after removing the influence of GA. Therefore, using propensity score matching for GA, this study was performed to explore the different risk factors for severe and mild PV-IVH. Materials And Methods Study population West China Second Hospital is a crucial tertiary hospital in Southwest China, where numerous critically ill newborns are treated in the neonatal intensive care unit. Our medical centre has 200 beds, including 100 neonatal intensive care unit cots and 100 cots in the general ward. Approximately 4,000 preterm infants are admitted to our centre each year. Per the American Academy of Neurology practice parameters and Chinese practice guidelines, a cranial ultrasound is performed on all preterm infants admitted to our neonatal intensive care unit. In this study, we selected inborn preterm infants at less than 32 weeks of gestation with PV-IVH between 2009 and 2018 to investigate the aetiologic differences between severe and mild cases. Diagnosis of PV-IVH PV-IVH grading and grouping We referred to the Papile grading system as follows [ 9 ]: grade I: haemorrhage restricted to the subependymal; grade II: intraventricular haemorrhage without ventricular dilatation; grade III: extended haemorrhage with ventricular dilatation; and grade IV: haemorrhage within the ventricular system and parenchymal. Grades I and II were regarded as mild PV-IVH, and grades III and IV were regarded as severe PV-IVH. If the highest PV-IVH grade detected on the serial cranial ultrasound was grade III or IV, the infants were included in the severe PV-IVH group (case group). Otherwise, infants with grades I or II were included in the control group (mild cases). Cranial ultrasound screening Serial cranial ultrasound was performed by paediatric sonographers as described in our previous study[ 8 ]. The initial screening was completed within 72 hours after birth. If no bleeding was detected, the screening was repeated at 7, 14, and 42 days. If bleeding was observed, then a repeat ultrasound was performed weekly until at least two consecutive scans demonstrated stabilisation or resolution of bleeding. The paediatric sonographers received uniform PV-IVH screening training and were blinded to the neonates’ clinical information to ensure consistent and reliable reporting. Data collection This study was a retrospective case-control study, and data were obtained from the patient database of our medical centre. We selected the possible risk factors for this study after reviewing numerous relevant studies on PV-IVH risk factors. All methods in this study adhered to the applicable guidelines and regulations. The data on variables collected in this study were consistent with those in our previous study[ 8 ] and are described as follows: 1) infant baseline characteristics including GA, birth weight (BW), sex, multiple gestations, primigravidity, primiparity, vaginal delivery, in vitro fertilisation, and asphyxia (umbilical artery pH < 7.0); 2) complications including pneumonia, respiratory distress syndrome, apnoea (i.e., respiratory arrest for more than 20 s), patent ductus arteriosus, scleroderma, anaemia (i.e., venous haemoglobin < 130 g/L or peripheral blood haemoglobin 25 × 10 9 cells/L, C-reactive protein level > 8 mg/L, platelet count 70 seconds); 4) treatments received including non-invasive mechanical ventilation (nasal intermittent positive pressure ventilation, bilevel positive airway pressure, or continuous positive airway pressure without endotracheal intubation), invasive mechanical ventilation (conventional ventilation or high-frequency oscillatory ventilation after endotracheal intubation), and administration of pulmonary surfactant, dopamine, or antibiotics; and 5) maternal characteristics including a history of foetal abnormalities (e.g., premature birth, teras, or hydatidiform mole), parity, gravidity, gestational hypertension, premature membrane rupture, and intrauterine infection (histological chorioamnionitis). The history also included placental abnormality (e.g., placenta previa or placental abruption), anaemia (i.e., blood haemoglobin < 100 g/L), intrahepatic cholestasis of pregnancy, and amniotic fluid contamination (also known as meconium-stained amniotic fluid). Abnormal foetal position, lower genital tract infection (i.e., culture-positive vaginal and cervical secretions), foetal intrauterine distress, antibiotic, dexamethasone (complete and incomplete course), and magnesium sulphate use (for preeclampsia/eclampsia) were considered as part of the maternal history. Cases with incomplete data were not included in the final analysis. Statistical analysis We used SPSS software (version 26, IBM Corp., Armonk, NY, USA) to perform the statistical analyses. First, infants were matched in a 1:1 ratio using the propensity score calculated from the GA. The propensity score was calculated by fitting a logistic regression model. Nearest-neighbor matching within a specified calliper width (a calliper of 0.2 standard deviations of the logit function of the propensity scores) was used. The first randomly selected infant in the severe PV-IVH group was matched to the patient in the mild PV-IVH group with the closest propensity score. If multiple infants in the mild PV-IVH group were equally close to this infant in the severe PV-IVH group, then one of the infants in the mild PV-IVH group was randomly selected for matching with this infant treated in the severe PV-IVH group. This process was repeated until all possible matches were formed. If for a given infant in the severe PV-IVH group, no available patient in the mild PV-IVH group was within the specified calliper width, then that infant in the severe PV-IVH group was excluded from the matched sample. Similarly, unmatched infants in the mild PV-IVH group were excluded from the matched sample. The continuous variables are presented as the mean ± standard deviation for normally distributed data, and independent sample t-tests were performed. The Wilcoxon test was used for continuous variables with a skewed distribution, which are presented as medians with interquartile ranges. Chi-square or Fisher’s exact tests were used to compare categorical variables. Correlation matrix analysis was performed for variables with statistical differences. Variables with correlation coefficients greater than 0.4 were selectively excluded. Finally, the variables that differed significantly between groups and without significant correlations were included in the multivariate analysis. Potential variables were used in a backward stepwise logistic regression analysis to calculate the adjusted odds ratios (ORs) and corresponding 95% confidence intervals (CIs). All hypothesis tests were two-tailed. Statistical significance was set at P < 0.05. Results A total of 3,783 inborn premature infants (in West China Second Hospital) were diagnosed with PV-IVH between 2009 and 2018. The total incidence of PV-IVH in the preterm infants was 15.58%, and the incidence of PV-IVH of grades I, II, III, and IV was 2.50%, 9.52%, 3.13%, and 0.42%, respectively. The mortality of mild and severe PV-IVH was 0.33% and 3.25%, respectively. Among all the included preterm infants with PV-IVH, the proportion of infants with GA less than 28 weeks, 28 weeks to less than 30 weeks, and 30 weeks to less than 32 weeks was 55.6%, 40.1%, and 28%, respectively. Ultimately, we included 630 premature infants with PV-IVH: 315 with mild PV-IVH and 315 with severe PV-IVH (Fig. 1). Almost all of these preterm infants were diagnosed with PV-IVH within 1 week, and all the variables in our study were collected before PV-IVH onset. GA and BW presented a skewed distribution, with a median GA of 30 (29–31) weeks and median BW of 1,420 (1,220–1,680) g and 1,390 (1,170–1,630) g for the mild and severe groups, respectively. The groups comprised 353 boys and 277 girls. General information regarding preterm infants with PV-IVH is presented in Table 1. We found no significant differences in GA, BW, primigravidity, primiparity, vaginal delivery, in vitro fertilisation, premature rupture of membranes, placental abruption, and asphyxia. Patients in the severe PV-IVH group were more likely to be male, with a greater incidence of multiple gestations and amniotic fluid pollution. Table 1. Univariate analysis of the basic information of preterm infants with PV–IVH. Variables Mild PV-IVH (n=315) Severe PV-IVH (n=315) χ 2 P Median gestational age (IQR) — wk 30 (29-31) 30 (29-31) Z = 0.747 0.388 Median birth weight (IQR) — g 1420 (1220-1680) 1390 (1170-1630) Z = 0.134 0.715 Female (n, %) 152(48.3) 125 (39.7) 4.697 0.03 Primigravidity (n, %) 128 (40.6) 147(46.7) 2.330 0.127 Primiparity (n, %) 226(71.7) 224 (71.1) 0.031 0.860 Multiple gestations (n, %) 70 (22.2) 96 (30.5) 2.529 0.019 Vaginal delivery (n, %) 138 (43.8) 134(42.4) 0.104 0.748 In vitro fertilization (n, %) 21(6.7) 28(8.9) 1.084 0.298 Premature rupture of membranes (n, %) 137(43.5) 151 (47.9) 1.254 0.264 Placental abruption (n, %) 46 (14.6) 64(20.3) 3.569 0.059 Amniotic fluid pollution (n, %) 27（8.6） 43（13.7） 4.114 0.043 Asphyxia (n, %) 101(32.1) 120 (38.1) 2.516 0.113 PV–IVH periventricular–intraventricular hemorrhage. Table 2 shows the complications and laboratory tests of preterm infants with PV-IVH. The early-onset sepsis rate was higher in infants with severe PV-IVH than with those with mild PV-IVH. The preterm infants with white blood cell count > 25 ×10 9 /L or 8 mg/L, thrombocytopenia, and abnormal coagulation were more likely to have severe PV-IVH than mild PV-IVH. There were no significant differences between the mild and severe PV-IVH groups in pneumonia, respiratory distress syndrome, apnoea, patent ductus arteriosus, scleroderma, anaemia, electrolyte disorder, and PH<7.3. Table 2. Univariate analysis complications and laboratory test of preterm infants with PV–IVH. Variables Mild PV-IVH (n=315) Severe PV-IVH (n=315) χ 2 P Pneumonia (n, %) 252 (80.0) 258 (81.9) 0.371 0.543 Respiratory distress syndrome (n, %) 135(42.9) 146 (46.3) 0.777 0.378 Apnea (n, %) 109 (34.6) 106 (33.7) 0.064 0.801 Patent ductus arteriosus (n, %) 78 (24.8) 80(25.4) 0.034 0.854 Scleredema (n, %) 31(9.8) 31 (9.8) 0.00 1.00 Anemia (n, %) 108 (34.3) 124(39.4) 1.747 0.186 Early-onset sepsis (n, %) 27(8.6) 73 (23.2) 25.152 0.00 Electrolyte disorder (n, %) 91（28.9） 73（23.3） 2.671 0.102 WBC > 25 ×10 9 /L or 8 mg/L (n, %) 62 (19.7) 118(37.5) 24.391 0.00 Thrombocytopenia (n, %) 24 (7.6) 70 (22.2) 26.458 0.00 Abnormal coagulation (n, %) 132 (41.9) 159 (50.5) 4.656 0.031 PH<7.30 (n, %) 78(24.8) 72(22.9) 1.292 0.524 PV–IVH periventricular–intraventricular haemorrhage. W BC white blood cell, CRP C-reactive protein. aBaseline values were tested before or within PV–IVH diagnosis. Treatments administered to preterm infants with PV-IVH are shown in Table 3. Our results showed that infants with severe PV-IVH required more invasive and non-invasive mechanical ventilation, pulmonary surfactant, and antibiotics. The use of dopamine and aminophylline did not differ between groups. Table 3. Univariate analysis of treatment of preterm infants with PV–IVH. Variables Mild PV-IVH (n=315) Severe PV-IVH (n=315) χ2 P Invasive mechanical ventilation (n, %) 80 (25.4) 131 (41.6) 18.535 0.00 Non-invasive mechanical ventilation (n, %) 10(3.2) 63 (20.0) 45.523 0.00 Pulmonary surfactant (n, %) 142 (45.1) 172(54.6) 5.714 0.017 Dopamine (n, %) 35(11.1) 48(15.2) 2.245 0.126 Antibiotics (n, %) 234 (74.3) 270 (85.7) 12.857 0.00 Aminophylline (n, %) 132(41.9) 117(37.1) 1.494 0.222 PV–IVH periventricular–intraventricular hemorrhage. Table 4 shows the maternal characteristics of preterm infants with PV-IVH. We found that severe PV-IVH was associated with maternal intrahepatic cholestasis of pregnancy, chorioamnionitis, lower genital tract infection, magnesium sulphate or antibiotic use, and a white blood cell count >15×10 9 /L. Table 4. Univariate analysis of maternal characters in PV-IVH premature infants. Variables Mild PV-IVH (n=315) Se vere PV-IVH (n=315) χ 2 P History of fetal abnormalities (n, %) 45(14.3) 31 (9.8) 2.933 0.087 History of abortion (n, %) 149(47.3) 151（47.98） 0.025 0.225 History of cesarean section (n, %) 78（24.8） 99（31.4） 3.465 0.063 Pre-eclampsia (n, %) 60（19.0） 43（13.7） 3.354 0.067 Gestational hypertension (n, %) 11 (3.5) 13(4.1) 0.173 0.677 Gestational diabetes (n, %) 78（24.8） 70（22.2） 0.565 0.452 Intrahepatic cholestasis of pregnancy (n, %) 31(9.8) 48 (15.2) 4.183 0.041 Pregnancy anemia (n, %) 78 (24.8) 86(27.3) 0.528 0.468 Chorioamnitis (n, %) 85（27.0） 110（34.9） 4.642 0.031 Lower genital tract infections (n, %) 67(21.3) 106 (33.7) 12.12 0.00 Magnesium sulfate (n, %) 202（64.1） 234（74.3） 7.627 0.006 Dexamethasone (n, %) 244（77.5） 245（77.8） 0.009 0.924 Antibiotics (n, %) 120（38.1） 154（48.9） 7.446 0.006 WBC > 15× 10 9 /L (n, %) 57（18.1） 87（27.6） 8.102 0.004 Platelets<100× 10 9 /L (n, %) 18（5.7） 13（4.1） 0.848 0.357 PV–IVH periventricular–intraventricular hemorrhage. In the univariate analysis, 12 significant variables were obtained and included in the multivariate analysis after stepwise elimination and clinical screening. The results (Table 5), adjusted for abnormal coagulation, pulmonary surfactants, intrahepatic cholestasis of pregnancy, amniotic fluid pollution, and maternal WBC > 15× 10 9 /L, chorioamnionitis), suggested that early-onset sepsis (OR 2.5, 95% CI: 1.50–4.16), thrombocytopenia (OR 2.37, 95% CI: 1.39–4.04), multiple gestations (OR 1.69, 95% CI: 1.15–2.49), invasive mechanical ventilation (OR 1.59, 95% CI: 1.10–2.31), and magnesium sulphate use (OR 1.46, 95% CI: 1.01–2.10) were independently associated with severe PV-IVH. Female sex (OR 0.65, 95% CI: 0.46–0.91) was an independent protective factor against severe PV-IVH. Table 5. Factors associated with PV-IVH severity in preterm infants. Variables β SE Wals P aOR 95% CI Early-onset sepsis 0.914 0.26 12.349 ＜0.001 2.50 1.50-4.16 Thrombocytopenia 0.863 0.273 10.034 0.002 2.37 1.39-4.04 Multiple gestations 0.526 0.197 7.127 0.008 1.69 1.15-2.49 Invasive mechanical ventilation 0.465 0.19 5.956 0.015 1.59 1.10-2.31 Magnesium sulfate 0.378 0.187 4.106 0.043 1.46 1.01-2.10 Female (n, %) -0.437 0.173 6.399 0.011 0.65 0.46-0.91 PV–IVH periventricular–intraventricular haemorrhage, aOR adjusted odds ratio, 95% CI 95% confidence interval. Adjusted for: abnormal coagulation, pulmonary surfactants, intrahepatic cholestasis of pregnancy, amniotic fluid pollution, maternal WBC > 15× 10 9 /L, chorioamnitis. Discussion GA, the most influential factor, is inversely correlated with the occurrence of PV-IVH[6, 8]. In this study, we conducted a propensity score-matched analysis to eliminate the influence of GA. To the best of our knowledge, this is the first study to identify the risk factors besides GA that contribute to the differences between severe and mild PV-IVH. Our study helps clarify the aetiological differences between the degrees of PV-IVH severity, which may be helpful for future clinical interventions. PV-IVH of all premature infants included in this study was diagnosed within 7 days of birth, and all risk factors occurred before the diagnosis of PV-IVH. Therefore, it is reasonable to believe that the risk factors we obtained may lead to severe PV-IVH, given that these risk factors have also been discussed in previous studies. Early-onset sepsis can cause an inflammatory cytokine storm. Our research shows that early-onset sepsis is a significant cause of severe PV-IVH, consistent with previous studies[5, 8, 10, 11]. Inflammatory factors detected in the blood of infants with PV-IVH were significantly higher than those in healthy neonates, correlating with IVH severity [5, 8, 10, 11]. The inflammatory factors damage the blood-brain barrier and brain’s blood vessels, increasing the blood vessels’ vulnerability to damage and rupture[12]. Inflammatory factors can also increase the oxygen consumption of brain tissue and disrupt the blood pressure regulation function of the brain, resulting in severe fluctuations in cerebral perfusion pressure in premature infants and subsequent PV-IVH[13, 14]. A systematic review suggested that thrombocytopenia is a risk factor for PV-IVH in preterm infants[15], which is consistent with our findings. Since thrombocyte counts regulate haemostatic function, thrombocytopenia is associated with a bleeding tendency, including PV-IVH. In addition, thrombocytopenia may be caused by infection and other abnormal coagulation events[16, 17], which may be risk factors for PV-IVH. Our findings are consistent with previous studies that identified multiple births as a risk factor for severe PV-IVH[18, 19]. A systematic review found that appropriate hormone therapy helped to reduce the incidence of respiratory distress syndrome and PV-IVH[20]. However, multiple births were associated with lower hormone levels compared with single pregnancies with the same dose regimen of prenatal hormones[20, 21]. This association may explain why PV-IVH is more likely to occur in multiple pregnancies. Our study suggests invasive mechanical ventilation is a risk factor for severe PV-IVH. Previous studies have shown that this may be related to mechanical ventilation, which disrupts cerebral blood flow and induces a local inflammatory response[13, 22]. Another study found that mechanical ventilation can cause lung damage, generate adenosine triphosphate, activate P2Y1 receptors, and increase dopamine release, causing or aggravating brain damage. This provides a possible explanation for why premature infants are prone to PV-IVH after mechanical ventilation[23]. Our study showed that antenatal magnesium sulphate use is a risk factor for severe PV-IVH in preterm infants. However, no consensus has been reached in the literature regarding the relationship between antenatal magnesium sulphate use and PV-IVH. The findings of a previous study suggested that PV-IVH may be related to high-dose magnesium sulphate exposure, supporting the results of our study[24]. However, another study suggested that prenatal magnesium sulphate use can reduce the incidence of PV-IVH in neonates, which may be related to the reduction in the cerebral metabolic load induced by magnesium sulphate[25]. Studies have shown that the protective or damaging effects of magnesium sulphate may be related to prenatal doses[26]. We found that the female sex was an independent protective factor against severe PV-IVH, supported by a previous study [27, 28]. The study suggests that male newborns are more susceptible to catecholamines and have a higher cerebral blood flow than female infants. In addition, sex differences in inflammatory factor gene polymorphisms and differences in hormone levels may explain why males are more prone to PV-IVH than females [27]. Our study had some limitations. First, due to our strict GA matching criteria, median GA was 30 (29–31) weeks, and a sufficient number of preterm infants with lower GA were not available to participate in this study. Hence, caution should be exercised when applying these findings to preterm infants with lower GA. Further research into lower GA preterm infants is warranted. Second, we found a high incidence of PV-IVH in preterm infants in this study, reflecting that PV-IVH is an important cause affecting the prognosis of preterm infants in this region and needs further study. In addition, because this was a retrospective clinical study, there was an uncontrollable recall bias. Hence, again, caution should be exercised when generalising our results to other settings, as this was a single-centre study conducted in China. Lastly, although the paediatric sonographers in this study received uniform PV-IVH screening training and were blinded to the clinical information, detection bias might have existed between paediatric sonographers. Conclusions Our findings suggest that early-onset sepsis, thrombocytopenia, multiple gestations, invasive mechanical ventilation, magnesium sulphate use, and male sex contribute to severe PV-IVH in preterm infants. Although this study has its limitations, the combination of these risk factors should be considered when predicting the incidence of PV-IVH. Abbreviations Birth weight (BW) Confidence interval (CI) Gestational age (GA) Periventricular-intraventricular haemorrhage (PV-IVH) Odds ratio (OR) Declarations Ethics approval and consent to participate: This study was approved by the Medical Ethics Committee of West China Second University Hospital (approval number: 20PJ071) and performed per the Declaration of Helsinki. Written informed consent was obtained from the parents or guardians of each infant. Consent for publication: Not applicable. Availability of data and materials The data that support the findings of this study are available from West China Second Hospital, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the corresponding authors upon reasonable request and with permission of West China Second Hospital. Competing interests: The authors declare no conflicts of interest. Funding: This research was funded by grants from the National Key Research and Development Program of China (No.2021YFC2701701), the Science and Technology Bureau of Sichuan Province (2020YJ0298), Health Commission of Sichuan Province (20PJ071), and China International Medical Foundation (Z-2019-41-2101-04). Authors’ contributions: JH, YW and TX drafted and revised the manuscript. All authors were involved with study design and carried out data collection. All authors agree to this final submission. Acknowledgements: Not applicable. References Yeo KT, Thomas R, Chow SS, Bolisetty S, Haslam R, Tarnow-Mordi W, et al. Improving incidence trends of severe intraventricular haemorrhages in preterm infants <32 weeks gestation: a cohort study. Arch Dis Child Fetal Neonatal Ed. 2020;105(2):145-50. Hollebrandse NL, Spittle AJ, Burnett AC, Anderson PJ, Roberts G, Doyle LW, et al. School-age outcomes following intraventricular haemorrhage in infants born extremely preterm. 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Mechanical ventilation induces lung and brain injury through ATP production, P2Y1 receptor activation and dopamine release. Bioengineered. 2022;13(2):2346-59. Mittendorf R, Dammann O, Lee KS. Brain lesions in newborns exposed to high-dose magnesium sulfate during preterm labor. J Perinatol. 2006;26(1):57-63. Bansal V, Desai A. Efficacy of Antenatal Magnesium Sulfate for Neuroprotection in Extreme Prematurity: A Comparative Observational Study. J Obstet Gynaecol India. 2022:72(Suppl 1):36-47. Mittendorf R, Pryde PG. A review of the role for magnesium sulphate in preterm labour. BJOG. 2005;112 Suppl 1:84-8. Mohamed MA, Aly H. Male gender is associated with intraventricular hemorrhage. Pediatrics. 2010;125(2):e333-9. Gagliardi L, Rusconi F, Reichman B, Adams M, Modi N, Lehtonen L, et al. Neonatal outcomes of extremely preterm twins by sex pairing: an international cohort study. Arch Dis Child Fetal Neonatal Ed. 2021;106(1):17-24. Additional Declarations No competing interests reported. Supplementary Files supplementaryfile.xlsx Cite Share Download PDF Status: Published Journal Publication published 05 Jul, 2023 Read the published version in BMC Pediatrics → Version 2 posted Editorial decision: Major revision 11 Jan, 2023 Reviews received at journal 10 Dec, 2022 Reviewers agreed at journal 29 Nov, 2022 Reviews received at journal 25 Nov, 2022 Reviewers agreed at journal 23 Nov, 2022 Reviewers invited by journal 10 Nov, 2022 Editor assigned by journal 10 Nov, 2022 Editor invited by journal 03 Nov, 2022 Submission checks completed at journal 03 Nov, 2022 First submitted to journal 08 Oct, 2022 You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-1937668","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[{"code":1,"date":"2022-08-11 21:08:55","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 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Center","correspondingAuthor":false,"prefix":"","firstName":"Tian","middleName":"","lastName":"Tian","suffix":""},{"id":159427004,"identity":"8044dc1f-f3cd-467f-9a6d-fccb24867e1e","order_by":3,"name":"Tingting Zhu","email":"","orcid":"","institution":"Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Tingting","middleName":"","lastName":"Zhu","suffix":""},{"id":159427005,"identity":"c04ab212-ec95-4049-9d5e-1f673de8c499","order_by":4,"name":"Jun Tang","email":"","orcid":"","institution":"Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Tang","suffix":""},{"id":159427006,"identity":"9ca90af6-1c5e-4cf0-b095-d001f40fc86c","order_by":5,"name":"Tao Xiong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAw0lEQVRIiWNgGAWjYNACAyBmb2x88IEYxTxwLTyHmw1nEK8FBCTS26Q5iNFiz374ADNPgU2efOTDBmkGBjs53QZCtvCkJTDOMEgrNryd2GBcwJBsbHaAoMNyDBg+GBxO3Dg7sSF5BsOBxG0EtfC/MWBIAGmZebDhMA9RWiSgtsyXYGxsJk7LjWdgvyRu4ElsBjKI8At7fzIwxP7YJM5vP/78x4cKOzmCWkC6foBIA7BKA8LKEUC+gRTVo2AUjIJRMKIAAJTuQF6P1fbKAAAAAElFTkSuQmCC","orcid":"","institution":"Sichuan University","correspondingAuthor":true,"prefix":"","firstName":"Tao","middleName":"","lastName":"Xiong","suffix":""}],"badges":[],"createdAt":"2022-08-07 09:31:05","currentVersionCode":2,"declarations":"","doi":"10.21203/rs.3.rs-1937668/v2","doiUrl":"https://doi.org/10.21203/rs.3.rs-1937668/v2","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12887-023-04114-x","type":"published","date":"2023-07-05T21:30:17+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":30269608,"identity":"fe706b3f-d018-4fa2-892b-c3bf94fe6089","added_by":"auto","created_at":"2022-12-13 16:19:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":34930,"visible":true,"origin":"","legend":"\u003cp\u003eFlow Chart in selection of preterm infants with PV-IVH. \u003cem\u003ePV–IVH \u003c/em\u003eperiventricular–intraventricular haemorrhage.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-1937668/v2/03bd90439b7c555a81fcba00.png"},{"id":44736988,"identity":"4cee80d8-b9ca-4daf-9437-350b622b52a9","added_by":"auto","created_at":"2023-10-16 22:32:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":651722,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1937668/v2/b30f0be2-d79f-4e37-931b-1c73b1f56ade.pdf"},{"id":30269609,"identity":"c172cb96-3a03-45dc-abfd-965b04f62b0b","added_by":"auto","created_at":"2022-12-13 16:19:28","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":133426,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfile.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1937668/v2/6f64e14caf794b5fb3e2af2f.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Risk factors for periventricular-intraventricular haemorrhage severity in preterm infants: A propensity score-matched analysis","fulltext":[{"header":"Background","content":"\u003cp\u003ePremature births and their consequences are significant clinical and social problems. Periventricular-intraventricular haemorrhage (PV-IVH) is a typical intracranial lesion in preterm infants[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], and the prognosis is mainly dependent on its severity[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. A previous study suggests that preterm infants with mild PV-IVH are at a higher risk of cerebral palsy compared to preterm infants without PV-IVH[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. As the grade of PV-IVH increases, the degree of neurological damage also increases; consequently severe PV-IVH (grades III and IV) is an independent risk factor for death and neurological sequelae[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Survivors of severe PV-IVH often experience cognitive, language, and motor deficits, requiring extensive and early rehabilitation interventions to improve neurological outcomes[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Severe PV-IVH results in a heavy burden on the affected infants, their families, and society. Therefore, identifying the risk factors for different degrees of PV-IVH is essential and may facilitate a better understanding of the PV-IVH aetiology.\u003c/p\u003e \u003cp\u003ePV-IVH occurrence, particularly severe PV-IVH, is inversely related to gestational age (GA)[\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The reasons include poor coagulation, fragile microvasculature in the germinal matrix, lack of autoregulatory mechanisms in cerebral blood flow, and increased complications and treatments associated with the small size of preterm infants[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. GA, the most influential and immutable factor, has been considered routinely in previous PV-IVH studies, which may have eliminated the effects of other factors. Therefore, exploring the other adjustable factors for PV-IVH is essential. Furthermore, current studies have only compared infants with and without PV-IVH in aetiology research. Only few studies have examined the different risk factors between severe and mild PV-IVH after removing the influence of GA. Therefore, using propensity score matching for GA, this study was performed to explore the different risk factors for severe and mild PV-IVH.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003eWest China Second Hospital is a crucial tertiary hospital in Southwest China, where numerous critically ill newborns are treated in the neonatal intensive care unit. Our medical centre has 200 beds, including 100 neonatal intensive care unit cots and 100 cots in the general ward. Approximately 4,000 preterm infants are admitted to our centre each year. Per the American Academy of Neurology practice parameters and Chinese practice guidelines, a cranial ultrasound is performed on all preterm infants admitted to our neonatal intensive care unit. In this study, we selected inborn preterm infants at less than 32 weeks of gestation with PV-IVH between 2009 and 2018 to investigate the aetiologic differences between severe and mild cases.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDiagnosis of PV-IVH\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003ePV-IVH grading and grouping\u003c/h2\u003e \u003cp\u003eWe referred to the Papile grading system as follows [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]: grade I: haemorrhage restricted to the subependymal; grade II: intraventricular haemorrhage without ventricular dilatation; grade III: extended haemorrhage with ventricular dilatation; and grade IV: haemorrhage within the ventricular system and parenchymal. Grades I and II were regarded as mild PV-IVH, and grades III and IV were regarded as severe PV-IVH. If the highest PV-IVH grade detected on the serial cranial ultrasound was grade III or IV, the infants were included in the severe PV-IVH group (case group). Otherwise, infants with grades I or II were included in the control group (mild cases).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eCranial ultrasound screening\u003c/h2\u003e \u003cp\u003eSerial cranial ultrasound was performed by paediatric sonographers as described in our previous study[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The initial screening was completed within 72 hours after birth. If no bleeding was detected, the screening was repeated at 7, 14, and 42 days. If bleeding was observed, then a repeat ultrasound was performed weekly until at least two consecutive scans demonstrated stabilisation or resolution of bleeding. The paediatric sonographers received uniform PV-IVH screening training and were blinded to the neonates\u0026rsquo; clinical information to ensure consistent and reliable reporting.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003e This study was a retrospective case-control study, and data were obtained from the patient database of our medical centre. We selected the possible risk factors for this study after reviewing numerous relevant studies on PV-IVH risk factors. All methods in this study adhered to the applicable guidelines and regulations.\u003c/p\u003e \u003cp\u003eThe data on variables collected in this study were consistent with those in our previous study[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and are described as follows: 1) infant baseline characteristics including GA, birth weight (BW), sex, multiple gestations, primigravidity, primiparity, vaginal delivery, \u003cem\u003ein vitro\u003c/em\u003e fertilisation, and asphyxia (umbilical artery pH\u0026thinsp;\u0026lt;\u0026thinsp;7.0); 2) complications including pneumonia, respiratory distress syndrome, apnoea (i.e., respiratory arrest for more than 20 s), patent ductus arteriosus, scleroderma, anaemia (i.e., venous haemoglobin\u0026thinsp;\u0026lt;\u0026thinsp;130 g/L or peripheral blood haemoglobin\u0026thinsp;\u0026lt;\u0026thinsp;145 g/L), and early-onset sepsis; 3) laboratory test results including electrolyte disorder, white blood cell count\u0026thinsp;\u0026gt;\u0026thinsp;25 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e cells/L, C-reactive protein level\u0026thinsp;\u0026gt;\u0026thinsp;8 mg/L, platelet count\u0026thinsp;\u0026lt;\u0026thinsp;100\u0026times;10\u003csup\u003e9\u003c/sup\u003e cells/L, and abnormal coagulation (i.e., activated partial thromboplastin time\u0026thinsp;\u0026gt;\u0026thinsp;70 seconds); 4) treatments received including non-invasive mechanical ventilation (nasal intermittent positive pressure ventilation, bilevel positive airway pressure, or continuous positive airway pressure without endotracheal intubation), invasive mechanical ventilation (conventional ventilation or high-frequency oscillatory ventilation after endotracheal intubation), and administration of pulmonary surfactant, dopamine, or antibiotics; and 5) maternal characteristics including a history of foetal abnormalities (e.g., premature birth, teras, or hydatidiform mole), parity, gravidity, gestational hypertension, premature membrane rupture, and intrauterine infection (histological chorioamnionitis). The history also included placental abnormality (e.g., placenta previa or placental abruption), anaemia (i.e., blood haemoglobin\u0026thinsp;\u0026lt;\u0026thinsp;100 g/L), intrahepatic cholestasis of pregnancy, and amniotic fluid contamination (also known as meconium-stained amniotic fluid). Abnormal foetal position, lower genital tract infection (i.e., culture-positive vaginal and cervical secretions), foetal intrauterine distress, antibiotic, dexamethasone (complete and incomplete course), and magnesium sulphate use (for preeclampsia/eclampsia) were considered as part of the maternal history. Cases with incomplete data were not included in the final analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eWe used SPSS software (version 26, IBM Corp., Armonk, NY, USA) to perform the statistical analyses. First, infants were matched in a 1:1 ratio using the propensity score calculated from the GA. The propensity score was calculated by fitting a logistic regression model. Nearest-neighbor matching within a specified calliper width (a calliper of 0.2 standard deviations of the logit function of the propensity scores) was used. The first randomly selected infant in the severe PV-IVH group was matched to the patient in the mild PV-IVH group with the closest propensity score. If multiple infants in the mild PV-IVH group were equally close to this infant in the severe PV-IVH group, then one of the infants in the mild PV-IVH group was randomly selected for matching with this infant treated in the severe PV-IVH group. This process was repeated until all possible matches were formed. If for a given infant in the severe PV-IVH group, no available patient in the mild PV-IVH group was within the specified calliper width, then that infant in the severe PV-IVH group was excluded from the matched sample. Similarly, unmatched infants in the mild PV-IVH group were excluded from the matched sample.\u003c/p\u003e \u003cp\u003eThe continuous variables are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation for normally distributed data, and independent sample t-tests were performed. The Wilcoxon test was used for continuous variables with a skewed distribution, which are presented as medians with interquartile ranges. Chi-square or Fisher\u0026rsquo;s exact tests were used to compare categorical variables.\u003c/p\u003e \u003cp\u003eCorrelation matrix analysis was performed for variables with statistical differences. Variables with correlation coefficients greater than 0.4 were selectively excluded. Finally, the variables that differed significantly between groups and without significant correlations were included in the multivariate analysis. Potential variables were used in a backward stepwise logistic regression analysis to calculate the adjusted odds ratios (ORs) and corresponding 95% confidence intervals (CIs). All hypothesis tests were two-tailed. Statistical significance was set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 3,783 inborn premature infants (in West China Second Hospital) were diagnosed with PV-IVH between 2009 and 2018. The total incidence of PV-IVH in the preterm infants was 15.58%, and the incidence of PV-IVH of grades I, II, III, and IV was 2.50%, 9.52%, 3.13%, and 0.42%, respectively. The mortality of mild and severe PV-IVH was 0.33% and 3.25%, respectively. Among all the included preterm infants with PV-IVH, the proportion of infants with GA less than 28 weeks, 28 weeks to less than 30 weeks, and 30 weeks to less than 32 weeks was 55.6%, 40.1%, and 28%, respectively. Ultimately, we included 630 premature infants with PV-IVH: 315 with mild PV-IVH and 315 with severe PV-IVH (Fig. 1). Almost all of these preterm infants were diagnosed with PV-IVH within 1 week, and all the variables in our study were collected before PV-IVH onset. GA and BW presented a skewed distribution, with a median GA of 30 (29\u0026ndash;31) weeks and median BW of 1,420 (1,220\u0026ndash;1,680) g and 1,390 (1,170\u0026ndash;1,630) g for the mild and severe groups, respectively. The groups comprised 353 boys and 277 girls.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGeneral information regarding preterm infants with PV-IVH is presented in Table 1. We found no significant differences in GA, BW, primigravidity, primiparity, vaginal delivery, \u003cem\u003ein vitro\u003c/em\u003e fertilisation, premature rupture of membranes, placental abruption, and asphyxia. Patients in the severe PV-IVH group were more likely to be male, with a greater incidence of multiple gestations and amniotic fluid pollution.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Univariate analysis of the basic information of preterm infants with PV\u0026ndash;IVH.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"555\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"60.946745562130175%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMild PV-IVH\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=315)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSevere PV-IVH\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=315)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.076923076923077%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.976331360946746%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.11711711711712%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian gestational age (IQR)\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026mdash;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;wk\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.73873873873874%\"\u003e\n \u003cp\u003e30 (29-31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.36036036036036%\"\u003e\n \u003cp\u003e30 (29-31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.054054054054054%\"\u003e\n \u003cp\u003eZ\u0026nbsp;= 0.747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.72972972972973%\"\u003e\n \u003cp\u003e0.388\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"60.946745562130175%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian birth weight (IQR)\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026mdash;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;g\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e1420 (1220-1680)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e1390 (1170-1630)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.076923076923077%\"\u003e\n \u003cp\u003eZ\u0026nbsp;= 0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.976331360946746%\"\u003e\n \u003cp\u003e0.715\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"60.946745562130175%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e152(48.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e125 (39.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.076923076923077%\"\u003e\n \u003cp\u003e4.697\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.976331360946746%\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"60.946745562130175%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimigravidity (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e128 (40.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e147(46.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.076923076923077%\"\u003e\n \u003cp\u003e2.330\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.976331360946746%\"\u003e\n \u003cp\u003e0.127\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"60.946745562130175%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimiparity (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e226(71.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e224 (71.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.076923076923077%\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.976331360946746%\"\u003e\n \u003cp\u003e0.860\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"60.946745562130175%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultiple gestations (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e70 (22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e96 (30.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.076923076923077%\"\u003e\n \u003cp\u003e2.529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.976331360946746%\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"60.946745562130175%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVaginal delivery (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e138 (43.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e134(42.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.076923076923077%\"\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.976331360946746%\"\u003e\n \u003cp\u003e0.748\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"60.946745562130175%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIn vitro fertilization (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e21(6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e28(8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.076923076923077%\"\u003e\n \u003cp\u003e1.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.976331360946746%\"\u003e\n \u003cp\u003e0.298\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"60.946745562130175%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePremature rupture of membranes (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e137(43.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e151 (47.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.076923076923077%\"\u003e\n \u003cp\u003e1.254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.976331360946746%\"\u003e\n \u003cp\u003e0.264\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlacental abruption (n, %)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e46 (14.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e64(20.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"59.09090909090909%\"\u003e\n \u003cp\u003e3.569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"40.90909090909091%\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmniotic fluid pollution (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e27（8.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e43（13.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"59.09090909090909%\"\u003e\n \u003cp\u003e4.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"40.90909090909091%\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"60.946745562130175%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAsphyxia (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e101(32.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e120 (38.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.076923076923077%\"\u003e\n \u003cp\u003e2.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.976331360946746%\"\u003e\n \u003cp\u003e0.113\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003ePV\u0026ndash;IVH\u0026nbsp;\u003c/em\u003eperiventricular\u0026ndash;intraventricular hemorrhage.\u003c/p\u003e\n\u003cp\u003eTable 2 shows the complications and laboratory tests of preterm infants with PV-IVH. The early-onset sepsis\u0026nbsp;rate was higher in infants with\u0026nbsp;severe PV-IVH than with those with mild PV-IVH. The preterm infants with white blood cell count \u0026gt;\u0026nbsp;25 \u0026times;10\u003csup\u003e9\u003c/sup\u003e/L or \u0026lt;5 \u0026times;10\u003csup\u003e9\u003c/sup\u003e/L, C-reactive protein level \u0026gt; 8 mg/L, thrombocytopenia, and abnormal coagulation were more likely to have severe PV-IVH than mild PV-IVH. There were no significant differences between the mild and severe PV-IVH groups in pneumonia, respiratory distress syndrome, apnoea, patent ductus arteriosus, scleroderma, anaemia, electrolyte disorder, and PH\u0026lt;7.3.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eUnivariate analysis complications and laboratory test of preterm infants with PV\u0026ndash;IVH.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"545\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMild PV-IVH\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=315)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSevere PV-IVH\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=315)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePneumonia (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e252 (80.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e258 (81.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e0.371\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e0.543\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.294117647058826%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRespiratory distress syndrome (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.11764705882353%\"\u003e\n \u003cp\u003e135(42.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.404411764705884%\"\u003e\n \u003cp\u003e146 (46.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.948529411764707%\"\u003e\n \u003cp\u003e0.777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.235294117647058%\"\u003e\n \u003cp\u003e0.378\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.294117647058826%\"\u003e\n \u003cp\u003e\u003cstrong\u003eApnea (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.11764705882353%\"\u003e\n \u003cp\u003e109 (34.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.404411764705884%\"\u003e\n \u003cp\u003e106 (33.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.948529411764707%\"\u003e\n \u003cp\u003e0.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.235294117647058%\"\u003e\n \u003cp\u003e0.801\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.294117647058826%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatent ductus arteriosus (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.11764705882353%\"\u003e\n \u003cp\u003e78 (24.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.404411764705884%\"\u003e\n \u003cp\u003e80(25.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.948529411764707%\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.235294117647058%\"\u003e\n \u003cp\u003e0.854\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.294117647058826%\"\u003e\n \u003cp\u003e\u003cstrong\u003eScleredema (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.11764705882353%\"\u003e\n \u003cp\u003e31(9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.404411764705884%\"\u003e\n \u003cp\u003e31 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.948529411764707%\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.235294117647058%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.294117647058826%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnemia (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.11764705882353%\"\u003e\n \u003cp\u003e108 (34.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.404411764705884%\"\u003e\n \u003cp\u003e124(39.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.948529411764707%\"\u003e\n \u003cp\u003e1.747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.235294117647058%\"\u003e\n \u003cp\u003e0.186\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.294117647058826%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEarly-onset sepsis (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.11764705882353%\"\u003e\n \u003cp\u003e27(8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.404411764705884%\"\u003e\n \u003cp\u003e73 (23.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.948529411764707%\"\u003e\n \u003cp\u003e25.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.235294117647058%\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.294117647058826%\"\u003e\n \u003cp\u003e\u003cstrong\u003eElectrolyte disorder (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.11764705882353%\"\u003e\n \u003cp\u003e91（28.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.404411764705884%\"\u003e\n \u003cp\u003e73（23.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.948529411764707%\"\u003e\n \u003cp\u003e2.671\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.235294117647058%\"\u003e\n \u003cp\u003e0.102\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e\u003cstrong\u003eWBC \u0026gt; 25 \u0026times;10\u003csup\u003e9\u003c/sup\u003e/L or \u0026lt;5 \u0026times;10\u003csup\u003e9\u003c/sup\u003e/L (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e59(18.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e142 (45.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e50.332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCRP \u0026gt; 8 mg/L (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e62 (19.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e118(37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e24.391\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e\u003cstrong\u003eThrombocytopenia (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e24 (7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e70 (22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e26.458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAbnormal coagulation (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e132 (41.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e159 (50.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e4.656\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePH\u0026lt;7.30 (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e78(24.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e72(22.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e1.292\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\"\u003e\n \u003cp\u003e0.524\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003ePV\u0026ndash;IVH\u0026nbsp;\u003c/em\u003eperiventricular\u0026ndash;intraventricular haemorrhage. W\u003cem\u003eBC\u0026nbsp;\u003c/em\u003ewhite blood cell, \u003cem\u003eCRP\u0026nbsp;\u003c/em\u003eC-reactive protein. aBaseline values were tested before or within PV\u0026ndash;IVH diagnosis.\u003c/p\u003e\n\u003cp\u003eTreatments administered to preterm infants with PV-IVH are shown in Table 3. Our results showed that\u0026nbsp;infants with severe PV-IVH required more invasive and non-invasive mechanical ventilation, pulmonary surfactant, and antibiotics. The use of dopamine and aminophylline\u0026nbsp;did not differ\u0026nbsp;between groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eUnivariate analysis of treatment of preterm infants with PV\u0026ndash;IVH.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"52.80373831775701%\"\u003e\n \u003cp\u003eMild PV-IVH\u003c/p\u003e\n \u003cp\u003e(n=315)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"47.19626168224299%\"\u003e\n \u003cp\u003eSevere PV-IVH\u003c/p\u003e\n \u003cp\u003e(n=315)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e\u0026chi;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"36.330275229357795%\"\u003e\n \u003cp\u003e\u003cstrong\u003eInvasive mechanical ventilation (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.73394495412844%\"\u003e\n \u003cp\u003e80 (25.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.53211009174312%\"\u003e\n \u003cp\u003e131 (41.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.944954128440367%\"\u003e\n \u003cp\u003e18.535\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.458715596330276%\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-invasive mechanical ventilation (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"52.80373831775701%\"\u003e\n \u003cp\u003e10(3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"47.19626168224299%\"\u003e\n \u003cp\u003e63 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e45.523\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePulmonary surfactant (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"52.80373831775701%\"\u003e\n \u003cp\u003e142 (45.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"47.19626168224299%\"\u003e\n \u003cp\u003e172(54.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e5.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDopamine (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"52.80373831775701%\"\u003e\n \u003cp\u003e35(11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"47.19626168224299%\"\u003e\n \u003cp\u003e48(15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e2.245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e0.126\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAntibiotics (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"52.80373831775701%\"\u003e\n \u003cp\u003e234 (74.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"47.19626168224299%\"\u003e\n \u003cp\u003e270 (85.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e12.857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAminophylline (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"52.80373831775701%\"\u003e\n \u003cp\u003e132(41.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"47.19626168224299%\"\u003e\n \u003cp\u003e117(37.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e1.494\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e0.222\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003ePV\u0026ndash;IVH\u0026nbsp;\u003c/em\u003eperiventricular\u0026ndash;intraventricular hemorrhage.\u003c/p\u003e\n\u003cp\u003eTable 4 shows the maternal characteristics of preterm infants with PV-IVH. We found that severe PV-IVH was associated with maternal\u0026nbsp;intrahepatic cholestasis of pregnancy, chorioamnionitis, lower genital tract infection,\u0026nbsp;magnesium sulphate or antibiotic use,\u0026nbsp;and a\u0026nbsp;white blood cell\u0026nbsp;count \u0026gt;15\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u003c/strong\u003e\u0026nbsp; Univariate analysis of maternal characters in PV-IVH premature infants.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"569\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.04042179261863%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.29525483304042%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMild PV-IVH\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=315)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.27768014059754%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSe\u003c/strong\u003e\u003cstrong\u003evere\u0026nbsp;PV-IVH\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=315)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.017574692442881%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.369068541300527%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.04042179261863%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of fetal abnormalities (n, %)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.29525483304042%\"\u003e\n \u003cp\u003e45(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.27768014059754%\"\u003e\n \u003cp\u003e31 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.017574692442881%\"\u003e\n \u003cp\u003e2.933\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.369068541300527%\"\u003e\n \u003cp\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.04042179261863%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of abortion (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.29525483304042%\"\u003e\n \u003cp\u003e149(47.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.27768014059754%\"\u003e\n \u003cp\u003e151（47.98）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.017574692442881%\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.369068541300527%\"\u003e\n \u003cp\u003e0.225\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.04042179261863%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of cesarean section (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.29525483304042%\"\u003e\n \u003cp\u003e78（24.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.27768014059754%\"\u003e\n \u003cp\u003e99（31.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.017574692442881%\"\u003e\n \u003cp\u003e3.465\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.369068541300527%\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.04042179261863%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePre-eclampsia (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.29525483304042%\"\u003e\n \u003cp\u003e60（19.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.27768014059754%\"\u003e\n \u003cp\u003e43（13.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.017574692442881%\"\u003e\n \u003cp\u003e3.354\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.369068541300527%\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.04042179261863%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGestational hypertension (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.29525483304042%\"\u003e\n \u003cp\u003e11 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.27768014059754%\"\u003e\n \u003cp\u003e13(4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.017574692442881%\"\u003e\n \u003cp\u003e0.173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.369068541300527%\"\u003e\n \u003cp\u003e0.677\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.04042179261863%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGestational diabetes (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.29525483304042%\"\u003e\n \u003cp\u003e78（24.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.27768014059754%\"\u003e\n \u003cp\u003e70（22.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.017574692442881%\"\u003e\n \u003cp\u003e0.565\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.369068541300527%\"\u003e\n \u003cp\u003e0.452\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.04042179261863%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntrahepatic cholestasis of pregnancy (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.29525483304042%\"\u003e\n \u003cp\u003e31(9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.27768014059754%\"\u003e\n \u003cp\u003e48 (15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.017574692442881%\"\u003e\n \u003cp\u003e4.183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.369068541300527%\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.04042179261863%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePregnancy anemia (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.29525483304042%\"\u003e\n \u003cp\u003e78 (24.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.27768014059754%\"\u003e\n \u003cp\u003e86(27.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.017574692442881%\"\u003e\n \u003cp\u003e0.528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.369068541300527%\"\u003e\n \u003cp\u003e0.468\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.04042179261863%\"\u003e\n \u003cp\u003e\u003cstrong\u003eChorioamnitis (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.29525483304042%\"\u003e\n \u003cp\u003e85（27.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.27768014059754%\"\u003e\n \u003cp\u003e110（34.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.017574692442881%\"\u003e\n \u003cp\u003e4.642\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.369068541300527%\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.04042179261863%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLower genital tract infections (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.29525483304042%\"\u003e\n \u003cp\u003e67(21.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.27768014059754%\"\u003e\n \u003cp\u003e106 (33.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.017574692442881%\"\u003e\n \u003cp\u003e12.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.369068541300527%\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.04042179261863%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMagnesium sulfate (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.29525483304042%\"\u003e\n \u003cp\u003e202（64.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.27768014059754%\"\u003e\n \u003cp\u003e234（74.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.017574692442881%\"\u003e\n \u003cp\u003e7.627\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.369068541300527%\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.04042179261863%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDexamethasone (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.29525483304042%\"\u003e\n \u003cp\u003e244（77.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.27768014059754%\"\u003e\n \u003cp\u003e245（77.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.017574692442881%\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.369068541300527%\"\u003e\n \u003cp\u003e0.924\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.04042179261863%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAntibiotics (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.29525483304042%\"\u003e\n \u003cp\u003e120（38.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.27768014059754%\"\u003e\n \u003cp\u003e154（48.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.017574692442881%\"\u003e\n \u003cp\u003e7.446\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.369068541300527%\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.04042179261863%\"\u003e\n \u003cp\u003e\u003cstrong\u003eWBC \u0026gt; 15\u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.29525483304042%\"\u003e\n \u003cp\u003e57（18.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.27768014059754%\"\u003e\n \u003cp\u003e87（27.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.017574692442881%\"\u003e\n \u003cp\u003e8.102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.369068541300527%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.04042179261863%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlatelets\u0026lt;100\u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L (n, %)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"28.29525483304042%\"\u003e\n \u003cp\u003e18（5.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.27768014059754%\"\u003e\n \u003cp\u003e13（4.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.017574692442881%\"\u003e\n \u003cp\u003e0.848\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.369068541300527%\"\u003e\n \u003cp\u003e0.357\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003ePV\u0026ndash;IVH\u0026nbsp;\u003c/em\u003eperiventricular\u0026ndash;intraventricular hemorrhage.\u003c/p\u003e\n\u003cp\u003eIn the univariate analysis, 12 significant variables were obtained and included in the multivariate analysis after stepwise elimination and clinical screening. The results (Table 5), adjusted for abnormal coagulation, pulmonary surfactants, intrahepatic cholestasis of pregnancy, amniotic fluid pollution, and maternal WBC \u0026gt; 15\u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L, chorioamnionitis), suggested that early-onset sepsis (OR 2.5, 95% CI: 1.50\u0026ndash;4.16),\u0026nbsp;thrombocytopenia (OR 2.37, 95% CI: 1.39\u0026ndash;4.04), multiple gestations (OR 1.69, 95% CI: 1.15\u0026ndash;2.49), invasive mechanical ventilation (OR 1.59, 95% CI: 1.10\u0026ndash;2.31), and magnesium sulphate use (OR 1.46, 95% CI: 1.01\u0026ndash;2.10) were independently associated with severe PV-IVH. Female sex (OR 0.65, 95% CI: 0.46\u0026ndash;0.91) was an independent protective factor against severe PV-IVH.\u003cstrong\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5.\u0026nbsp;\u003c/strong\u003eFactors associated with PV-IVH severity in preterm infants.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.63157894736842%\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.421052631578947%\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.526315789473685%\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.578947368421053%\"\u003e\n \u003cp\u003eWals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.473684210526315%\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.526315789473685%\"\u003e\n \u003cp\u003eaOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.842105263157894%\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEarly-onset sepsis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e0.914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"38.46153846153846%\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e12.349\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e2.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"61.53846153846154%\"\u003e\n \u003cp\u003e1.50-4.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.63157894736842%\"\u003e\n \u003cp\u003e\u003cstrong\u003eThrombocytopenia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.421052631578947%\"\u003e\n \u003cp\u003e0.863\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.526315789473685%\"\u003e\n \u003cp\u003e0.273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.578947368421053%\"\u003e\n \u003cp\u003e10.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.473684210526315%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.526315789473685%\"\u003e\n \u003cp\u003e2.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.842105263157894%\"\u003e\n \u003cp\u003e1.39-4.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultiple gestations\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e0.526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"38.46153846153846%\"\u003e\n \u003cp\u003e0.197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e7.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"61.53846153846154%\"\u003e\n \u003cp\u003e1.15-2.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.63157894736842%\"\u003e\n \u003cp\u003e\u003cstrong\u003eInvasive mechanical ventilation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.421052631578947%\"\u003e\n \u003cp\u003e0.465\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.526315789473685%\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.578947368421053%\"\u003e\n \u003cp\u003e5.956\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.473684210526315%\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.526315789473685%\"\u003e\n \u003cp\u003e1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.842105263157894%\"\u003e\n \u003cp\u003e1.10-2.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMagnesium sulfate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e0.378\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"38.46153846153846%\"\u003e\n \u003cp\u003e0.187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e4.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"0%\"\u003e\n \u003cp\u003e1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"61.53846153846154%\"\u003e\n \u003cp\u003e1.01-2.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"32.63157894736842%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.421052631578947%\"\u003e\n \u003cp\u003e-0.437\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.526315789473685%\"\u003e\n \u003cp\u003e0.173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.578947368421053%\"\u003e\n \u003cp\u003e6.399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.473684210526315%\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.526315789473685%\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.842105263157894%\"\u003e\n \u003cp\u003e0.46-0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003ePV\u0026ndash;IVH\u0026nbsp;\u003c/em\u003eperiventricular\u0026ndash;intraventricular haemorrhage, \u003cem\u003eaOR\u0026nbsp;\u003c/em\u003eadjusted odds ratio, \u003cem\u003e95% CI\u0026nbsp;\u003c/em\u003e95% confidence interval. Adjusted for: abnormal coagulation, pulmonary surfactants, intrahepatic cholestasis of pregnancy, amniotic fluid pollution, maternal WBC \u0026gt; 15\u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L, chorioamnitis.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eGA, the most influential factor, is inversely correlated with the occurrence of PV-IVH[6, 8]. In this study, we conducted a propensity score-matched analysis to eliminate the influence of GA. To the best of our knowledge, this is the first study to identify the risk factors besides GA that contribute to the differences between severe and mild PV-IVH. Our study helps clarify the aetiological differences between the degrees of PV-IVH severity, which may be helpful for future clinical interventions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePV-IVH of all premature infants included in this study was diagnosed within 7 days of birth, and all risk factors occurred before the diagnosis of PV-IVH. Therefore, it is reasonable to believe that the risk factors we obtained may lead to severe PV-IVH, given that these risk factors have also been discussed in previous studies.\u003c/p\u003e\n\u003cp\u003eEarly-onset sepsis\u0026nbsp;can cause\u0026nbsp;an\u0026nbsp;inflammatory cytokine storm. Our research shows that early-onset sepsis is a significant cause of severe PV-IVH, consistent with previous studies[5, 8, 10, 11]. Inflammatory factors detected in the blood of infants with PV-IVH were significantly higher than\u0026nbsp;those in healthy neonates, correlating with\u0026nbsp;IVH severity\u0026nbsp;[5, 8, 10, 11]. The inflammatory factors damage the blood-brain barrier and brain\u0026rsquo;s blood vessels, increasing the blood vessels\u0026rsquo;\u0026nbsp;vulnerability to damage and rupture[12]. Inflammatory factors can also increase the oxygen consumption of\u0026nbsp;brain tissue and\u0026nbsp;disrupt the blood pressure regulation function of the brain, resulting in severe fluctuations\u0026nbsp;in cerebral perfusion pressure in premature infants and subsequent PV-IVH[13, 14].\u003c/p\u003e\n\u003cp\u003eA systematic review suggested that thrombocytopenia is\u0026nbsp;a risk factor for PV-IVH in preterm infants[15], which is consistent with our findings. Since thrombocyte counts regulate haemostatic function, thrombocytopenia is associated with a bleeding tendency, including\u0026nbsp;PV-IVH. In addition, thrombocytopenia may be\u0026nbsp;caused by infection and other abnormal coagulation\u0026nbsp;events[16, 17], which may be risk factors for PV-IVH.\u003c/p\u003e\n\u003cp\u003eOur findings are consistent with previous studies that\u0026nbsp;identified multiple births as a risk factor for\u0026nbsp;severe PV-IVH[18, 19]. A systematic review found that appropriate hormone therapy helped to reduce the incidence of respiratory distress syndrome and PV-IVH[20]. However, multiple births were associated with lower hormone levels compared with single pregnancies with the same dose regimen of prenatal hormones[20, 21]. This association may explain why PV-IVH is more likely to occur in multiple pregnancies.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; Our study suggests\u0026nbsp;invasive mechanical\u0026nbsp;ventilation is a risk factor for severe PV-IVH. Previous studies have shown\u0026nbsp;that this may be related to mechanical ventilation, which\u0026nbsp;disrupts cerebral blood flow and induces\u0026nbsp;a\u0026nbsp;local inflammatory response[13, 22]. Another study found that mechanical ventilation can cause lung damage, generate adenosine triphosphate, activate P2Y1 receptors, and increase dopamine release, causing or aggravating brain damage. This provides a possible explanation for why premature infants are prone to PV-IVH after mechanical ventilation[23].\u003c/p\u003e\n\u003cp\u003eOur study showed that antenatal magnesium sulphate use is a risk factor for severe PV-IVH in preterm infants. However, no consensus has been reached in the literature regarding the relationship between antenatal magnesium sulphate use and PV-IVH. The findings of a previous study suggested that PV-IVH may be related to high-dose magnesium sulphate exposure, supporting the results of our study[24]. However, another study suggested that prenatal magnesium sulphate use can reduce the incidence of PV-IVH in neonates, which may be related to the reduction in the cerebral metabolic load induced by magnesium sulphate[25]. Studies have shown that the protective or damaging effects of magnesium sulphate may be related to\u0026nbsp;prenatal doses[26].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe found that the female sex was an independent protective factor against severe PV-IVH, supported by\u0026nbsp;a previous\u0026nbsp;study\u0026nbsp;[27, 28]. The study suggests that male newborns are more susceptible to catecholamines and have a\u0026nbsp;higher cerebral blood flow than female infants. In addition,\u0026nbsp;sex differences in inflammatory factor gene polymorphisms and differences in hormone levels may explain why males are more prone to PV-IVH than females\u0026nbsp;[27].\u003c/p\u003e\n\u003cp\u003eOur study had some limitations. First, due to our strict GA matching criteria, median GA was 30 (29\u0026ndash;31) weeks, and a sufficient number of preterm infants with lower GA were not available to participate in this study. Hence, caution should be exercised when applying these findings to preterm infants with lower GA. Further research into lower GA preterm infants is warranted. Second, we found a high incidence of PV-IVH in preterm infants in this study, reflecting that PV-IVH is an important cause affecting the prognosis of preterm infants in this region and needs further study. In addition, because this was a retrospective clinical study, there was an uncontrollable recall bias. Hence, again, caution should be exercised when generalising our results to other settings, as this was a single-centre study conducted in China. Lastly, although the paediatric sonographers in this study received uniform PV-IVH screening training and were blinded to the clinical information, detection bias might have existed between paediatric sonographers.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur findings suggest that early-onset sepsis, thrombocytopenia, multiple gestations, invasive mechanical ventilation, magnesium sulphate use, and male sex contribute to severe PV-IVH in preterm infants. Although this study has its limitations, the combination of these risk factors should be considered when predicting the incidence of PV-IVH.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBirth weight (BW)\u003c/p\u003e\n\u003cp\u003eConfidence interval (CI)\u003c/p\u003e\n\u003cp\u003eGestational age (GA)\u003c/p\u003e\n\u003cp\u003ePeriventricular-intraventricular haemorrhage (PV-IVH)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOdds ratio (OR)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eThis study was approved by the Medical Ethics Committee of West China Second University Hospital (approval number: 20PJ071) and performed per the Declaration of Helsinki. Written informed consent was obtained from the parents or guardians of each infant.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from West China Second Hospital, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the corresponding authors upon reasonable request and with permission of West China Second Hospital.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis research was funded by grants from the National Key Research and Development Program of China (No.2021YFC2701701), the Science and Technology Bureau of Sichuan Province (2020YJ0298), Health Commission of Sichuan Province (20PJ071), and China International Medical Foundation (Z-2019-41-2101-04).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions:\u003c/strong\u003e JH, YW and TX drafted and revised the manuscript. All authors were involved with study design and carried out data collection. All authors agree to this final submission.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eYeo KT, Thomas R, Chow SS, Bolisetty S, Haslam R, Tarnow-Mordi W, et al. Improving incidence trends of severe intraventricular haemorrhages in preterm infants \u0026lt;32 weeks gestation: a cohort study. Arch Dis Child Fetal Neonatal Ed. 2020;105(2):145-50.\u003c/li\u003e\n\u003cli\u003eHollebrandse NL, Spittle AJ, Burnett AC, Anderson PJ, Roberts G, Doyle LW, et al. School-age outcomes following intraventricular haemorrhage in infants born extremely preterm. Arch Dis Child Fetal Neonatal Ed. 2021;106(1):4-8. \u003c/li\u003e\n\u003cli\u003eMcCauley KE, Carey EC, Weaver AL, Mara KC, Clark RH, Carey WA, et al. Survival of Ventilated Extremely Premature Neonates With Severe Intraventricular Hemorrhage. Pediatrics. 2021;147(4):e20201584.\u003c/li\u003e\n\u003cli\u003eBassan H, Limperopoulos C, Visconti K, Mayer DL, Feldman HA, Avery L, et al. Neurodevelopmental outcome in survivors of periventricular hemorrhagic infarction. Pediatrics. 2007;120(4):785-92.\u003c/li\u003e\n\u003cli\u003eHuang J, Meng J, Choonara I, Xiong T, Wang Y, Wang H, et al. Antenatal infection and intraventricularhemorrhage in preterm infants：A meta-analysis. Medicine. 2019;31(98):e16665.\u003c/li\u003e\n\u003cli\u003eAdams-Chapman I, Hansen NI, Stoll BJ, Higgins R, Network NR. Neurodevelopmental outcome of extremely low birth weight infants with posthemorrhagic hydrocephalus requiring shunt insertion. Pediatrics. 2008;121(5):e1167-77. \u003c/li\u003e\n\u003cli\u003eLai GY, Shlobin N, Garcia RM, Wescott A, Kulkarni AV, Drake J, et al. Global incidence proportion of intraventricular haemorrhage of prematurity: a meta-analysis of studies published 2010-2020. Arch Dis Child Fetal Neonatal Ed. 2022;107(5):513-9.\u003c/li\u003e\n\u003cli\u003eWu T, Wang Y, Xiong T, Huang S, Tian T, Tang J, et al. Risk factors for the deterioration of periventricular-intraventricular hemorrhage in preterm infants. Sci Rep. 2020;10(1):13609.\u003c/li\u003e\n\u003cli\u003ePapile LA, Burstein J, Burstein R, Koffler H. Incidence and evolution of subependymal and intraventricular hemorrhage: a study of infants with birth weights less than 1,500 gm. J pediatr. \u003c/li\u003e\n\u003cli\u003ePayne AH, Hintz SR, Hibbs AM, Walsh MC, Vohr BR, Bann CM, et al. Neurodevelopmental outcomes of extremely low-gestational-age neonates with low-grade periventricular-intraventricular hemorrhage. JAMA Pediatr. 2013;167(5):451-9. \u003c/li\u003e\n\u003cli\u003eHofer N, Kothari R, Morris N, Muller W, Resch B. The fetal inflammatory response syndrome is a risk factor for morbidity in preterm neonates. Am J Obstet Gynecol. 2013;209(6):542.e1- 542.e11. \u003c/li\u003e\n\u003cli\u003eGalea I. The blood-brain barrier in systemic infection and inflammation. Cell Mol Immunol. 2021;18(11):2489-501. \u003c/li\u003e\n\u003cli\u003ePolglase GR, Nitsos I, Baburamani AA, Crossley KJ, Slater MK, Gill AW, et al. Inflammation in utero exacerbates ventilation-induced brain injury in preterm lambs. Journal of applied physiology (Bethesda, Md : 1985). 2012;112(3):481-9.\u003c/li\u003e\n\u003cli\u003eVesoulis ZA, Flower AA, Zanelli S, Rambhia A, Abubakar M, Whitehead HV, et al. Blood pressure extremes and severe IVH in preterm infants. Pediatr Res. 2020;87(1):69-73. \u003c/li\u003e\n\u003cli\u003eGrevsen AK, Hviid CV, Hansen AK, Hvas AM. The Role of Platelets in Premature Neonates with Intraventricular Hemorrhage: A Systematic Review and Meta-Analysis. Semin Thromb Hemost. 2020;46(3):366-78. \u003c/li\u003e\n\u003cli\u003ePortier I, Campbell RA. Role of Platelets in Detection and Regulation of Infection. Arterioscler, thromb vasc biol. 2021;41(1):70-8.\u003c/li\u003e\n\u003cli\u003eSang Y, Roest M, de Laat B, de Groot PG, Huskens D. Interplay between platelets and coagulation. Blood Rev. 2021;46:100733.\u003c/li\u003e\n\u003cli\u003eWard C, Caughey AB. Late preterm births: neonatal mortality and morbidity in twins vs. singletons. J Matern Fetal Neonatal Med. 2021:1-6. \u003c/li\u003e\n\u003cli\u003eHayes EJ, Paul D, Ness A, Mackley A, Berghella V. Very-low-birthweight neonates: do outcomes differ in multiple compared with singleton gestations? Am J Perinatol. 2007;24(6):373-6. \u003c/li\u003e\n\u003cli\u003eLin D, Fan D, Chen G, Luo C, Guo X, Liu Z. Association of antenatal corticosteroids with morbidity and mortality among preterm multiple gestations: meta-analysis of observational studies. BMJ Open. 2021;11(9):e047651. \u003c/li\u003e\n\u003cli\u003eBallabh P, Lo ES, Kumari J, Cooper TB, Zervoudakis I, Auld PA, et al.Pharmacokinetics of betamethasone in twin and singleton pregnancy. Clin pharmacol Ther. 2002;71(1):39-45.\u003c/li\u003e\n\u003cli\u003eCannavo L, Rulli I, Falsaperla R, Corsello G, Gitto E. Ventilation, oxidative stress and risk of brain injury in preterm newborn. Ital J Pediatr. 2020;46(1):100. \u003c/li\u003e\n\u003cli\u003eWei W, Sun Z, He S, Zhang W, Chen S, Cao YN, et al. Mechanical ventilation induces lung and brain injury through ATP production, P2Y1 receptor activation and dopamine release. Bioengineered. 2022;13(2):2346-59. \u003c/li\u003e\n\u003cli\u003eMittendorf R, Dammann O, Lee KS. Brain lesions in newborns exposed to high-dose magnesium sulfate during preterm labor. J Perinatol. 2006;26(1):57-63. \u003c/li\u003e\n\u003cli\u003eBansal V, Desai A. Efficacy of Antenatal Magnesium Sulfate for Neuroprotection in Extreme Prematurity: A Comparative Observational Study. J Obstet Gynaecol India. 2022:72(Suppl 1):36-47. \u003c/li\u003e\n\u003cli\u003eMittendorf R, Pryde PG. A review of the role for magnesium sulphate in preterm labour. BJOG. 2005;112 Suppl 1:84-8.\u003c/li\u003e\n\u003cli\u003eMohamed MA, Aly H. Male gender is associated with intraventricular hemorrhage. Pediatrics. 2010;125(2):e333-9. \u003c/li\u003e\n\u003cli\u003eGagliardi L, Rusconi F, Reichman B, Adams M, Modi N, Lehtonen L, et al. Neonatal outcomes of extremely preterm twins by sex pairing: an international cohort study. Arch Dis Child Fetal Neonatal Ed. 2021;106(1):17-24. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"preterm infants, periventricular-intraventricular haemorrhage, gestational age, propensity score, risk factor","lastPublishedDoi":"10.21203/rs.3.rs-1937668/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1937668/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eMost\u003cstrong\u003e \u003c/strong\u003eprevious\u003cstrong\u003e \u003c/strong\u003estudies comparing etiological studies in infants with and without periventricular-intraventricular haemorrhage (PV-IVH) concluded that younger gestational age (GA) was associated with a higher prevalence rate of PV-IVH. However, only few studies have examined the risk factors associated with the severity of PV-IVH after removing the influence of GA.\u003cstrong\u003e \u003c/strong\u003eTherefore, we investigated the risk factors apart from GA for PV-IVH severity in preterm infants less than 32 weeks.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThis was a retrospective case-control study of preterm infants born in West China Second Hospital with PV-IVH between 2009 and 2018. PV-IVH was defined using cranial ultrasound screening. Preterm infants with PV-IVH were divided into mild and severe groups. Both groups were matched in a 1:1 ratio using propensity score calculated from GA. Variables were collected from infant–mother pairs. A stepwise forward multivariate logistic regression model was adopted to select factors that affected the severity of PV-IVH in preterm infants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e A total of 3,783 preterm infants with PV-IVH were included. The total incidence of PV-IVH in preterm infants was 15.58%, and the incidence of PV-IVH of grades I, II, III, and IV was 2.50%, 9.52%, 3.13%, and 0.42%, respectively. The mortality of mild and severe PV-IVH was 0.33% and 3.25%, respectively. We matched 315 infants with severe PV-IVH with 315 infants with mild PV-IVH. The results suggested that early-onset sepsis (odds ratio [OR] 2.50, 95% confidence interval [CI]: \u0026nbsp;1.50–4.16), thrombocytopenia (OR 2.37, 95% CI: 1.39–4.04), multiple gestations (OR 1.69, 95% CI: 1.15–2.49), invasive mechanical ventilation (OR 1.59, 95% CI: 1.10–2.31), and magnesium sulphate use (OR 1.46, 95% CI: 1.01–2.10) were associated with severe PV-IVH. Female sex (OR 0.65, 95% CI: 0.46–0.91) was a protective factor against severe PV-IVH.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: Early-onset sepsis, thrombocytopenia, multiple gestations, invasive mechanical ventilation, magnesium sulphate use, and male sex contributed to severe PV-IVH in preterm infants regardless of GA, these risk factors may combine to predict the incidence of PV-IVH in preterm infants.\u003c/p\u003e","manuscriptTitle":"Risk factors for periventricular-intraventricular haemorrhage severity in preterm infants: A propensity score-matched analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2022-12-13 16:19:23","doi":"10.21203/rs.3.rs-1937668/v2","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2023-01-12T03:33:44+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-12-10T07:57:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"af9686c2-6b5d-406f-a4cd-b601d8968f2a","date":"2022-11-29T18:41:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-11-25T18:17:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"d9912538-81e6-4616-b1bd-8ded7dfade66","date":"2022-11-23T08:50:19+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-11-10T09:15:49+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-11-10T08:41:49+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2022-11-03T23:20:14+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-11-03T23:17:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pediatrics","date":"2022-10-08T06:08:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5dc4258a-1405-4886-a018-7f4829fa6dfa","owner":[],"postedDate":"December 13th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T22:27:56+00:00","versionOfRecord":{"articleIdentity":"rs-1937668","link":"https://doi.org/10.1186/s12887-023-04114-x","journal":{"identity":"bmc-pediatrics","isVorOnly":false,"title":"BMC Pediatrics"},"publishedOn":"2023-07-05 21:30:17","publishedOnDateReadable":"July 5th, 2023"},"versionCreatedAt":"2022-12-13 16:19:23","video":"","vorDoi":"10.1186/s12887-023-04114-x","vorDoiUrl":"https://doi.org/10.1186/s12887-023-04114-x","workflowStages":[]},"version":"v2","identity":"rs-1937668","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1937668","identity":"rs-1937668","version":["v2"]},"buildId":"J0_U0BvcaRcwD8yVFaRlm","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}