https://orcid.org/0000-0001-8591-8395
Abstract
Objective
In this study, we aimed to investigate the relationship between unexplained stillbirth (SB) cases and the complete blood parameter indices and we compared them with uncomplicated healthy cases.
Methods
Patients diagnosed with unexplained SB cases in a tertiary center between 2019-2022 were included in this retrospective case-control study. The gestational age threshold for SBs was accepted as births after the 20th week of pregnancy. Consecutive patients with no adverse obstetric outcomes were accepted as the control group. Patients’ complete blood parameter results at the time of the first admission to the hospital until 14 weeks were labeled as “1’’ and at the time of delivery were labeled as “2’’ and recorded. As inflammatory parameters, neutrophile-lymphocyte ratio, derivated neutrophile-lymphocyte ratio, platelet-lymphocyte ratio, lymphocyte-monocyte ratio (LMR), and hemoglobin-lymphocyte ratio (HLR) were calculated from complete blood results and recorded.
Results
There were statistically significant differences between the groups’ LMR1 (p = .040). Additionally, whereas HLR1 of the study group was 0.693 (0.38–2.72), it was 0.645 (0.15–1.82) in the control group (p = .026). However, the HLR2 of the study group was significantly lower than the control group (p = .021).
Conclusion
Necessary precautions such as fetal biophysical profile examination can be taken more frequently in the antenatal follow-up in patients considered to be at high risk of SB by using HLR. It is a novel marker that can be easily accessible and calculated from the complete blood parameters.
Introduction
Stillbirth (SB) is defined as the cessation of the baby’s heartbeat after the 20th week of pregnancy. Over the years, a decrease in SBs has been observed, thanks to advances in prenatal care [Citation1]. However, despite these advances, it is still seen at a rate of 18.4/1000 births [Citation2]. Moreover, most of these SB occurs in the period before 37 weeks of gestation, which is accepted as preterm [Citation3].
Various risk scores have been used to predict SBs [Citation4]. Even, patients with an SB history were followed up and included in special care programs in their next pregnancies [Citation5]. It is already known that there is a strong relationship between inflammation and SB [Citation6,Citation7]. Some inflammatory indices of complete blood like the systemic immune‐inflammation index have been studied to predict nonviable pregnancy under 20 weeks [Citation8]. Although SB has generally complex underlying pathologies, inflammatory markers may be used as ancillary tests to predict SB according to various studies [Citation7].
To deliver a stillborn baby is a psychological and physical burden and tragedy for both the family and the pregnant woman. After the exclusion of explainable causes of SB, a large group of unexplained patients still remains which accounts for almost %76 of all SBs [Citation2]. Complete blood parameters, which can be checked even by general practitioners and also in every clinic, are inexpensive and easily accessible tests. On that account, we investigated if there was a relationship between the complete blood parameter indices in unexplained SB cases and we compared them to uncomplicated healthy cases.
Materials and methods
This present study is a case-control study. Approval was obtained from the Ankara City Hospital institutional review board (20.12.2021/4). The records of the patients were obtained retrospectively from the hospital data. Patients diagnosed with SB in a tertiary center between 2019–2022 were included. The gestational age threshold for SBs was accepted as births after the 20th week of pregnancy [Citation1]. Consecutive patients who had no adverse obstetric outcomes and had given birth in the same hospital were accepted as the control patients. The control patients were assigned randomly to avoid bias.
Patients with both complete blood parameter results at the time of the first admission to the hospital until 14 weeks and at the time of delivery were included in the study. Since our study group consisted of unexplained SB patients, patients with maternal infection, chronic diseases, drug use, thrombophilia, diseases such as gestational diabetes mellitus and preeclampsia detected during pregnancy, obesity, alcohol, and cigarette consumption were excluded from the study. In addition, patients with fetal anomaly and patients with high risk in first and second-trimester anomaly screening tests were excluded from the study.
As for the study parameters, maternal age, obstetrical history (gravidity, parity, abortion), and gestational age at delivery were recorded. The patients’ complete blood parameters from the first admission to the hospital until 14 weeks and at the time of delivery were recorded. Basophile, eosinophil, hematocrit, hemoglobin, large unstained cells (luc), lymphocyte (lym), mean corpuscular hemoglobin (mch), mean corpuscular hemoglobin concentration (mchc), mean corpuscular volume (mcv), monocyte, mean platelet volume (mpv), neutrophile, platelet distribution width (pdw), platelet (plt), red blood cell (rbc), red cell distribution width (rdw), white blood cell (wbc) levels were recorded from the complete blood cell results. Complete blood cell parameters recorded at first admission to the hospital were labeled as “1”’. On the other hand, complete blood cell parameters recorded at the time of delivery were labeled as “2. As inflammatory parameters, neutrophile-lymphocyte ratio (NLR), derivated neutrophile-lymphocyte ratio (DNLR), platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), and hemoglobin-lymphocyte ratio (HLR) were calculated from complete blood results and recorded.
The histopathological reports of the placentas of SB patients were also evaluated. The findings of the placentas were classified as normal, maternal vascular lesions (placental hemorrhage, fibrin deposition increase, villous agglutination/hypoplasia, and infarct), fetal vascular lesions (chorionic plate and stem villous vessels thrombosis, avascular villi), inflammatory and umbilical cord findings.
Statistical analysis
Statistical Package for the Social Sciences 24 program was used in order to analyze the data. Kolmogorov–Smirnov test and Shapiro–Wilk test was used to analyze the conformity of the data to the normal distribution. As the data did not show normal distribution, non-parametric methods were used for the analysis. Mann–Whitney U test was used to compare the parameters between the groups. Non-normally distributed data were shown as median (min – max). Categorical data was shown in numbers (n) and percentages (%). A p Value less than .05 was accepted as significant.
Results
This present study was performed on a total of 227 patients. Whereas 111 patients diagnosed to have unexplained SB formed the study group, 116 randomly assigned consecutive patients with no adverse obstetric outcomes formed the control group.
The gestational age at birth was 32 (20–40) weeks in the study and it was 39 (35–41) weeks in the control group. The comparison of clinicodemographic characteristics and complete blood parameter results at the time of the first admission to the hospital were shown in . The mean age of the study group was 32 (18–44), whereas the mean age of the control group was 27 (18–39) (p < .001). We found no significant difference between the groups’ obstetrical history (number of gravidity, parity, abortion).
Table 1. Clinicodemographic characteristics and complete blood parameter results of the groups at the time of first admission to the hospital.
As for the complete blood parameters at the time of the first admission to the hospital, whereas the mean lymphocyte number of the study group was 1.95 (0.60–7.62), it was 1.75 (0.46–3.61) in the control group. Lymphocyte number and percent of the study group were found to be higher than the control group (p = .015, p = .036 respectively).
The patients’ complete blood parameters at the time of delivery were shown in . The number and percent of luc2 were found to be significantly lower in the study group. While the monocyte2 number was found to be lower, the monocyte2 percentage was found to be higher in the study group. In addition, there were statistically significant differences between the groups’ mchc2, mpv2, pct2, and rdw2 levels ().
Table 2. Complete blood parameters of the groups at the time of delivery.
The groups were compared in terms of inflammatory markers calculated from complete blood parameters (.) There was a statistically significant difference between the groups’ LMR1 (p = .040). Additionally, whereas HLR1 of the study group was 0.693 (0.38–2.72), it was 0.645 (0.15–1.82) in the control group. The study group’s HLR1 was statistically higher than the control group (p = .026). However, HLR2 of the study group was significantly lower than the control group (p = .021). Moreover, no statistically significant differences were found between the groups’ NLR1, NLR2, DNLR1, DNLR2, PLR1, PLR2, and LMR2.
Table 3. Inflammatory markers of the groups calculated from complete blood parameters.
Seventy-five patients’ placental pathology reports were reached. There were 24 patients (32%) reported to have a normal placenta. Maternal vascular lesions were detected in 29 patients (38.7%). Inflammatory lesions were detected in 13 patients (17.3%), umbilical cord findings in 7 patients (9.3%), and 2 patients (2.7%) were detected to have fetal vascular lesions.
Discusssion
In this current study, we investigated the complete blood parameter indices of SB patients at the time of the first admission to the hospital and at the time of delivery and compared them with healthy controls. We found that the lymphocyte number and percent of the study group which consists of SB patients were found to be higher than the control group at the time of the first admission to the hospital. The number and percent of luc2 were significantly lower in SB patients. In addition, as for the inflammatory markers calculated from complete blood parameters, there was statistically significant difference between the groups’ LMR1. Whereas SB patients’ HLR1 was statistically higher than control patients, HLR2 of SB patients was significantly lower than control patients. However, no statistically significant differences were found among the groups’ NLR, DNLR, and PLR.
Models to predict SB have been developed. Risk assessments were made upon maternal characteristics, medical and obstetric history [Citation9,Citation10]. However, a recent review revealed that these prediction models might have bias [Citation11]. Although many parameters such as fetoplacental proteins, combined tests, antiphospholipid antibodies, and placental pathologies have been examined in the literature to predict SB [Citation12,Citation13], as far as we know, this study is one of the first to evaluate the complete blood parameter indices in SB patients.
In a study held by Harrison et al. to predict SB, inflammatory markers ferritin, C-reactive protein (CRP), white blood cell count were examined [Citation7]. The patients were divided into 3 groups according to prepregnancy body mass index (BMI). In this study, higher ferritin levels, lower CRP, and elevated white blood cell count were found to be associated with the risk of SB. However, these inflammatory biomarkers were collected only around the time of delivery so it can be thought that these outcomes cannot be used to predict the SB situation as it has already occurred. On the other hand, in our study, we examined the complete blood results of the patients both at the time of the first admission to the hospital and at the time of delivery. Another difference from our study is that obese patients were also included in this study and it is already known that obesity is a major risk factor for SB [Citation14]. In addition, the prepregnancy BMI may not reflect accurate results since the weight gain during pregnancy was not recorded. In our study obesity was excluded and only unexplained SB patients were included.
Although inflammatory markers, which can be calculated from complete blood parameters, have not been studied in SB patients in the literature, it has been studied whether they can be used to predict miscarriages which are under the 20th gestational week. In this study, no significant differences were found between the miscarriage and the control groups in terms of NLR and PLR [Citation15]. Similar to this study, no significant differences were found between the groups’ NLR, and PLR. However, we found higher HLR1 and lower HLR2 in SB patients when compared with controls. In contrast, another study suggested that decreased NLR levels can be used as inflammatory markers to predict miscarriages [Citation16].
Pregnancy is a complex process that includes immunologic, physiologic, and adaptive mechanisms providing an appropriate environment for the developing placenta and the fetus. In the first trimester, placental invasion and decidualization are the main events leading a relatively excessive inflammation and immunoregulation [Citation17]. On the other hand, immune tolerance is necessary to prevent the rejection of the semi-allograft conception material by the maternal immune system [Citation18]. For this reason, both activator and inhibitory responses take place in the maternal-immune system to maintain a healthy pregnancy. Furthermore, as gestational age progresses an increasing trend in the activation of immune response is observed to prepare the cascade of events leading to labor and delivery [Citation19]. Another important factor is the alteration of hemoglobin levels throughout the pregnancy. It has been reported that hemoglobin levels tend to decrease as gestational age increases [Citation20]. In our opinion, higher HLR1 and lower HLR2 values in SB patients may be associated with the mentioned immunologic processes. HLR has the potential to be used as a novel complete blood cell index for the prediction of unexplained SB. However, more data is necessary to confirm this theory.
Studies examining placentas have been conducted to determine the cause of SBs [Citation21,Citation22]. In a study conducted in 2016, one-third of the SB patients’ placentas were reported to have normal histology similar to our study [Citation21]. Maternal vascular lesions were found in almost 40 percent of the SB patients in our study. Fibrin deposition which was evaluated in maternal vascular lesions was thought to be a physiological rather than a pathological finding in some studies [Citation23]. This may be the reason for such a high rate in the current study. The second common placental pathological finding in our study was inflammation. Although in a systematic review, fetal SB was attributed to placental inflammatory pathologies [Citation24], chronic villitis was detected in one-third of the patients’ placentas and the majority of the patients had normal outcomes [Citation25]. Therefore, it is not possible to distinguish the normal from the pathological. There is a need for future studies with numerous patients’ placentas of healthy live births.
The strengths of our study were that a large number of complete blood parameters and the inflammatory indices that can be calculated from it were evaluated both in the first trimester and at the time of delivery. We also evaluated a novel parameter, HLR which we think is associated with inflammation. Since we evaluated the unexplained SB patients, we had strict exclusion criteria. Therefore, the number of SB patients in this study was relatively low. An Autopsy is not routinely performed on the fetuses as it is dependent on the family’s request. So, the autopsy results of the SB fetuses were not available in the study. Another limitation was the retrospective design of the study.
In conclusion, we think that necessary precautions such as fetal biophysical profile examination can be taken more frequently in the antenatal follow-up in patients considered to be under high risk by using HLR. It is a novel marker that can be easily accessible and calculated from the complete blood parameters to predict SB. However, further studies are needed for this novel ratio to be used in clinics.
Authors’ contributions
Concept- D.T.E, B.L.K, A.T.; Design- D.T.E., A.T.; Supervision- Ö.K., D.Ş; Resource- D.T.E, B.L.K.; Data collection/Processing- D.T.E., B.L.K., S.S.; Analysis/Interpretation- D.T.E., A.T., S.S.; Literature search- D.T.E., Ö.K.; Writing- D.T.E., S.S., A.T., D.Ş; Critical Reviews- Ö.K., A.T., D.Ş. All authors read and approved the final version of the manuscript.
Compliance with ethical standards
All procedures performed were in accordance with the ethical standards of the institutional committee.
Ethical approval
All procedures performed were in accordance with the ethical standards of the institutional committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Disclosure statement
The authors declare that they have no conflict of interest. The authors declare no financial disclosure. All authors read and approved the final manuscript. This manuscript is not under consideration for publication anywhere else.
Additional information
Funding
References
- Wojcieszek AM, Shepherd E, Middleton P, et al. Interventions for investigating and identifying the causes of stillbirth. Cochrane Database of Systematic Reviews. 2018;2018(4):CD012504.
- Reinebrant HE, Leisher SH, Coory M, et al. Making stillbirths visible: a systematic review of globally reported causes of stillbirth. BJOG. 2018;125(2):212–224.
- Tindal K, Bimal G, Flenady V, et al. Causes of perinatal deaths in Australia: slow progress in the preterm period. Aust NZ J Obst Gynaeco. 2022;62(4):511–517.
- Malacova E, Tippaya S, Bailey HD, et al. Stillbirth risk prediction using machine learning for a large cohort of births from Western Australia, 1980–2015. Sci Rep. 2020;10(1):1–8.
- Fadiloglu E, Tanacan A, Unal C, et al. Evaluation and management of women who have experienced stillbirth in their previous pregnancies. Gynecology Obstet Reprod Med. 2021;27(1):40–43.
- Derricott H, Jones RL, Greenwood SL, et al. Characterizing villitis of unknown etiology and inflammation in stillbirth. Am J Pathology. 2016;186(4):952–961.
- Harrison MS, Thorsten VR, Dudley DJ, et al. Stillbirth, inflammatory markers, and obesity: results from the stillbirth collaborative research network. Am J Perinatol. 2018;35(11):1071–1078.
- Turgut E, Yildirim M, Sakcak B, et al. Predicting miscarriage using systemic immune‐inflammation index. J of Obstet Gynaecol. 2022;48(3):587–592.
- Muin DA, Windsperger K, Attia N, et al. Predicting singleton antepartum stillbirth by the demographic fetal medicine foundation risk calculator—A retrospective case-control study. PLoS ONE. 2022;17(1):e0260964.
- Dagdeviren G, Uysal NS, Dilbaz K, et al. Application of the international classification of diseases-perinatal mortality (ICD-PM) system to stillbirths: a single center experience in a Middle income country. J Gynecol Obstet Human Reprod. 2022;51(2):102285.
- Townsend R, Manji A, Allotey J, et al. Can risk prediction models help us individualise stillbirth prevention? A systematic review and critical appraisal of published risk models. BJOG. 2021;128(2):214–224.
- Conde‐Agudelo A, Bird S, Kennedy S, et al. First‐and second‐trimester tests to predict stillbirth in unselected pregnant women: a systematic review and meta‐analysis. BJOG. 2015;122(1):41–55.
- Jones F, Thibon P, Guyot M, et al. Practice of pathological examinations in stillbirths: a 10-year retrospective study. J Gynecol Obstet Hum Reprod. 2017;46(1):61–67.
- Yao R, Ananth CV, Park BY, et al. Obesity and the risk of stillbirth: a population-based cohort study. Am J Obstet Gynecol. 2014;210(5):457.e1–e9.
- Liu D, Huang X, Xu Z, et al. Predictive value of NLR and PLR in missed miscarriage. J Clin Lab Anal. 2022;36(3):e24250.
- Kim Y. Retrospective analysis of prognostic value of the neutrophil-to-lymphocyte ratio in early miscarriages: a 8-year survey. Medicine. 2020;99(27):e20888.
- Cavalcante MB, Sarno M, Araujo Júnior E, et al. Lymphocyte immunotherapy in the treatment of recurrent miscarriage: systematic review and meta-analysis. Arch Gynecol Obstet. 2017;295(2):511–518.
- Meuleman T, Lashley LE, Dekkers OM, et al. HLA associations and HLA sharing in recurrent miscarriage: a systematic review and meta-analysis. Human İmmunol. 2015;76(5):362–373.
- Mor G, Cardenas I. The immune system in pregnancy: a unique complexity. Am J Reprod İmmunol. 2010;63(6):425–433.
- Whittaker PG, Macphail S, Lind T. Serial hematologic changes and pregnancy outcome. Obstet Gynecol. 1996;88(1):33–39.
- Man J, Hutchinson JC, Heazell AE, et al. Stillbirth and intrauterine fetal death: role of routine histopathological placental findings to determine cause of death. Ultrasound Obstet Gynecol. 2016;48(5):579–584.
- Heazell AE, Martindale EA. Can post-mortem examination of the placenta help determine the cause of stillbirth? J Obstet Gynaecol. 2009;29(3):225–228.
- Redline RW. Extending the spectrum of massive perivillous fibrin deposition (maternal floor ınfarction). Pediatr Dev Pathol. 2021;24(1):10–11.
- Cornish EF, McDonnell T, Williams DJ. Chronic ınflammatory placental disorders associated with recurrent adverse pregnancy outcome. Front Immunol. 2022;13:825075.
- Nowak C, Joubert M, Jossic F, et al. Perinatal prognosis of pregnancies complicated by placental chronic villitis or intervillositis of unknown etiology and combined lesions: about a series of 178 cases. Placenta. 2016;44:104–108.