https://orcid.org/0000-0003-0551-0942
Figures
Abstract
Objective
Preterm prelabor rupture of membranes (PPROM) is frequently complicated by intra-amniotic inflammation. Interleukin-6 (IL-6) measured in amniotic fluid is considered the gold-standard biomarker for the diagnosis of this condition; however, diagnostic thresholds have been derived primarily from biobanked samples. It remains unclear whether IL-6 concentrations measured in fresh amniotic fluid are directly comparable with those obtained from previously processed samples. The primary aim of this study was to compare IL-6 concentrations in fresh amniotic fluid samples with those in biobanked samples that had undergone a single freeze–thaw cycle.
Method
This retrospective study included consecutive singleton pregnancies with PPROM between 24 + 0 and 36 + 6 weeks of gestation. Amniotic fluid samples were collected on admission, prior to the administration of antibiotics and corticosteroids. IL-6 concentrations were measured in both fresh and biobanked (processed) samples using an automated electrochemiluminescence immunoassay.
Results
The study population comprised 152 women. IL-6 concentrations in fresh and processed samples were strongly correlated (rho = 0.97; p < 0.0001). Bland–Altman analysis demonstrated a systematic bias toward higher concentrations in processed samples, with a mean ratio of 1.2, indicating that processed samples yielded on average approximately 20% higher values than fresh samples. When applying the validated diagnostic threshold of 3,000 pg/mL (established in processed samples) to fresh samples, three false-negative cases were observed. In these cases, intra-amniotic inflammation was present, but IL-6 concentrations in fresh samples were below the threshold despite corresponding processed values ≥ 3,000 pg/mL. Using intra-amniotic inflammation defined by processed samples as the reference, the diagnostic performance of the 3,000 pg/mL threshold applied to fresh samples was as follows: sensitivity 92%, specificity 100%, positive predictive value 100%, and negative predictive value 97%.
Citation: Spacek R, Bubenikova S, Musilova I, Kuzniciusova N, Janochova K, Kostelkova M, et al. (2026) Effect of a freeze–thaw cycle on amniotic fluid interleukin-6 concentrations in pregnancies with preterm prelabor rupture of membranes: Implications for the diagnosis of intra-amniotic inflammation. PLoS One 21(6): e0347105. https://doi.org/10.1371/journal.pone.0347105
Editor: Ali Cetin, University of Health Sciences (Istanbul, Türkiye), TÜRKIYE
Received: October 22, 2025; Accepted: March 28, 2026; Published: June 11, 2026
Copyright: © 2026 Spacek et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: This study was supported by University Hospital Hradec Kralove (The Biomedical Indicators for Personalized Medicine project (BIPOLE), project ID CZ.02.01.01/00/23_021/0008439, is co-funded by the European Union). The authors are solely responsible for the content and writing of this paper.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Preterm prelabor rupture of membranes (PPROM), defined as rupture of the fetal membranes before 37 weeks of gestation and prior to the onset of labor [1,2]. PPROM represents approximately one-third of all preterm birth and contributes substantially to neonatal morbidity and mortality worldwide [1,2]. A considerable proportion of PPROM cases are complicated by intra-amniotic inflammation, a condition strongly associated with adverse pregnancy outcomes, including preterm delivery, neonatal sepsis, and long-term neurodevelopmental impairment [3–5].
Recent studies suggest that individualized management of PPROM based on the presence or absence of intra-amniotic inflammation is associated with improved maternal and neonatal outcomes compared with uniform expectant treatment strategy [6,7]. Reliable identification of intra-amniotic inflammation is therefore essential for guiding personalized clinical decision-making.
Interleukin (IL)-6 has emerged as the gold-standard biomarker for the diagnosis of intra-amniotic inflammation [8–10]. Several diagnostic thresholds have been established, depending on the method of measurement: 2.6 ng/mL for enzyme-linked immunosorbent assay (ELISA) [11], 0.745 ng/mL for the Millenia point-of-care test [12,13], and 3.0 ng/mL for automated electrochemiluminescence immunoassay [14]. Importantly, these cut-offs were derived from analyses of biobanked amniotic fluid samples that had undergone at least one freeze–thaw cycle [8,12–14].
In clinical practice, however, IL-6 concentrations are measured in fresh amniotic fluid obtained immediately after sampling [9,15,16]. It still remains unclear whether IL-6 concentrations in fresh and previously processed samples are comparable, and whether diagnostic thresholds derived from frozen/thawed specimens can be directly applied to fresh clinical samples. To address this knowledge gap, the main aim of this study was to compare IL-6 concentrations in fresh amniotic fluid samples with those in biobanked samples that had undergone a freeze–thaw cycle in women with PPROM, and to assess the implications for the diagnosis of intra-amniotic inflammation. Both measurements were performed in a high-volume biochemistry laboratory using an automated electrochemiluminescence immunoassay to ensure clinical relevance.
Materials and methods
This retrospective cohort study was conducted at the Department of Obstetrics and Gynecology, University Hospital Hradec Kralove, Czech Republic. Participants were pregnant women admitted between January 1, 2021, and June 30, 2023. Inclusion criteria were: a) singleton pregnancy; b) maternal age ≥ 18 years; c) PPROM at 24 + 0–36 + 6 gestational weeks; and d) transabdominal amniocentesis performed at admission to assess intra-amniotic inflammation. Exclusion criteria were: a) medical or obstetric complications (e.g., fetal growth restriction, pre-gestational or gestational diabetes, chronic or gestational hypertension and preeclampsia; b) chromosomal or structural fetal abnormality; c) signs of fetal hypoxia; and d) significant vaginal bleeding.
Gestational age was determined based on the first trimester fetal biometry. PPROM diagnosis was established by sterile speculum examination to identify pooling of amniotic fluid in the posterior vaginal fornix. In cases of diagnostic uncertainty, amniotic fluid leakage was confirmed by testing vaginal fluid for insulin-like growth factor-binding proteins (Actim PROM test; Medix Biochemica, Kauniainen, Finland) [17,18].
Women with PPROM received intravenous antibiotics: benzylpenicillin (or clindamycin in case of penicillin allergy) if intra-amniotic inflammation was absent, and clarithromycin if intra-amniotic inflammation was present. Antibiotic therapy was continued for seven days unless delivery occurred earlier.
Women with PPROM and intra-amniotic infection at gestational age > 28 + 0 weeks underwent induction of labor or elective cesarean section within 72 hours of admission. Remaining women with PPROM were managed expectantly. Women with PPROM at < 35 + 0 weeks’ gestation were given intramuscular betamethasone to accelerate fetal lung maturation and reduce neonatal morbidity and mortality. During active labor, women with PPROM who had positive vaginal-rectal swabs for Streptococcus agalactiae, or an unknown colonization status, received intravenous benzylpenicillin (or clindamycin, in case of penicillin allergy).
All women were Caucasian and provided written informed consent prior to sampling. Ethical approval for the collection of leftovers of amniotic fluid for research, was granted by the Institutional Review Board of the University Hospital Hradec Kralove (February 2019, No. 201902 S16P). The study itself was approved by the Institutional Review Board of University Hospital Hradec Kralove (June 2025, No. 202506 P05). Prior to analysis, which began September 1, 2025, all data were fully anonymized. Information that could identify participants during or after data collection was accessible only to the study authors. All sampling and analyses were performed in accordance with the relevant guidelines and regulations. Aliquots of these samples were used in our previous studies [19–21]
Amniotic fluid sampling and analysis
Amniotic fluid was obtained via transabdominal amniocentesis. Each sample was divided into 0.5 mL aliquots, which were immediately sent for: i) assessment of IL-6 concentrations using an automated electrochemiluminescence immunoassay method (fresh amniotic fluid); ii) aerobic and anaerobic cultivation; iii) species-specific polymerase chain reaction (PCR) to detect Ureaplasma spp., Mycoplasma hominis, and Chlamydia trachomatis DNA; and iv) species-nonspecific PCR targeting the 16S rRNA gene, followed by Sanger sequencing. The remaining amniotic fluid was processed (processed amniotic fluid) and stored at −80°C until analyses.
Amniotic fluid IL-6 concentrations in fresh and processed samples
Fresh amniotic fluid samples were delivered immediately after collection to a high-volume biochemistry laboratory, where they were centrifuged for 5 minutes at 2000 g at 4°C to remove cells and debris, and then analyzed.
Processed amniotic fluid samples were placed into refrigerator (4°C) immediately after collection and centrifuged within one hour for 15 minutes at 2000 g at 4°C to remove cells and debris. The samples were then divided into the 0.5 mL aliquots and stored at −80°C until analyses. For this study, only aliquots subjected to a single freeze-thaw cycle were used.
IL-6 concentrations in both fresh and processed samples were determined using a Cobas e602 immunoanalyzer, part of the Cobas 8000 platform (Roche Diagnostics, Basel, Switzerland). The measuring range was 1.5–5,000 pg/mL, extendable to 50,000 pg/mL, with 10-fold dilution. Samples with IL-6 concentrations > 50,000 pg/mL were assigned a value of 50,001 pg/mL [14]. The coefficient of variation for inter-assay and intra-assay precisions were < 10% [14].
Detection of Ureaplasma spp., M. hominis, C. trachomatis and other bacteria in amniotic fluid
The commercial AmpliSens® C. trachomatis/Ureaplasma/M. hominis-FRT kit (Federal State Institution of Science, Central Research Institute of Epidemiology, Moscow, Russia) was used to detect DNA of Ureaplasma spp., M. hominis and C. trachomatis. Details of the detection of other bacteria in amniotic fluid by sequencing of the 16S rRNA gene and by aerobic/anaerobic cultures have been described previously [17].
Clinical definitions
Intra-amniotic inflammation: interleukin-6 concentration in fresh amniotic fluid ≥ 3000 pg/mL. Microbial invasion of the amniotic cavity: presence of microorganisms and/or their nucleic acids in amniotic fluid. Intra-amniotic infection: concomitant presence of both intra-amniotic inflammation and microbial invasion of the amniotic cavity. Sterile intra-amniotic inflammation: presence of intra-amniotic inflammation without microbial invasion of the amniotic cavity. Colonization of the amniotic cavity: presence of microbial invasion of the amniotic cavity without intra-amniotic inflammation. Negative amniotic fluid: absence of both intra-amniotic inflammation and microbial invasion of the amniotic cavity
Statistics
The nonparametric Kruskal-Wallis H test was applied to compare continuous variables (presented as median values; interquartile range [IQR]) among demographic and clinical characteristics. Categorical variables, presented as numbers (%), were compared using Chi-square test. Normality of data was assessed with the Anderson–Darling test. Amniotic fluid IL-6 concentrations in fresh and processed samples were compared with the paired Wilcoxon test. Spearman’s correlation coefficient was used to assess the correlation between amniotic fluid IL-6 concentrations in fresh and processed samples. A ratio-based Bland-Altman plot was constructed to assess agreement between amniotic fluid IL-6 concentrations in fresh and processed samples. Log transformation was not applied, as IL-6 concentrations are used directly in clinical practice to rule in or rule out intra-amniotic inflammation based on absolute threshold. Sensitivity analyses excluding samples with IL-6 concentrations above the upper measuring limit were performed to assess the robustness of correlation, paired comparison, and Bland-Altman analyses. All p values were two-tailed, and differences were regarded as statistically significant at p < 0.05. All statistical analyses were performed using GraphPad Prism, version 10.6.1 for Mac OS X (GraphPad Software, San Diego, CA, USA).
Results
A total of 192 women with late PPROM were recruited. Forty women were excluded due to gestation diabetes mellitus (n = 25), fetal growth restriction (n = 6), preeclampsia (n = 5), gestational hypertension (n = 2), and chronic hypertension (n = 2). The final study population therefore comprised 152 women.
Among the included women, 24% (36/152) had intra-amniotic inflammation and 26% (40/152) microbial invasion of the amniotic cavity. When women were stratified into groups according to the presence or absence of these conditions, 18% (27/152) had intra-amniotic infection, 6% (9/152) had sterile intra-amniotic inflammation, 9% (13/152) had colonization of the amniotic cavity, and 67% (103/152) had negative amniotic fluid for both inflammation and microorganisms. The demographic and clinical characteristics of the women and their neonates according to these groups are summarized and 26% (40/152) in Table 1.
Concentrations of IL-6 in fresh amniotic fluid in women with intra-amniotic inflammation, sterile intra-amniotic inflammation, colonization of the amniotic cavity and negative amniotic fluid are shown in Fig 1.
Red circles indicated women who had intra-amniotic inflammation in the processed samples despite having negative amniotic fluid results in the fresh samples.
IL-6 concentrations above the upper measuring limit (> 50,000 pg/mL) were observed in 8 of 152 fresh samples (5.3%) and 9 of 152 processed samples (5.9%).
The median storage duration of the processed amniotic fluid was 40 months (IQR 34–46). There was no difference in storage duration among groups (p = 0.22): intra-amniotic infection (median 39 months, IQR 34–45), sterile intra-amniotic inflammation (median 39 months, IQR 35–46), colonization of the amniotic cavity (median 45 months, IQR 37–51), and negative amniotic fluid (median 40 months, IQR 34–46).
Comparison of IL-6 concentrations between fresh and processed amniotic fluid samples
IL-6 concentrations measured in fresh and processed amniotic fluid samples were highly correlated (rho = 0.97; p < 0.0001; Fig 2). However, values were lower in fresh samples compared to processed samples (fresh: median 1,071 pg/mL, IQR 471−2,905 vs. processed: median 1,421 pg/mL, IQR 507−3,271; p < 0.0001; Fig 3).
Bland-Altman analysis using a ratio-based approach demonstrated a systematic bias toward higher IL-6 concentrations in processed samples, with a mean ratio of 1.2, indicating that processed samples yielded on average approximately 20% higher values than fresh samples (Fig 4). The limits of agreement ranged from 0.5 to 1.9, indicating that IL-6 concentrations in processed samples were generally between 50% lower and 90% higher than the corresponding concentrations in fresh samples.
When applying the validated diagnostic threshold of 3,000 pg/mL (established in processed samples) to fresh samples, three false-negative cases were observed (all with sterile intra-amniotic inflammation). In these cases, intra-amniotic inflammation was present, but IL-6 concentrations in fresh samples were below the threshold, despite corresponding processed values ≥ 3,000 pg/mL.
Sensitivity analyses excluding samples with IL-6 concentrations > 50,000 pg/mL did not alter the correlation (rho = 0.97; p < 0.0001), paired comparison (fresh: median 994 pg/mL, IQR 418−2,150 vs. processed: median 1,323 pg/mL, IQR 491−2,700; p < 0.0001), and Bland-Altman agreement between fresh and processed samples (mean ratio of 1.2, the limits of agreement from 0.5 to 1.9).
Using intra-amniotic inflammation in processed samples as the reference, the diagnostic performance of the 3,000 pg/mL threshold applied to fresh samples was as follows: sensitivity of 92% (36/39; 95% confidence interval [CI], 80–97), specificity 100% (103/103; 95% CI, 96–100), positive predictive value 100% (36/36; 95% CI, 90–100%), and negative predictive value 97% (103/106; 95% CI, 92–99).
Discussion
In this study we demonstrate that IL-6 concentrations measured in amniotic fluid supernatant are consistently higher after a single freeze–thaw cycle than in matched fresh samples. Because IL-6 is a key biomarker of intra-amniotic inflammation, this finding may have direct implications for both clinical decision-making and research based on stored biological material.
Most published investigations on cytokine stability have focused on serum or plasma [22–25]. These studies generally suggest that IL-6 is relatively stable across several freeze–thaw cycles, although variability has been reported [22–25]. Some investigations observed little to no change in IL-6 concentrations even after multiple freeze–thaw events, whereas others documented gradual declines during long-term storage, particularly in amniotic fluid [22–27]. Overall, findings indicate that cytokine stability may depend on sample matrix, storage conditions, and analytical method, underscoring the need for validation in clinically relevant settings [22–25].
Our present results build on and extend previous work from our group investigating the impact of pre-analytical handling and storage on amniotic fluid IL-6 concentrations [14]. In an earlier study, we demonstrated that variations in sample processing, including latency time before centrifugation, centrifugation conditions, and addition of protease inhibitors, did not significantly influence IL-6 concentrations, although no direct comparison with fresh samples was performed [14]. Later, our group showed that IL-6 concentrations measured by a point-of-care IL-6 test (the lateral immunoflow assay) were lower in fresh amniotic fluid samples compared with their processed counterparts [28]. In that study, however, the fresh samples were analyzed without prior centrifugation [28]. This previous observation is in line with the result of the present study, where both types of samples underwent centrifugation.
Several biological and analytical factors may explain the observed increase in IL-6 concentrations in processed samples, which underwent a freeze-thaw cycle. First, extracellular vesicle disruption. Amniotic fluid is rich in exosomes and microvesicles capable of encapsulating or surface-binding cytokines [29,30]. Conventional pre-analytical centrifugation at low g-forces does not fully remove these vesicles [31]. Ice crystal formation and osmotic stress during freezing and thawing can rupture vesicles, releasing IL-6 into the soluble phase that is accessible to immunoassays [32,33]. Second, dissociation of protein complexes. IL-6 circulates partly bound to soluble IL-6 receptor or other carrier proteins [34]. Freezing can destabilize these complexes, expose epitopes and increase antibody recognition [35,36]. Last, matrix and assay effects. Physical changes of the matrix (pH, ionic strength, viscosity) and cryoconcentration may enhance antigen–antibody interactions or reduce inhibitory matrix effects [36,37]. Minor evaporation during freezing could further concentrate solutes if mixing is incomplete after thawing. These mechanisms are not mutually exclusive and may act synergistically.
In the present study, the diagnostic cut-off of 3,000 pg/mL for IL-6, originally validated in processed samples [14], did not fully translate to fresh specimens. Although correlation between fresh and processed values was excellent, a ratio-based Bland–Altman analysis demonstrated a systematic bias, with processed samples yielding approximately 20% higher concentrations. While the limits of agreement were relatively wide, the clinical impact of this variability is primarily confined to IL-6 concentrations near the diagnostic threshold. At concentrations far exceeding the threshold – clearly indicate intra-amniotic inflammation – proportional differences between fresh and processed samples are unlikely to affect clinical decision-making.
From a clinical perspective, our findings suggest that caution is warranted when applying diagnostic threshold for intra-amniotic inflammation derived exclusively from biobanked specimens. In our cohort, use of the 3,000 pg/mL threshold, validated in processed samples, resulted in three false-negative cases when applied to fresh samples, all corresponding to sterile intra-amniotic inflammation. Although the overall diagnostic performance of this threshold remained high, these missed cases underscore the risk of underdiagnosis when thresholds are not validated directly in fresh clinical material.
Given that individualized management of PPROM is based on the presence of intra-amniotic inflammation even a small number of missed cases may carry clinical significance. Such misclassification has the potential to influence clinical management, including antibiotic selection and the choice between expectant and active management, depending on gestational age and subsequent microbiological findings. These considerations highlight the clinical relevance of validating diagnostic cut-offs specifically for fresh amniotic fluid samples.
The strengths of this study are several. First, we used a paired design, directly comparing fresh and processed aliquots of the same amniotic fluid sample. Second, both fresh and processed samples were handled according to the standardized protocols and analyzed on the same automated electrochemiluminescence platform, thereby minimizing inter-individual and batch variability among the fresh and processed samples. Third, a relatively large cohort of women with one well-defined clinical phenotype of spontaneous preterm labor (PPROM) was included in the study. Finally, the study population was ethnically homogeneous (Caucasian), which reduced variability related to population-specific or genetic factors. Limitations should also be acknowledged. First, we evaluated only a single freeze–thaw cycle, while additional cycles or prolonged storage may produce different effects, including potential cytokine degradation. Second, pre-analytical handling of fresh and processed samples differed and may represent a potential source of bias. For examples, fresh samples were centrifuged promptly in the biochemistry laboratory but for a shorter duration than processed samples. Third, storage time of the processed samples was not uniform, ranging from 28 to 51 months, which could have affected cytokine stability. Fourth, we did not assess extracellular vesicles or IL-6–binding complexes, which may influence measured IL-6 concentrations and could help explain differences between fresh and processed specimens. Last, the exploratory nature of this study should be acknowledged. No a priori sample size or power calculation was performed for the agreement analyses, as no prior data were available to inform such calculations. Nevertheless, the relatively large number of paired samples strengthens the robustness of the observed associations.
In conclusion, IL-6 concentrations in fresh and processed amniotic fluid samples are highly correlated, but processed samples consistently yield higher values. This discrepancy is most critical for fresh samples with IL-6 concentrations just below the diagnostic threshold, which may be falsely classified as negative, underscoring the need to validate and possibly adjust cut-offs for fresh clinical specimens to ensure accurate diagnosis of intra-amniotic inflammation.
References
- 1. Romero R, Yeo L, Gotsch F, Soto E, Hassan SS, Kusanovic JP, et al. Prelabor rupture of the membranes. Clinical Maternal-Fetal Medicine Online. CRC Press. 2021. p. 2.1-2.24.
- 2.
Romero RGL, Chaiworapongsa T, Kusanovic J, Espinoza J. Mechanisms of preterm labor and preterm premature rupture of the membranes. In: Kurjak A, Chervenak F, editors. Textbook of Perinatal Medicine. 2nd ed. London, UK: Informa UK Ltd. 2006. p. 1379–93.
- 3. Romero R, Miranda J, Chaemsaithong P, Chaiworapongsa T, Kusanovic JP, Dong Z, et al. Sterile and microbial-associated intra-amniotic inflammation in preterm prelabor rupture of membranes. J Matern Fetal Neonatal Med. 2015;28(12):1394–409. pmid:25190175
- 4. Musilova I, Kutová R, Pliskova L, Stepan M, Menon R, Jacobsson B, et al. Intraamniotic Inflammation in Women with Preterm Prelabor Rupture of Membranes. PLoS One. 2015;10(7):e0133929. pmid:26208287
- 5. Rodríguez-Trujillo A, Ríos J, Ángeles MA, Posadas DE, Murillo C, Rueda C, et al. Influence of perinatal inflammation on the neurodevelopmental outcome of premature infants. J Matern Fetal Neonatal Med. 2019;32(7):1069–77. pmid:29082789
- 6. Cobo T, Aldecoa V, Ferrero S, Balcells J, Contreras AL, Valenzuela A, et al. Preterm prelabor rupture of membranes: the use of amniocentesis to detect intraamniotic infection reduces maternal and neonatal duration of antibiotic exposure. Am J Obstet Gynecol. 2025;233(5):477.e1-477.e11. pmid:40505796
- 7. Ronzoni S, Cobo T, D’Souza R, Asztalos E, O’Rinn SE, Cao X, et al. Individualized treatment of preterm premature rupture of membranes to prolong the latency period, reduce the rate of preterm birth, and improve neonatal outcomes. Am J Obstet Gynecol. 2022;227(2):296.e1-296.e18. pmid:35257664
- 8. Romero R, Kadar N, Miranda J, Korzeniewski SJ, Schwartz AG, Chaemsaithong P, et al. The diagnostic performance of the Mass Restricted (MR) score in the identification of microbial invasion of the amniotic cavity or intra-amniotic inflammation is not superior to amniotic fluid interleukin-6. J Matern Fetal Neonatal Med. 2014;27(8):757–69. pmid:24028673
- 9. Kacerovsky M, Romero R, Stepan M, Stranik J, Maly J, Pliskova L, et al. Antibiotic administration reduces the rate of intraamniotic inflammation in preterm prelabor rupture of the membranes. Am J Obstet Gynecol. 2020;223(1):114.e1-114.e20. pmid:32591087
- 10. Romero R, Yoon BH, Mazor M, Gomez R, Gonzalez R, Diamond MP, et al. A comparative study of the diagnostic performance of amniotic fluid glucose, white blood cell count, interleukin-6, and gram stain in the detection of microbial invasion in patients with preterm premature rupture of membranes. Am J Obstet Gynecol. 1993;169(4):839–51. pmid:7694463
- 11. Yoon BH, Romero R, Moon JB, Shim SS, Kim M, Kim G, et al. Clinical significance of intra-amniotic inflammation in patients with preterm labor and intact membranes. Am J Obstet Gynecol. 2001;185(5):1130–6. pmid:11717646
- 12. Chaemsaithong P, Romero R, Korzeniewski SJ, Martinez-Varea A, Dong Z, Yoon BH, et al. A point of care test for interleukin-6 in amniotic fluid in preterm prelabor rupture of membranes: a step toward the early treatment of acute intra-amniotic inflammation/infection. J Matern Fetal Neonatal Med. 2016;29(3):360–7. pmid:25758620
- 13. Chaemsaithong P, Romero R, Korzeniewski SJ, Martinez-Varea A, Dong Z, Yoon BH, et al. A rapid interleukin-6 bedside test for the identification of intra-amniotic inflammation in preterm labor with intact membranes. J Matern Fetal Neonatal Med. 2016;29(3):349–59. pmid:25758618
- 14. Musilova I, Andrys C, Holeckova M, Kolarova V, Pliskova L, Drahosova M, et al. Interleukin-6 measured using the automated electrochemiluminescence immunoassay method for the identification of intra-amniotic inflammation in preterm prelabor rupture of membranes. J Matern Fetal Neonatal Med. 2020;33(11):1919–26. pmid:30293462
- 15. Musilova I, Stranik J, Jacobsson B, Kacerovsky M. Antibiotic treatment reduces the intensity of intraamniotic inflammation in pregnancies with idiopathic vaginal bleeding in the second trimester of pregnancy. Am J Obstet Gynecol. 2024;230(2):245.e1-245.e14. pmid:37516399
- 16. Kacerovsky M, Vrbacky F, Matulova J, Bolehovska R, Kukla R, Pavlikova L, et al. Late preterm prelabor rupture of membrane (>33 weeks): the risk of intraamniotic inflammation and fetal inflammation is influenced by the cervical microbial ecosystem and cervical inflammation. Am J Obstet Gynecol. 2025;233(5):479.e1-479.e18. pmid:40516585
- 17. Stranik J, Kacerovsky M, Soucek O, Kolackova M, Musilova I, Pliskova L, et al. IgGFc-binding protein in pregnancies complicated by spontaneous preterm delivery: a retrospective cohort study. Sci Rep. 2021;11(1):6107. pmid:33731725
- 18.
Preterm labour and birth. NICE. 2022.
- 19. Soucek O, Kacerovsky M, Musilova I, Kukla R, Bolehovska R, Bostik P, et al. Amniotic and cervical fluids progranulin levels in pregnancies complicated by spontaneous preterm delivery with respect to intra-amniotic complications-a retrospective cohort study. Sci Rep. 2025;15(1):25054. pmid:40645975
- 20. Kacerovsky M, Stranik J, Matulova J, Chalupska M, Mls J, Faist T, et al. Clinical characteristics of colonization of the amniotic cavity in women with preterm prelabor rupture of membranes, a retrospective study. Sci Rep. 2022;12(1):5062. pmid:35332204
- 21. Kacerovsky M, Matulova J, Andrys C, Mls J, Hornychova H, Kukla R, et al. Preterm prelabor rupture of membranes without microbial invasion of the amniotic cavity and intra-amniotic inflammation: a heterogeneous group with differences in adverse outcomes. J Matern Fetal Neonatal Med. 2022;35(25):9145–56. pmid:34918985
- 22. Kenis G, Teunissen C, De Jongh R, Bosmans E, Steinbusch H, Maes M. Stability of interleukin 6, soluble interleukin 6 receptor, interleukin 10 and CC16 in human serum. Cytokine. 2002;19(5):228–35. pmid:12393169
- 23. Chowdhury RN, Armato A, Culver E, Shteynman L, Kurien C, Cradin B, et al. Quantitative and qualitative analysis of stability for 16 serum immunoregulators over 50 freeze-thaw cycles. Am J Hum Biol. 2024;36(9):e24087. pmid:38682460
- 24. Rebholz SL, Melchior JT, Welge JA, Remaley AT, Davidson WS, Woollett LA. Effects of Multiple Freeze/Thaw Cycles on Measurements of Potential Novel Biomarkers Associated With Adverse Pregnancy Outcomes. J Clin Lab Med. 2017;2(1):10.16966/2572-9578.107. pmid:29226278
- 25. Kordulewska NK, Topa J, Tanska M, Cieslinska A, Fiedorowicz E, Jarmolowska B. Stability of interleukin-1beta, -4, -6, -8, -10, -13, interferon-gamma and tumor necrosis factor-alpha in human sera after repetitive freeze-thaw cycles and long storage. J Pharm Biomed Anal. 2021;196:113900.
- 26. Spong CY, Ghidini A, Ossandon M, Walker CN, Pezzullo JC. Are the cytokines interleukin-6 and angiogenin stable in frozen amniotic fluid?. Am J Obstet Gynecol. 1998;178(4):783–6. pmid:9579444
- 27. Porter AE, Auth J, Prince M, Ghidini A, Brenneman DE, Spong CY. Optimization of cytokine stability in stored amniotic fluid. Am J Obstet Gynecol. 2001;185(2):459–62. pmid:11518909
- 28. Kacerovsky M, Musilova I, Stepan M, Andrys C, Drahosova M, Jacobsson B. Detection of intraamniotic inflammation in fresh and processed amniotic fluid samples with the interleukin-6 point of care test. Am J Obstet Gynecol. 2015;213(3):435–6. pmid:26003057
- 29. Fitzgerald W, Freeman ML, Lederman MM, Vasilieva E, Romero R, Margolis L. A System of Cytokines Encapsulated in ExtraCellular Vesicles. Sci Rep. 2018;8(1):8973. pmid:29895824
- 30. Bhatti G, Romero R, Rice GE, Fitzgerald W, Pacora P, Gomez-Lopez N, et al. Compartmentalized profiling of amniotic fluid cytokines in women with preterm labor. PLoS One. 2020;15(1):e0227881. pmid:31945128
- 31. Coumans FAW, Brisson AR, Buzas EI, Dignat-George F, Drees EEE, El-Andaloussi S, et al. Methodological Guidelines to Study Extracellular Vesicles. Circ Res. 2017;120(10):1632–48. pmid:28495994
- 32. Mohak S, Fabian Z. Extracellular Vesicles as Precision Delivery Systems for Biopharmaceuticals: Innovations, Challenges, and Therapeutic Potential. Pharmaceutics. 2025;17(5):641. pmid:40430932
- 33. Ahmadian S, Jafari N, Tamadon A, Ghaffarzadeh A, Rahbarghazi R, Mahdipour M. Different storage and freezing protocols for extracellular vesicles: a systematic review. Stem Cell Res Ther. 2024;15(1):453. pmid:39593194
- 34. Mihara M, Hashizume M, Yoshida H, Suzuki M, Shiina M. IL-6/IL-6 receptor system and its role in physiological and pathological conditions. Clin Sci (Lond). 2012;122(4):143–59. pmid:22029668
- 35. Lugos M, Polit U, Damen J. A study on the impact of repeat freeze-thaw cycles on the serum cytokine enzyme-linked immunosorbent assay (ELISA). Int J Med Lab Res. 2018;3(3):29–36.
- 36. Jain K, Salamat-Miller N, Taylor K. Freeze-thaw characterization process to minimize aggregation and enable drug product manufacturing of protein based therapeutics. Sci Rep. 2021;11(1):11332. pmid:34059716
- 37. Shamlou PA, Breen LH, Bell WV, Pollo M, Thomas BA. A new scaleable freeze-thaw technology for bulk protein solutions. Biotechnol Appl Biochem. 2007;46(Pt 1):13–26. pmid:16903838