The frequency of cesarean sections (CS), a common obstetric procedure, has gradually increased over the last 10 years [1]. Post-cesarean infections are classified into 2 main categories: general (systemic) infections and specific gynecological infections. General infections include urinary tract infections, pyelonephritis, pneumonia, and mastitis, whereas gynecological infections encompass conditions such as ovarian vein thrombosis, endometritis, and surgical site infections (SSIs) [2].

Specifically, surgical site infection (SSI) following cesarean delivery is defined as an infection occurring within 30 days after the surgical procedure, involving the incision site or deeper tissues manipulated during the operation [3]. SSI is one of the most serious infectious side effects of cesarean delivery, involving either an abdominal incision or a uterine infection. Due to variations in surveillance procedures, patient characteristics, and the use of antibiotic prophylaxis, the incidence of SSI ranges from 3 to 30 percent [4].

SSI is typically characterized by symptoms such as erythema, induration, and purulent or serous discharge, usually occurring within the first week after CS [5]. The occurrence of SSI after CS may be influenced by patient characteristics, healthcare provider factors, and perioperative conditions [6]. Known risk factors for maternal infections following cesarean section include excessive weight or obesity, emergency cesarean delivery, pre-existing psychiatric disorders, the need for blood transfusion during or after delivery, hypertension (gestational hypertension and/or preeclampsia), undergoing 5 or more vaginal examinations during labor, Black race, tobacco use, vertical skin incision, diabetes (pre-gestational and/or gestational), multiple pregnancy, anemia, younger maternal age, and premature rupture of membranes [7].

The most commonly reported risk factors associated with SSIs following cesarean section include preoperative membrane rupture, labor duration exceeding 24 hours, chorioamnionitis, elevated body mass index, severe anemia, vertical skin incision, emergency cesarean delivery, and the lack of preoperative antibiotic prophylaxis. Additionally, prolonged operative time, estimated blood loss greater than 500 mL, postoperative hemoglobin levels below 11 g/dL, advanced maternal age, and a history of more than 6 pregnancies have also been identified as significant risk factors for the development of SSIs [8, 9].

In order to reduce the risk of infection after CS, recommendations include controlling blood glucose and blood pressure, using a preoperative antiseptic douche, preparing the incision site with antiseptics, administering prophylactic antibiotics, performing vaginal cleansing, removing the placenta with traction, applying subcutaneous suturing (for subcutaneous tissue $>$3 cm), and early removal of the bladder catheter [5, 10].

According to recent research, hematologic indices such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and mean platelet volume (MPV) are being used as indicators of systemic inflammation [11, 12]. In obstetrics and gynecology, NLR and PLR have been identified as biomarkers associated with SSIs in several studies [13].

The aim of this study was to investigate whether hematologic indices derived from complete blood count, measured both preoperatively and postoperatively, could be used as early and accessible biomarkers for predicting infections following cesarean delivery.

Throughout the study, 50 control subjects and 50 study group patients were paired. Of the patients in the study group, 42 (84 percent) had SSI, 4 (8 percent) had endometritis, 2 (4 percent) had urinary tract infections, and 2 (4 percent) had mastitis. In 70% of the cases, the infection developed between the 4th and 7th days, while in 30% it occurred after the 7th day. SSI developed in 42 out of 50 patients (84%) in the study group. Wound dehiscence occurred in 30 of the patients (71.4%) diagnosed with SSI, and the wounds were resutured. All 50 patients received antibiotic treatment; 45 (90%) were managed with intravenous antibiotics, while 5 (10%) received oral antibiotic therapy.

The median maternal age of patients with postoperative infections was 28.0 years, while it was 26.5 years in the control group, with no significant difference observed (p = 0.417). Likewise, the median BMI was 30 kg/m² in the infection group and 29 kg/m² in the control group, showing no notable difference (p = 0.994). The median birth weight was 3150 g in the infection group and 3180 g in the control group, also with no significant variation (p = 0.852). The mean operative time was 40.42 minutes for patients with infections and 39.86 minutes for controls, showing no significant variation (p = 0.513). Both groups had a median blood loss of 500 cc and a median gestational age of 38 weeks, with no notable differences (p = 0.678, p = 0.974). Regarding prior cesarean history, 66% (n = 33) of patients with infections and 70% (n = 35) of controls had a history of previous cesarean delivery, with no significant difference (p = 0.830). Additionally, smoking, gestational diabetes mellitus (GDM), hypertensive disorders of pregnancy, intensive care unit admission, history of emergency CS, gravidity and parity were similar between the groups (p = 0.287, p = 1.000, p = 0.795, p = 0.712, p = 0.173, p = 0.057 and p = 0.155, respectively) (Table 1).

There were no significant differences in preoperative and postoperative measurements of PLT, MPV/PLT, PLR, and MPV between the case and control groups (p $>$ 0.05). Similarly, the percentage changes in PLT, MPV/PLT, PLR, and MPV values before and after surgery were not significantly different in the postoperative infection group (p = 0.888, p = 0.874, p = 0.128 and p = 0.815, respectively). While preoperative MLR measurements did not differ significantly between the groups (p = 0.749), postoperative MLR values showed a significant difference (p = 0.002), with an increase of 61% in the infection group and a decrease of 29% in the control group. The percentage changes in MLR between the groups were also significant (p = 0.007). Preoperative NLR measurements showed no significant difference (p = 0.087), but postoperative NLR values were significantly higher in the infection group (p 0.001). NLR increased by 57% in the infection group and by 42% in the control group compared to the preoperative period. Although both groups showed a notable increase, the difference in percentage change between the groups was statistically significant (p = 0.026) (Table 2).

ROC analysis was used to examine significant differences in preoperative and postoperative blood measurements, as well as in percentage changes between the groups (Table 3).

With an area under the ROC curve (AUC) of 0.656 (p 0.001), the cut-off value for the percentage change in MLR from preoperative to postoperative was found to be $>$74.01 for the prediction of surgical infections (p 0.001). This suggests that patients with an MLR percentage change exceeding 74.01 are at higher risk of developing surgical infections (Fig. 1). The cut-off value for postoperative MLR was identified as $>$0.43 and 0.681 (p 0.001) as the AUC (p 0.001), indicating a significant association with surgical infections (Fig. 2). Similarly, the cut-off value for postoperative NLR was calculated as $>$6.16’s predictive potential for surgical infections is further highlighted by its AUC of 0.727 (p 0.001) (Fig. 3). With an area AUC of 0.629 (p = 0.022), the cut-off value for the percentage change in NLR from preoperative to postoperative was found to be $>$34.21 for the prediction of surgical infections. This suggests that patients with an NLR percentage change exceeding 34.21 are at higher risk of developing surgical infections (Fig. 4). The blue dashed lines surrounding the ROC curve represent the 95% confidence interval and indicate the statistical reliability of the curve. These lines reflect the variation at each point on the ROC curve, corresponding to the uncertainty in the measurement of sensitivity. Confidence intervals provide an important statistical reference in the interpretation of ROC analysis, as they demonstrate the extent to which the diagnostic performance of the test may vary depending on the sample.

Fig. 1.

ROC Analysis of Pre- and Postoperative MLR Change in Infection Prediction (AUC = 0.656, p 0.001). ROC, receiver operating curve; MLR, monocyte-to-lymphocyte ratio; AUC, area under the ROC curve.

Fig. 2.

ROC Analysis of Postoperative 24 h MLR in Predicting Post-Cesarean Infection (AUC = 0.681, p 0.001).

Fig. 3.

ROC Curve for 24-Hour Postoperative NLR in Predicting Post-Cesarean Infection (AUC = 0.727, p 0.001). NLR, neutrophil-to-lymphocyte ratio.

Fig. 4.

ROC Analysis of Pre- and Postoperative NLR Change in Infection Prediction (AUC = 0.629, p = 0.022).

Given the increasing rates of CS worldwide, along with the associated infection risks and the potential adverse effects of mother-infant separation, addressing this issue and developing new strategies for the early diagnosis of infections is critical. In this context, considering the high incidence of infections following cesarean delivery and the advantages of readily available blood tests with predictive potential, this study examined the relationship between hematologic indices measured before and after CS, the development of these infections, and their contribution to early diagnosis. The null hypothesis was rejected for NLR and MLR.

A significant difference was observed in postoperative MLR levels (p = 0.002), with a 61% increase in the infection group and a 29% decrease in the control group. The intergroup difference in the percentage change in MLR was also statistically significant (p = 0.007). Similarly, the infection group had a significantly higher postoperative NLR level (p 0.001). Compared to the preoperative period, NLR increased by 57% in the infection group and by 42% in the control group. Although both groups exhibited a substantial rise, the difference in the percentage change between them was statistically significant (p = 0.026).

In the study by Rotem et al. [2], NLR was found to be independently associated with infections after CS, and PLR values were also found to be significant. This study is one of the few in the literature that attempts to predict infections after obstetric and gynecological surgeries. They found SSI to be the most prevalent infection (71 percent), which is consistent with this study [2]. Similarly, Erciyestepe et al. [15] examined the role of NLR and PLR in predicting the risk of infection after hysterectomy and demonstrated that postoperative NLR and PLR levels were higher in patients with infections. İbanoğlu et al. [16] highlighted the prognostic significance of NLR in wound infections following CS and found a relationship between increased infection risk and factors such as high BMI, multiple cesarean sections, and operation times of 30–50 minutes, although they did not categorize infections. Aktoz et al. [12] also reported that both NLR and PLR levels increased in the SSI group after CS. Differences in results between studies may stem from population characteristics, study design, type of infection, and measurement methods. However, according to this study, high postoperative NLR ($>$6.16) and MLR ($>$0.43) values can serve as predictive criteria for infection development. Furthermore, the percentage changes in preoperative and postoperative NLR and MLR values (AUC: 0.629 and AUC: 0.656, respectively) may help predict the risk of postoperative infection. These findings suggest that MLR and NLR may be an effective marker for predicting infections, not only as a single measurement but also through its change over time. Patients with elevated NLR and MLR values may be at increased risk for post-cesarean infections, and in such cases, proper wound care, adherence to hygiene practices, adequate nutrition, early mobilization, observation for potential signs of infection, and regular medical follow-up are recommended to support early detection and timely intervention. However, large-scale prospective randomized studies are needed to establish specific treatment strategies.

Similar results have been reported in studies involving surgical procedures outside the field of obstetrics and gynecology. For instance, Wang et al. [17] demonstrated that postoperative NLR could predict complications secondary to infections, with an AUC value of 0.641. In the context of diabetic nephropathy, the optimal MLR cut-off value was reported to be 0.23, with 85% sensitivity, 74% specificity, and an AUC of 0.874 [18]. Zhuo et al. [19] found that NLR and PLR effectively predicted SSI in the preoperative period. NLR achieved an AUC of 0.875, with a sensitivity of 97.44% and specificity of 70.3%, while PLR had an AUC of 0.723, with a sensitivity of 74.36% and specificity of 64.24%. However, in this study, preoperative NLR, PLR, and MLR values, as well as postoperative PLR values, were not found to be significant. Similarly, the preoperative and postoperative percentage changes in NLR and PLR were also not significant.

When neutrophils are inappropriately activated, they can cause tissue damage by producing reactive oxygen species, a process that constitutes one of the fundamental mechanisms of inflammatory diseases [20]. Lymphocytopenia serves as an indicator of cytokine activity, while neutrophilia highlights the prominence of the inflammatory response. In this context, NLR is regarded as a reliable predictor of post-surgical complications and a significant marker of systemic inflammation [21, 22, 23]. Similarly, PLR is associated with elevated levels of pro-inflammatory mediators and is recognized as an effective indicator of inflammation [24]. Studies by Yombi et al. [25] and Naess et al. [26] demonstrated that high NLR and MLR levels are directly linked to infection and inflammation.

On the other hand, maintaining the balance between immune tolerance and inflammation during pregnancy is essential for successful implantation and the healthy progression of gestation. Controlled inflammatory activity is necessary for successful implantation, placental development, and the initiation of labor. While regulated inflammation supports physiological processes, disruption of this balance may lead to complications such as pregnancy loss and preterm birth. Therefore, inflammation in pregnancy should be considered a dynamic process that can result in both physiological and pathological outcomes [27].

In our study, no significant differences were observed in inflammatory markers during the preoperative period, whereas a marked increase was noted postoperatively in patients who developed infections. These findings suggest that changes in hematologic parameters may be more closely associated with the development of infection rather than the natural physiological course of pregnancy. This distinction is important for the accurate interpretation of hematological findings in obstetric populations.

Platelets play a critical role in wound healing and hemostasis by secreting cytokines to initiate inflammation. Following surgical incision, platelets actively participate in wound sterilization and tissue regeneration processes [28]. However, MPV, a measure of platelet size, is inversely correlated with platelet count. According to the literature, MPV levels decrease in inflammatory conditions, making this parameter a useful marker for the diagnosis and monitoring of certain inflammatory diseases [29]. Furthermore, the MPV/PLT ratio has been proposed as a novel inflammatory marker for predicting both the clinical severity and mortality outcomes in sepsis [30].

However, in our study, preoperative and postoperative MPV, PLT, and MPV/PLT ratio values were not found to be significant. Additionally, the percentage changes in these values before and after surgery were not statistically significant. These results suggest that hematologic parameters used to assess the inflammatory response after surgery may not always yield meaningful insights, as inflammation can be influenced by individual variables and varying clinical contexts. More comprehensive studies involving larger populations are needed to better understand the role of these parameters in predicting infection and inflammatory processes.

There were no significant differences between the infection and control groups in this study in terms of maternal age, BMI, birth weight, length of surgery, blood loss, gestational age at birth, history of CS, smoking, GDM, hypertensive disorders of pregnancy, admission to the intensive care unit, history of emergency CS, gravidity, and parity (p $>$ 0.05). But unlike what we found, Castillo et al. [10]. Determiend that the following are documented risk factors for infections following cesarean sections: maternal age, insufficient prenatal care visits, chorioamnionitis, multiple cesarean deliveries, emergency procedures, extended operating times, and substantial blood loss.

Furthermore, there was no correlation between maternal BMI and SSI that had been previously documented. The reason for this disparity could be that the study population had a lower prevalence of obesity than in earlier research [31]. Likewise, this study did not find any correlation between GDM or diabetes mellitus (DM) and SSI, despite the fact that these conditions have been linked to SSI in other research [32]. Even though earlier research has shown that longer operating times raise the risk of bacterial contamination and wound desiccation [33], our cohort did not find any evidence of a significant correlation between operating time and risk of SSI. This finding is also inconsistent with the results of Cheng et al. [33], who highlighted the role of prolonged surgical times in increasing the risk of SSI. These differences may be attributed to the demographic and clinical characteristics of the study population, assessment methods, and potential environmental or healthcare-related factors. The findings indicate that the etiology of surgical site infections is more complex and not solely confined to known risk factors. Our study highlights the need for further research involving larger and more diverse populations to better identify these factors.

In this retrospective study, only cases of infection that developed during hospitalization or led to rehospitalization after CS were evaluated. The exclusion of outpatient-managed infection cases from the analysis represents an important limitation of the study and may restrict the generalizability of the results regarding infection incidence and risk factors to the broader population. In addition, the relatively limited sample size may reduce the statistical power and the ability to detect weaker associations, underscoring the need for validation through larger-scale studies.

Future research should include outpatient cases and a variety of demographic and geographic groups in order to offer a more comprehensive view. More thorough data could be obtained using this method, which would help to improve management tactics and comprehend the extent of post-cesarean infections. A prospective design may also improve the accuracy of the findings by providing a stronger methodological framework for gathering and analyzing data.

Studying NLR, MLR, and other hematologic and inflammatory biomarkers in a larger patient population could enhance our understanding of the role of these parameters in the early diagnosis and management of infections. Validating the cut-off values established for these biomarkers in diverse populations is essential to improve their applicability in clinical practice. Additionally, evaluating hematological indices in conjunction with other biomarkers may yield more reliable and effective results for predicting infection risk and developing individualized treatment approaches. Such comprehensive studies could contribute to the development of more effective strategies for managing infections following CS.

NLR and MLR emerge as easily applicable, cost-effective, and reliable biomarkers for the early detection and prediction of infections after CS. Regular preoperative and postoperative monitoring of these parameters can enhance clinical decision-making and optimize patient management by enabling accurate assessment of infection risk and facilitating early intervention.

The data sets analyzed during the current study are not publicly available due to the data that has been used is confidential, but are available from the corresponding author on reasonable request.

Concept—IT; Design—IT; Supervision—IT; Resources—IT; Materials—IT; Data Collection and Processing—IT; Analysis and Interpretation—IT; Literature Search—IT; Writing Manuscript—IT; Critical Review—IT. The author approved the final version of the manuscript and agrees to be accountable for all aspects of the work.

The study was carried out in accordance with the guidelines of the Declaration of Helsinki and was approved by the Non-Interventional Clinical Research Ethics Committee of Niğde Ömer Halisdemir University (Approval No: 2022/128). Written informed consent was obtained from all participants.

This research received no external funding.

The author declares no conflict of interest.