scholarly journals Nomogram for perinatal prediction of intrapartum fever: a retrospective case–control study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhenfei Jiang ◽  
Xiaoyi Hu ◽  
Huabei Zeng ◽  
Xinghe Wang ◽  
Cheng Tan ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Pregnant Women ◽  
Validation Cohort ◽  
Vaginal Birth ◽  
Labour Analgesia ◽  
Trial Registration ◽  
Multivariate Logistic Regression ◽  
Training Cohort ◽  
Link Type

Abstract Objective To explore the risk factors for intrapartum fever and to develop a nomogram to predict the incidence of intrapartum fever. Methods The general demographic characteristics and perinatal factors of 696 parturients who underwent vaginal birth at the Affiliated Hospital of Xuzhou Medical University from May 2019 to April 2020 were retrospectively analysed. Data was collected from May 2019 to October 2019 on 487 pregnant women who formed a training cohort. A multivariate logistic regression model was used to identify the independent risk factors associated with intrapartum fever during vaginal birth, and a nomogram was developed to predict the occurrence. To verify the nomogram, data was collected from January 2020 to April in 2020 from 209 pregnant women who formed a validation cohort. Results The incidence of intrapartum fever in the training cohort was found in 72 of the 487 parturients (14.8%), and the incidence of intrapartum fever in the validation cohort was 31 of the 209 parturients (14.8%). Multivariate logistic regression analysis showed that the following factors were significantly related to intrapartum fever: primiparas (odds ratio [OR] 2.43; 95% confidence interval [CI] 1.15–5.15), epidural labour analgesia (OR 2.89; 95% CI 1.23–6.82), premature rupture of membranes (OR 2.37; 95% CI 1.13–4.95), second stage of labour ≥ 120 min (OR 4.36; 95% CI 1.42–13.41), amniotic fluid pollution degree III (OR 10.39; 95% CI 3.30–32.73), and foetal weight ≥ 4000 g (OR 7.49; 95% CI 2.12–26.54). Based on clinical experience and previous studies, the duration of epidural labour analgesia also appeared to be a meaningful factor for intrapartum fever; therefore, these seven variables were used to develop a nomogram to predict intrapartum fever in parturients. The nomogram achieved a good area under the ROC curve of 0.86 and 0.81 in the training and in the validation cohorts, respectively. Additionally, the nomogram had a well-fitted calibration curve, which also showed excellent diagnostic performance. Conclusion We constructed a model to predict the occurrence of fever during childbirth and developed an accessible nomogram to help doctors assess the risk of fever during childbirth. Such assessment may be helpful in implementing reasonable treatment measures. Trial registration Clinical Trial Registration: (www.chictr.org.cnChiCTR2000035593)

scholarly journals Nomogram for Perinatal Prediction of Intrapartum Fever: A Case-control Study

2021 ◽  
Author(s):  
Zhenfei Jiang ◽  
Xiaoyi Hu ◽  
Huabei Zeng ◽  
Xinghe Wang ◽  
Cheng Tan ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Vaginal Delivery ◽  
Validation Cohort ◽  
Multivariate Logistic Regression Analysis ◽  
Labor Analgesia ◽  
Multivariate Logistic Regression Model ◽  
Multivariate Logistic Regression ◽  
Clinical Trial Registration ◽  
Training Cohort

Abstract Objective: To explore the risk factors of intrapartum fever and develop a nomogram to predict the incidence of intrapartum fever.Methods: The general demographic characteristics and perinatal factors of 696 parturient who underwent vaginal delivery in the Affiliated Hospital of Xuzhou Medical University from May 2019 to April 2020 were retrospectively analyzed. 487 patients collected from May 2019 to October 2019 were formed into a training cohort. A multivariate logistic regression model was used to identify the independent risk factors associated with intrapartum fever during vaginal delivery, then a nomogram was developed to predict the occurrence. 209 cases collected from January 2020 to April 2020 were formed into a validation cohort to verify the nomogram.Results: Intrapartum fever was found in 72 of 487 parturient (14.78%) in the training cohort, and the incidence of intrapartum fever in the validation cohort was 14.83% (31/209). Multivariate logistic regression analysis showed that primiparas (Odds Ratio [OR]2.433; 95% confidence interval [CI]1.149-5.150), epidural labor analgesia (OR2.890; 95%CI 1.225-6.818), premature rupture of membranes (OR2.366; 95%CI 1.130-4.954), second stage of labor ≥120min (OR4.363; 95%CI 1.419-13.410), amniotic fluid pollution Ⅲ degree (OR10.391; 95%CI 3.299-32.729), fetal weight ≥4000g (OR7.492; 95%CI 2.115-26.542) were significantly related to intrapartum fever. According to clinical experience and previous studies, the duration of epidural labor analgesia also seemed to be a meaningful factor for intrapartum fever, so these 7 variables were incorporated to develop a nomogram, which achieved good area under ROC curve of 0.855 in the training cohort and 0.808 in the validation cohort, and it had a well-fitted calibration curve, which showed an excellent diagnostic performance.Conclusion: We constructed a model to predict the occurrence of fever during childbirth and developed an accessible nomogram. The nomogram can help doctors assess the risk of fever during childbirth, so as to lead to reasonable treatment measures.Clinical Trial Registration: (www.chictr.org.cn ChiCTR2000035593)

scholarly journals A Predictive Model of Live Birth Based on Obesity and Metabolic Parameters in Patients With PCOS Undergoing Frozen-Thawed Embryo Transfer

2022 ◽  
Vol 12 ◽  
Author(s):  
Xiaohua Jiang ◽  
Ruijun Liu ◽  
Ting Liao ◽  
Ye He ◽  
Caihua Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Embryo Transfer ◽  
Live Birth ◽  
Goodness Of Fit ◽  
Validation Cohort ◽  
Advanced Age ◽  
Training Cohort ◽  
Frozen Thawed Embryo Transfer ◽  
Thawed Embryo Transfer

AimsTo determine the clinical predictors of live birth in women with polycystic ovary syndrome (PCOS) undergoing frozen-thawed embryo transfer (F-ET), and to determine whether these parameters can be used to develop a clinical nomogram model capable of predicting live birth outcomes for these women.MethodsIn total, 1158 PCOS patients that were clinically pregnant following F-ET treatment were retrospectively enrolled in this study and randomly divided into the training cohort (n = 928) and the validation cohort (n = 230) at an 8:2 ratio. Relevant risk factors were selected via a logistic regression analysis approach based on the data from patients in the training cohort, and odds ratios (ORs) were calculated. A nomogram was constructed based on relevant risk factors, and its performance was assessed based on its calibration and discriminative ability.ResultsIn total, 20 variables were analyzed in the present study, of which five were found to be independently associated with the odds of live birth in univariate and multivariate logistic regression analyses, including advanced age, obesity, total cholesterol (TC), triglycerides (TG), and insulin resistance (IR). Having advanced age (OR:0.499, 95% confidence interval [CI]: 0.257 – 967), being obese (OR:0.506, 95% CI: 0.306 - 0.837), having higher TC levels (OR: 0.528, 95% CI: 0.423 - 0.660), having higher TG levels (OR: 0.585, 95% CI: 0.465 - 737), and exhibiting IR (OR:0.611, 95% CI: 0.416 - 0.896) were all independently associated with a reduced chance of achieving a live birth. A predictive nomogram incorporating these five variables was found to be well-calibrated and to exhibit good discriminatory capabilities, with an area under the curve (AUC) for the training group of 0.750 (95% CI, 0.709 - 0.788). In the independent validation cohort, this model also exhibited satisfactory goodness-of-fit and discriminative capabilities, with an AUC of 0.708 (95% CI, 0.615 - 0.781).ConclusionsThe nomogram developed in this study may be of value as a tool for predicting the odds of live birth for PCOS patients undergoing F-ET, and has the potential to improve the efficiency of pre-transfer management.

scholarly journals Radiomics Analysis Based on Contrast-Enhanced MRI for Prediction of Therapeutic Response to Transarterial Chemoembolization in Hepatocellular Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Ying Zhao ◽  
Nan Wang ◽  
Jingjun Wu ◽  
Qinhe Zhang ◽  
Tao Lin ◽  
...  
Keyword(s):  
Risk Factors ◽  
Hepatocellular Carcinoma ◽  
Logistic Regression ◽  
Therapeutic Response ◽  
Validation Cohort ◽  
Combined Model ◽  
Training Cohort ◽  
Contrast Enhanced ◽  
Three Phase ◽  
Radiological Model

PurposeTo investigate the role of contrast-enhanced magnetic resonance imaging (CE-MRI) radiomics for pretherapeutic prediction of the response to transarterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC).MethodsOne hundred and twenty-two HCC patients (objective response, n = 63; non-response, n = 59) who received CE-MRI examination before initial TACE were retrospectively recruited and randomly divided into a training cohort (n = 85) and a validation cohort (n = 37). All HCCs were manually segmented on arterial, venous and delayed phases of CE-MRI, and total 2367 radiomics features were extracted. Radiomics models were constructed based on each phase and their combination using logistic regression algorithm. A clinical-radiological model was built based on independent risk factors identified by univariate and multivariate logistic regression analyses. A combined model incorporating the radiomics score and selected clinical-radiological predictors was constructed, and the combined model was presented as a nomogram. Prediction models were evaluated by receiver operating characteristic curves, calibration curves, and decision curve analysis.ResultsAmong all radiomics models, the three-phase radiomics model exhibited better performance in the training cohort with an area under the curve (AUC) of 0.838 (95% confidence interval (CI), 0.753 - 0.922), which was verified in the validation cohort (AUC, 0.833; 95% CI, 0.691 - 0.975). The combined model that integrated the three-phase radiomics score and clinical-radiological risk factors (total bilirubin, tumor shape, and tumor encapsulation) showed excellent calibration and predictive capability in the training and validation cohorts with AUCs of 0.878 (95% CI, 0.806 - 0.950) and 0.833 (95% CI, 0.687 - 0.979), respectively, and showed better predictive ability (P = 0.003) compared with the clinical-radiological model (AUC, 0.744; 95% CI, 0.642 - 0.846) in the training cohort. A nomogram based on the combined model achieved good clinical utility in predicting the treatment efficacy of TACE.ConclusionCE-MRI radiomics analysis may serve as a promising and noninvasive tool to predict therapeutic response to TACE in HCC, which will facilitate the individualized follow-up and further therapeutic strategies guidance in HCC patients.

scholarly journals Seroepidemiology Study of Cytomegalovirus and Rubella in Pregnant Women in Luanda, Angola: Geospatial Distribution and its Association with Socio-Demographic and Clinical-Obstetric Determinants

2021 ◽  
Author(s):  
Amélia Nkutxi Vueba ◽  
Clarissa Faria ◽  
Ricardo Almendra ◽  
Paula Santana ◽  
Maria Sousa
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Virus Infection ◽  
Pregnant Women ◽  
Logistic Regression Analysis ◽  
Rubella Virus ◽  
Multivariate Logistic Regression Analysis ◽  
Multivariate Logistic Regression ◽  
Rubella Virus Infection

Abstract Background: The main objective was to study the seroprevalence of anti-CMV and anti-Rubella antibodies in pregnant women of Luanda (Angola), identify the primary maternal infection during gestation and to evaluate the socio-demographic risk factors associated with CMV and Rubella virus infections. Methods: A prospective cross-sectional study was conducted from August 2016 to May 2017. Blood samples were collected and specific anti-CMV and anti-Rubella antibodies (IgG and IgM) were quantified by electrochemiluminescence (COBAS e411). Demographic and clinical data were collected by standardized questionnaire. Bivariate and multivariate logistic regression analysis was used to quantify the effect of clinical and obstetric risk factors on virus seroprevalence. The level of statistical significance was set as p<0.05, and Odds Ratio (OR) and 95% Confidence Intervals (95% CI) were computed. Results: The 396 pregnant women participated in the study aged from 15 to 47. Of the participants, 382 (96.5%) had anti-CMV IgG antibodies, 8 (2.0%) had anti-CMV IgG and IgM antibodies and 6 (1.5%) were seronegative. For Rubella virus, 347 (87.6%) were positive for anti-IgG, 4 (1.0%) positive for anti-IgG and IgM, and 45 (11.4%) were seronegative. The mean age of CMV positivity was 28.4 (SD ± 6.2) and for Rubella virus was 28.6 (SD ± 6.1). The multivariate logistic regression analysis has shown a significant association between Rubella virus infection and pregnant women without child (OR 2.673; CI: 1.026 - 7.007) and suffering spontaneous abortion (OR 3.232; CI: 1.192 - 7.952). In contrast, the level of schooling, residence, occupation, marital status, number of children in the household, basic sanitation, gestational age, history of miscarriages and hepatitis B were not significantly associated with the Rubella virus infection. Conclusions: Overall, this study showed that there is a high seroprevalence of anti-CMV and anti-Rubella antibodies in pregnant women in Luanda. Therefore, it is important a rapid and accurate diagnosis of CMV and Rubella infection in pregnant women to prevent congenital infections. Rubella vaccination should be offered to women non-immune to Rubella. Overall, it would be important to implement national screening for CMV, Rubella and other diseases linked to maternal and child health.

Short-Term Outcomes Following Removal of Infected Hernia Mesh

2021 ◽  
pp. 000313482110241
Author(s):  
Christine Tung ◽  
Junko Ozao-Choy ◽  
Dennis Y. Kim ◽  
Christian de Virgilio ◽  
Ashkan Moazzez
Keyword(s):  
Risk Factors ◽  
Body Mass Index ◽  
Logistic Regression ◽  
Body Mass ◽  
Smoking History ◽  
Multivariate Logistic Regression ◽  
Short Term ◽  
Mesh Removal ◽  
Mesh Placement ◽  
Infected Mesh

There are limited studies regarding outcomes of replacing an infected mesh with another mesh. We reviewed short-term outcomes following infected mesh removal and whether placement of new mesh is associated with worse outcomes. Patients who underwent hernia repair with infected mesh removal were identified from 2005 to 2018 American College of Surgeons-National Surgical Quality Improvement Program database. They were divided into new mesh (Mesh+) or no mesh (Mesh-) groups. Bivariate and multivariate logistic regression analyses were used to compare morbidity between the two groups and to identify associated risk factors. Of 1660 patients, 49.3% received new mesh, with higher morbidity in the Mesh+ (35.9% vs. 30.3%; P = .016), but without higher rates of surgical site infection (SSI) (21.3% vs. 19.7%; P = .465). Mesh+ had higher rates of acute kidney injury (1.3% vs. .4%; P = .028), UTI (3.1% vs. 1.3%, P = .014), ventilator dependence (4.9% vs. 2.4%; P = .006), and longer LOS (8.6 vs. 7 days, P < .001). Multivariate logistic regression showed new mesh placement (OR: 1.41; 95% CI: 1.07-1.85; P = .014), body mass index (OR: 1.02; 95% CI: 1.00-1.03; P = .022), and smoking (OR: 1.43; 95% CI: 1.05-1.95; P = .025) as risk factors independently associated with increased morbidity. New mesh placement at time of infected mesh removal is associated with increased morbidity but not with SSI. Body mass index and smoking history continue to contribute to postoperative morbidity during subsequent operations for complications.

scholarly journals Risk factors for tissue expander infection in scar reconstruction: a retrospective cohort study of 2374 consecutive cases

2020 ◽  
Vol 8 ◽  
Author(s):  
Chen Dong ◽  
Minhui Zhu ◽  
Luguang Huang ◽  
Wei Liu ◽  
Hengxin Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Treatment Failure ◽  
Logistic Regression Analysis ◽  
Disease Duration ◽  
Multivariate Logistic Regression Analysis ◽  
Tissue Expansion ◽  
Multivariate Logistic Regression ◽  
Hematoma Evacuation

Abstract Background Tissue expansion is used for scar reconstruction owing to its excellent clinical outcomes; however, the complications that emerge from tissue expansion hinder repair. Infection is considered a major complication of tissue expansion. This study aimed to analyze the perioperative risk factors for expander infection. Methods A large, retrospective, single-institution observational study was carried out over a 10-year period. The study enrolled consecutive patients who had undergone tissue expansion for scar reconstruction. Demographics, etiological data, expander-related characteristics and postoperative infection were assessed. Univariate and multivariate logistic regression analysis were performed to identify risk factors for expander infection. In addition, we conducted a sensitivity analysis for treatment failure caused by infection as an outcome. Results A total of 2374 expanders and 148 cases of expander infection were assessed. Treatment failure caused by infection occurred in 14 expanders. Multivariate logistic regression analysis identified that disease duration of ≤1 year (odds ratio (OR), 2.07; p &lt; 0.001), larger volume of expander (200–400 ml vs &lt;200 ml; OR, 1.74; p = 0.032; &gt;400 ml vs &lt;200 ml; OR, 1.76; p = 0.049), limb location (OR, 2.22; p = 0.023) and hematoma evacuation (OR, 2.17; p = 0.049) were associated with a high likelihood of expander infection. Disease duration of ≤1 year (OR, 3.88; p = 0.015) and hematoma evacuation (OR, 10.35; p = 0.001) were so related to high risk of treatment failure. Conclusions The rate of expander infection in patients undergoing scar reconstruction was 6.2%. Disease duration of &lt;1 year, expander volume of &gt;200 ml, limb location and postoperative hematoma evacuation were independent risk factors for expander infection.

scholarly journals 10-Year Renal Function Trajectories in Community-Dwelling Older Adults: Exploring the Risk Factors for Different Patterns

2018 ◽  
Vol 7 (10) ◽  
pp. 373
Author(s):  
Chia-Ter Chao ◽  
Yung-Ming Chen ◽  
Fu-Hui Ho ◽  
Kun-Pei Lin ◽  
Jen-Hau Chen ◽  
...  
Keyword(s):  
Risk Factors ◽  
Older Adults ◽  
Logistic Regression ◽  
Renal Function ◽  
Estimated Glomerular Filtration Rate ◽  
Community Dwelling ◽  
Multivariate Logistic Regression ◽  
Improve Risk Stratification ◽  
Leukocyte Counts ◽  
Community Dwelling Older Adults

Longitudinal changes of renal function help inform patients’ clinical courses and improve risk stratification. Rare studies address risk factors predicting changes in estimated glomerular filtration rate (eGFR) over time in older adults, particularly of Chinese ethnicity. We identified prospectively enrolled community-dwelling older adults (≥65 years) receiving annual health examinations between 2005 and 2015 with serum creatinine available continuously in a single institute, and used linear regression to derive individual’s annual eGFR changes, followed by multivariate logistic regression analyses to identify features associated with different eGFR change patterns. Among 500 elderly (71.3 ± 4.2 years), their mean annual eGFR changes were 0.84 ± 1.67 mL/min/1.73 m2/year, with 136 (27.2%) and 238 (47.6%) classified as having downward (annual eGFR change <0 mL/min/1.73 m2/year) and upward eGFR (≥1 mL/min/1.73 m2/year) trajectories, respectively. Multivariate logistic regression showed that higher age (odds ratio (OR) 1.08), worse renal function (OR 13.2), and more severe proteinuria (OR 9.86) or hematuria (OR 3.39) were predictive of a declining eGFR while greater waist circumference (OR 1.06) and higher leukocyte counts (OR 1.21) were predictive of an uprising 10-year eGFR. These findings elucidate important features associated with geriatric renal function variations, which are expected to improve their renal care.

scholarly journals A novel procalcitonin-based score for detecting sepsis among critically ill patients

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245748
Author(s):  
Tung-Lin Tsui ◽  
Ya-Ting Huang ◽  
Wei-Chih Kan ◽  
Mao-Sheng Huang ◽  
Min-Yu Lai ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Validation Cohort ◽  
Multivariate Logistic Regression Analysis ◽  
Sepsis Group ◽  
C Reactive Protein ◽  
Multivariate Logistic Regression ◽  
Reactive Protein

Background Procalcitonin (PCT) has been widely investigated as an infection biomarker. The study aimed to prove that serum PCT, combining with other relevant variables, has an even better sepsis-detecting ability in critically ill patients. Methods We conducted a retrospective cohort study in a regional teaching hospital enrolling eligible patients admitted to intensive care units (ICU) between July 1, 2016, and December 31, 2016, and followed them until March 31, 2017. The primary outcome measurement was the occurrence of sepsis. We used multivariate logistic regression analysis to determine the independent factors for sepsis and constructed a novel PCT-based score containing these factors. The area under the receiver operating characteristics curve (AUROC) was applied to evaluate sepsis-detecting abilities. Finally, we validated the score using a validation cohort. Results A total of 258 critically ill patients (70.9±16.3 years; 55.4% man) were enrolled in the derivation cohort and further subgrouped into the sepsis group (n = 115) and the non-sepsis group (n = 143). By using the multivariate logistic regression analysis, we disclosed five independent factors for detecting sepsis, namely, “serum PCT level,” “albumin level” and “neutrophil-lymphocyte ratio” at ICU admission, along with “diabetes mellitus,” and “with vasopressor.” We subsequently constructed a PCT-based score containing the five weighted factors. The PCT-based score performed well in detecting sepsis with the cut-points of 8 points (AUROC 0.80; 95% confidence interval (CI) 0.74–0.85; sensitivity 0.70; specificity 0.76), which was better than PCT alone, C-reactive protein and infection probability score. The findings were confirmed using an independent validation cohort (n = 72, 69.2±16.7 years, 62.5% men) (cut-point: 8 points; AUROC, 0.79; 95% CI 0.69–0.90; sensitivity 0.64; specificity 0.87). Conclusions We proposed a novel PCT-based score that performs better in detecting sepsis than serum PCT levels alone, C-reactive protein, and infection probability score.

scholarly journals Risk factors for anastomotic complications after one-stage anastomosis for oesophageal atresia

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Jin-Xi Huang ◽  
Song-Ming Hong ◽  
Qiang Chen ◽  
Zeng-Chun Wang ◽  
Dian-Ming Wu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Birth Weight ◽  
Oesophageal Atresia ◽  
Prognostic Nutritional Index ◽  
Anastomotic Stenosis ◽  
Multivariate Logistic Regression ◽  
One Stage ◽  
Nutritional Index ◽  
Anastomotic Fistula

Abstract Background Oesophageal atresia is a congenital malformation of the oesophagus and a serious malformation of the digestive system, postoperative complications include acute respiratory failure, pneumonia, anastomotic fistula, anastomotic stenosis, tracheal stenosis, gastroesophageal reflux and eosinophilic oesophagitis, anastomotic fistula is one of the important causes of postoperative death. The objective of this study is to identify the risk factors for anastomotic complications after one-stage anastomosis for oesophageal atresia. Methods A retrospective analysis was performed on the clinical data of 107 children with congenital oesophageal atresia who underwent one-stage anastomosis in our hospital from January 2013 to December 2018. Single-factor and multivariate logistic regression analyses were performed to determine the risk factors for anastomotic fistula and anastomotic stenosis. Results A total of 107 children with oesophageal atresia underwent one-stage anastomosis, and the incidence of anastomotic fistula was 26.2%. The probability of anastomotic stenosis in the long term was 52.3%, and the incidence of refractory stenosis (dilation ≥5 times) was 13.1%. Analysis of the clinical count data in the anastomotic fistula group and non-anastomotic fistula group showed that preoperative albumin (F = 4.199, P = 0.043), low birth weight (F = 7.668, P = 0.007) and long gap defects (F = 6.107, P = 0.015) were risk factors for postoperative anastomotic fistula. Further multivariate logistic regression analysis showed that low birth weight (Wald2 = 4.499, P = 0.034, OR = 2.775) and long gap defects (Wald2 = 6.769, P = 0.009, OR = 4.939) were independent risk factors for postoperative anastomotic fistula. Premature delivery (F = 5.338, P = 0.023), anastomotic fistula (F = 11.381, P = 0.001), endoscopic surgery (F = 6.343, P = 0.013), preoperative neutrophil count (F = 8.602, P = 0.004), preoperative low albumin (F = 8.410, P = 0.005), and a preoperative prognostic nutritional index < 54 (F = 5.54, P = 0.02) were risk factors for refractory anastomotic stenosis in children. Further multivariate logistic regression analysis showed that postoperative anastomotic fistula (Wald2 = 11.417, P = 0.001, OR = 8.798), endoscopic surgery (Wald2 = 9.633, P = 0.002, OR = 4.808), and a prognostic nutritional index < 54 (Wald2 = 4.540, P = 0.002, OR = 2.3798) were independent risk factors for refractory anastomotic stenosis. Conclusion Low birth weight and long gap defects are important predictors of postoperative anastomotic fistula, and the possibility of refractory anastomotic stenosis should be considered. The long-term risk of anastomotic stenosis was increased in children undergoing endoscopic surgery and in those with a preoperative prognostic nutritional index < 54.

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