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Background Identifying the risk factors for low APGAR scores at birth is critical for improving neonatal outcomes and guiding clinical interventions. Methods This study aimed to develop a machine-learning model that predicts low APGAR scores by incorporating maternal, fetal, and perinatal factors in Wad Medani, Sudan. Using a Random Forest Classifier, we performed hyper-parameter optimization through Grid Search cross-validation (CV) to identify the best-performing model configuration. Results The optimized model achieved excellent predictive performance, as evidenced by high F1 scores, accuracy, and balanced precision-recall metrics on the test set. In addition to prediction, feature importance analysis was conducted to identify the most influential risk factors contributing to low APGAR scores. Key predictors included gestational age, maternal BMI, mode of delivery, and history of previous complications such as stillbirth or abortion. Using 5-fold cross-validation (CV), the random forest model performance scored accuracy at 96%, precision at 98%, recall at 97%, and F1-score at 97% when classifying infants with APGAR score. Conclusion This study underscores the importance of incorporating machine learning approaches in obstetric care to understand better and mitigate the risk factors associated with adverse neonatal outcomes, particularly low APGAR scores. The results provide a foundation for developing targeted interventions and improving prenatal care practices.

Low Apgar scores and low umbilical arterial (UA) blood pH are considered indicators of adverse perinatal events. This study investigated trends of these perinatal health indicators in Germany. Perinatal data on 10,696,831 in-hospital live births from 2008 to 2022 were obtained from quality assurance institutes. Joinpoint regression analysis was used to quantify trends of low Apgar score and UA pH. Additional analyses stratified by mode of delivery were performed on term singletons with cephalic presentation. Robustness against unmeasured confounding was analyzed using the E -value sensitivity analysis. The overall rates of 5-min Apgar scores < 7 and UA pH < 7.10 in liveborn infants were 1.17% and 1.98%, respectively. For low Apgar scores, joinpoint analysis revealed an increase from 2008 to 2011 (annual percent change (APC) 5.19; 95% CI 3.66–9.00) followed by a slower increase from 2011 to 2019 (APC 2.56; 95% CI 2.00–3.03) and a stabilization from 2019 onwards (APC − 0.64; 95% CI − 3.60 to 0.62). The rate of UA blood pH < 7.10 increased significantly between 2011 and 2017 (APC 5.90; 95% CI 5.15–7.42). For term singletons in cephalic presentation, the risk amplification of low Apgar scores was highest after instrumental delivery (risk ratio 1.623, 95% CI 1.509–1.745), whereas those born spontaneous had the highest increase in pH < 7.10 (risk ratio 1.648, 95% CI 1.615–1.682).           Conclusion : Rates of low 5-min Apgar scores and UA pH in liveborn infants increased from 2008 to 2022 in Germany. What is Known: • Low Apgar scores at 5 min after birth and umbilical arterial blood pH are associated with adverse perinatal outcomes. • Prospective collection of Apgar scores and arterial blood pH data allows for nationwide quality assurance. What is New: • The rates of liveborn infants with 5-min Apgar scores < 7 rose from 0.97 to 1.30% and that of umbilical arterial blood pH < 7.10 from 1.55 to 2.30% between 2008–2010 and 2020–2022. • In spontaneously born term singletons in cephalic presentation, the rate of metabolic acidosis with pH < 7.10 and BE < −5 mmol/L in umbilical arterial blood roughly doubled between the periods 2008–2010 and 2020–2022.

To develop and validate a simple delirium-predicting scoring system in patients undergoing major abdominal surgery by incorporating preoperative risk factors and intraoperative surgical Apgar score (SAS). Observational retrospective cohort study. A tertiary general hospital in China. 1055 patients who received major abdominal surgery from January 2015 to December 2019. We collected data on preoperative and intraoperative variables, and postoperative delirium. A risk scoring system for postoperative delirium in patients after major open abdominal surgery was developed and validated based on traditional logistic regression model. The elastic net algorithm was further developed and evaluated. The incidence of postoperative delirium was 17.8% (188/1055) in these patients. They were randomly divided into the development (n = 713) and validation (n = 342) cohorts. Both the logistic regression model and the elastic net regression model identified that advanced age, arrythmia, hypoalbuminemia, coagulation dysfunction, mental illness or cognitive impairments and low surgical Apgar score are related with increased risk of postoperative delirium. The elastic net algorithm has an area under the receiver operating characteristic curve (AUROC) of 0.842 and 0.822 in the development and validation cohorts, respectively. A prognostic score was calculated using the following formula: Prognostic score = Age classification (0 to 3 points) + arrythmia + 2 * hypoalbuminemia + 2 * coagulation dysfunction + 4 * mental illness or cognitive impairments + (10-surgical Apgar score). The 22-point risk scoring system had good discrimination and calibration with an AUROC of 0.823 and 0.834, and a non-significant Hosmer-Lemeshow test P = 0.317 and P = 0.853 in the development and validation cohorts, respectively. The bootstrapping internal verification method (R = 1000) yielded a C-index of 0.822 (95% CI: 0.759–0.857). The prognostic scoring system, which used both preoperative risk factors and surgical Apgar score, serves as a good first step toward a clinically useful predictive model for postoperative delirium in patients undergoing major open abdominal surgery. •A postoperative delirium prediction scoring system for patients with major abdominal surgery was developed and validated.•This large-sample study found that low SAS was associated with increased risk for postoperative delirium.•The elastic net regression model with high significance was further established to predict postoperative delirium.

ObjectiveThe Surgical Apgar Score quantifies three intraoperative parameters: lowest heart rate, lowest mean arterial pressure, and estimated blood loss (EBL). This scoring system predicts postoperative complications based on these measured factors. The aim of this study was to investigate the value of modified Surgical Apgar Score (mSAS) in predicting postoperative complications in patients with rectal cancer treated with robotic surgery in order to improve the survival and quality of life of rectal cancer patients.MethodsThe study included patients with rectal cancer who underwent robotic surgery in the Department of Gastrointestinal Surgery at the First Affiliated Hospital of Nanchang University from January 2015 to December 2023. In minimally invasive surgery, we developed a modified Surgical Apgar Score (mSAS) tailored for robotic rectal cancer surgery, incorporating an adjusted threshold for EBL. This threshold was derived from quartile analysis of a cohort of 524 patients, with a median EBL of 100 mL (IQR 80–130 mL). We analyzed the association of postoperative complications with low mSAS.ResultsThis study included 524 patients, of which 91 (17.4%) experienced complications and 22 (4.2%) suffered severe complications. mSAS of 6 provided maximal Youden index and were determined as the cut-off values. The area under the ROC curve for predicting complications using the mSAS was 0.740. Univariate and multivariate analyses indicated that an older age, lower tumor localization, longer operation time, radiotherapy alone, combined chemoradiotherapy, and lower mSAS as independent risk factors for complications. The AUC of the prediction nomogram was 0.834 (95% CI 0.774–0.867). The calibration curve demonstrated excellent concordance with the nomogram, indicating the prediction curve ft the diagonal well.ConclusionThis study suggests that mSAS might be a valuable predictive indicator for postoperative complications following robotic rectal cancer surgery, with potentially higher clinical utility.

OBJECTIVES Esophagectomy is the most effective treatment for oesophageal cancer, although the incidence of postoperative complications remains high. Severe major complications, such as intrathoracic anastomotic leakage, are costly and life-threatening to patients. Therefore, early identification of postoperative complications is essential. The surgical Apgar score (SAS) was introduced by Gawande and colleagues to predict major complications after oesophagectomy. Several studies were carried out with inconsistent results. METHODS PubMed, Embase, Web of Science, ClinicalTrials.gov and the Cochrane Library were searched for studies regarding SAS and oesophagectomy. Forest plots were generated using a random-effects model to investigate the actual predictive value of SAS in identifying major complications after oesophagectomy. RESULTS Nine retrospective cohort studies were finally identified from selected electronic databases. The meta-analysis demonstrated that SAS could forecast the incidence of postoperative complications (odds ratio = 1.82, 95% confidence interval: 1.43–2.33, P < 0.001). Subgroup analysis validated the predictive value of SAS whether as continuous or discrete variables. In addition, a meta-analysis of 4 studies demonstrated that SAS could predict the incidence of pulmonary complications (odds ratio = 2.32, 95% confidence interval: 1.61–3.36, P < 0.001). Significant heterogeneity but no publication bias was found. CONCLUSIONS Lower SAS scores could predict the incidence of major morbidities and pulmonary complications after oesophagectomy. Significant heterogeneity limits the reliability of the results, even if publication bias is not observed. More high-quality prospective research should be conducted to verify the findings. PROSPERO registration ID: CRD42020209004.

Background Delayed neurocognitive recovery (dNCR) is a prevalent postoperative complication in elderly patients. Currently, there is no effective treatment for it. Consequently, timely risk identification and prevention of it are crucial. Objective The aim of our study is to provide a clinical tool for the prediction of dNCR by exploring the relationship between the surgical Apgar score (SAS) and dNCR in elderly patients and investigating its predictive value. Methods The elderly patients undergoing general anesthesia at Southwest Medical University Hospital from January 2024 to May 2025 were included in this study. Cognitive function was tested by the MoCA scale before surgery, postoperative day 7 and postoperative day 30. The dNCR and non-dNCR groups were classified according to whether dNCR occurred after surgery. SAS were calculated as the lowest mean arterial pressure (LMAP), lowest heart rate (LHR) and blood loss. The relationship between dNCR and SAS was analyzed, we drew the receiver operating characteristic (ROC) curve of SAS-predicted dNCR, and calculated the area under the curve, the optimal cut-off, sensitivity and specificity. Results The incidence of dNCR was 23.86%, including 15.7% at 7 days, 19.6% at 30 days, and 14.7% had dNCR both at 7 and 30 days after surgery. Logistic regression analysis showed SAS (OR = 6.326, P  = 0.001), Pittsburgh Sleep Index (OR = 3.834, P <  0.001), frailty (OR = 3.388, P  = 0.027) and anxiety (OR = 3.520, P  = 0.002) were risk factors for dNCR. The AUC value of dNCR ROC curve was 0.876 (95% CI: 0.794–0.948, P <  0.001). When taking 8 as the optimal cut-off, the sensitivity is 0.630 and the specificity is 0.893. Conclusion This study demonstrated that low SAS is a risk factor for dNCR; and SAS score < 8 is classified as high-risk population. It provides a simple and objective prediction tool for dNCR, not only enabling medical staff to identify patients at risk and take early interventions, but also to support their goal-directed management decisions for the intraoperative circulatory system. Furthermore, we also found that sleep, frailty and anxiety are also influencing factors of dNCR. Trial registration China Clinical Experiment Center (ChiCTR2300078388), December 7, 2023.

This retrospective cohort study aimed to assess the frequency of emergency cesarean sections with epidural analgesia and its implications on Apgar scores and Neonatal Intensive Care Unit (NICU) admissions among patients at Tehran University of Medical Sciences Hospitals from 2017 to 2018. Data from 7170 patients were extracted from the hospital information system (HIS) through a consensus method. Descriptive statistics, cross-tabulation, and logistic regression analyses were conducted using Stata v17 software. Out of 9387 patients, 62.7% underwent cesarean sections, and 37.1% had normal vaginal deliveries. Epidural analgesia was administered to 127 patients, with 98.4% achieving successful normal vaginal delivery. Nulliparous women constituted 64.29% of those receiving epidural analgesia. Apgar scores at five and ten minutes were comparable between epidural and non-epidural groups. Emergency cesarean rates with epidural analgesia were low (1.6%). Findings align with previous research indicating no significant impact of epidural analgesia on Apgar scores. Nulliparous women predominated in the epidural group, consistent with pain pattern disparities. The study supports recent research showing epidural analgesia does not increase emergency cesarean rates, even in high-risk pregnancies. This study suggests that epidural analgesia does not significantly impact Apgar scores, NICU admissions, or emergency cesarean rates. While the comprehensive dataset enhances reliability, retrospective design limitations are acknowledged. Prospective studies exploring factors contributing to neonatal mortality and overall labor duration are recommended for more robust evidence.

Background The Surgical Apgar score (SAS) is a straightforward and unbiased measure to assess the probability of experiencing complications after surgery. It is calculated upon completion of the surgical procedure and provides valuable predictive information. The SAS evaluates three specific factors during surgery: the estimated amount of blood loss (EBL), the lowest recorded mean arterial pressure (MAP), and the lowest heart rate (LHR) observed. Considering these factors, the SAS offers insights into the probability of encountering postoperative complications. Methods Three authors independently searched the Medline, PubMed, Web of Science, Scopus, and Embase databases until June 2022. This search was conducted without any language or timeframe restrictions, and it aimed to cover relevant literature on the subject. The inclusion criteria were the correlation between SAS and any modified/adjusted SAS (m SAS, (Modified SAS). eSAS, M eSAS, and SASA), and complications before, during, and after surgeries. Nevertheless, the study excluded letters to the editor, reviews, and case reports. Additionally, the researchers employed Begg and Egger's regression model to evaluate publication bias. Results In this systematic study, a total of 78 studies \\were examined. The findings exposed that SAS was effective in anticipating short-term complications and served as factor for a long-term prognostic following multiple surgeries. While the SAS has been validated across various surgical subspecialties, based on the available evidence, the algorithm's modifications may be necessary to enhance its predictive accuracy within each specific subspecialty. Conclusions The SAS enables surgeons and anesthesiologists to recognize patients at a higher risk for certain complications or adverse events. By either modifying the SAS (Modified SAS) or combining it with ASA criteria, healthcare professionals can enhance their ability to identify patients who require continuous observation and follow-up as they go through the postoperative period. This approach would improve the accuracy of identifying individuals at risk and ensure appropriate measures to provide necessary care and support.

Background Exposure to general anesthetics (GA) in early childhood is associated with developmental disorders. However, few studies have addressed in-utero exposure to anesthetics during delivery and subsequent developmental disorders in the offspring. This study aimed to investigate whether GA for cesarean delivery is associated with developmental disorders in children. Methods Using data retrieved from the National Health Insurance Research Database linked to the Birth Reporting Database and the Maternal and Child Health Database between 2015 and 2020, this nationwide retrospective cohort study compared the incidence of developmental disorders following cesarean delivery under GA with that under neuraxial anesthesia (NA). Developmental disorders were diagnosed using the corresponding International Classification of Diseases codes traced 2–6 years after delivery. Results After excluding twins, children born with congenital anomalies or diseases and those with missing data, 325,309 eligible singleton pregnancies delivered through cesarean section under either GA or NA were enrolled. Of the total, 6973 of them were delivered under GA and 318,336 under NA. After propensity score-based fine stratification weighting with a model including age, socioeconomic deprivation, gestational status, infant sex, preterm delivery, low birth weight, and cesarean delivery duration, children delivered under GA were associated with a higher risk of developmental disorders diagnosed within 2 years (adjusted odds ratio [aOR], 1.17; 95% confidence interval [CI], 1.07–1.28), 3 years (aOR, 1.12; 95% CI, 1.04–1.21), and 4 years (aOR, 1.12; 95% CI, 1.04–1.21) compared with those under NA. This association was no longer present when the confounding effect of Apgar scores was included in the propensity-score model. Conclusions GA for cesarean delivery may be associated with developmental disorders diagnosed within 2–4 years after birth manifested through poorer 1- and 5-min Apgar scores. There is no evidence of a direct relationship between GA-related neurotoxicity and subsequent developmental disorders.

Background: Identifying high-risk patients for intensive care unit (ICU) admission after intra-abdominal surgery is crucial, especially in resource-limited settings. This study evaluates the predictive accuracy of the surgical apgar score combined with ASA classification (SASA) for ICU admission within 48 hours. Methods: A retrospective cohort of 242 patients (24 ICU admissions, 9.9%) was analyzed, with a mean age of 58.25 years (standard deviation = 15.41) and 137 males (56.6%). The performance of SAS and SASA was assessed using ROC curve and calibration analysis. Results: SASA outperformed SAS (area under the receiver operating characteristic [auROC]: 0.9483 vs. 0.8772). An optimal SASA cutoff score of 13 provided 83.33% sensitivity and 94.95% specificity for ICU admission. ASA classification, open abdominal surgery, operative duration, hemodynamic instability, and blood loss were significant ICU predictors (p < 0.001). Conclusion: SASA demonstrates superior predictive accuracy for ICU admission and enhances perioperative risk stratification. Prospective studies are recommended to validate its role in predicting morbidity and mortality.