This study aimed to evaluate the efficacy of fluid responsiveness-guided strategies for preventing spinal anesthesia-induced hypotension (SAIH) in parturients undergoing cesarean delivery, comparing prophylactic fluid loading with norepinephrine infusion. In this fluid responsiveness-based stratified randomized controlled trial, eligible parturients were stratified into fluid responsive (FR(+)) and non-fluid responsive (FR(-)) cohorts according to carotid corrected flow time (FTc). Each stratum had a preset sample size of 236, and within each stratum, participants were randomly assigned to receive either prophylactic colloid infusion (Co) or norepinephrine infusion (NE), ultimately forming four subgroups: FR(+)/Co, FR(+)/NE, FR(-)/Co, and FR(-)/NE.Primary outcomes included the incidence of SAIH and maximum reduction in mean arterial pressure (MAP). Secondary outcomes encompassed neonatal umbilical cord blood gas analysis, Apgar scores, intraoperative hemodynamic changes, and postoperative recovery parameters. Among fluid-responsive parturients, prophylactic fluid loading (FR(+)/Co) and norepinephrine infusion (FR(+)/NE) demonstrated comparable efficacy in preventing SAIH (16.7

Background Herpes zoster-associated pain (ZAP) imposes a substantial burden with frequently suboptimal treatment outcomes. High-voltage long-duration pulsed radiofrequency (HL-PRF)) has emerged as a promising treatment. This study explored HL-PRF’s application in ZAP, identified efficacy-influencing factors, and established a clinical prediction model.​ Methods Retrospective analysis of 128 ZAP patients treated with HL-PRF (Department of Anesthesiology and Pain Medicine, First Affiliated Hospital of Wannan Medical College, Mar 2023–Dec 2024) was done. Independent predictors of treatment inefficacy were identified via univariate and multivariate logistic regression. A predictive model was developed utilizing a nomogram. Model performance was evaluated using area under the curve (AUC), calibration curves, Hosmer-Lemeshow test, and decision curve analysis (DCA). Results HL-PRF demonstrated 60% efficacy at 3-month follow-up. Univariate analysis identified significant associations ( P < 0.05) between HL-PRF efficacy and multiple factors, including age, disease duration, prolonged hormone use, early non-utilization of antiviral medications, use of antiepileptic drugs, tramadol use, coexisting connective tissue disorders, concurrent malignancy, coexisting cerebral infarction, acute-phase VAS score, and the CD4+/CD8 + T-cell ratio. Multivariate regression confirmed 7 risk factors for reduced efficacy (age, disease duration, connective tissue disease, malignant tumors, long-term hormone use, acute-phase VAS score, CD4+/CD8 + T-cell ratio; P < 0.05). The predictive model exhibited excellent discriminatory power(AUC = 0.988, 95%CI:0.976-1.000), good fit (Hosmer-Lemeshow P = 0.969), and high accuracy (93.0% overall accuracy, 90.7% sensitivity, 96.2% specificity).​ Conclusion HL-PRF is safe and effective for ZAP but affected by multiple factors. Older patients, prolonged disease duration, comorbidities (connective tissue disease/malignant tumors), long-term hormone use, acute-phase VAS > 7, and low CD4+/CD8 + ratio may have suboptimal outcomes. Future research should focus on individualized HL-PRF protocols.​

This study aimed to investigate the effects of dexamethasone on blood glucose in diabetic patients undergoing thoracoscopic surgery, providing a reference for its safe intraoperative use in this population. In this randomized, double-blind controlled trial, 60 diabetic patients with reasonably controlled blood glucose (HbA1c < 9

Ischemic stroke remains a leading cause of global mortality and disability. While timely vascular recanalization is the most direct and clinically validated intervention for cerebral ischemia, reperfusion often induces secondary brain injury, with neuroinflammation playing a central role. Single-cell sequencing data from an ischemic stroke mouse model identify G protein-coupled receptor 35 (GPR35) as a potential regulator of post-ischemic inflammatory responses. GPR35 expression was markedly increased in both in vivo cerebral ischemia-reperfusion models and in vitro oxygen-glucose deprivation systems, predominantly localizing to microglia. Functional studies revealed that genetic knockdown of GPR35 in murine brain tissue significantly exacerbated cerebral infarction volume, neurological deficits, and neuroinflammation in animal models, whereas GPR35 overexpression produced therapeutic effects. Consistently, pharmacological activation of GPR35 using zaprinast attenuated ischemia-reperfusion injury and reduced proinflammatory cytokine production. Mechanistically, zaprinast-mediated GPR35 activation suppressed proinflammatory cytokine production via modulation of the Raf1/ERK1/2/MAPK signaling cascade. Notably, Raf1 knockdown attenuated the pathological exacerbation induced by GPR35 deficiency in peri-infarct regions. Co-immunoprecipitation analyses revealed a direct interaction between GPR35 and Raf1, with the CR2 domain, a critical region for Raf1 autoinhibition, identified as the primary binding interface. Collectively, these findings demonstrate that zaprinast confers cerebroprotective effects in cerebral ischemia-reperfusion injury by activating GPR35, ultimately attenuating infarct progression and neuroinflammation. This mechanistic insight positions GPR35 as a promising therapeutic target for mitigating reperfusion injury in ischemic stroke.

Background Neuropathic pain (NP) is frequently accompanied by anxiety and depression, and current treatments do not adequately address this comorbidity. The anterior cingulate cortex (ACC) plays a central role in sensory and emotional processing. However, the molecular pathways that connect these functions remain unclear. G protein-coupled receptor 35 (GPR35), an orphan receptor enriched in neurons, has been implicated in neuroinflammation and pain signaling. However, its specific involvement in NP and associated affective disturbances has not been fully elucidated.Methods Peripheral blood GPR35 expression was measured in human patients with NP and healthy controls. In mice, chronic constriction injury (CCI) was used to induce NP. Lentiviral knockdown or overexpression of GPR35 was performed in ACC cells. Behavioral assays were used to assess mechanical and thermal sensitivity, locomotor and anxiety metrics, cognitive performance, and depression-related behaviors. Molecular analyses included western blotting, RT-qPCR, immunofluorescence, RNA sequencing, and co-immunoprecipitation. Additional Nr4a1 knockdown and L-kynurenine (L-Kyna, a GPR35 agonist) administration were used to validate pathway involvement.Results Patients with NP had higher circulating GPR35 levels, which positively correlated with pain intensity. CCI induced a time-dependent increase in GPR35 expression in the ACC of mice, accompanied by hypersensitivity and emotional disturbances. GPR35 knockdown in the ACC worsens mechanical and thermal hypersensitivity, impairs cognition, increases depression-related behaviors, and amplifies microglial activation and pro-inflammatory cytokine production. GPR35 overexpression reversed these effects by reducing hypersensitivity, improving affective behaviors, and restoring the inflammatory balance. Transcriptomic and biochemical analyses identified Nr4a1 as a key downstream effector of GPR35, and Nr4a1 knockdown eliminated the protective effects of GPR35 overexpression. GPR35 primarily regulated the PI3K/AKT pathway. Treatment with L-Kyna reduced pain hypersensitivity, improved depression-related behaviors, and decreased neuroinflammation in CCI mice.Conclusions GPR35 is an essential regulator of NP and pain-related affective disturbances in the ACC. Its effects are mediated through the Nr4a1-dependent activation of the PI3K/AKT pathway and suppression of neuroinflammation. The pharmacological activation of GPR35 using L-Kyna provides analgesic and antidepressant benefits, highlighting GPR35 as a promising therapeutic target for NP and its emotional comorbidities.

This study aims to evaluate the effects of two strategies for preventing hypotension after spinal anesthesia (prophylactic fluid loading and norepinephrine infusion) on intracranial pressure (ICP) in preeclamptic women by measuring the optic nerve sheath diameter (ONSD) using ultrasound. In this prospective, randomized, controlled trial, 60 healthy parturients and 60 preeclamptic parturients undergoing cesarean delivery under spinal anesthesia were enrolled. Normal parturients were randomly assigned to the infusion group (NA group, n = 30) and NE (norepinephrine) group (NB group, n = 30), while preeclamptic parturients were randomly assigned to the infusion group (PA group, n = 30) and NE group (PB group, n = 30). The primary outcome was bilateral ONSD values at baseline, pretreatment, 5 min after spinal anesthesia (Post-SA), and 5 min after fetal delivery (Post-birth). The secondary outcomes included maternal general characteristics, renal function indices, postoperative headache, fetal umbilical cord arterial blood gas indices, and Apgar scores. Pretreatment ONSD was significantly higher than baseline in both infusion groups, and baseline ONSD was higher in preeclamptic versus normal parturients (all P < 0.01). Among preeclamptic parturients, pretreatment ONSD was higher in the PA group than in the PB group (P < 0.01), with a similar difference (PA > PB) confirmed in normal parturients (P < 0.01). In addition, compared to the PA group, the PB group showed no significant differences in systolic blood pressure (SBP), diastolic blood pressure (DBP), or mean arterial pressure (MAP) at any time point in preeclamptic parturients (P > 0.05). Conversely, in normal parturients, post-birth SBP, DBP, and MAP were significantly higher in the NB than in the NA group (P < 0.01). Baseline hemodynamic values were higher in preeclamptic versus normal parturients (P < 0.01), and post-birth values decreased significantly from baseline in the PA and PB groups (P < 0.001). No significant intergroup differences were observed in maternal heart rate (HR), renal function indices, umbilical artery blood gas indices, Apgar scores, or the incidence of postpartum headache (all P > 0.05). For preeclamptic parturients, the risks induced by ICP increase should be noted. Compared to colloids, prophylactic infusion of NE was more effective and safer and did not increase ICP. This randomized controlled trial was registered on Chinese Clinical Trial Registry (ChiCTR2400092317; http://www.chictr.org.cn/) with the Clinical Trial Registry (1)

Despite equalizing blood pressure(BP), ephedrine and phenylephrine exhibit distinct impacts on rSO2. However, whether this heterogeneity in rSO2 affects the occurrence of POD remains understudied. This study aimed to explore the effects of maintaining BP with ephedrine versus phenylephrine on the incidence of POD in elderly patients undergoing knee arthroplasty under general anesthesia. A total of 120 patients aged 60-90 years undergoing knee arthroplasty were included in this study.The patients were randomly divided into two groups: the ephedrine group and the phenylephrine group. After anesthesia induction, continuous infusion of the respective medication was initiated to maintain intraoperative mean arterial pressure within the normal range (baseline mean arterial pressure ± 20%).The primary outcome measures included the incidence of POD within 1-3 days after the surgery. The incidence of POD on the first day after surgery was lower in the ephedrine group compared to the phenylephrine group (33% vs 7%, P < 0.001 ). However, there was no significant difference in the incidence of POD between the two groups on the second and third postoperative days. During surgery, the ephedrine group exhibited significantly increased CO and rSO2 compared to the phenylephrine group (P < 0.05). Clinical Trials Registry: ChiCTR2200064849, principal investigator: Changjian Zheng.

In addition to stabilizing blood pressure (BP), ephedrine and phenylephrine have distinct effects on regional cerebral oxygen saturation (rSO2). However, whether its effect on rSO2 affects the occurrence of postoperative delirium (POD) remains unclear. Therefore, the aim of this study is to compare the effects of ephedrine and phenylephrine for BP maintenance on the incidence of POD in olderly adults who underwent knee arthroplasty under general anesthesia. One hundred twenty patients who were between 60 and 90 years old and underwent knee arthroplasty were included in this study. The patients were randomly divided into two groups: the ephedrine group and the phenylephrine group. After anesthesia induction, ephedrine and phenylephrine were continuously infused to maintain the intraoperative mean arterial pressure within the normal range (baseline mean arterial pressure ± 20%). The primary outcome measures included the incidence of POD within 1-3 days after surgery. The incidence of POD on the first day after surgery was lower in the ephedrine group than in the phenylephrine group (33% vs. 7%, P < 0.001). However, there was no significant difference in the incidence of POD between the two groups on the second and third postoperative days. Compared with the phenylephrine group, the ephedrine group experienced significantly greater cardiac output (CO) and rSO2 (P < 0.05).Clinical Trials Registry: ChiCTR2200064849, principal investigator: Changjian Zheng.

The upper lip bite test (ULBT) is considered an effective method for predicting difficult airways, but data on the ULBT for predicting difficult tracheal intubation are lacking. This study aimed to examine the clinical utility of the ULBT in predicting difficult endotracheal intubation. We conducted an observational case-cohort study of adult patients undergoing elective surgery and requiring endotracheal intubation for general anesthesia. Difficult airway assessment was performed on the recruited patients before the operation, including the ULBT, mouth opening, thyromental distance, modified Mallampati test, and body mass index. The primary outcome was the incidence of difficult tracheal intubation. The receiver operating characteristic curve analysis was used to compare the performance of variables in predicting difficult tracheal intubation. We successfully recruited 2522 patients for analysis and observed 64 patients with difficult tracheal intubation. When predicting difficult tracheal intubation, grade 2 ULBT had a sensitivity of 0.75 and a specificity of 0.54, and grade 3 had a sensitivity of 0.28 and a specificity of 0.75. Compared with mouth opening, the area under the receiver operating characteristic curve of the ULBT was lower in predicting difficult tracheal intubation (0.69 [95% confidence interval: 0.67–0.71] vs. 0.84 [95% confidence interval: 0.82–0.87], P < 0.05). Clinical Trials Registry : ChiCTR-ROC-16009050, principal investigator: Weidong Yao.

Ischaemic stroke (IS) is the second most common cause of death worldwide. Traditional treatment strategies, including blood flow recanalization therapy and neuroprotective drugs, have reduced safety and effectiveness due to their lack of targeting and inability to penetrate the blood-brain barrier (BBB). Targeted nanoparticles (NPs) can improve BBB penetration and brain targeting by changing their composition and structure, which can integrate a variety of treatment components to match the complex pathological process of IS. In this review, we describe recent advances in IS therapy, specifically in the prevention, detection, and treatment of IS, by using targeted NPs, presenting basic knowledge and possible therapeutic targets to highlight their potential for early treatment in the clinic. Targeted nanoparticles can be used to treat ischemic stroke by targeting the complex pathological mechanism of ischemic stroke and the blood-brain barrier that is difficult to penetrate by most traditional drugs.

Background: The accurate prediction of difficult airway (DA) is important in ICU and general anaesthesia. Our hypothesis is that machine learning models can predict difficult tracheal intubation (DTI) and difficult laryngoscopy (DL).Methods: We performed a secondary analysis of two prospective observational DA research programmes. DTI and DL prediction models were established by machine learning based on multivariate data. Machine learning algorithms, such as logistic regression, support vector machine, and random forest, were used. Five times repeated 5-fold cross-validation were used to compare parameters such as the area under the receiver operating characteristic (ROC) curve (AUC), recall rate, accuracy and the F1 score. The feature importance of the indicators were analysed by the random forest and AdaBoost models.Results: 3958 tracheal intubation patients were included in this study. Among the five machine learning algorithms, the best AUCs were obtained by the Bayes model for DTI (0.956, 95% CI 0.950–0.961) and the random forest model for DL (0.903, 95% CI 0.895–0.911). The random forest model had the best accuracy for DTI (0.966, 95% CI 0.964–0.968) and DL (0.926, 95% CI 0.923–0.929). The random forest model also had the highest F1 score for DTI (0.361, 95% CI 0.327–0.394) and DL (0.530, 95% CI 0.492–0.569). The naïve Bayes model had the highest recall rate for DTI (0.902, 95% CI 0.877–0.927) and DL (0.809, 95% CI 0.787–0.830).Conclusions: Machine learning algorithms based on multivariate indicators were effective in predicting DA.

BackgroundThe anatomical characteristics of difficult airways can be analysed geometrically. This study aims to develop and validate a geometry-assisted difficult airway screening method (GADAS method) for difficult tracheal intubation.MethodsIn the GADAS method, a geometric simulated model was established based on computer graphics. According to the law of deformation of the upper airway on laryngoscopy, the expected visibility of the glottis was calculated to simulate the real visibility on laryngoscopy. Validation of the new method: Approved by the Ethics Committee of Yijishan Hospital of Wannan Medical College. Adult patients who needed tracheal intubation under general anaesthesia for elective surgery were enrolled. The data of patients were input into the computer software to calculate the expected visibility of the glottis. The results of tracheal intubation were recorded by anaesthesiologists. The primary observation outcome was the screening performance of the expected visibility of the glottis for difficult tracheal intubation.ResultsThe geometric model and software of the GADAS method were successfully developed and are available for use. We successfully observed 2068 patients, of whom 56 patients had difficult intubation. The area under the receiver operating characteristic curve of low expected glottis visibility for predicting difficult laryngoscopy was 0.96 (95% confidence interval [CI]: 0.95-0.96). The sensitivity and specificity were 89.3% (95% CI: 78.1-96.0%) and 94.3% (95% CI: 93.2%-95.3), respectively.ConclusionsIt is feasible to screen difficult-airway patients by applying computer techniques to simulate geometric changes in the upper airway.

Background: Hyomental distance (HMD), an anatomical feature of the upper airway, can be measured precisely by ultrasonography. But the sensitivity and specificity of HMD compared to thyromental distance (TMD) to predict difficult airways is still unknown. Methods: A case-cohort study was conducted. The written informed consent was obtained. Elective surgery adult patients undergoing general anaesthesia and tracheal intubation were recruited. The other inclusion criteria were: no maxillofacial deformity, trauma, airway stenosis, known difficult airway. The exclusion criteria were: tracheal intubations or operations were canceled, or patients' data were missing. HMD ultrasound measurements of patients in a sniffing position and other usual airway evaluations were performed before general anaesthesia induction. The primary outcome was the intubation difficulty level. Predictive values were calculated. Results: We successfully enrolled 2357 patients (62 difficult intubation patients) in the cohort study for analysis. The area under the receiver operating characteristic curve (AUC) of the HMD and TMD for predicting difficult intubation was 0.86 (95% CI, 0.84-0.87) and 0.77 (95% CI, 0.75-0.78) respectively (comparison: P < 0.001). With an optimal cut-off value of HMD < 4.9 cm, we observed a sensitivity and specificity of 0.90 (95% CI, 0.80-0.96) and 0.73 (95% CI, 0.71-0.75). Meanwhile, with TMD < 7.0 cm, the sensitivity and specificity were 0.77 (95% CI, 0.65-0.87) and 0.65 (95% CI, 0.63-0.67) respectively.Conclusion: In comparison to TMD, HMD measured by ultrasound was more sensitive in predicting difficult intubation. ?(C) 2022 Societefranc , aise d'anesthesie et de reanimation (Sfar). Published by Elsevier Masson SAS. All rights reserved.

This paper has aimed to review the available evidence on the association between Interleukin (IL) -10 -1082G/A, -592C/A gene polymorphisms and the risk of human immunodeficiency virus-1(HIV-1) infection. The data of PubMed updated in May 2021 were retrieved. The HIV infection risks were estimated in allelic, recessive, dominant, homozygous, heterozygous, over-dominant models of IL-10-1082G/A and-592C/A gene locus as odds ratio (OR) with the corresponding 95% confidence interval (95% CI). The correlation was not significant between -1082G/A polymorphism and HIV-1 susceptibility (allelic model (G vs. A: OR (95% CI)=0.968 (0.878-1.067)); recessive model (GG vs. AA+AG: OR (95% CI)=0.940, (0.771-1.146)); dominant model (GG+AG vs. AA: OR (95% CI)=0.967(0.846-1.106)); homozygous model (GG vs. AA: OR (95% CI)=0.971(0.780-1.209)); heterozygous model (AG vs. AA: OR (95% CI)=0.988(0.797-1.224)) and over-dominant model (GG+AA vs. AG: OR (95% CI)=0.969(0.781-1.201)). IL-10-592C/A polymorphism might be related to HIV-1 in allelic model, dominant model, homozygous model and heterozygous model (OR (95% CI)(0.796-0.965); OR (95% CI)=0.793(0.664-0.948); OR (95% CI)=0.755,(0.612-0.930); OR (95% CI)=0.820(0.679-0.991), respectively), but not to recessive model and over-dominant model (OR (95% CI)=0.882(0.770-1.010) and OR (95% CI)=1.009(0.897-1.148)).

The valid prediction of unanticipated difficult tracheal intubation (DTI) is very important in clinic anesthesia. The purpose of this study was to develop a machine learning model for predicting unanticipated DTI. A comprehensive analysis of two prospective observational difficult airway research programs was performed. In total, 3958 patients who underwent tracheal intubation were included in this study. Data were split into a training set and a test set according to 70%:30% randomly. XGBoost machine learning was used to develop a machine learning model for predicting unanticipated DTI. The F1 score was used as the main performance metric because of data imbalance. The model parameter tuning was performed in the training set via pipeline grid search with the aim of optimizing the F1 score. Then, the tuning model were used for unanticipated DTI prediction in the test set. The indicators feature importance and decision rule were analyzed. With the XGBoost machine learning model for unanticipated DTI prediction, the best F1 score of 0.500 ± 0.102 was obtained on the training set with ten-fold cross-validation. The XGBoost model had the area under the precision recall curve (AUPRC) 0.600 and the area under the receiver operating characteristic curve (AUROC) 0.924 with an F1 value of 0.57 in the test set. XGBoost was an effective machine learning model for unanticipated DTI prediction.

Abstract Background Based on the upper airway anatomy and joint function parameters examined by ultrasound, a multiparameter ultrasound model for difficult airway assessment (ultrasound model) was established, and we evaluated its ability to predict difficult airways. Methods A prospective case-cohort study of difficult airway prediction in adult patients undergoing elective surgery with endotracheal intubation under general anesthesia, and ultrasound phantom examination for difficult airway assessment before anesthesia, including hyomental distance, tongue thickness, mandibular condylar mobility, mouth opening, thyromental distance, and modified Mallampati tests, was performed. Receiver operating characteristic (ROC) curve analysis was used to evaluate the effectiveness of the ultrasound model and conventional airway assessment methods in predicting difficult airways. Results We successfully enrolled 1000 patients, including 51 with difficult laryngoscopy (DL) and 26 with difficult tracheal intubation (DTI). The area under the ROC curve (AUC) for the ultrasound model to predict DL was 0.84 (95% confidence interval [CI]: 0.82–0.87), and the sensitivity and specificity were 0.75 (95% CI: 0.60–0.86) and 0.82 (95% CI: 0.79–0.84), respectively. The AUC for predicting DTI was 0.89 (95% CI: 0.87–0.91), and the sensitivity and specificity were 0.85 (95% CI: 0.65–0.96) and 0.81 (95% CI: 0.78–0.83), respectively. Compared with mouth opening, thyromental distance, and modified Mallampati tests, the ultrasound model predicted a greater AUC for DL (P < 0.05). Compared with mouth opening and modified Mallampati tests, the ultrasound model predicted a greater AUC for DTI (P < 0.05). Conclusions The ultrasound model has good predictive performance for difficult airways. Trial registration This study is registered on chictr.org.cn (ChiCTR-ROC-17013258); principal investigator: Jianling Xu; registration date: 06/11/2017).

Abstract Background Deep neck space abscess (DNSA) is a serious infection in the head and neck. Antibiotic therapy is an important treatment in patients with DNSA. However, the results of bacterial culture need at least 48 h, and the positive rate is only 30–50%, indicating that the use of empiric antibiotic treatment for most patients with DNSA should at least 48 h or even throughout the whole course of treatment. Thus, how to use empiric antibiotics has always been a problem for clinicians. This study analyzed the distribution of bacteria based on disease severity and clinical characteristics of DNSA patients, and provides bacteriological guidance for the empiric use of antibiotics. Methods We analyzed 433 patients with DNSA who were diagnosed and treated at nine medical centers in Guangdong Province between January 1, 2015, and December 31, 2020. A nomogram for disease severity (mild/severe) was constructed using least absolute shrinkage and selection operator–logistic regression analysis. Clinical characteristics for the Gram reaction of the strain were identified using multivariate analyses. Results 92 (21.2%) patients developed life-threatening complications. The nomogram for disease severity comprised of seven predictors. The area under the receiver operating characteristic curves of the nomogram in the training and validation cohorts were 0.951 and 0.931, respectively. In the mild cases, 43.2% (101/234) had positive culture results (49% for Gram-positive and 51% for Gram-negative strains). The positive rate of cultures in the patients with severe disease was 63% (58/92, 37.9% for Gram-positive, and 62.1% for Gram-negative strains). Diabetes mellitus was an independent predictor of Gram-negative strains in the mild disease group, whereas gas formation and trismus were independent predictors of Gram-positive strains in the severe disease group. The positivity rate of multidrug-resistant strains was higher in the severe disease group (12.1%) than in the mild disease group (1.0%) (P < 0.001). Metagenomic sequencing was helpful for the bacteriological diagnosis of DNSA by identifying anaerobic strains (83.3%). Conclusion We established a DNSA clinical severity prediction model and found some predictors for the type of Gram-staining strains in different disease severity cases. These results can help clinicians in effectively choosing an empiric antibiotic treatment.

Background Airway management, including noninvasive endotracheal intubation or invasive tracheostomy, is an essential treatment strategy for patients with deep neck space abscess (DNSA) to reverse acute hypoxia, which aids in avoiding acute cerebral hypoxia and cardiac arrest. This study aimed to develop and validate a novel risk score to predict the need for airway management in patients with DNSA. Methods Patients with DNSA admitted to 9 hospitals in Guangdong Province between January 1, 2015, and December 31, 2020, were included. The cohort was divided into the training and validation cohorts. The risk score was developed using the least absolute shrinkage and selection operator (LASSO) and logistic regression models in the training cohort. The external validity and diagnostic ability were assessed in the validation cohort. Results A total of 440 DNSA patients were included, of which 363 (60 required airway management) entered into the training cohort and 77 (13 required airway management) entered into the validation cohort. The risk score included 7 independent predictors (p < 0.05): multispace involvement (odd ratio [OR] 6.42, 95% confidence interval [CI] 1.79–23.07, p < 0.001), gas formation (OR 4.95, 95% CI 2.04–12.00, p < 0.001), dyspnea (OR 10.35, 95% CI 3.47–30.89, p < 0.001), primary region of infection, neutrophil percentage (OR 1.10, 95% CI 1.02–1.18, p = 0.015), platelet count to lymphocyte count ratio (OR 1.01, 95% CI 1.00–1.01, p = 0.010), and albumin level (OR 0.86, 95% CI 0.80–0.92, p < 0.001). Internal validation showed good discrimination, with an area under the curve (AUC) of 0.951 (95% CI 0.924–0.971), and good calibration (Hosmer–Lemeshow [HL] test, p = 0.821). Application of the clinical risk score in the validation cohort also revealed good discrimination (AUC 0.947, 95% CI 0.871–0.985) and calibration (HL test, p = 0.618). Decision curve analyses in both cohorts demonstrated that patients could benefit from this risk score. The score has been transformed into an online calculator that is freely available to the public. Conclusions The risk score may help predict a patient’s risk of requiring airway management, thus advancing patient safety and supporting appropriate treatment.

Background Postoperative pulmonary complications (PPCs) after thoracoscopic surgery are common. This retrospective study aimed to develop a nomogram to predict PPCs in thoracoscopic surgery. Methods A total of 905 patients who underwent thoracoscopy were randomly enrolled and divided into a training cohort and a validation cohort at 80%:20%. The training cohort was used to develop a nomogram model, and the validation cohort was used to validate the model. Univariate and multivariable logistic regression were applied to screen risk factors for PPCs, and the nomogram was incorporated in the training cohort. The discriminative ability and calibration of the nomogram for predicting PPCs were assessed using C-indices and calibration plots. Results Among the patients, 207 (22.87%) presented PPCs, including 166 cases in the training cohort and 41 cases in the validation cohort. Using backward stepwise selection of clinically important variables with the Akaike information criterion (AIC) in the training cohort, the following seven variables were incorporated for predicting PPCs: American Society of Anesthesiologists (ASA) grade III/IV, operation time longer than 180 min, one-lung ventilation time longer than 60 min, and history of stroke, heart disease, chronic obstructive pulmonary disease (COPD) and smoking. With incorporation of these factors, the nomogram achieved good C-indices of 0.894 (95% confidence interval (CI) [0.866–0.921]) and 0.868 (95% CI [0.811–0.925]) in the training and validation cohorts, respectively, with well-fitted calibration curves. Conclusion The nomogram offers good predictive performance for PPCs after thoracoscopic surgery. This model may help distinguish the risk of PPCs and make reasonable treatment choices.