Development and validation of a novel nomogram for prediction of ketosis-prone type 2 diabetes.

Background: Ketosis-prone type 2 diabetes (KPD), as a unique emerging clinical entity, often has no clear inducement or obvious clinical symptoms at the onset of the disease. Failure to determine ketosis in time may lead to more serious consequences and even death. Therefore, our study aimed to develop and validate a novel nomogram to predict KPD. Methods: In this retrospective study, clinical data of a total of 398 newly diagnosed type 2 diabetes in our hospital who met our research standards with an average age of 48.75 ± 13.86 years years old from January 2019 to December 2022 were collected. According to the occurrence of ketosis, there were divided into T2DM groups(228 cases)with an average age of 52.19 ± 12.97 years, of whom 69.74% were male and KPD groups (170cases)with an average age of 44.13 ± 13.72 years, of whom males account for 80.59%. Univariate and multivariate logistic regression analysis was performed to identify the independent influencing factors of KPD and then a novel prediction nomogram model was established based on these independent predictors visually by using R4.3. Verification and evaluation of predictive model performance comprised receiver-operating characteristic (ROC) curve, corrected calibration curve, and clinical decision curve (DCA). Results: 4 primary independent predict factors of KPD were identified by univariate and multivariate logistic regression analysis and entered into the nomogram including age, family history, HbA1c and FFA. The model incorporating these 4 predict factors displayed good discrimination to predict KPD with the area under the ROC curve (AUC) of 0.945. The corrected calibration curve of the nomogram showed good fitting ability with an average absolute error =0.006 < 0.05, indicating a good accuracy. The decision analysis curve (DCA) demonstrated that when the risk threshold was between 5% and 99%, the nomogram model was more practical and accurate. Conclusion: In our novel prediction nomogram model, we found that age, family history, HbA1c and FFA were the independent predict factors of KPD. The proposed nomogram built by these 4 predictors was well developed and exhibited powerful predictive performance for KPD with high discrimination, good accuracy, and potential clinical applicability, which may be a useful tool for early screening and identification of high-risk population of KPD and therefore help clinicians in making customized treatment strategy.

Development and Validation of an Intraoperative Nomogram to Predict Breast Cancer-Related Lymphedema Based on the Arm Lymphatics Distribution.

BACKGROUND: Preoperatively determining those patients who are at high risk of encountering breast cancer-related lymphedema (BCRL) is still not well understood. OBJECTIVE: This study aimed to develop a simple intraoperative nomogram for BCRL, incorporating a protective factor. METHODS: Overall, 320 breast cancer patients at Zhongnan Hospital (training set) and 221 patients at Dongfeng General Hospital (external validation cohort) treated between November 2017 and December 2018 were included. Prior to axillary lymph node dissection (ALND), 1 mL (2.5 mg) of indocyanine green was administered to the area of the internal bicipital sulcus of the upper limb. The fluorescence image was obtained and the proportion of arm lymph flow above the level of the axillary vein was calculated. Multivariate logistic regression was performed using this proportion together with clinical data. A nomogram was then constructed and assessed for its discrimination and calibration ability and clinical utility in the training and external validation sets. RESULTS: The cumulative incidence of BCRL was 18.7% (60/320), with a median follow-up of 29 months (20-34). In the multivariate logistic regression analysis, body mass index, taxane, radiotherapy, and proportion of arm lymph flow above the level of the axillary vein were identified as independent risk factors. In the training and validation cohorts, the calibration curve performed well (p = 0.721 and p = 0.315, respectively), and the area under the receiver operating characteristic curve values were 0.829 (95% confidence interval [CI] 0.773-0.885) and 0.804 (95% CI 0.732-0.877), respectively. CONCLUSION: High-risk patients could be identified intraoperatively with this nomogram, and timely intervention could be performed with preservation of the arm lymphatics.

Overexpression of CCNE1 confers a poorer prognosis in triple-negative breast cancer identified by bioinformatic analysis.

BACKGROUND: Triple-negative breast cancer (TNBC) is a major subtype of breast cancer. Due to the lack of effective therapeutic targets, the prognosis is poor. In order to find an effective target, despite many efforts, the molecular mechanisms of TNBC are still not well understood which remain to be a profound clinical challenge. METHODS: To identify the candidate genes in the carcinogenesis and progression of TNBC, microarray datasets GSE36693 and GSE65216 were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and functional and pathway enrichment analyses were performed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases via DAVID. We constructed the protein-protein interaction network (PPI) and performed the module analysis using STRING and Cytoscape. Then, we reanalyzed the selected DEG genes, and the survival analysis was performed using cBioportal. RESULTS: A total of 140 DEGs were identified, consisting of 69 upregulated genes and 71 downregulated genes. Three hub genes were upregulated among the selected genes from PPI, and biological process analysis uncovered the fact that these genes were mainly enriched in p53 pathway and the pathways in cancer. Survival analysis showed that only CCNE1 may be involved in the carcinogenesis, invasion, or recurrence of TNBC. The expression levels of CCNE1 were significantly higher in TNBC cells than non-TNBC cells that were detected by qRT-PCR (P < 0.05). CONCLUSION: CCNE1 could confer a poorer prognosis in TNBC identified by bioinformatic analysis and plays key roles in the progression of TNBC which may contribute potential targets for the diagnosis, treatment, and prognosis assessment of TNBC.

Warning criterion to predict recurrent laryngeal nerve injury with percentage reduction of the amplitude of V2/R2d in neuromonitoring thyroidectomy.

OBJECTIVE: To evaluate the contribution of amplitude reduction compared vagal stimulation at the end of thyroid dissection (V2) to the most distal RLN stimulation during thyroidectomy in predicting postoperative vocal cords paralysis (VCP). METHODS: Patients with intact preoperative RLN function who underwent monitored thyroidectomy between August 2017 and April 2018 were included. We routinely tested the exposed RLN at the lowest proximal end (R2p signal) and the most distal end near the laryngeal entry point (R2d signal), and then routinely detected the vagal nerve at the horizontal plane of the inferior pole of thyroid with 2mA stimulation current. The cut-off value was calculated with Receiver Operating Characteristic curve. Rates of specificity, sensitivity, negative predictive value, positive predictive value (PPV) for V2/R2d and R2p/R2d were compared. RESULTS: Percentage reduction of the amplitude of V2/R2d ranged from 34.8% to 76.7%. Twenty-two (1.5%) nerves developed temporary VCP, in which one nerve with VCP showed no significant amplitude reduction at the end of the surgery. There was no permanent or bilateral VCP. Sensitivity, specificity, PPV, NPV, and accuracy for the amplitude reduction of V2/R2d> 60% were 95.5%, 99.8%, 99.9%, 98.2%, respectively, for R2p/R2d were 99.5%, 99.2%, 63.6%, 99.9%, 97.7%, respectively. CONCLUSION: Percentage reduction of the amplitude of V2/R2d is a reliable and practical warning criterion for RLN injury. When the amplitude reduction> 60% surgeons should consider the possibility of postoperative VCP and correct some surgical maneuvers.

Development of Predictive Nomograms for Clinical Use to Quantify the Risk of Amputation in Patients with Diabetic Foot Ulcer.

OBJECTIVE: To determine the novel proposed nomogram model accuracy in the prediction of the lower-extremity amputations (LEA) risk in diabetic foot ulcer (DFU). METHODS AND MATERIALS: In this retrospective study, data of 125 patients with diabetic foot ulcer who met the research criteria in Zhongnan Hospital of Wuhan University from January 2015 to December 2019 were collected by filling in the clinical investigation case report form. Firstly, univariate analysis was used to find the primary predictive factors of amputation in patients with diabetic foot ulcer. Secondly, single factor and multiple factor logistic regression analysis were employed to screen the independent influencing factors of amputation introducing the primary predictive factors selected from the univariate analysis. Thirdly, the independent influencing factors were applied to build a prediction model of amputation risk in patients with diabetic foot ulcer by using R4.3; then, the nomogram was established according to the selected variables visually. Finally, the performance of the prediction model was evaluated and verified by receiver working characteristic (ROC) curve, corrected calibration curve, and clinical decision curve. RESULTS: 7 primary predictive factors were selected by univariate analysis from 21 variables, including the course of diabetes, peripheral angiopathy of diabetic (PAD), glycosylated hemoglobin A1c (HbA1c), white blood cells (WBC), albumin (ALB), blood uric acid (BUA), and fibrinogen (FIB); single factor logistic regression analysis showed that albumin was a protective factor for amputation in patients with diabetic foot ulcer, and the other six factors were risk factors. Multivariate logical regression analysis illustrated that only five factors (the course of diabetes, PAD, HbA1c, WBC, and FIB) were independent risk factors for amputation in patients with diabetic foot ulcer. According to the area under curve (AUC) of ROC was 0.876 and corrected calibration curve of the nomogram displayed good fitting ability, the model established by these 5 independent risk factors exhibited good ability to predict the risk of amputation. The decision analysis curve (DCA) indicated that the nomogram model was more practical and accurate when the risk threshold was between 6% and 91%. CONCLUSION: Our novel proposed nomogram showed that the course of diabetes, PAD, HbA1c, WBC, and FIB are the independent risk factors of amputation in patients with DFU. This prediction model was well developed and behaved a great accurate value for LEA so as to provide a useful tool for screening LEA risk and preventing DFU from developing into amputation.

Lymph node metastasis in suprasternal space and intra-infrahyoid strap muscle space from papillary thyroid carcinoma.

BACKGROUND: This study was performed to evaluate the clinicopathologic characteristics of Lymph Node metastasis between investing layer of Cervical fascia and deep fascia of infrahyoid strap Muscles (LNCM) in papillary thyroid carcinoma (PTC). METHODS: Retrospective review of patients with PTC who underwent thyroidectomy and central compartment neck dissection (CND) from January 2016 to January 2018 was performed in two tertiary referral academic medical centers. A total of 2104 consecutive patients with PTC who underwent thyroidectomy and CND were included in the retrospective review. The LNCM was resected as a separate specimen by the surgeon and the clinicopathologic characteristics of the patients were recorded. Multivariate logistic regression analysis was performed to identify risk factors for LNCM metastasis. RESULTS: Of 2104 PTC patients, 451 patients (21.4%) had lymph nodes in the LNCM. Among them, 68 (15.1%) cases were confirmed to be positive in the LNCM. In total, the metastasis rate of LNCM in PTC patients was 3.2% (68/2104). Univariate analysis revealed that the metastasis of LNCM were more likely to have a primary site in the inferior pole, extrathyroidal extension (ETE), central cervical metastasis, level III and level IV metastasis. Multivariate analysis further showed tumor location in the inferior pole, ETE, level III and level IV metastasis conferred a significantly increased odds ratio for LNCM metastasis. CONCLUSION: Attention should be paid to the lymph tissue in the LNCM for PTC patients, especially in presence of a primary site in the inferior pole, ETE, level III and level IV metastasis.

Selective vagus-recurrent laryngeal nerve anastomosis in thyroidectomy with cancer invasion or iatrogenic transection.

PURPOSE: Immediate recurrent laryngeal nerve (RLN) reconstruction at the time of thyroid cancer extirpation can provide excellent postoperative phonatory function. This study is to present our experience with the methods of RLN reconstruction, and to evaluate the role of selective vagus to RLN anastomosis (SVR) in thyroidectomy. METHODS: Respective review of RLN reconstruction in thyroid surgery from January 2004 to October 2018 was conducted in two tertiary referral academic medical centers. Immediate RLN reconstruction was performed for primary thyroidectomy patients with intraoperative nerve tumor invasion or iatrogenic transection. Laryngofiberoscopic examination, voice evaluation of maximum phonation time, and GRBAS scale were performed preoperatively, on the second day after surgery, and monthly postoperatively for the first year. RESULTS: A total of 37 patients were enrolled. Twenty-nine RLNs were resected caused by tumor-associated trauma; the other nerves were inadvertently transected. Direct anastomosis (DA) was performed in eight patients, free nerve graft (FNG) was performed in four patients, ansa cervicalis to RLN anastomosis (ARA) was performed in eight patients, and SVR was performed in 17 patients. The mean periods from the reinnervation surgery of DA, SVR, ARA, and FNG to the phonation recovery were 46 ± 19 (days), 41 ± 29 (days), 83 ± 21 (days), and 137 ± 32 (days), respectively. There were improvements in the GRBAS scale of perceptual voice quality at 1 month for DA and SVR, 2months for ARA. CONCLUSIONS: Intraoperative SVR reinnervation demonstrated voice improvement postoperatively and might be an effective treatment for thyroidectomy-related permanent unilateral vocal cord paralysis.

Correlation Between Electrophysiological Changes and Outcomes of Vocal Cord Function in 1764 Recurrent Laryngeal Nerves with Visual Integrity During Thyroidectomy.

Background: The correlation between the injured recurrent laryngeal nerve (RLN) with incomplete loss of signal (LOS) and the outcomes of vocal cord function is still not well understood. This large cohort validation study was aimed to evaluate the effectiveness of the warning criterion, the reduction of the R2p/R2d ratio, in neuromonitoring during thyroidectomy. Methods: A total of 1108 consecutive patients (1764 nerves) with normal vocal cord function undergoing monitored thyroidectomy were included. Standardized intraoperative neuromonitoring procedures were strictly followed, after complete dissection of RLN, the exposed RLN was routinely stimulated at the lowest proximal end (R2p signal) and the most distal end near the laryngeal entry point (R2d signal). If the reduction of the R2p/R2d ratio (([R2d - R2p]/R2d) × 100%) reached >20%, the whole exposed RLN would be checked to pinpoint the injured area of the nerve. Results: Visual anatomical integrity of the RLN was ensured in all 1764 nerves. Eighteen nerves had complete LOS, and the other 97 nerves had incomplete LOS where the reduction of the R2p/R2d ratio ranged from 21% to 84%. Postoperative temporary vocal cord paralysis (VCP) was noted in 11 (61.1%) RLNs with complete LOS and 16 (16.5%) RLNs with incomplete LOS, where the reduction of the R2p/R2d ratio ranged from 63% to 84%. The positive predictive value of a R2p/R2d ratio >63% for postoperative VCP was 79.4%. Conclusions: Testing and comparing the R2p and R2d signals were useful to detect RLN neurophysiologic injury, elucidating the mechanism of nerve injury and predicting vocal cord function. Determining R2p-R2d was found to be essential and can be applied in routine neuromonitoring thyroidectomy.

Subtotal parathyroidectomy versus total parathyroidectomy with autotransplantation for secondary hyperparathyroidism: an updated systematic review and meta-analysis.

PURPOSE: The optimal surgical approach of parathyroidectomy for patients with secondary hyperparathyroidism (SHPT) has been controversial. The updated meta-analysis aimed to compare the effectiveness of subtotal parathyroidectomy (SPTX) versus total parathyroidectomy with autotransplantation (TPTX + AT). METHODS: A thorough systematic search was performed on the databases of PubMed, EMBASE, and Cochrane library to identify eligible studies. Data were extracted and pooled into a meta-analysis. The primary outcomes were the symptomatic improvement, radiological changes, hypocalcemia rate, the requirement for vitamin D analogues, time to recurrence, recurrence, persistence, and reoperation rates of SPTX versus TPTX + AT. RESULTS: A total of 18 studies with 3656 patients (1864 patients in SPTX and 1792 patients in TPTX + AT group) were included, and 15 studies were included in quantitative synthesis. No significant difference was observed in symptomatic improvement (93.3%, 89.0%; P = 0.99), radiological changes (85.4%, 85.3%; P = 0.91), hypocalcemia rate (16.6%, 18.1%; P = 0.29), persistence rate (6.1%, 2.0%; P = 0.16), time to recurrence (mean difference 1.46; P = 0.87), recurrence rate (9.2%, 7.1%; P = 0.76), and reoperation rate (5.3%, 5.8%; P = 0.66) between SPTX and TPTX + AT groups. Longer operative time (150 vs. 120 min), prolonged in-hospital stay (5.0 vs. 4.1 days), lower 1-month serum calcium level, and higher requirement for vitamin D analogues at 12 months were significantly observed in patients who underwent TPTX + AT compared to SPTX. CONCLUSIONS: The two surgical approaches were both effective at controlling SHPT in clinical and laboratory terms. However, most of the data shown were not statistically significant. It was acceptable that surgeons chose either SPTX or TPTX + AT for SHPT.