Deep learning-guided adjuvant chemotherapy selection for elderly patients with breast cancer.

PURPOSE: The efficacy of adjuvant chemotherapy in elderly breast cancer patients is currently controversial. This study aims to provide personalized adjuvant chemotherapy recommendations using deep learning (DL). METHODS: Six models with various causal inference approaches were trained to make individualized chemotherapy recommendations. Patients who received actual treatment recommended by DL models were compared with those who did not. Inverse probability treatment weighting (IPTW) was used to reduce bias. Linear regression, IPTW-adjusted risk difference (RD), and SurvSHAP(t) were used to interpret the best model. RESULTS: A total of 5352 elderly breast cancer patients were included. The median (interquartile range) follow-up time was 52 (30-80) months. Among all models, the balanced individual treatment effect for survival data (BITES) performed best. Treatment according to following BITES recommendations was associated with survival benefit, with a multivariate hazard ratio (HR) of 0.78 (95% confidence interval (CI): 0.64-0.94), IPTW-adjusted HR of 0.74 (95% CI: 0.59-0.93), RD of 12.40% (95% CI: 8.01-16.90%), IPTW-adjusted RD of 11.50% (95% CI: 7.16-15.80%), difference in restricted mean survival time (dRMST) of 12.44 (95% CI: 8.28-16.60) months, IPTW-adjusted dRMST of 7.81 (95% CI: 2.93-11.93) months, and p value of the IPTW-adjusted Log-rank test of 0.033. By interpreting BITES, the debiased impact of patient characteristics on adjuvant chemotherapy was quantified, which mainly included breast cancer subtype, tumor size, number of positive lymph nodes, TNM stages, histological grades, and surgical type. CONCLUSION: Our results emphasize the potential of DL models in guiding adjuvant chemotherapy decisions for elderly breast cancer patients.

US-guided Percutaneous Radiofrequency Ablation for Secondary Hyperparathyroidism: Long-term Outcomes and Prognostic Factors.

Background Although favorable outcomes have been reported with radiofrequency ablation (RFA) for secondary hyperparathyroidism (SHPT), the long-term efficacy remains insufficiently investigated. Purpose To evaluate the long-term efficacy and safety of US-guided percutaneous RFA in patients with SHPT undergoing dialysis and to identify possible predictors associated with treatment failure. Materials and Methods This retrospective study included consecutive patients with SHPT with at least one enlarged parathyroid gland accessible for RFA who were undergoing dialysis at seven tertiary centers from May 2013 to July 2022. The primary end point was the proportion of patients with parathyroid hormone (PTH) levels less than or equal to 585 pg/mL at the end of follow-up. Secondary end points were the proportion of patients with normal calcium and phosphorus levels, the technical success rate, procedure-related complications, and improvement in self-rated hyperparathyroidism-related symptoms (0-3 ranking scale). The Wilcoxon signed rank test and generalized estimating equation model were used to evaluate treatment outcomes. Univariable and multivariable regression analyses identified variables associated with treatment failure (recurrent or persistent hyperparathyroidism). Results This study included 165 patients (median age, 51 years [IQR, 44-60 years]; 92 female) and 582 glands. RFA effectively reduced PTH, calcium, and phosphorus levels, with targeted ranges achieved in 78.2% (129 of 165), 72.7% (120 of 165), and 60.0% (99 of 165) of patients, respectively, at the end of follow-up (mean, 51 months). For the RFA sessions, the technical success rate was 100% (214 of 214). Median symptom scores (ostealgia, arthralgia, pruritus) decreased (all P < .001). Regarding complications, only hypocalcemia (45.8%, 98 of 214) was common. Treatment failure occurred in 36 patients (recurrent [n = 5] or persistent [n = 31] hyperparathyroidism). The only potential independent predictor of treatment failure was having less than four treated glands (odds ratio, 17.18; 95% CI: 4.34, 67.95; P < .001). Conclusion US-guided percutaneous RFA was effective and safe in the long term as a nonsurgical alternative for patients with SHPT undergoing dialysis; the only potential independent predictor of treatment failure was a lower number (<4) of treated glands. © RSNA, 2024 Supplemental material is available for this article.

A Study on the Evaluation of a Risk Score of Osteonecrosis of the Femoral Head Based on Survival Analysis.

BACKGROUND: This study aimed at developing a risk score predicting the probability of developing an osteonecrosis of the femoral head (ONFH) in patients with femoral neck fracture within 3 years after closed reduction internal fixation and evaluating its performance, clinical utility, and internal validity. METHODS: A retrospective follow-up study of 378 newly injured femoral neck fracture patients treated with 3 partially threaded parallel cannulated screws in 3 hospitals in Shanghai from March 2013 to January 2017 was performed. The patients were divided into development (n = 284) and validation (n = 94) cohorts. The risk score was constructed by Cox regression analysis in a form of nomogram. The performance and clinical utility were illustrated by box plots, calibration plots, and decision curve analysis. RESULTS: Eighty-three of 378 patients had developed ONFH within 3 years. Garden alignment index, time to surgery, preoperative displace, impaction, and postoperative malposition were used as predictors to construct the risk score in a form of nomogram. In the development and validation cohort, the concordance index was 0.96 and 0.94, respectively; the discrimination slope was 0.51 and 0.47, respectively. In both cohorts, the calibration slopes and intercepts were 1 and 0, respectively. The risk score was clinically useful between the risk threshold of 0% and 88%. The performance and utility in the validation data illustrated good repeatability. CONCLUSION: The risk score had satisfactory discrimination and calibration performance and demonstrated clinical utility with good internal validity. It managed to distinguish high-risk groups for post-traumatic ONFH.

Treatment Outcome of Combined Continuous Venovenous Hemofiltration and Hemoperfusion in Acute Paraquat Poisoning: A Prospective Controlled Trial.

OBJECTIVES: To investigate whether combined continuous venovenous hemofiltration and hemoperfusion among paraquat-poisoned patients would improve survival. DESIGN: Prospective, controlled interventional study over 4 years. SETTING: Single, tertiary, academic medical center. PATIENTS: We recruited patients admitted to Shanghai Tenth People's Hospital within 48 hours after paraquat ingestion. Exclusions were under 14 years old, ingestion of paraquat with other toxicants, pregnant, a history of chronic pulmonary disease, psychosis, hyperthyroidism, or diabetes with impaired liver or renal function. INTERVENTIONS: All patients were assigned to receive continuous venovenous hemofiltration with hemoperfusion therapy (continuous venovenous hemofiltration group) and to receive conventional therapy (conventional group). The study outcomes were death from any cause within 90 days after paraquat ingestion and the frequencies of hypoxia, acute kidney injury, or adverse events. MEASUREMENTS AND MAIN RESULTS: Of the 110 enrolled patients, 59 were assigned to continuous venovenous hemofiltration group and 51 to conventional group. The two groups had similar baseline demographics and clinical features. At 90 days after paraquat ingestion, 19 of 59 patients (32.2%) in the continuous venovenous hemofiltration group and 29 of 51 patients (56.9%) in the conventional group had died (hazard ratio, 0.43; 95% CI, 0.24-0.76; p = 0.004). In multivariable Cox proportional hazard models controlling for baseline characteristics, combined continuous venovenous hemofiltration and hemoperfusion was independently associated with reduced risk of death compared with conventional therapy (adjusted hazard ratio, 0.35; 95% CI, 0.19-0.64; p = 0.001). Patients in the continuous venovenous hemofiltration group, as compared to the conventional group, had a reduced occurrence rate of hypoxia (40.7% vs 72.5%; p = 0.001) and of acute kidney injury (59.3% vs 78.4%; p = 0.03). Hypophosphatemia and thrombocytopenia were more common in the continuous venovenous hemofiltration group (p < 0.05). CONCLUSIONS: In patients with paraquat poisoning, treatment with combined continuous venovenous hemofiltration and hemoperfusion significantly improved 90-day survival rates.

An integrated analysis of cancer genes in clear cell renal cell carcinoma.

AIM: This study was performed to detect driver genes and implement integrated analyses on these drivers in clear cell renal cell carcinoma (ccRCC). METHODS: Driver genes and pathways were predicted by OncodriveFM and Dendrix using 39,636 somatic mutations from The Cancer Genome Atlas, followed by DNA methylation, copy number variation, differential expression and survival analyses. RESULTS: Overall, 342 driver genes and 106 pathways were determined by OncodriveFM, two driver genes by Dendrix. 28 driver genes were found hypomethylated, overexpressed and associated to a poor prognosis. By contrast, 17 driver genes showed decreased expression, hypermethylation and indicated a better outcome in ccRCC. CONCLUSION: The set of new cancer genes and pathways opens the avenue for developing potential therapeutic targets and prognostic biomarkers in ccRCC.

A modified nontransposed brachiobasilic arteriovenous fistula versus brachiocephalic arteriovenous fistula for maintenance hemodialysis access.

OBJECTIVE: With the growing need for reliable and durable upper arm hemodialysis access, we sought to compare the performance of a novel modified nontransposed brachiobasilic arteriovenous fistula (mNT-BBAVF) with that of the more traditional brachiocephalic arteriovenous fistula (BCAVF). METHODS: Briefly, to construct an mNT-BBAVF, an incision is made on the ulnar side of the elbow. The brachial artery and basilic vein are then isolated, and a side-to-side anastomosis is performed without transposition of the basilic vein. Next, the proximal basilic vein and the perforating veins within the surgical field are ligated. In this study, we retrospectively reviewed the medical records of all patients who underwent either an mNT-BBAVF or a BCAVF between January 2011 and October 2014 to compare 1-year primary unassisted patency, cumulative patency, and complications. We also examined hemodynamic parameters of vessels in each fistula type. RESULTS: We identified a total of 84 patients: 45 had a BCAVF, and 39 had an mNT-BBAVF. The two groups were well matched for baseline characteristics. Maturation rates at 1 month were 97% for mNT-BBAVF and 96% for BCAVF. The 1-year primary unassisted patency was significantly higher in the mNT-BBAVF group than that in the BCAVF group (87% vs 67%; hazard ratio, 2.86; 95% confidence interval, 1.11-6.40; P = .03), although cumulative patency did not differ (90% vs 73%; hazard ratio, 2.80; 95% confidence interval, 0.98-6.96 ; P = .06). There were no differences in thrombosis, failure of maturation, bleeding, steal syndrome, arm swelling, aneurysm, and stenosis between the two groups during the 12-month study. Importantly, diameters and blood flow volumes of the proximal cephalic vein, distal cephalic vein, and distal basilic vein in patients who received an mNT-BBAVF increased significantly after 12 months. All three vessels met the Kidney Disease Outcomes Quality Initiative (KDOQI) criteria for fistula maturation and were available for dialysis cannulation, whereas only the proximal cephalic vein in the BCAVF group met the maturation criteria and could be used for cannulation. CONCLUSIONS: mNT-BBAVF appeared to be an effective alternative to BCAVF for upper arm hemodialysis access.

Mapping the neck disability index to SF-6D in patients with chronic neck pain.

BACKGROUND: This study sought to statistically map the neck disability index (NDI) to the six-dimension health state short form (SF-6D) to estimate algorithms for use in economic analyses in patients with chronic neck pain (CNP). METHODS: The relationships between NDI and SF-6D scores were estimated by using data from a cohort of patients with chronic neck pain (n = 272). By using ordinary least squares (OLS), generalized linear modeling (GLM), censored least absolute deviations (CLAD) and Tobit regression, scores from all 10 items of the NDI instruments were univariately tested against SF-6D values and retained in a multivariate regression model, if statistically significant. The predictive ability of the model was assessed by mean absolute error (MAE), root mean square error (RMSE) and normalized RMSE. RESULTS: The mean age of the 272 CNP patients was 39.9 ± 12.3 years; 57.8 % of the CNP patients were female. An OLS regression equation that included recreation item of NDI was optimal, with a MAE of 0.04and 0.04 and an RMSE of 0.06and 0.05in the derivation set and validation set, respectively. Predicted utilities accurately represented the observed ones. CONCLUSIONS: We have provided algorithms for the estimation of health state utility values from the response of NDI. Future economic evaluations of the interventions for chronic neck pain could be informed by these algorithms.

A comparative efficacy evaluation of ultrasound-guided pulsed radiofrequency treatment in the gastrocnemius in managing plantar heel pain: a randomized and controlled trial.

OBJECTIVE: The treatment of plantar heel pain is highly challenging. We report ultrasound-guided pulsed radiofrequency treatment (UG-PRF) in the gastrocnemius to treat plantar heel pain and minimize the safety issues. DESIGN: This study compared UG-PRF with sham treatment in 100 patients with plantar heel pain. Primary outcome measures include the pain subscale of the Foot Health Status Questionnaire (FHSQ-pain) and "first step" pain as measured on a visual analogue scale (VAS-"first-step" pain). The secondary outcome measures include the FHSQ-foot function and general foot health, and health related quality of life (assessed using the Short Form-36 questionnaire [SF-36]). All outcomes were measured at 3 and 6 months post-treatment. RESULTS: The results showed the efficacy of UG-PRF in terms of pain management, as reflected by higher FHSQ-pain score (increased by 20.0 (P < 0.0001) and 17.9 (P = 0.001) compared with the sham treatment at 3 or 6 months, respectively) and lower VAS-"first-step" pain (reduced by 26.1 (P < 0.0001) and 14.3 (P = 0.01) compared with the sham group at 3 or 6 months, respectively). The FHSQ-foot function and FHSQ-general foot health were increased by the UG-PRF (P < 0.05, vs sham treatment at 3 or 6 months). The SF-36 physical component score in the sham group was 10.8 (P = 0.042) and 10.4 (P = 0.044) lower than the UG-PRF group at 3 or 6 months, respectively. No severe complications were observed. CONCLUSIONS: We conclude that the UG-PRF is both safe and efficacious in managing plantar heel pain.

Transarticular fixation by hook plate versus coracoclavicular stabilization by single multistrand titanium cable for acute Rockwood grade-V acromioclavicular joint dislocation: a case-control study.

BACKGROUND: Hook plate (HP) is popularly used for acute and severely displaced acromioclavicular (AC) dislocations. However, subacromial impingement and acromion osteolysis induced by transarticular fixation are notorious. The current case-control study was to compare transarticular fixation by HP to coracoclavicular (CC) stabilization by single multistrand titanium cable (MSTC). METHODS: Between January 2006 and August 2009, 24 patients with acute AC dislocations were surgically treated by open reduction and transarticular fixation with HP. These patients were matched to a series of 24 patients, who were managed by CC stabilization with MSTC in the same period. All AC dislocations were graded as Rockwood type V. Implant was removed 8-12 months after the primary operation in all patients, and 12 months at least were needed to assess the maintenance of AC joint. Functional results were evaluated before implant removal as well as in the last follow-up based on Constant-Murley criteria. RESULTS: There were no differences of demographic data including age, dominant gender and side, injury-to-surgery interval, operation time and follow-up period. In terms of functionality, Constant score was 95.8 ± 4.1 in MSTC group, while 76.7 ± 8.0 in HP group before implant removal (P < 0.001). In detail, MSTC was superior to HP in pain, ROM and activities. Constant score was significantly improved to 86.1 ± 5.7 after hardware removal for patients in HP (P < 0.001). Degenerative change of acromioclavicular joint presented in 16 patients (66.7%) in patients treated by HP, while it was found in only 3 patients (12.5%) treated by MSTC (P < 0.001). CONCLUSIONS: MSTC is superior to HP for the treatment of Rockwood type-V acromioclavicular dislocation both before and after removal of the implant. Hardware removal is of great benefits for functional improvement in patients treated by HP.

N-acetylcysteine for the prevention of contrast-induced nephropathy in patients with pre-existing renal insufficiency or diabetes: a systematic review and meta-analysis.

PURPOSE: To identify benefit of N-acetylcysteine (NAC) on patients with pre-existing renal insufficiency or diabetes. BACKGROUND: NAC administration is a common method for prevention of contrast-induced nephropathy (CIN). Nevertheless, its benefit on patients with pre-existing renal insufficiency or diabetes remains uncertain and controversial. METHODS: Randomized controlled trials (RCTs) to evaluate the efficacy of NAC for the prevention of CIN in patients with pre-existing renal insufficiency or diabetes were searched from the databases of MEDLINE, EMBASE, and Cochrane library. Pooled odds ratio (OR) with 95% confidence interval (95% CI) were calculated using fixed-effects model by the Mantel-Haenszel test. RESULTS: Twenty RCTs involving 3466 subjects (1756 assigned to NAC and 1710 assigned to the control) were included in the pre-existing renal dysfunction group. Pooled analysis suggested a significant reduction in CIN among this group (OR, 0.76; 95% CI, 0.61-0.93; p = 0.008). However, the nine trials comparing NAC versus control among patients with diabetes (NAC, 367 subjects; control, 358 subjects) showed no benefit of NAC for prevention of CIN (OR = 0.87; 95% CI, 0.58-1.30; p = 0.50). No significant heterogeneity was detected (p = 0.07; I2 = 34% for the group of pre-existing renal dysfunction; p = 0.40; I2 = 5% for the group of diabetes). CONCLUSION: Our results suggest that NAC decreases the incidence of contrast-induced nephropathy among patients with pre-existing renal insufficiency. The benefit was not existed in patients with diabetes.

Evolution of Digital Health and Exploration of Patented Technologies (2017-2021): Bibliometric Analysis.

BACKGROUND: The significant impact of digital health emerged prominently during the COVID-19 pandemic. Despite this, there is a paucity of bibliometric analyses focusing on technologies within the field of digital health patents. Patents offer a wealth of insights into technologies, commercial prospects, and competitive landscapes, often undisclosed in other publications. Given the rapid evolution of the digital health industry, safeguarding algorithms, software, and advanced surgical devices through patent systems is imperative. The patent system simultaneously acts as a valuable repository of technological knowledge, accessible to researchers. This accessibility facilitates the enhancement of existing technologies and the advancement of medical equipment, ultimately contributing to public health improvement and meeting public demands. OBJECTIVE: The primary objective of this study is to gain a more profound understanding of technology hotspots and development trends within the field of digital health. METHODS: Using a bibliometric analysis methodology, we assessed the global technological output reflected in patents on digital health published between 2017 and 2021. Using Citespace5.1R8 and Excel 2016, we conducted bibliometric visualization and comparative analyses of key metrics, including national contributions, institutional affiliations, inventor profiles, and technology topics. RESULTS: A total of 15,763 digital health patents were identified as published between 2017 and 2021. The China National Intellectual Property Administration secured the top position with 7253 published patents, whereas Koninklijke Philips emerged as the leading institution with 329 patents. Notably, Assaf Govari emerged as the most prolific inventor. Technology hot spots encompassed categories such as "Medical Equipment and Information Systems," "Image Analysis," and "Electrical Diagnosis," classified by Derwent Manual Code. A patent related to the technique of receiving and transmitting data through microchips garnered the highest citation, attributed to the patentee Covidien LP. CONCLUSIONS: The trajectory of digital health patents has been growing since 2017, primarily propelled by China, the United States, and Japan. Applications in health interventions and enhancements in surgical devices represent the predominant scenarios for digital health technology. Algorithms emerged as the pivotal technologies protected by patents, whereas techniques related to data transfer, storage, and exchange in the digital health domain are anticipated to be focal points in forthcoming basic research.

Optimizing adjuvant treatment options for patients with glioblastoma.

Background: This study focused on minimizing the costs and toxic effects associated with unnecessary chemotherapy. We sought to optimize the adjuvant therapy strategy, choosing between radiotherapy (RT) and chemoradiotherapy (CRT), for patients based on their specific characteristics. This selection process utilized an innovative deep learning method. Methods: We trained six machine learning (ML) models to advise on the most suitable treatment for glioblastoma (GBM) patients. To assess the protective efficacy of these ML models, we employed various metrics: hazards ratio (HR), inverse probability treatment weighting (IPTW)-adjusted HR (HRa), the difference in restricted mean survival time (dRMST), and the number needed to treat (NNT). Results: The Balanced Individual Treatment Effect for Survival data (BITES) model emerged as the most effective, demonstrating significant protective benefits (HR: 0.53, 95% CI, 0.48-0.60; IPTW-adjusted HR: 0.65, 95% CI, 0.55-0.78; dRMST: 7.92, 95% CI, 7.81-8.15; NNT: 1.67, 95% CI, 1.24-2.41). Patients whose treatment aligned with BITES recommendations exhibited notably better survival rates compared to those who received different treatments, both before and after IPTW adjustment. In the CRT-recommended group, a significant survival advantage was observed when choosing CRT over RT (p < 0.001). However, this was not the case in the RT-recommended group (p = 0.06). Males, older patients, and those whose tumor invasion is confined to the ventricular system were more frequently advised to undergo RT. Conclusion: Our study suggests that BITES can effectively identify GBM patients likely to benefit from CRT. These ML models show promise in transforming the complex heterogeneity of real-world clinical practice into precise, personalized treatment recommendations.

Individualized survival prediction and surgery recommendation for patients with glioblastoma.

Background: There is a lack of individualized evidence on surgical choices for glioblastoma (GBM) patients. Aim: This study aimed to make individualized treatment recommendations for patients with GBM and to determine the importance of demographic and tumor characteristic variables in the selection of extent of resection. Methods: We proposed Balanced Decision Ensembles (BDE) to make survival predictions and individualized treatment recommendations. We developed several DL models to counterfactually predict the individual treatment effect (ITE) of patients with GBM. We divided the patients into the recommended (Rec.) and anti-recommended groups based on whether their actual treatment was consistent with the model recommendation. Results: The BDE achieved the best recommendation effects (difference in restricted mean survival time (dRMST): 5.90; 95% confidence interval (CI), 4.40-7.39; hazard ratio (HR): 0.71; 95% CI, 0.65-0.77), followed by BITES and DeepSurv. Inverse probability treatment weighting (IPTW)-adjusted HR, IPTW-adjusted OR, natural direct effect, and control direct effect demonstrated better survival outcomes of the Rec. group. Conclusion: The ITE calculation method is crucial, as it may result in better or worse recommendations. Furthermore, the significant protective effects of machine recommendations on survival time and mortality indicate the superiority of the model for application in patients with GBM. Overall, the model identifies patients with tumors located in the right and left frontal and middle temporal lobes, as well as those with larger tumor sizes, as optimal candidates for SpTR.

Personalized surgical recommendations and quantitative therapeutic insights for patients with metastatic breast cancer: Insights from deep learning.

Background: The role of surgery in metastatic breast cancer (MBC) is currently controversial. Several novel statistical and deep learning (DL) methods promise to infer the suitability of surgery at the individual level. Objective: The objective of this study was to identify the most applicable DL model for determining patients with MBC who could benefit from surgery and the type of surgery required. Methods: We introduced the deep survival regression with mixture effects (DSME), a semi-parametric DL model integrating three causal inference methods. Six models were trained to make individualized treatment recommendations. Patients who received treatments in line with the DL models' recommendations were compared with those who underwent treatments divergent from the recommendations. Inverse probability weighting (IPW) was used to minimize bias. The effects of various features on surgery selection were visualized and quantified using multivariate linear regression and causal inference. Results: In total, 5269 female patients with MBC were included. DSME was an independent protective factor, outperforming other models in recommending surgery (IPW-adjusted hazard ratio [HR] = 0.39, 95% confidence interval [CI]: 0.19-0.78) and type of surgery (IPW-adjusted HR = 0.66, 95% CI: 0.48-0.93). DSME was superior to other models and traditional guidelines, suggesting a higher proportion of patients benefiting from surgery, especially breast-conserving surgery. The debiased effect of patient characteristics, including age, tumor size, metastatic sites, lymph node status, and breast cancer subtypes, on surgery decision was also quantified. Conclusions: Our findings suggested that DSME could effectively identify patients with MBC likely to benefit from surgery and the specific type of surgery needed. This method can facilitate the development of efficient, reliable treatment recommendation systems and provide quantifiable evidence for decision-making.

Determining individual suitability for neoadjuvant systemic therapy in breast cancer patients through deep learning.

BACKGROUND: The survival advantage of neoadjuvant systemic therapy (NST) for breast cancer patients remains controversial, especially when considering the heterogeneous characteristics of individual patients. OBJECTIVE: To discern the variability in responses to breast cancer treatment at the individual level and propose personalized treatment recommendations utilizing deep learning (DL). METHODS: Six models were developed to offer individualized treatment suggestions. Outcomes for patients whose actual treatments aligned with model recommendations were compared to those whose did not. The influence of certain baseline features of patients on NST selection was visualized and quantified by multivariate logistic regression and Poisson regression analyses. RESULTS: Our study included 94,487 female breast cancer patients. The Balanced Individual Treatment Effect for Survival data (BITES) model outperformed other models in performance, showing a statistically significant protective effect with inverse probability treatment weighting (IPTW)-adjusted baseline features [IPTW-adjusted hazard ratio: 0.51, 95% confidence interval (CI), 0.41-0.64; IPTW-adjusted risk difference: 21.46, 95% CI 18.90-24.01; IPTW-adjusted difference in restricted mean survival time: 21.51, 95% CI 19.37-23.80]. Adherence to BITES recommendations is associated with reduced breast cancer mortality and fewer adverse effects. BITES suggests that patients with TNM stage IIB, IIIB, triple-negative subtype, a higher number of positive axillary lymph nodes, and larger tumors are most likely to benefit from NST. CONCLUSIONS: Our results demonstrated the potential of BITES to aid in clinical treatment decisions and offer quantitative treatment insights. In our further research, these models should be validated in clinical settings and additional patient features as well as outcome measures should be studied in depth.

Logistic regression analysis of factors associated with avascular necrosis of the femoral head following femoral neck fractures in middle-aged and elderly patients.

BACKGROUND: Risk factors for femoral neck fracture-induced avascular necrosis of the femoral head have not been elucidated clearly in middle-aged and elderly patients. Moreover, the high incidence of screw removal in China and its effect on the fate of the involved femoral head require statistical methods to reflect their intrinsic relationship. METHODS: Ninety-nine patients older than 45 years with femoral neck fracture were treated by internal fixation between May 1999 and April 2004. Descriptive analysis, interaction analysis between associated factors, single factor logistic regression, multivariate logistic regression, and detailed interaction analysis were employed to explore potential relationships among associated factors. RESULTS: Avascular necrosis of the femoral head was found in 15 cases (15.2 %). Age × the status of implants (removal vs. maintenance) and gender × the timing of reduction were interactive according to two-factor interactive analysis. Age, the displacement of fractures, the quality of reduction, and the status of implants were found to be significant factors in single factor logistic regression analysis. Age, age × the status of implants, and the quality of reduction were found to be significant factors in multivariate logistic regression analysis. In fine interaction analysis after multivariate logistic regression analysis, implant removal was the most important risk factor for avascular necrosis in 56-to-85-year-old patients, with a risk ratio of 26.00 (95 % CI = 3.076-219.747). CONCLUSION: The middle-aged and elderly have less incidence of avascular necrosis of the femoral head following femoral neck fractures treated by cannulated screws. The removal of cannulated screws can induce a significantly high incidence of avascular necrosis of the femoral head in elderly patients, while a high-quality reduction is helpful to reduce avascular necrosis.

Injury-to-surgery interval does not affect postfracture osteonecrosis of the femoral head in young adults: a systematic review.

BACKGROUND: Osteonecrosis of the femoral head (ONFH) is a common and severe complication following femoral neck fractures in young adults. Despite significant advances in surgical techniques, radiological evaluation and comprehensive treatment for the prevention of ONFH, the incidence of traumatic ONFH has remained unchanged at approximately 20% in recent decades. The injury-to-surgery interval is considered as a principal factor affecting the occurrence of ONFH, and traditionally, femoral neck fractures are treated emergently. However, the relationship between the injury-to-surgery interval and ONFH occurrence is poorly understood, and previous reviews have not provided a precise explanation due to the lack of strict selection criteria for studies. METHODS: We reviewed previously published articles and included in current systematic review those studies with accurate multivariate analyses that included age, fracture type, operation method, follow-up, ONFH occurrence and injury-to-surgery interval. RESULTS: Six case studies were included and reevaluated. The studies included 263 hips for final analysis, with an overall incidence of postfracture ONFH of 17.5%. Patients were categorized into groups of less/more than 8 h, less/more than 24 h, less/more than 48 h and less/more than 3 weeks based on the individual injury-to-surgery interval. The postfracture ONFH incidence ranged from 13.3% (<8 weeks) to 21.7% (>3 weeks). Operations performed within 3 weeks of injury resulted in a lower ONFH incidence compared with operations performed after 3 weeks; however, this difference was not statistically significant. The ONFH incidence remained relatively stable when the operations were performed within 3 weeks of injury. CONCLUSIONS: The injury-to-surgery interval did not significantly affect the incidence of postoperative ONFH.

Evaluation of Chinese healthcare organizations' innovative performance in the digital health era.

Background: Healthcare workers' relationship with industry is not merely an agent mediating between consumer and vendor, but they are also inventors of the interventions they exist to deliver. Driven by the background of the digital health era, scientific research and technological (Sci-tech) innovation in the medical field are becoming more and more closely integrated. However, scholars shed little light on Sci-tech relevance to evaluate the innovation performance of healthcare organizations, a distinctive feature of healthcare organizations' innovation in the digital health era. Methods: Academic publications and patents are the manifestations of scientific research outputs and technological innovation outcomes, respectively. The study extracted data from publications and patents of 159 hospitals in China to evaluate their innovation performance. A total of 18 indicators were constructed, four of which were based on text similarity match and represented the Sci-tech relevance. We then applied factor analyses, analytical hierarchy process, and logistic regression to construct an evaluation model. We also examined the relationship between hospitals' innovation performance and their geographical locations. Finally, we implemented a mediation analysis to show the influence of digital health on hospital innovation performance. Results: A total of 16 indicators were involved, four of which represented the Sci-tech including the number of articles matched per patent (NAMP), the number of patents matched per article (NPMA), the proportion of highly matched patents (HMP), and the proportion of highly matched articles (HMA). Indicators of HMP (r = 0.52, P = 2.40 × 10-12), NAMP (r = 0.52, P = 2.54 × 10-12), and NPMA (r = 0.51, P = 5.53 × 10-12) showed a strong positive correlation with hospital innovation performance score. The evaluation model in this study was different from other Chinese existing hospital ranking systems. The regional innovation performance index (RIP) of healthcare organizations is highly correlated with per capita disposable income (r = 0.58) and regional GDP (r = 0.60). There was a positive correlation between digital health innovation performance scores and overall hospital innovation performance scores (r = 0.20). In addition, the hospitals' digital health innovation performance affected the hospital's overall innovation score with the mediation of Sci-tech relevance indicators (NPMA and HMA). The hospitals' digital health innovation performance score showed a significant correlation with the number of healthcare workers (r = 0.44). Conclusion: This study constructed an assessment model with four invented indicators focusing on Sci-tech relevance to provide a novel tool for researchers to evaluate the innovation performance of healthcare organizations in the digital health era. The regions with high RIP were concentrated on the eastern coastal areas with a higher level of economic development. Therefore, the promotion of scientific and technological innovation policies could be carried out in advance in areas with better economic development. The innovations in the digital health field by healthcare workers enhance the Sci-tech relevance in hospitals and boost their innovation performance. The development of digital health in hospitals depends on the input of medical personnel.

Analyzing and predicting the risk of death in stroke patients using machine learning.

Background: Stroke is an acute disorder and dysfunction of the focal neurological system that has long been recognized as one of the leading causes of death and severe disability in most regions globally. This study aimed to supplement and exploit multiple comorbidities, laboratory tests and demographic factors to more accurately predict death related to stroke, and furthermore, to make inferences about the heterogeneity of treatment in stroke patients to guide better treatment planning. Methods: We extracted data from the Medical Information Mart from the Intensive Care (MIMIC)-IV database. We compared the distribution of the demographic factors between the control and death groups. Subsequently, we also developed machine learning (ML) models to predict mortality among stroke patients. Furthermore, we used meta-learner to recognize the heterogeneity effects of warfarin and human albumin. We comprehensively evaluated and interpreted these models using Shapley Additive Explanation (SHAP) analysis. Results: We included 7,483 patients with MIMIC-IV in this study. Of these, 1,414 (18.9%) patients died during hospitalization or 30 days after discharge. We found that the distributions of age, marital status, insurance type, and BMI differed between the two groups. Our machine learning model achieved the highest level of accuracy to date in predicting mortality in stroke patients. We also observed that patients who were consistent with the model determination had significantly better survival outcomes than the inconsistent population and were better than the overall treatment group. Conclusion: We used several highly interpretive machine learning models to predict stroke prognosis with the highest accuracy to date and to identify heterogeneous treatment effects of warfarin and human albumin in stroke patients. Our interpretation of the model yielded a number of findings that are consistent with clinical knowledge and warrant further study and verification.

Effective early strategy to prevent olfactory and gustatory dysfunction in COVID-19: A randomized controlled trial.

BACKGROUND: Olfactory and gustatory dysfunctions (OGDs) are key symptoms of COVID-19, which may lead to neurological complications, and lack of effective treatment. This may be because post-disease treatments may be too late to protect the olfactory and gustatory functions. AIM: To evaluate the effectiveness of early use of saline nasal irrigation (SNI), corticosteroid nasal spray, and saline or chlorhexidine gluconate mouthwash for preventing OGDs in COVID-19. DESIGN: This study was a double-blind randomized controlled trial. METHODS: The study was conducted from May 5 to June 16, 2022. We recruited patients from three hospitals who were admitted with COVID-19 but without OGDs on the day of admission. Olfactory and gustatory functions were evaluated using the Taste and Smell Survey and the numerical visual analog scale. Participants were randomized to the saline, drug, or control groups. The control group received no intervention, saline group received SNI plus saline nasal spray and mouthwash, and the trial group received SNI plus budesonide nasal spray and chlorhexidine gluconate mouthwash. Participants were assessed again on the day of discharge. RESULTS: A total of 379 patients completed the trial. The prevalence of OGDs was significantly lower in the saline (11.8%, 95% CI, 6.6-19.0%; P < 0.001) and trial (8.3%, 95% CI, 4.1-14.8%; P < 0.001) groups than in the control group (40.0%, 95% CI, 31.8-48.6%). Additionally, both interventions reduced the severity of OGDs. CONCLUSIONS: We demonstrated effective strategies for preventing COVID-19-related OGDs, and the findings may guide early management of SARS-CoV-2 infection to reduce the incidence of COVID-19-related complications.