Identifying the Characteristics of Patients With Cervical Degenerative Disease for Surgical Treatment From 17-Year Real-World Data: Retrospective Study

Current trends and future prospects of drug repositioning in gastrointestinal oncology

Gastrointestinal (GI) cancers comprise a significant number of cancer cases worldwide and contribute to a high percentage of cancer-related deaths. To improve survival rates of GI cancer patients, it is important to find and implement more effective therapeutic strategies with better prognoses and fewer side effects. The development of new drugs can be a lengthy and expensive process, often involving clinical trials that may fail in the early stages. One strategy to address these challenges is drug repurposing (DR). Drug repurposing is a developmental strategy that involves using existing drugs approved for other diseases and leveraging their safety and pharmacological data to explore their potential use in treating different diseases. In this paper, we outline the existing therapeutic strategies and challenges associated with GI cancers and explore DR as a promising alternative approach. We have presented an extensive review of different DR methodologies, research efforts and examples of repurposed drugs within various GI cancer types, such as colorectal, pancreatic and liver cancers. Our aim is to provide a comprehensive overview of employing the DR approach in GI cancers to inform future research endeavors and clinical trials in this field.

Characteristics and Admission Preferences of Pediatric Emergency Patients and Their Waiting Time Prediction Using Electronic Medical Record Data: Retrospective Comparative Analysis

BACKGROUND

The growing number of patients visiting pediatric emergency departments could have a detrimental impact on the care provided to children who are triaged as needing urgent attention. Therefore, it has become essential to continuously monitor and analyze the admissions and waiting times of pediatric emergency patients. Despite the significant challenge posed by the shortage of pediatric medical resources in China's health care system, there have been few large-scale studies conducted to analyze visits to the pediatric emergency room.

OBJECTIVE

This study seeks to examine the characteristics and admission patterns of patients in the pediatric emergency department using electronic medical record (EMR) data. Additionally, it aims to develop and assess machine learning models for predicting waiting times for pediatric emergency department visits.

METHODS

This retrospective analysis involved patients who were admitted to the emergency department of Children's Hospital Capital Institute of Pediatrics from January 1, 2021, to December 31, 2021. Clinical data from these admissions were extracted from the electronic medical records, encompassing various variables of interest such as patient demographics, clinical diagnoses, and time stamps of clinical visits. These indicators were collected and compared. Furthermore, we developed and evaluated several computational models for predicting waiting times.

RESULTS

In total, 183,024 eligible admissions from 127,368 pediatric patients were included. During the 12-month study period, pediatric emergency department visits were most frequent among children aged less than 5 years, accounting for 71.26% (130,423/183,024) of the total visits. Additionally, there was a higher proportion of male patients (104,147/183,024, 56.90%) compared with female patients (78,877/183,024, 43.10%). Fever (50,715/183,024, 27.71%), respiratory infection (43,269/183,024, 23.64%), celialgia (9560/183,024, 5.22%), and emesis (6898/183,024, 3.77%) were the leading causes of pediatric emergency room visits. The average daily number of admissions was 501.44, and 18.76% (34,339/183,204) of pediatric emergency department visits resulted in discharge without a prescription or further tests. The median waiting time from registration to seeing a doctor was 27.53 minutes. Prolonged waiting times were observed from April to July, coinciding with an increased number of arrivals, primarily for respiratory diseases. In terms of waiting time prediction, machine learning models, specifically random forest, LightGBM, and XGBoost, outperformed regression methods. On average, these models reduced the root-mean-square error by approximately 17.73% (8.951/50.481) and increased the R2 by approximately 29.33% (0.154/0.525). The SHAP method analysis highlighted that the features "wait.green" and "department" had the most significant influence on waiting times.

CONCLUSIONS

This study offers a contemporary exploration of pediatric emergency room visits, revealing significant variations in admission rates across different periods and uncovering certain admission patterns. The machine learning models, particularly ensemble methods, delivered more dependable waiting time predictions. Patient volume awaiting consultation or treatment and the triage status emerged as crucial factors contributing to prolonged waiting times. Therefore, strategies such as patient diversion to alleviate congestion in emergency departments and optimizing triage systems to reduce average waiting times remain effective approaches to enhance the quality of pediatric health care services in China.

Efficacy and safety of traditional Chinese medicine adjuvant therapy for severe pneumonia: evidence mapping of the randomized controlled trials, systematic reviews, and meta-analyses

Background and Objective: Severe pneumonia is a critical respiratory disease with high mortality. There is insufficient evidence on the efficacy and safety of traditional Chinese medicine (TCM) adjuvant therapy for severe pneumonia. This study aims to identify, describe, assess, and summarize the currently available high-quality design evidence on TCM adjuvant therapy for severe pneumonia to identify evidence gaps using the evidence mapping approach. Methods: Systematic searches were performed on English and Chinese online databases (PubMed, EMBASE, Cochrane Library, Web of Science, CNKI, WanFang Data, CQVIP, and SinoMed) to identify papers from inception until August 2023 for inclusion into the review. Randomized controlled trials (RCTs), systematic reviews (SRs), and meta-analyses concerning TCM adjuvant therapy for severe pneumonia or its complications in adults were included. The risk of bias in RCTs was evaluated by using the Cochrane Handbook ROB tool. The Assessment of Multiple Systematic Reviews 2 (AMSTAR-2), the Risk of Bias in Systematic Review (ROBIS) tool, and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system were used to assess the methodological quality, risk of bias, and evidence quality of SRs or meta-analyses, respectively. Then, a bubble plot was designed to visually display information in four dimensions. Results: A total of 354 RCTs and 17 SRs or meta-analyses met the inclusion criteria. The published RCTs had several flaws, such as unreasonable design, limited sample size, insufficient attention to non-drug therapy studies and syndrome differentiation, improper selection or use of outcome indicators, and failure to provide high-quality evidence. Sixteen SRs or meta-analyses of methodological quality scored "Critically Low" confidence. Twelve SRs or meta-analyses were rated as "High Risk." Most outcomes were rated as "Low" evidence quality. We found that TCM combined with conventional treatment could improve the clinical total effective rate and the TCM syndromes efficacy. The combined approach could also shorten mechanical ventilation time, infection control time, and length of hospital and ICU stay; significantly reduce temperature, respiratory rate, heart rate, white blood cell counts, levels of C-reactive protein, procalcitonin, blood inflammatory factors, bacteriological response, and D-dimer; decrease CPIS, APACHE II score, and PSI score; improve pulmonary imaging features, arterial blood gas indicators (including arterial oxygen pressure, arterial oxygen saturation, and oxygen index), and lung function (including forced vital capacity and forced expiratory volume in the first second) for severe pneumonia compared with conventional treatment only (p < 0.05). There was no significant difference in adverse reactions and incidence of adverse events (p > 0.05). In addition, compared with conventional treatment only, most SRs or meta-analyses concluded that TCM combined with conventional treatment was "Beneficial" or "Probably beneficial." Conclusion: TCM combined with conventional treatment had advantages in efficacy, clinical signs, laboratory results, and life quality outcomes of severe pneumonia, with no difference in safety outcomes compared with conventional treatment only. QingJin Huatan decoction is the most promising target, and Xuanbai Chengqi decoction has a "Probably beneficial" conclusion. XueBiJing injection and TanReQing injection are two commonly used Chinese herbal injections for treating severe pneumonia, and both are "Probably beneficial." However, there was a need for multicenter RCTs with large sample sizes and high methodological quality in the future. In addition, the methodological design and quality of SRs or meta-analyses should be improved to form high-quality, evidence-based medical evidence and provide evidence for the effectiveness and safety of TCM adjuvant therapy for severe pneumonia.

Changes of improvement in upper limb function predict surgical outcome after laminoplasty in 1 year in patients with cervical spondylotic myelopathy: a retrospective study

BACKGROUND

Cervical spondylotic myelopathy preoperative prognostic factors include age, preoperative severity, and disease duration. However, there are no reports on the relationship between changes in physical function during hospitalization and postoperative course, and in recent years, the length of hospital stay has shortened. We aimed to investigate whether changes in physical function during hospitalization can predict the postoperative outcome.

METHODS

We recruited 104 patients who underwent laminoplasty for cervical spondylotic myelopathy by the same surgeon. Physical functions, including Simple Test for Evaluating Hand Function (STEF), grip strength, timed up and go test, 10-m walk, and time to stand on one leg, were assessed at admission and discharge. Patients with the Japanese Orthopaedic Association (JOA) score improvement rate of 50% or more were defined as the improved group. Decision tree analysis was investigated factor for identifying improvement in the JOA score. According to this analysis, we divided into two groups using age. Then, we conducted a logistic regression analysis to identify factors that improve the JOA score.

RESULTS

The improved and non-improved groups had 31 and 73 patients, respectively. The improved group was younger (p = 0.003) and had better improved Δgrip strength (p = 0.001) and ΔSTEF (p < .0007). Age was significantly positively correlated with disease duration (r = 0.4881, p =  < .001). Disease duration exhibited a significant negative correlation with the JOA score improvement rate (r = - 0.2127, p = 0.031). Based on the decision tree analysis results, age was the first branching variable, with 15% of patients ≥ 67 years showing JOA score improvement. This was followed by ΔSTEF as the second branching factor. ΔSTEF was selected as the factor associated with JOA improvement in patients ≥ 67 years (odds ratio (OR) 0.95, 95% confidence interval (CI) 0.90-0.99, p = .047); in patients < 67 years, Δgrip strength was identified (OR 0.53, CI 0.33‒0.85, p = .0086).

CONCLUSIONS

In the improved group, upper limb function improved more than lower limb function from the early postoperative period. Upper limb function changes during hospitalization were associated with outcomes one year postoperatively. Improvement factors in upper extremity function differed by age, with changes in grip strength in patients < 67 years and STEF in patients ≥ 67 years, reflecting the outcome at one year postoperatively.

Overcoming cancer therapeutic bottleneck by drug repurposing

Ever present hurdles for the discovery of new drugs for cancer therapy have necessitated the development of the alternative strategy of drug repurposing, the development of old drugs for new therapeutic purposes. This strategy with a cost-effective way offers a rare opportunity for the treatment of human neoplastic disease, facilitating rapid clinical translation. With an increased understanding of the hallmarks of cancer and the development of various data-driven approaches, drug repurposing further promotes the holistic productivity of drug discovery and reasonably focuses on target-defined antineoplastic compounds. The "treasure trove" of non-oncology drugs should not be ignored since they could target not only known but also hitherto unknown vulnerabilities of cancer. Indeed, different from targeted drugs, these old generic drugs, usually used in a multi-target strategy may bring benefit to patients. In this review, aiming to demonstrate the full potential of drug repurposing, we present various promising repurposed non-oncology drugs for clinical cancer management and classify these candidates into their proposed administration for either mono- or drug combination therapy. We also summarize approaches used for drug repurposing and discuss the main barriers to its uptake.