Haploidentical transplantation has a superior graft-versus-leukemia effect than HLA-matched sibling transplantation for Ph– high-risk B-cell acute lymphoblastic leukemia

Background:Compared with human leukocyte antigen (HLA)-matched sibling donor (MSD) transplantation, it remains unclear whether haploidentical donor (HID) transplantation has a superior graft-versus-leukemia (GVL) effect for Philadelphia-negative (Ph–) high-risk B-cell acute lymphoblastic leukemia (B-ALL). This study aimed to compare the GVL effect between HID and MSD transplantation for Ph– high-risk B-ALL.Methods:This study population came from two prospective multicenter trials ({"type":"clinical-trial","attrs":{"text":"NCT01883180","term_id":"NCT01883180"}}NCT01883180, {"type":"clinical-trial","attrs":{"text":"NCT02673008","term_id":"NCT02673008"}}NCT02673008). Immunosuppressant withdrawal and prophylactic or pre-emptive donor lymphocyte infusion (DLI) were administered in patients without active graft-versus-host disease (GVHD) to prevent relapse. All patients with measurable residual disease (MRD) positivity posttransplantation (post-MRD+) or non-remission (NR) pre-transplantation received prophylactic/pre-emptive interventions. The primary endpoint was the incidence of post-MRD+.Results:A total of 335 patients with Ph– high-risk B-ALL were enrolled, including 145 and 190, respectively, in the HID and MSD groups. The 3-year cumulative incidence of post-MRD+ was 27.2% (95% confidence interval [CI]: 20.2%–34.7%) and 42.6% (35.5%–49.6%) in the HID and MSD groups (P = 0.003), respectively. A total of 156 patients received DLI, including 60 (41.4%) and 96 (50.5%), respectively, in the HID and MSD groups (P = 0.096). The 3-year cumulative incidence of relapse was 18.6% (95% CI: 12.7%–25.4%) and 25.9% (19.9%–32.3%; P = 0.116) in the two groups, respectively. The 3-year overall survival (OS) was 67.4% (95% CI: 59.1%–74.4%) and 61.6% (54.2%–68.1%; P = 0.382), leukemia-free survival (LFS) was 63.4% (95% CI: 55.0%–70.7%) and 58.2% (50.8%–64.9%; P = 0.429), and GVHD-free/relapse-free survival (GRFS) was 51.7% (95% CI: 43.3%–59.5%) and 37.8% (30.9%–44.6%; P = 0.041), respectively, in the HID and MSD groups.Conclusion:HID transplantation has a lower incidence of post-MRD+ than MSD transplantation, suggesting that HID transplantation might have a superior GVL effect than MSD transplantation for Ph– high-risk B-ALL patients.Trial registration:ClinicalTrials.gov: {"type":"clinical-trial","attrs":{"text":"NCT01883180","term_id":"NCT01883180"}}NCT01883180, {"type":"clinical-trial","attrs":{"text":"NCT02673008","term_id":"NCT02673008"}}NCT02673008.     

Functional mitral regurgitation combined with increased early diastolic transmitral velocity to early mitral annulus diastolic velocity ratio is associated with a poor prognosis in patients with shock

Background:Functional mitral regurgitation (FMR) is common in critically ill patients and may cause left atrial (LA) pressure elevation. This study aims to explore the prognostic impact of synergistic LA pressure elevation and FMR in patients with shock.Methods:We retrospectively screened 130 consecutive patients of 175 patients with shock from April 2016 to June 2017. The incidence and impact of FMR and early diastolic transmitral velocity to early mitral annulus diastolic velocity ratio (E/e’) ≥ 4 within 6 h of shock on the prognosis of patients were evaluated. Finally, the synergistic effect of FMR and E/e’ were assessed by combination, grouping, and trend analyses.Results:Forty-four patients (33.8%) had FMR, and 15 patients (11.5%) had E/e’ elevation. A multivariate analysis revealed FMR and E/e’ as independent correlated factors for 28-day mortality (P = 0.043 and 0.028, respectively). The Kaplan-Meier survival analysis revealed a significant difference in survival between patients with and without FMR (χ² = 7.672, P = 0.006) and between the E/e’ ≥ 14 and E/e’ < 14 groups (χ² = 19.351, P < 0.010). Twenty-eight-day mortality was significantly different among the four groups (χ² = 30.141, P < 0.010). The risk of 28-day mortality was significantly higher in group 4 (E/e’ ≥ 14 with FMR) compared with groups 1 (E/e’ < 14 without FMR) and 2 (E/e’ < 14 with FMR) (P = 0.001 and 0.046, respectively).Conclusions:Patients with shock can be identified by the presence of FMR. FMR and E/e’ are independent risk factors for a poor prognosis in these patients, and prognosis is worst when FMR and E/e’ ≥ 14 are present. It may be possible to improve prognosis by reducing LA pressure and E/e’.Trial Registration:ClinicalTrials.gov, {"type":"clinical-trial","attrs":{"text":"NCT03082326","term_id":"NCT03082326"}}NCT03082326.     

Aggregating large-scale databases for PubMed author name disambiguation

ObjectivePubMed has suffered from the author ambiguity problem for many years. Existing studies on author name disambiguation (AND) for PubMed only used internal metadata for development. However, some of them are incomplete (eg, a large number of names are only abbreviated and their full names are not available) or less discriminative. To this end, we present a new disambiguation method, namely AggAND, by aggregating information from external databases.Materials and MethodsWe address this issue by exploring Microsoft Academic Graph, Semantic Scholar, and PubMed Knowledge Graph to enhance the built-in name metadata, and extend the internal metadata with some external and more discriminative metadata.ResultsExperimental results on enhanced name metadata demonstrate comparable performance to 3 author identifier systems, as well as show superiority over the original name metadata. More importantly, our method, AggAND, incorporating both enhanced name and extended metadata, yields F1 scores of 95.80% and 93.71% on 2 datasets and outperforms the state-of-the-art method by a large margin (3.61% and 6.55%, respectively).ConclusionsThe feasibility and good performance of our methods not only help better understand the importance of external databases for disambiguation, but also point to a promising direction for future AND studies in which information aggregated from multiple bibliographic databases can be effective in improving disambiguation performance. The methodology shown here can be generalized to broader bibliographic databases beyond PubMed. Our code and data are available online (https://github.com/carmanzhang/PubMed-AND-method).     

Using Twitter data to understand public perceptions of approved versus off-label use for COVID-19-related medications

ObjectiveUnderstanding public discourse on emergency use of unproven therapeutics is essential to monitor safe use and combat misinformation. We developed a natural language processing-based pipeline to understand public perceptions of and stances on coronavirus disease 2019 (COVID-19)-related drugs on Twitter across time.MethodsThis retrospective study included 609 189 US-based tweets between January 29, 2020 and November 30, 2021 on 4 drugs that gained wide public attention during the COVID-19 pandemic: (1) Hydroxychloroquine and Ivermectin, drug therapies with anecdotal evidence; and (2) Molnupiravir and Remdesivir, FDA-approved treatment options for eligible patients. Time-trend analysis was used to understand the popularity and related events. Content and demographic analyses were conducted to explore potential rationales of people’s stances on each drug.ResultsTime-trend analysis revealed that Hydroxychloroquine and Ivermectin received much more discussion than Molnupiravir and Remdesivir, particularly during COVID-19 surges. Hydroxychloroquine and Ivermectin were highly politicized, related to conspiracy theories, hearsay, celebrity effects, etc. The distribution of stance between the 2 major US political parties was significantly different (P < .001); Republicans were much more likely to support Hydroxychloroquine (+55%) and Ivermectin (+30%) than Democrats. People with healthcare backgrounds tended to oppose Hydroxychloroquine (+7%) more than the general population; in contrast, the general population was more likely to support Ivermectin (+14%).ConclusionOur study found that social media users with have different perceptions and stances on off-label versus FDA-authorized drug use across different stages of COVID-19, indicating that health systems, regulatory agencies, and policymakers should design tailored strategies to monitor and reduce misinformation for promoting safe drug use. Our analysis pipeline and stance detection models are made public at https://github.com/ningkko/COVID-drug.     

Multi-PheWAS intersection approach to identify sex differences across comorbidities in 59 140 pediatric patients with autism spectrum disorder

ObjectiveTo identify differences related to sex and define autism spectrum disorder (ASD) comorbidities female-enriched through a comprehensive multi-PheWAS intersection approach on big, real-world data. Although sex difference is a consistent and recognized feature of ASD, additional clinical correlates could help to identify potential disease subgroups, based on sex and age.Materials and MethodsWe performed a systematic comorbidity analysis on 1860 groups of comorbidities exploring all spectrum of known disease, in 59 140 individuals (11 440 females) with ASD from 4 age groups. We explored ASD sex differences in 2 independent real-world datasets, across all potential comorbidities by comparing (1) females with ASD vs males with ASD and (2) females with ASD vs females without ASD.ResultsWe identified 27 different comorbidities that appeared significantly more frequently in females with ASD. The comorbidities were mostly neurological (eg, epilepsy, odds ratio [OR] > 1.8, 3-18 years of age), congenital (eg, chromosomal anomalies, OR > 2, 3-18 years of age), and mental disorders (eg, intellectual disability, OR > 1.7, 6-18 years of age). Novel comorbidities included endocrine metabolic diseases (eg, failure to thrive, OR = 2.5, ages 0-2), digestive disorders (gastroesophageal reflux disease: OR = 1.7, 6-11 years of age; and constipation: OR > 1.6, 3-11 years of age), and sense organs (strabismus: OR > 1.8, 3-18 years of age).DiscussionA multi-PheWAS intersection approach on real-world data as presented in this study uniquely contributes to the growing body of research regarding sex-based comorbidity analysis in ASD population.ConclusionsOur findings provide insights into female-enriched ASD comorbidities that are potentially important in diagnosis, as well as the identification of distinct comorbidity patterns influencing anticipatory treatment or referrals. The code is publicly available (https://github.com/hms-dbmi/sexDifferenceInASD).     

Efficacy and safety of high-dose esomeprazole–amoxicillin dual therapy for Helicobacter pylori rescue treatment: a multicenter,prospective, randomized,controlled trial

Background:High-dose dual therapy (HDDT) with proton pump inhibitors (PPIs) and amoxicillin has attracted widespread attention due to its favorable efficacy in eradicating Helicobacter pylori (H. pylori). This study aimed to compare the efficacy and safety of high-dose PPI–amoxicillin dual therapy and bismuth-containing quadruple therapy for H. pylori rescue treatment.Methods:This was a prospective, randomized, multicenter, non-inferiority trial. Patients recruited from eight centers who had failed previous treatment were randomly (1:1) allocated to two eradication groups: HDDT (esomeprazole 40 mg and amoxicillin 1000 mg three times daily; the HDDT group) and bismuth-containing quadruple therapy (esomeprazole 40 mg, bismuth potassium citrate 220 mg, and furazolidone 100 mg twice daily, combined with tetracycline 500 mg three times daily; the tetracycline, furazolidone, esomeprazole, and bismuth [TFEB] group) for 14 days. The primary endpoint was the H. pylori eradication rate. The secondary endpoints were adverse effects, symptom improvement rates, and patient compliance.Results:A total of 658 patients who met the criteria were enrolled in this study. The HDDT group achieved eradication rates of 75.4% (248/329), 81.0% (248/306), and 81.3% (248/305) asdetermined by the intention-to-treat (ITT), modified intention-to-treat (MITT), and per-protocol (PP) analyses, respectively. The eradication rates were similar to those in the TFEB group: 78.1% (257/329), 84.2% (257/305), and 85.1% (257/302). The lower 95% confidence interval boundary (−9.19% in the ITT analysis, − 9.21% in the MITT analysis, and −9.73% in the PP analysis) was greater than the predefined non-inferiority margin of −10%, establishing a non-inferiority of the HDDT group vs. the TFEB group. The incidence of adverse events in the HDDT group was significantly lower than that in the TFEB group (11.1% vs. 26.8%, P < 0.001). Symptom improvement rates and patients’ compliance were similar between the two groups.Conclusions:Fourteen-day HDDT is non-inferior to bismuth-containing quadruple therapy, with fewer adverse effects and good treatment compliance, suggesting HDDT as an alternative for H. pylori rescue treatment in the local region.Trial registration:Clinicaltrials.gov, {"type":"clinical-trial","attrs":{"text":"NCT04678492","term_id":"NCT04678492"}}NCT04678492.     

Distantly supervised biomedical relation extraction using piecewise attentive convolutional neural network and reinforcement learning

ObjectiveThere have been various methods to deal with the erroneous training data in distantly supervised relation extraction (RE), however, their performance is still far from satisfaction. We aimed to deal with the insufficient modeling problem on instance-label correlations for predicting biomedical relations using deep learning and reinforcement learning.Materials and MethodsIn this study, a new computational model called piecewise attentive convolutional neural network and reinforcement learning (PACNN+RL) was proposed to perform RE on distantly supervised data generated from Unified Medical Language System with MEDLINE abstracts and benchmark datasets. In PACNN+RL, PACNN was introduced to encode semantic information of biomedical text, and the RL method with memory backtracking mechanism was leveraged to alleviate the erroneous data issue. Extensive experiments were conducted on 4 biomedical RE tasks.ResultsThe proposed PACNN+RL model achieved competitive performance on 8 biomedical corpora, outperforming most baseline systems. Specifically, PACNN+RL outperformed all baseline methods with the F1-score of 0.5592 on the may-prevent dataset, 0.6666 on the may-treat dataset, and 0.3838 on the DDI corpus, 2011. For the protein-protein interaction RE task, we obtained new state-of-the-art performance on 4 out of 5 benchmark datasets.ConclusionsThe performance on many distantly supervised biomedical RE tasks was substantially improved, primarily owing to the denoising effect of the proposed model. It is anticipated that PACNN+RL will become a useful tool for large-scale RE and other downstream tasks to facilitate biomedical knowledge acquisition. We also made the demonstration program and source code publicly available at http://112.74.48.115:9000/.     

Comparison of sequential feeding and continuous feeding on the blood glucose of critically ill patients: a non-inferiority randomized controlled trial

Background:Glucose control is an important aspect in managing critically ill patients. The goal of this study was to compare the effects of sequential feeding (SF) and continuous feeding (CF) on the blood glucose of critically ill patients.Methods:A non-inferiority randomized controlled trial was adopted in this study. A total of 62 patients who were fed enteral nutritional suspension through gastric tubes were enrolled. After achieving 80% of the nutrition target calories (25 kcal·kg⁻¹·day⁻¹) through CF, the patients were then randomly assigned into SF and CF groups. In the SF group, the feeding/fasting time was reasonably determined according to the circadian rhythm of the human body as laid out in traditional Chinese medicine theory. The total daily dosage of the enteral nutritional suspension was equally distributed among three time periods of 7 to 9 o’clock, 11 to 13 o’clock, and 17 to 19 o’clock. The enteral nutritional suspension in each time period was pumped at a uniform rate within 2 h by an enteral feeding pump. In the CF group, patients received CF at a constant velocity by an enteral feeding pump throughout the study. Blood glucose values at five points (6:00/11:00/15:00/21:00/1:00) were monitored and recorded for seven consecutive days after randomization. Enteral feeding intolerance was also recorded. Non-inferiority testing was adopted in this study, the chi-square test or Fisher test was used for qualitative data, and the Mann-Whitney U test was used for quantitative data to determine differences between groups. In particular, a repeated measure one-way analysis of variance was used to identify whether changes in glucose value variables across the time points were different between the two groups.Results:There were no significant demographic or physiological differences between the SF and CF groups (P > 0.050). The average glucose level in SF was not higher than that in CF (8.8 [7.3–10.3] vs. 10.7 [9.1–12.1] mmol/L, Z = −2.079, P for non-inferiority = 0.019). Hyperglycemia incidence of each patient was more common in the CF group than that in the SF group (38.4 [19.1–63.7]% vs. 11.8 [3.0–36.7]%, Z = −2.213, P = 0.027). Hypoglycemia was not found in either group. Moreover, there was no significant difference during the 7 days in the incidence of feeding intolerance (P > 0.050).Conclusions:In this non-inferiority study, the average blood glucose in SF was not inferior to that in CF. The feeding intolerance in SF was similar to that in CF. SF may be as safe as CF for critically ill patients.Trial RegistrationClinicalTrials.gov, {"type":"clinical-trial","attrs":{"text":"NCT03439618","term_id":"NCT03439618"}}NCT03439618; https://clinicaltrials.gov/ct2/show/record/{"type":"clinical-trial","attrs":{"text":"NCT03439618","term_id":"NCT03439618"}}NCT03439618     

Pre-operative nasal probe tests with adrenaline and lidocaine ease insertion during flexible bronchoscopy and reduce post-operative bleeding: a randomized controlled trial

Background:Nasal insertion is the preferred method for non-intubated patients in flexible bronchoscopy; however, the relatively narrow nasal cavity results in difficulties related to bronchoscope insertion. This study aimed to investigate whether pre-operative nasal probe tests could reduce the time to pass the glottis, improve the first-pass success rate and patients’ tolerance, and reduce postoperative bleeding.Methods:This three-arm prospective randomized controlled trial was conducted in a tertiary hospital between May and October 2020. Three hundred patients requiring diagnosis and treatment using flexible bronchoscopy were randomly allocated to three groups: control group, simple cotton bud detection group (CD group), and adrenaline + lidocaine detection group (AD group). The primary outcome was the time to pass the glottis. Secondary outcomes included the first-pass success rate, the patients’ tolerance scores, and post-operative bleeding. One-way analysis of variance, Kruskal-Wallis H test, Chi-squared test, Fisher''s exact test, and Bonferroni''s multiple comparison tests were used in this study.Results:In total, 189 men and 111 women were enrolled in this study, with a mean age of 55.72 ± 12.86 years. The insertion time was significantly shorter in the AD group than in the control group (18.00 s [12.00–26.50 s] vs. 24.00 s [14.50–45.50 s], P = 0.005). Both the AD (99% vs. 83%, χ² = 15.62, P < 0.001) and CD groups (94% vs. 83%, χ² = 5.94, P = 0.015) had a significantly higher first-pass success rate than the control group. Compared with the control group, post-operative bleeding (1% vs. 13%, χ² = 11.06, P < 0.001) was significantly lower in the AD group. However, no significant difference was found in the patients’ tolerance scores.Conclusions:Pre-operative nasal cavity probe tests especially with adrenaline and lidocaine during flexible bronchoscopy can significantly reduce the time to pass the glottis, improve the first-pass success rate, and reduce post-operative nasal bleeding. Pre-operative nasal probe tests are recommended as a time-saving procedure for patients undergoing flexible bronchoscopy.Trial registration:Chinese Clinical Trial Registry (ChiCTR), ChiCTR2000032668; http://www.chictr.org.cn/showprojen.aspx?proj=53321.     

Metrics and tools for consistent cohort discovery and financial analyses post-transition to ICD-10-CM

In the United States, International Classification of Disease Clinical Modification (ICD-9-CM, the ninth revision) diagnosis codes are commonly used to identify patient cohorts and to conduct financial analyses related to disease. In October 2015, the healthcare system of the United States will transition to ICD-10-CM (the tenth revision) diagnosis codes. One challenge posed to clinical researchers and other analysts is conducting diagnosis-related queries across datasets containing both coding schemes. Further, healthcare administrators will manage growth, trends, and strategic planning with these dually-coded datasets. The majority of the ICD-9-CM to ICD-10-CM translations are complex and nonreciprocal, creating convoluted representations and meanings. Similarly, mapping back from ICD-10-CM to ICD-9-CM is equally complex, yet different from mapping forward, as relationships are likewise nonreciprocal. Indeed, 10 of the 21 top clinical categories are complex as 78% of their diagnosis codes are labeled as “convoluted” by our analyses. Analysis and research related to external causes of morbidity, injury, and poisoning will face the greatest challenges due to 41 745 (90%) convolutions and a decrease in the number of codes. We created a web portal tool and translation tables to list all ICD-9-CM diagnosis codes related to the specific input of ICD-10-CM diagnosis codes and their level of complexity: “identity” (reciprocal), “class-to-subclass,” “subclass-to-class,” “convoluted,” or “no mapping.” These tools provide guidance on ambiguous and complex translations to reveal where reports or analyses may be challenging to impossible.Web portal: http://www.lussierlab.org/transition-to-ICD9CM/Tables annotated with levels of translation complexity: http://www.lussierlab.org/publications/ICD10to9     

Short-term combined treatment with exenatide and metformin for overweight/obese women with polycystic ovary syndrome

Background:Obesity and insulin resistance (IR) are common features of polycystic ovary syndrome (PCOS). Metformin (MET) increases insulin sensitivity, but it is associated with unsatisfactory weight loss. The glucagon-like peptide-1 receptor agonist exenatide has been shown to reduce weight and IR in patients with diabetes. This study aimed to explore the therapeutic effects of exenatide once-weekly (QW) combined with MET on body weight, as well as metabolic and endocrinological parameters in overweight/obese women with PCOS.Methods:Fifty overweight/obese women with PCOS diagnosed via the Rotterdam criteria were randomized to one of two treatment groups: MET (500 mg three times a day [TID]) or combination treatment (COM) (MET 500 mg TID, exenatide 2 mg QW) for 12 weeks. The primary outcomes were anthropometric changes associated with obesity, and the secondary outcomes included changes in reproductive hormone levels, glucose and lipid metabolism, and C-reactive protein.Results:Forty (80%) patients completed the study. COM therapy was superior to MET monotherapy in reducing weight (P = 0.045), body mass index (BMI) (P = 0.041), and waist circumference (P = 0.023). Patients in the COM group on an average lost 3.8 ± 2.4 kg compared with 2.1 ± 3.0 kg in the MET group. In the COM group, BMI and waist circumference decreased by 1.4 ± 0.87 kg/m² and 4.63 ± 4.42 cm compared with 0.77 ± 1.17 kg/m² and 1.72 ± 3.07 cm in the MET group, respectively. Moreover, levels of fasting glucose, oral glucose tolerance test (OGTT) 2-h glucose, and OGTT 2-h insulin were significantly lower with COM therapy than with MET (P < 0.050). Mild and moderate gastrointestinal reactions were the most common adverse events in both groups.Conclusions:COM therapy was more effective than MET alone in reducing body weight, BMI, and waist circumference, and improving insulin sensitivity in overweight/obese women with PCOS, with acceptable short-term side effects.Trial registration:ClinicalTrials.gov, {"type":"clinical-trial","attrs":{"text":"NCT04029272","term_id":"NCT04029272"}}NCT04029272. https://clinicaltrials.gov/ct2/show/{"type":"clinical-trial","attrs":{"text":"NCT04029272","term_id":"NCT04029272"}}NCT04029272     

Anticancer drug synergy prediction in understudied tissues using transfer learning

ObjectiveDrug combination screening has advantages in identifying cancer treatment options with higher efficacy without degradation in terms of safety. A key challenge is that the accumulated number of observations in in-vitro drug responses varies greatly among different cancer types, where some tissues are more understudied than the others. Thus, we aim to develop a drug synergy prediction model for understudied tissues as a way of overcoming data scarcity problems.Materials and MethodsWe collected a comprehensive set of genetic, molecular, phenotypic features for cancer cell lines. We developed a drug synergy prediction model based on multitask deep neural networks to integrate multimodal input and multiple output. We also utilized transfer learning from data-rich tissues to data-poor tissues.ResultsWe showed improved accuracy in predicting synergy in both data-rich tissues and understudied tissues. In data-rich tissue, the prediction model accuracy was 0.9577 AUROC for binarized classification task and 174.3 mean squared error for regression task. We observed that an adequate transfer learning strategy significantly increases accuracy in the understudied tissues.ConclusionsOur synergy prediction model can be used to rank synergistic drug combinations in understudied tissues and thus help to prioritize future in-vitro experiments. Code is available at https://github.com/yejinjkim/synergy-transfer.     

Celecoxib as an adjuvant to chemotherapy for patients with metastatic colorectal cancer: A randomized controlled clinical study

Objectives:To investigate the anti-tumor activity and tolerability of celecoxib as an adjuvant therapy for patients with metastatic colorectal cancer (CRC).Methods:In this randomized controlled study, 54 patients with metastatic CRC were randomized into 2 groups; the control group (n=28) which received 6 cycles of folinic acid, fluorouracil and irinotecan (FOLFIRI) regimen (5-flourouracil, leucovorin, irinotecan), and the celecoxib group (n=26) which received 6 cycles of FOLFIRI regimen plus celecoxib 200 mg twice daily. The study duration was 3 months. Patients were assessed at baseline and at the end of intervention through the Response Evaluation Criteria in Solid Tumors objective response rate (ORR) and through evaluating the serum concentrations of vascular endothelial growth factor (VEGF), soluble factor-related apoptosis (sFAS), sFAS ligand (sFASL), and epithelial neutrophil-activating peptide -78 (ENA-78/CXCL5). Common Terminology Criteria for Adverse Events version 6.0 was used for evaluating drug-related toxicity.Results:After intervention, celecoxib/FOLFIRI arm showed significant elevation in ORR as compared to FOLFIRI arm (p=0.001). As compared to FOLFIRI arm, celecoxib/FOLFIRI arm showed significantly lower VEGF (p<0.001), CXCL5 (p<0.001), and sFASL (p<0.001) serum levels and significantly higher sFAS serum level and sFAS/FASL ratio (p<0.001). Furthermore, celecoxib/FOLFIRI arm showed significantly higher progression-free survival and one-year overall survival when compared to FOLFIRI arm.Conclusion:Celecoxib plus chemotherapy may represent an effective and safe synergetic protocol for patients with metastatic CRC. Clinicaltrial.gov ID:{"type":"clinical-trial","attrs":{"text":"NCT03645187","term_id":"NCT03645187"}}NCT03645187     

ACE: the Advanced Cohort Engine for searching longitudinal patient records

ObjectiveTo propose a paradigm for a scalable time-aware clinical data search, and to describe the design, implementation and use of a search engine realizing this paradigm.Materials and MethodsThe Advanced Cohort Engine (ACE) uses a temporal query language and in-memory datastore of patient objects to provide a fast, scalable, and expressive time-aware search. ACE accepts data in the Observational Medicine Outcomes Partnership Common Data Model, and is configurable to balance performance with compute cost. ACE’s temporal query language supports automatic query expansion using clinical knowledge graphs. The ACE API can be used with R, Python, Java, HTTP, and a Web UI.ResultsACE offers an expressive query language for complex temporal search across many clinical data types with multiple output options. ACE enables electronic phenotyping and cohort-building with subsecond response times in searching the data of millions of patients for a variety of use cases.DiscussionACE enables fast, time-aware search using a patient object-centric datastore, thereby overcoming many technical and design shortcomings of relational algebra-based querying. Integrating electronic phenotype development with cohort-building enables a variety of high-value uses for a learning health system. Tradeoffs include the need to learn a new query language and the technical setup burden.ConclusionACE is a tool that combines a unique query language for time-aware search of longitudinal patient records with a patient object datastore for rapid electronic phenotyping, cohort extraction, and exploratory data analyses.     

Clinical risk score for postoperative pneumonia following heart valve surgery

Background:Postoperative pneumonia (POP) is one of the most common infections following heart valve surgery (HVS) and is associated with a significant increase in morbidity, mortality, and health care costs. This study aimed to identify the major risk factors associated with the occurrence of POP following HVS and to derive and validate a clinical risk score.Methods:Adults undergoing open HVS between January 2016 and December 2019 at a single institution were enrolled in this study. Patients were randomly assigned to the derivation and validation sets at 1:1 ratio. A prediction model was developed with multivariable logistic regression analysis in the derivation set. Points were assigned to independent risk factors based on their regression coefficients.Results:POP occurred in 316 of the 3853 patients (8.2%). Multivariable analysis identified ten significant predictors for POP in the derivation set, including older age, smoking history, chronic obstructive pulmonary disease, diabetes mellitus, renal insufficiency, poor cardiac function, heart surgery history, longer cardiopulmonary bypass, blood transfusion, and concomitant coronary and/or aortic surgery. A 22-point risk score based on the multivariable model was then generated, demonstrating good discrimination (C-statistic: 0.81), and calibration (Hosmer-Lemeshow χ² = 8.234, P = 0.312). The prediction rule also showed adequate discriminative power (C-statistic: 0.83) and calibration (Hosmer-Lemeshow χ² = 5.606, P = 0.691) in the validation set. Three risk intervals were defined as low-, medium-, and high-risk groups.Conclusion:We derived and validated a 22-point risk score for POP following HVS, which may be useful in preventive interventions and risk management.Trial Registration:Chictr.org, ChiCTR1900028127; http://www.chictr.org.cn/showproj.aspx?proj=46932     

A simple and easily implemented risk model to predict 1-year ischemic stroke and systemic embolism in Chinese patients with atrial fibrillation

Background:Accurate prediction of ischemic stroke is required for deciding anticoagulation use in patients with atrial fibrillation (AF). Even though only 6% to 8% of AF patients die from stroke, about 90% are indicated for anticoagulants according to the current AF management guidelines. Therefore, we aimed to develop an accurate and easy-to-use new risk model for 1-year thromboembolic events (TEs) in Chinese AF patients.Methods:From the prospective China Atrial Fibrillation Registry cohort study, we identified 6601 AF patients who were not treated with anticoagulation or ablation at baseline. We selected the most important variables by the extreme gradient boosting (XGBoost) algorithm and developed a simplified risk model for predicting 1-year TEs. The novel risk score was internally validated using bootstrapping with 1000 replicates and compared with the CHA₂DS₂-VA score (excluding female sex from the CHA₂DS₂-VASc score).Results:Up to the follow-up of 1 year, 163 TEs (ischemic stroke or systemic embolism) occurred. Using the XGBoost algorithm, we selected the three most important variables (congestive heart failure or left ventricular dysfunction, age, and prior stroke, abbreviated as CAS model) to predict 1-year TE risk. We trained a multivariate Cox regression model and assigned point scores proportional to model coefficients. The CAS scheme classified 30.8% (2033/6601) of the patients as low risk for TE (CAS score = 0), with a corresponding 1-year TE risk of 0.81% (95% confidence interval [CI]: 0.41%–1.19%). In our cohort, the C-statistic of CAS model was 0.69 (95% CI: 0.65–0.73), higher than that of CHA₂DS₂-VA score (0.66, 95% CI: 0.62–0.70, Z = 2.01, P = 0.045). The overall net reclassification improvement from CHA₂DS₂-VA categories (low = 0/high ≥1) to CAS categories (low = 0/high ≥1) was 12.2% (95% CI: 8.7%–15.7%).Conclusion:In Chinese AF patients, a novel and simple CAS risk model better predicted 1-year TEs than the widely-used CHA₂DS₂-VA risk score and identified a large proportion of patients with low risk of TEs, which could potentially improve anticoagulation decision-making.Trial Registration:www.chictr.org.cn (Unique identifier No. ChiCTR-OCH-13003729).     

Clinical concept extraction using transformers

ObjectiveThe goal of this study is to explore transformer-based models (eg, Bidirectional Encoder Representations from Transformers [BERT]) for clinical concept extraction and develop an open-source package with pretrained clinical models to facilitate concept extraction and other downstream natural language processing (NLP) tasks in the medical domain.MethodsWe systematically explored 4 widely used transformer-based architectures, including BERT, RoBERTa, ALBERT, and ELECTRA, for extracting various types of clinical concepts using 3 public datasets from the 2010 and 2012 i2b2 challenges and the 2018 n2c2 challenge. We examined general transformer models pretrained using general English corpora as well as clinical transformer models pretrained using a clinical corpus and compared them with a long short-term memory conditional random fields (LSTM-CRFs) mode as a baseline. Furthermore, we integrated the 4 clinical transformer-based models into an open-source package.Results and ConclusionThe RoBERTa-MIMIC model achieved state-of-the-art performance on 3 public clinical concept extraction datasets with F1-scores of 0.8994, 0.8053, and 0.8907, respectively. Compared to the baseline LSTM-CRFs model, RoBERTa-MIMIC remarkably improved the F1-score by approximately 4% and 6% on the 2010 and 2012 i2b2 datasets. This study demonstrated the efficiency of transformer-based models for clinical concept extraction. Our methods and systems can be applied to other clinical tasks. The clinical transformer package with 4 pretrained clinical models is publicly available at https://github.com/uf-hobi-informatics-lab/ClinicalTransformerNER. We believe this package will improve current practice on clinical concept extraction and other tasks in the medical domain.     

A Code of Professional Ethical Conduct for the American Medical Informatics Association: An AMIA Board of Directors Approved White Paper

The AMIA Board of Directors has decided to periodically publish AMIA’s Code of Professional Ethical Conduct for its members in the Journal of the American Medical Informatics Association. The Code also will be available on the AMIA Web site at www.amia.org as it continues to evolve in response to feedback from the AMIA membership. The AMIA Board acknowledges the continuing work and dedication of the AMIA Ethics Committee. AMIA is the copyright holder of this work.     

Immunogenicity and safety of a recombinant fusion protein vaccine (V-01) against coronavirus disease 2019 in healthy adults: a randomized,double-blind,placebo-controlled,phase II trial

Background:Innovative coronavirus disease 2019 (COVID-19) vaccines, with elevated global manufacturing capacity, enhanced safety and efficacy, simplified dosing regimens, and distribution that is less cold chain-dependent, are still global imperatives for tackling the ongoing pandemic. A previous phase I trial indicated that the recombinant COVID-19 vaccine (V-01), which contains a fusion protein (IFN-PADRE-RBD-Fc dimer) as its antigen, is safe and well tolerated, capable of inducing rapid and robust immune responses, and warranted further testing in additional clinical trials. Herein, we aimed to assess the immunogenicity and safety of V-01, providing rationales of appropriate dose regimen for further efficacy study.Methods:A randomized, double-blind, placebo-controlled phase II clinical trial was initiated at the Gaozhou Municipal Centre for Disease Control and Prevention (Guangdong, China) in March 2021. Both younger (n = 440; 18–59 years of age) and older (n = 440; ≥60 years of age) adult participants in this trial were sequentially recruited into two distinct groups: two-dose regimen group in which participants were randomized either to follow a 10 or 25 μg of V-01 or placebo given intramuscularly 21 days apart (allocation ratio, 3:3:1, n = 120, 120, 40 for each regimen, respectively), or one-dose regimen groups in which participants were randomized either to receive a single injection of 50 μg of V-01 or placebo (allocation ratio, 3:1, n = 120, 40, respectively). The primary immunogenicity endpoints were the geometric mean titers of neutralizing antibodies against live severe acute respiratory syndrome coronavirus 2, and specific binding antibodies to the receptor binding domain (RBD). The primary safety endpoint evaluation was the frequencies and percentages of overall adverse events (AEs) within 30 days after full immunization.Results:V-01 provoked substantial immune responses in the two-dose group, achieving encouragingly high titers of neutralizing antibody and anti-RBD immunoglobulin, which peaked at day 35 (161.9 [95% confidence interval [CI]: 133.3–196.7] and 149.3 [95%CI: 123.9–179.9] in 10 and 25 μg V-01 group of younger adults, respectively; 111.6 [95%CI: 89.6–139.1] and 111.1 [95%CI: 89.2–138.4] in 10 and 25 μg V-01 group of older adults, respectively), and remained high at day 49 after a day-21 second dose; these levels significantly exceed those in convalescent serum from symptomatic COVID-19 patients (53.6, 95%CI: 31.3–91.7). Our preliminary data show that V-01 is safe and well tolerated, with reactogenicity predominantly being absent or mild in severity and only one vaccine-related grade 3 or worse AE being observed within 30 days. The older adult participants demonstrated a more favorable safety profile compared with those in the younger adult group: with AEs percentages of 19.2%, 25.8%, 17.5% in older adults vs. 34.2%, 23.3%, 26.7% in younger adults at the 10, 25 μg V-01 two-dose group, and 50 μg V-01 one-dose group, respectively.Conclusions:The vaccine candidate V-01 appears to be safe and immunogenic. The preliminary findings support the advancement of the two-dose, 10 μg V-01 regimen to a phase III trial for a large-scale population-based evaluation of safety and efficacy.Trial Registration:http://www.chictr.org.cn/index.aspx (No. ChiCTR2100045107, http://www.chictr.org.cn/showproj.aspx?proj=124702).