Achieving high inter-rater reliability in establishing data labels: a retrospective chart review study

BACKGROUND

In medical research, the effectiveness of machine learning algorithms depends heavily on the accuracy of labeled data. This study aimed to assess inter-rater reliability (IRR) in a retrospective electronic medical chart review to create high quality labeled data on comorbidities and adverse events (AEs).

METHODS

Six registered nurses with diverse clinical backgrounds reviewed patient charts, extracted data on 20 predefined comorbidities and 18 AEs. All reviewers underwent four iterative rounds of training aimed to enhance accuracy and foster consensus. Periodic monitoring was conducted at the beginning, middle, and end of the testing phase to ensure data quality. Weighted Kappa coefficients were calculated with their associated 95% confidence intervals (CIs).

RESULTS

Seventy patient charts were reviewed. The overall agreement, measured by Conger's Kappa, was 0.80 (95% CI: 0.78-0.82). IRR scores remained consistently high (ranging from 0.70 to 0.87) throughout each phase.

CONCLUSION

Our study suggests the detailed manual for chart review and structured training regimen resulted in a consistently high level of agreement among our reviewers during the chart review process. This establishes a robust foundation for generating high-quality labeled data, thereby enhancing the potential for developing accurate machine learning algorithms.

Effect of health rights accessibility on the urban integration of minority rural migrants in China: a cross-sectional study

BACKGROUND

Accessing health rights is an integral component of people's aspirations for a better life. Existing discussions and evaluations regarding the accessibility of health rights for minority rural migrants are insufficient. In comparison to objective health conditions, inequalities in health rights lead to chronic and long-term depletion of human capital among minority rural migrants. This study aimed to assess the overall impact, heterogeneity effects, and mechanisms of health rights accessibility on the urban integration of minority rural migrants.

METHODS

Based on the 2017 China Migrants Dynamic Survey Data (CMDS), this study employs OLS models, 2SLS models, conditional mixed process (CMP) methods, and omitted variable tests to estimate the impact of health rights accessibility on the urban integration of minority rural migrants. Additionally, from the perspectives of migration scope and illness experience, this study explored the heterogeneity in the relationship between health rights accessibility and urban integration. Finally, using the Karlson-Holm-Breen (KHB) model, this study dissects the mechanisms through which health rights accessibility influences the urban integration of minority rural migrants.

RESULTS

Health rights accessibility significantly enhances the urban integration of minority rural migrants. Moreover, compared to minority rural migrants who move across provinces and who have no history of illness, those who migrate within the same province and who have experienced illness are more sensitive to the positive impact of health rights accessibility. However, the enhancing effect of health rights accessibility does not significantly differ between the new and old generations of minority rural migrants. Furthermore, health rights accessibility can indirectly improve the urban integration of minority rural migrants by elevating health levels, improving health habits, and reinforcing health behaviors. Among these, the indirect effects mediated by health habits are more pronounced.

CONCLUSION

The research conclusions underscore the issue of health accessibility and urban integration among minority rural migrants, providing a reexamination and clarification of the policy effects of health rights in promoting the urban integration of minority rural migrants. Relevant policy design should commence with improving the health rights of minority rural migrants, enhancing their health integration capabilities, and effectively boosting their ability to integrate into urban life.

How does choice of residential community affect the social integration of rural migrants: insights from China

The construction of public space is a new and important way to integrate rural migrants into urban society. Existing studies mainly discussed the factors affecting the social integration of rural migrants from the micro-individual and macro-system levels. Still, they seldom analyzed the differences between rural migrants' residential communities and the roles these differences play in their social integration, especially from the perspective of residential space. Based on the data of the 2014 China Migrants Dynamic Monitoring Survey, this paper systematically examines the impact of residential community selection on the social integration of rural migrants and its possible effects using OLS, 2SLS, CMP, omitted variable test method, and KHB mediating effect model. It is found that the choice of residential community has a significant positive impact on the social integration of rural migrants, and the social integration of rural migrants living in formal communities has increased by 2.44%-3.20%. To overcome the potential endogeneity problems and selection bias of the empirical model, the study further adopted an instrumental variable estimation approach, combined with the omitted variable method for robustness check; the results still revealed the positive effect of living in formal communities on the social integration of rural migrants. The heterogeneous results showed that living in formal communities has a greater effect on the social integration of women and older-generation rural migrants. The farther the migration range and the longer the residence time of rural migrants, the greater the effect of living in the formal community on their social integration. Further mechanism testing revealed that living in formal communities not only directly enhances the social integration of rural migrants but also indirectly improves their social integration through public resource allocation, human capital accumulation, social status screening, and social network expansion. The indirect effect of capital accumulation is even greater. Therefore, to accelerate the full integration of rural migrants into urban society and achieve real urbanization and citizenship, the study proposes that the government should scientifically plan the layout of rural migrants' living space and the construction of supporting facilities.

[Analysis of ultrasound images features and diagnostic model establishment of alveolar soft part sarcoma and intramuscular capillary-type hemangiomas]

Objective: The ultrasonography features of alveolar soft part sarcoma (ASPS) and intramuscular capillary-type hemangiomas (ICTH) were analyzed, and the diagnostic model of ASPS was established. Methods: A cross-sectional study was carried out. The clinical data of 52 patients [28 males and 24 females, aged (20.7±15.1) years] with pathologically confirmed ASPS and ICTH admitted to People's Hospital of Henan Province from January 2005 to February 2023 were included in the study. According to pathological types, the patients were divided into ASPS group and ICTH group. Clinical data of patients were retrospectively collected, and meaningful indicators in the univariate analysis were included in the regression analysis for screening. After comprehensive consideration of clinical significance and statistical significance, eligible indicators were selected for inclusion in the regression analysis. Binary logistic regression analysis was used to screen the factors that distinguished the pathological types of ASPS and ICTH, and the diagnostic model was established. The area under receiver operating characteristic (ROC) curve (AUC) was used to evaluate the diagnostic effectiveness of the diagnostic model in distinguishing ASPS from ICTH. Results: There were 20 patients in ASPS group, 10 males and 10 females, aged (26.9±13.5) years, and 32 patients in ICTH group, 18 males and 14 females, aged (16.8±15.0) years. The age difference between the ASPS group and the ICTH group was statistically significant (P<0.05), and there were statistically significant differences in the ultrasound imaging features of "clear boundary" "peripheral lobe" "thin blood vessels inside the lesion are straight and out of shape" "intra-lesion liquification" "peripheral thick blood vessels" and "peripheral muscle fiber disruption" between the two groups (all P<0.001).Variables with clinical and statistical significance were selected as independent variables. Binary logistic regression analysis showed that peripheral muscle fiber interruption (OR=97.358, 95%CI:6.833-1 387.249) and internal thin blood vessels were flat and out of shape (OR=0.052, 95%CI:0.003-0.921) was the correlation factor to distinguish the pathological types of ASPS and ICTH. Two ultrasonic image features of "peripheral muscle fiber interruption" and "internal thin blood vessels are straight and out of shape" were used to establish the diagnostic model. The sensitivity of "peripheral muscle fiber interruption" diagnostic model was 81.3%, and the specificity was 95.0%. The AUC was 0.811(95%CI: 0.761-0.954). The sensitivity, specificity and AUC of the diagnosis model of "internal thin vessels with flat misshape" were 90.0%, 96.9% and 0.934(95%CI: 0.830-0.984). The sensitivity, specificity and AUC of the combined diagnosis model of "peripheral muscle fiber interruption" and "internal thin blood vessel straight out of shape" were 96.9%, 90.0% and 0.974(95%CI:0.877-0.999). Conclusion: Ultrasonography can be used to distinguish ASPS from ICTH, and the combined diagnostic model based on the two ultrasonic imaging features of "peripheral muscle fiber interruption" and "internal thin blood vessel straight out of shape" can further improve the diagnostic efficiency.

High-throughput virtual screening to identify potential small molecule inhibitors of the Zα domain of the adenosine deaminases acting on RNA 1(ADAR1)

Changes in RNA editing are closely associated with diseases such as cancer, viral infections, and autoimmune disorders. Adenosine deaminase (ADAR1), which acts on RNA 1, plays a key role in adenosine to inosine editing and is a potential therapeutic target for these various diseases. The p150 subtype of ADAR1 is the only one that contains a Zα domain that binds to both Z-DNA and Z-RNA. The Zα domain modulates immune responses and may be suitable targets for antiviral therapy and cancer immunotherapy. In this study, we attempted to utilize molecular docking to identify potential inhibitors that bind to the ADAR1 Zα domain. The virtual docking method screened the potential activity of more than 100,000 compounds on the Zα domain of ADAR1 and filtered to obtain the highest scoring results.We identified 71 compounds promising to bind to ADAR1 and confirmed that two of them, lithospermic acid and Regaloside B, interacts with the ADAR1 Zα domain by surface plasmonic resonance technique. The molecular dynamics calculation of the complex of lithospermic acid and ADAR1 also showed that the binding effect of lithospermic acid to ADAR1 was stable.This study provides a new perspective for the search of ADAR1 inhibitors, and further studies on the anti-ADAR11 activity of these compounds have broad prospects.

Quantitative CT features on admission combined with laboratory biomarkers for predicting severe acute pancreatitis

AIM

To assess the association of quantitative computed tomography (CT) features on admission with acute pancreatitis (AP) severity, and to explore the performance of combined CT and laboratory markers for predicting severe AP (SAP).

MATERIALS AND METHODS

Data from 208 AP patients were reviewed retrospectively. Pancreas volume, the area of extrapancreatic inflammation, extrapancreatic fluid collection volume, and number were calculated based on CT images on admission. Laboratory biomarkers within 24 h of admission were collected. Interobserver agreement for CT measurements was measured by calculating interclass correlation coefficient (ICC). The associations of quantitative CT features with AP severity were evaluated. Predictive models for SAP were constructed based on CT and laboratory markers. Performances of single marker and the models were evaluated using receiver operating characteristic (ROC) curve and area under the ROC curve (AUC).

RESULTS

Pancreas volume, area of extrapancreatic inflammation, extrapancreatic fluid collection volume, and number were significantly different between severe and non-severe AP groups. In predicting SAP, the AUCs of quantitative CT indicators ranged from 0.72 to 0.79; the AUCs of laboratory biomarkers were between 0.53 and 0.66. The combined model of area of extrapancreatic inflammation, serum calcium, and haematocrit yielded an AUC of 0.84, significantly higher than that of the laboratory model, single CT, or laboratory marker. Interobserver agreements for quantitative CT indicators were excellent, with ICC ranging from 0.91 to 0.98.

CONCLUSION

Quantitative CT features on admission were significantly associated with AP severity; the combination of extrapancreatic inflammation area, serum calcium, and haematocrit could be taken as a new method for predicting SAP.

BERT-Based Neural Network for Inpatient Fall Detection From Electronic Medical Records: Retrospective Cohort Study

BACKGROUND

Inpatient falls are a substantial concern for health care providers and are associated with negative outcomes for patients. Automated detection of falls using machine learning (ML) algorithms may aid in improving patient safety and reducing the occurrence of falls.

OBJECTIVE

This study aims to develop and evaluate an ML algorithm for inpatient fall detection using multidisciplinary progress record notes and a pretrained Bidirectional Encoder Representation from Transformers (BERT) language model.

METHODS

A cohort of 4323 adult patients admitted to 3 acute care hospitals in Calgary, Alberta, Canada from 2016 to 2021 were randomly sampled. Trained reviewers determined falls from patient charts, which were linked to electronic medical records and administrative data. The BERT-based language model was pretrained on clinical notes, and a fall detection algorithm was developed based on a neural network binary classification architecture.

RESULTS

To address various use scenarios, we developed 3 different Alberta hospital notes-specific BERT models: a high sensitivity model (sensitivity 97.7, IQR 87.7-99.9), a high positive predictive value model (positive predictive value 85.7, IQR 57.2-98.2), and the high F1-score model (F1=64.4). Our proposed method outperformed 3 classical ML algorithms and an International Classification of Diseases code-based algorithm for fall detection, showing its potential for improved performance in diverse clinical settings.

CONCLUSIONS

The developed algorithm provides an automated and accurate method for inpatient fall detection using multidisciplinary progress record notes and a pretrained BERT language model. This method could be implemented in clinical practice to improve patient safety and reduce the occurrence of falls in hospitals.

Diamond-Like Carbon: A Surface for Extreme, High-Wear Environments

In this study, we present an in-depth characterization of a diamond-like carbon (DLC) film, using a range of techniques to understand the structure and chemistry of the film both in the interior and particularly at the DLC/air surface and DLC/liquid interface. The DLC film is found to be a combination of sp2 and sp3 carbon, with significant oxygen present at the surface. The oxygen seems to be present as OH groups, making the DLC somewhat hydrophilic. Quartz-Crystal Microbalance (QCM) isotherms and complementary neutron reflectivity data indicate significant adsorption of a model additive, bis(2-ethylhexyl) sulfosuccinate sodium salt (AOT) surfactant, onto the DLC from water solutions and indicate the adsorbed film is a bilayer. This initial study of the structure and composition of a model surfactant is intended to give a clearer insight into how DLC and additives function as antiwear systems.

Beyond Vision: A View from Eye to Alzheimer's Disease and Dementia

With the aging of the global population, the health care burden of Alzheimer's disease (AD) and dementia is considered to increase dramatically in the coming decades. Given the insufficiency of effective interventions for AD and dementia, clinical research on identifying potentially modifiable risk factors and early diagnostic biomarkers becomes a public health priority. Currently, extracerebral manifestations with a large proportion of ocular involvement are usually recognized to precede the symptoms of AD and dementia. Growing epidemiologic evidence also suggests that eye disorders, such as cataracts, age-related macular degeneration, glaucoma, diabetic retinopathy, and so on, are closely associated with and even have a higher incidence of AD and dementia. The eye, as an extension of the central nervous system, therefore has the potential to provide a feasible approach to detecting structural and functional abnormalities of the brain. Numerous new imaging modalities are developed and give novel insights into the detection of several neurodegenerative, vascular, neuropathological, and other ocular abnormalities of AD and dementia in scientific research and clinical application. This review provides an overview of the epidemiologic associations between eye disorders and AD or dementia and summarizes the recent advances in ocular examinations and techniques employed for the detection of AD and dementia. With more brain-and-eye interconnections being identified, the eye is becoming a noninvasive and easily accessible window for the early diagnosis and prevention of AD and dementia.

Factors influencing the detection rate of fumarate peak in 1H MR spectroscopy of fumarate hydratase-deficient renal cell carcinoma at 3 T MRI

AIM

To identify factors that may be associated with fumarate detection rate in 1H-magnetic resonance spectroscopy (MRS) in fumarate hydratase-deficient renal cell carcinoma (FH-RCC).

MATERIALS AND MEHODS

Between February 2018 and March 2022, 16 FH-RCC patients with 30 lesions underwent 1H-MRS. Detection results were classified as having a detected fumarate peak (n=12), undetected peak (n=10), or technical failure (n=8). Factors including tumour size, tumour location, treatment history, and metastasis status were collected and analysed. A Bayesian logistic regression model was applied to evaluate the association between these factors and the detection result.

RESULTS

Bayesian analysis demonstrated significant associations between fumarate detection results and the following factors: long-axis diameter (odds ratio [OR] of 1.64; 95% confidence interval [CI] of 1.07-2.53), short-axis diameter (OR of 1.90; 95% CI of 1.19-3.06), voxel size (OR of 2.85; 95% CI of 1.70-4.75), treatment history (OR of 0.35; 95% CI of 0.21-0.58), non-metastatic state (OR of 2.45; 95% CI of 1.48-4.06), and lymph node metastasis (OR of 0.35; 95% CI of 0.21-0.58). Technical failure results were associated with factors such as treatment history (OR of 2.59; 95% CI of 1.37-4.66), non-metastatic state (OR of 0.36; 95% CI of 0.19-0.66), and lymph node metastasis (OR of 2.61; 95% CI of 1.39-4.74).

CONCLUSION

Tumour size, treatment history, and metastasis character were associated with the detection of abnormal fumarate accumulation. This finding will serve as a reference for interpreting 1H-MRS results and for selecting suitable scenarios to evaluate FH-RCC.

Clonal hematopoiesis related TET2 loss-of-function impedes IL1β-mediated epigenetic reprogramming in hematopoietic stem and progenitor cells

Clonal hematopoiesis (CH) is defined as a single hematopoietic stem/progenitor cell (HSPC) gaining selective advantage over a broader range of HSPCs. When linked to somatic mutations in myeloid malignancy-associated genes, such as TET2-mediated clonal hematopoiesis of indeterminate potential or CHIP, it represents increased risk for hematological malignancies and cardiovascular disease. IL1β is elevated in patients with CHIP, however, its effect is not well understood. Here we show that IL1β promotes expansion of pro-inflammatory monocytes/macrophages, coinciding with a failure in the demethylation of lymphoid and erythroid lineage associated enhancers and transcription factor binding sites, in a mouse model of CHIP with hematopoietic-cell-specific deletion of Tet2. DNA-methylation is significantly lost in wild type HSPCs upon IL1β administration, which is resisted by Tet2-deficient HSPCs, and thus IL1β enhances the self-renewing ability of Tet2-deficient HSPCs by upregulating genes associated with self-renewal and by resisting demethylation of transcription factor binding sites related to terminal differentiation. Using aged mouse models and human progenitors, we demonstrate that targeting IL1 signaling could represent an early intervention strategy in preleukemic disorders. In summary, our results show that Tet2 is an important mediator of an IL1β-promoted epigenetic program to maintain the fine balance between self-renewal and lineage differentiation during hematopoiesis.

Roxadustat protects rat renal tubular epithelial cells from hypoxia-induced injury through the TGF-β1/Smad3 signaling pathway

OBJECTIVE

Roxadustat is used to treat renal anemia. The renoprotective effect of roxadustat needs to be further confirmed, and the mechanism of action is unknown. This study aims to evaluate the effect and mechanism of roxadustat in hypoxia-related nephropathy with the renal tubular epithelial cell line NRK-52E.

MATERIALS AND METHODS

The cell Counting Kit-8 (CCK-8) assay was employed to assess cellular proliferation in the current investigation. Flow cytometry was used to conduct cell apoptosis analysis. The utilization of electron microscopy facilitated the identification of changes in cellular ultrastructure. Immunofluorescence was used to detect the expression trend of hypoxia-inducible factor-1α (HIF-1α). The connective tissue growth factor (CTGF), transforming growth factor-β1 (TGF-β1), Smad family member 3 (Smad3), p-Smad3, α-smooth muscle actin (α-SMA), collagen I, and HIF-1α were assessed by western blotting. Real-time fluorescent quantitative PCR (RT-qPCR) was used to measure TGF-β1 and Smad3 mRNA.

RESULTS

Significant growth inhibition and increased apoptosis were observed in NRK-52E cells cultured under hypoxic conditions (1% and 5% O2), which can be rescued by roxadustat. From a morphological perspective, it has been observed that roxadustat can counteract cellular damage features produced by hypoxia. These features include the contraction of the nuclear envelope and an increase in the formation of apoptotic bodies. Roxadustat increases HIF-1α expression acutely at 24 h, followed by a gradual reduction of HIF-1α expression to levels significantly below that of the hypoxia group by 72 h. Roxadustat can also inhibit hypoxia-induced increased expression of CTGF, TGF-β1, p-Smad3, α-SMA, collagen I, and HIF-1α. Combined treatment with roxadustat and siRNA against TGF-β1 synergistically reduced the expression of CTGF and HIF-1α, while the effect on TGF-β1 and p-Smad3 were comparable to that of the individual treatment alone. Comparably, the combined administration of roxadustat and siRNA targeting Smad3 had a synergistic impact on diminishing the expression of CTGF.

CONCLUSIONS

These findings indicate that roxadustat attenuates experimental renal fibrosis likely by inhibiting the TGF-β1/Smad3 pathways, while its effect on CTGF and HIF-1α may involve other signaling pathways.

Development of machine learning models for the detection of surgical site infections following total hip and knee arthroplasty: a multicenter cohort study

BACKGROUND

Population based surveillance of surgical site infections (SSIs) requires precise case-finding strategies. We sought to develop and validate machine learning models to automate the process of complex (deep incisional/organ space) SSIs case detection.

METHODS

This retrospective cohort study included adult patients (age ≥ 18 years) admitted to Calgary, Canada acute care hospitals who underwent primary total elective hip (THA) or knee (TKA) arthroplasty between Jan 1st, 2013 and Aug 31st, 2020. True SSI conditions were judged by the Alberta Health Services Infection Prevention and Control (IPC) program staff. Using the IPC cases as labels, we developed and validated nine XGBoost models to identify deep incisional SSIs, organ space SSIs and complex SSIs using administrative data, electronic medical records (EMR) free text data, and both. The performance of machine learning models was assessed by sensitivity, specificity, positive predictive value, negative predictive value, F1 score, the area under the receiver operating characteristic curve (ROC AUC) and the area under the precision-recall curve (PR AUC). In addition, a bootstrap 95% confidence interval (95% CI) was calculated.

RESULTS

There were 22,059 unique patients with 27,360 hospital admissions resulting in 88,351 days of hospital stay. This included 16,561 (60.5%) TKA and 10,799 (39.5%) THA procedures. There were 235 ascertained SSIs. Of them, 77 (32.8%) were superficial incisional SSIs, 57 (24.3%) were deep incisional SSIs, and 101 (42.9%) were organ space SSIs. The incidence rates were 0.37 for superficial incisional SSIs, 0.21 for deep incisional SSIs, 0.37 for organ space and 0.58 for complex SSIs per 100 surgical procedures, respectively. The optimal XGBoost models using administrative data and text data combined achieved a ROC AUC of 0.906 (95% CI 0.835-0.978), PR AUC of 0.637 (95% CI 0.528-0.746), and F1 score of 0.79 (0.67-0.90).

CONCLUSIONS

Our findings suggest machine learning models derived from administrative data and EMR text data achieved high performance and can be used to automate the detection of complex SSIs.

Towards texture accurate slice interpolation of medical images using PixelMiner

Quantitative image analysis models are used for medical imaging tasks such as registration, classification, object detection, and segmentation. For these models to be capable of making accurate predictions, they need valid and precise information. We propose PixelMiner, a convolution-based deep-learning model for interpolating computed tomography (CT) imaging slices. PixelMiner was designed to produce texture-accurate slice interpolations by trading off pixel accuracy for texture accuracy. PixelMiner was trained on a dataset of 7829 CT scans and validated using an external dataset. We demonstrated the model's effectiveness by using the structural similarity index (SSIM), peak signal to noise ratio (PSNR), and the root mean squared error (RMSE) of extracted texture features. Additionally, we developed and used a new metric, the mean squared mapped feature error (MSMFE). The performance of PixelMiner was compared to four other interpolation methods: (tri-)linear, (tri-)cubic, windowed sinc (WS), and nearest neighbor (NN). PixelMiner produced texture with a significantly lowest average texture error compared to all other methods with a normalized root mean squared error (NRMSE) of 0.11 (p < .01), and the significantly highest reproducibility with a concordance correlation coefficient (CCC) ≥ 0.85 (p < .01). PixelMiner was not only shown to better preserve features but was also validated using an ablation study by removing auto-regression from the model and was shown to improve segmentations on interpolated slices.

A longitudinal seroepidemiology study to evaluate antibody response to SARS-CoV-2 virus infection and vaccination in children in Calgary, Canada from July 2020 to April 2022: Alberta COVID-19 Childhood Cohort (AB3C) Study

BACKGROUND

Measurement of SARS-CoV-2 antibody seropositivity is important to accurately understand exposure to infection and/or vaccination in specific populations. This study aimed to estimate the serologic response to SARS-CoV-2 virus infection and vaccination in children in Calgary, Alberta over a two-year period.

METHODS

Children with or without prior SARS-CoV-2 infections, were enrolled in Calgary, Canada in 2020. Venous blood was sampled 4 times from July 2020 to April 2022 for SARS-CoV-2 nucleocapsid and spike antibodies. Demographic and clinical information was obtained including SARS-CoV-2 testing results and vaccination records.

RESULTS

1035 children were enrolled and 88.9% completed all 4 visits; median age 9 years (IQR: 5,13); 519 (50.1%) female; and 815 (78.7%) Caucasian. Before enrolment, 118 (11.4%) had confirmed or probable SARS-CoV-2. By April 2022, 39.5% of previously uninfected participants had a SARS-CoV-2 infection. Nucleocapsid antibody seropositivity declined to 16.4% of all infected children after more than 200 days post diagnosis. Spike antibodies remained elevated in 93.6% of unvaccinated infected children after more than 200 days post diagnosis. By April 2022, 408 (95.6%) children 12 years and older had received 2 or more vaccine doses, and 241 (61.6%) 5 to 11 year-old children had received 2 vaccine doses. At that time, all 685 vaccinated children had spike antibodies, compared with 94/176 (53.4%) of unvaccinated children.

CONCLUSIONS

In our population, after the first peak of Omicron variant infections and introduction of COVID-19 vaccines for children, all vaccinated children, but just over one-half of unvaccinated children, had SARS-CoV-2 spike antibodies indicating infection and/or vaccination, highlighting the benefit of vaccination. It is not yet known whether a high proportion of seropositivity at the present time predicts sustained population-level protection against future SARS-CoV-2 transmission, infection or severe COVID-19 outcomes in children.

A New Method of Identifying Pathologic Complete Response After Neoadjuvant Chemotherapy for Breast Cancer Patients Using a Population-Based Electronic Medical Record System

BACKGROUND

Accurate identification of pathologic complete response (pCR) from population-based electronic narrative data in a timely and cost-efficient manner is critical. This study aimed to derive and validate a set of natural language processing (NLP)-based machine-learning algorithms to capture pCR from surgical pathology reports of breast cancer patients who underwent neoadjuvant chemotherapy (NAC).

METHODS

This retrospective cohort study included all invasive breast cancer patients who underwent NAC and subsequent curative-intent surgery during their admission at all four tertiary acute care hospitals in Calgary, Alberta, Canada, between 1 January 2010 and 31 December 2017. Surgical pathology reports were extracted and processed with NLP. Decision tree classifiers were constructed and validated against chart review results. Machine-learning algorithms were evaluated with a performance matrix including sensitivity, specificity, positive predictive value (PPV), negative predictive value [NPV], accuracy, area under the receiver operating characteristic curve [AUC], and F1 score.

RESULTS

The study included 351 female patients. Of these patients, 102 (29%) achieved pCR after NAC. The high-sensitivity model achieved a sensitivity of 90.5% (95% confidence interval [CI], 69.6-98.9%), a PPV of 76% (95% CI, 59.6-87.2), an accuracy of 88.6% (95% CI, 78.7-94.9%), an AUC of 0.891 (95% CI, 0.795-0.987), and an F1 score of 82.61. The high-PPV algorithm reached a sensitivity of 85.7% (95% CI, 63.7-97%), a PPV of 81.8% (95% CI, 63.4-92.1%), an accuracy of 90% (95% CI, 80.5-95.9%), an AUC of 0.888 (95% CI, 0.790-0.985), and an F1 score of 83.72. The high-F1 score algorithm obtained a performance equivalent to that of the high-PPV algorithm.

CONCLUSION

The developed algorithms demonstrated excellent accuracy in identifying pCR from surgical pathology reports of breast cancer patients who received NAC treatment.

Identification of novel characteristic biomarkers and immune infiltration profile for the anaplastic thyroid cancer via machine learning algorithms

PURPOSE

Anaplastic thyroid cancer (ATC) is a rare and lethal malignant cancer. In recent years, the application of molecular-driven targeted therapy and immunotherapy has markedly improved the prognosis of ATC. This study aimed to identify characteristic genes for ATC diagnosis and revealed the role of ATC characteristic genes in drug sensitivity and immune cell infiltration.

METHODS

We downloaded ATC RNA-sequencing data from the GEO database. Following the combination and normalization of the dataset, we first divided the combined datasets into the training cohort and the validation cohort. We identified differentially expressed genes (DEGs) in ATC by differential expression analysis in the training cohort. We used two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) to identify ATC characteristic genes. The CIBERSORT algorithm was performed to calculate the abundance of various immune cells in ATC. Finally, we validated the expression of ATC characteristic genes by quantitative RT-PCR (RT-qPCR) in ATC cell lines and immunohistochemistry (IHC).

RESULTS

A total of 425 DEGs were identified in the training cohort, including 240 upregulated genes and 185 downregulated genes. Four ATC characteristic genes (ADM, PXDN, MMP1, and TFF3) were identified, and their diagnostic value was validated in the validation cohort (AUC in ROC analysis > 0.75). We established a practical gene expression-based nomogram to accurately predict the probability of ATC. We also found that ATC characteristic biomarkers are associated with the tumor immune microenvironment and drug sensitivity.

CONCLUSION

ADM, PXDN, MMP1, and TFF3 might serve as potential ATC diagnostic biomarkers and may be helpful for ATC molecular targeted therapy and immunotherapy.

10-Gingerol Enhances the Effect of Taxol in Triple-Negative Breast Cancer via Targeting ADRB2 Signaling

Purpose

Although paclitaxel is widely used in cancer treatment, severe side effects and drug resistance limit its clinical use. 10-gingerol (10-G) is a natural compound isolated from ginger, which displays anti-inflammatory, antioxidant, and antiproliferative properties. However, the chemotherapy-sensitization effect of 10-G on triple-negative breast cancer (TNBC) has not been fully clarified. This study is aimed at investigating the effect of 10-G on the paclitaxel sensitivity in TNBC, and its underlying mechanism.

Methods

The study was determined through in vitro and in vivo experiments. Cell viability and proliferation were detected by cell counting kit 8 (CCK-8) and colony formation. To detect cell apoptosis, flow cytometry and TUNEL were used. The expression of proteins was detected by Western blotting and immunohistochemistry. The molecular docking and gene knockout were corroborated by interactions between 10-G and adrenoceptor Beta 2 (ADRB2). The body weight of mice, histopathology and organs (kidney and spleen) coefficients were used to monitor the drug toxicities.

Results

In vitro, 10-G increased the sensitivity of TNBC cells to paclitaxel, and could synergistically promote the apoptosis of TNBC cells induced by paclitaxel. In combination with molecular docking and lentivirus knockdown studies, ADRB2 was identified as a 10-G binding protein. 10-G inhibited ADRB2 by binding to the active site of ADRB2. Knockdown of ADRB2 reduces the proliferation activity of TNBC cells but also attenuates the sensitizing effects of 10-G to paclitaxel. Western blotting and immunohistochemistry showed that 10-G played an anti-proliferation and chemotherapy-sensitizing role by inhibiting the ADRB2/ERK signal. Toxicity evaluation showed that 10-G would not increase hepatorenal toxicity with paclitaxel.

Conclusion

This data suggests that 10-G may be used as a new chemotherapeutic synergist in combination with paclitaxel to enhance anticancer activity. The potential value of ADRB2 as a target for improving chemotherapy sensitivity was also emphasized.

Disrupted gut microbiota aggravates working memory dysfunction induced by high-altitude exposure in mice

BACKGROUND

The widely accepted microbiome-gut-brain axis (MGBA) hypothesis may be essential for explaining the impact of high-altitude exposure on the human body, especially brain function. However, studies on this topic are limited, and the underlying mechanism remains unclear. Therefore, this study aimed to determine whether high-altitude-induced working memory dysfunction could be exacerbated with gut microbiota disruption.

METHODS AND RESULTS

C57BL/6 mice were randomly divided into three groups: control, high-altitude exposed (HAE), and high-altitude exposed with antibiotic treatment (HAE-A). The HAE and HAE-A groups were exposed to a low-pressure oxygen chamber (60-65 kPa) simulating the altitude of 3,500-4,000 m for 14 days, The air pressure level for the control group was maintained at 94.5 kPa. Antibiotic water (mixed with 0.2 g/L of ciprofloxacin and 1 g/L of metronidazole) was provided to the HAE-A group. Based on the results of the novel object test and P300 in the oddball behavioral paradigm training test, working memory dysfunction was aggravated by antibiotic treatment. We determined the antioxidant capacity in the prefrontal cortex and found a significant negative influence (p < 0.05) of disturbed gut microbiota on the total antioxidant capacity (T-AOC) and malondialdehyde (MDA) content, as well as the activities of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px). The same trend was also observed in the apoptosis-related functional protein content and mRNA expression levels in the prefrontal cortex, especially the levels of bcl-2, Bax, and caspase-3. The high-altitude environment and antibiotic treatment substantially affected the richness and diversity of the colonic microbiota and reorganized the composition and structure of the microbial community. S24-7, Lachnospiraceae, and Lactobacillaceae were the three microbial taxa with the most pronounced differences under the stimulation by external factors in this study. In addition, correlation analysis between colonic microbiota and cognitive function in mice demonstrated that Helicobacteraceae may be closely related to behavioral results.

CONCLUSION

Disrupted gut microbiota could aggravate working memory dysfunction induced by high-altitude exposure in mice, indicating the existence of a link between high-altitude exposure and MGBA.

Preparing Thick Gradient Surface Layer in Cu-Zn Alloy via Ultrasonic Severe Surface Rolling for Strength-Ductility Balance

A gradient structure (GS) design is a prominent strategy for strength-ductility balance in metallic materials, including Cu alloys. However, producing a thick GS surface layer without surface damage is still a challenging task limited by the available processing technology. In this work, a gradient structure (GS) surface layer with a thickness at the millimeter scale is produced in the Cu-38 wt.% Zn alloy using ultrasonic severe surface rolling technology at room temperature. The GS surface layer is as thick as 1.1 mm and involves the gradient distribution of grain size and dislocation density. The grain size is refined to 153.5 nm in the topmost surface layer and gradually increases with increasing depth. Tensile tests indicate that the single-sided USSR processed alloy exhibits balanced strength (467.5 MPa in yield strength) and ductility (10.7% in uniform elongation). Tailoring the volume fraction of the GS surface layer can tune the combination of strength and ductility in a certain range. The high strength of GS surface layer mainly stems from the high density of grain boundaries, dislocations and dislocation structures, deformation twins, and GS-induced synergistic strengthening effect. Our study elucidates the effect of the thick GS surface layer on strength and ductility, and provides a novel pathway for optimizing the strength-ductility combination of Cu alloys.

[Application of branch-first technique in total thoracic aorta replacement: short and medium term effect of 11 cases]

Objective: To examine the short and medium term effect of branch-first technique in total thoracic aorta replacement. Methods: The clinical data of eleven patients with ascending aortic aneurysms or type A aortic dissection+Crawford Ⅰ or Ⅱ total thoracoabdominal aortic aneurysm who were treated at Department of Cardiovascular Surgery in Henan Province Chest Hospital from January 2018 to July 2021 were retrospectively analyzed. There were 7 males and 4 females, aging (38±5) years (range: 28 to 45 years), 7 cases of whom were diagnosed with Marfan syndrome, 1 case was diagnosed with coarctation of aorta. Operations were performed under mild hypothermic and branch-first technique. Firstly, the middle and small incision in the chest was combined with the 6th intercostal incision in the left posterior lateral side. Secondly, four branches artificial blood vessels were anastomosed with the brachiocephalic artery to ensure the blood supply to the brain. After the circulation was blocked, intracardiac and aortic proximal operations were performed. Intercostal artery reconstruction and thoracic descending aorta replacement were completed after opening circulation. Results: The operative time of this group was (645.9±91.7) minutes (range: 505 to 840 minutes). One case had cerebral infarction and 1 case had chylothorax. The patients were followed up 4 to 47 months, 1 patient underwent thoracic and abdominal aorta+iliac artery resection and replacement due to the progression of abdominal aortic aneurysm 3 months after operation. Intercostal artery obstruction occurred in 2 cases, and the rest lived well. Conclusions: One-stage whole thoracic aorta replacement with branch-first technique has satisfactory results in the short and medium term, with no risk of residual aortic aneurysm rupture. It is an effective treatment for young and organs function well patients with complex aortic lesions.

Research on the Efficiency of Green Agricultural Science and Technology Innovation Resource Allocation Based on a Three-Stage DEA Model-A Case Study of Anhui Province, China

In order to achieve sustainable development of agriculture, people have gradually begun to attach importance to the development of low-carbon agriculture and to regard green agricultural technology innovation and promotion as increasingly more important. Taking the Anhui Province of China as an example, this study analyzed the impact of green agricultural science and technology innovation resource allocation on rural revitalization by constructing an econometric model. We found that the overall efficiency of the overall allocation of agricultural science and technology innovation resources in Anhui Province increased in the sample period, but the scale efficiency level was relatively low. The key path to improving the overall efficiency of allocation was to improve the scale efficiency level. The allocation of agricultural science and technology innovation resources in 16 cities and prefectures performed well in terms of pure technical efficiency, but there were significant differences in scale efficiency, which further affected the overall allocation efficiency of different regions. Among them, the allocation efficiencies of agricultural science and technology innovation resources in Hefei and Fuyang were at the leading level in Anhui Province. Similar to the overall situation of the province, the improvement path of areas with low comprehensive efficiency lay in the improvement of scale efficiency. In view of this, from the policy level, we need to optimize the relationship between the government and the market, speed up the construction of platforms and carriers, attach importance to the construction of the agricultural science and technology talent training system, and improve the open sharing mechanism.

Developing EMR-based algorithms to Identify hospital adverse events for health system performance evaluation and improvement: Study protocol

Background

Measurement of care quality and safety mainly relies on abstracted administrative data. However, it is well studied that administrative data-based adverse event (AE) detection methods are suboptimal due to lack of clinical information. Electronic medical records (EMR) have been widely implemented and contain detailed and comprehensive information regarding all aspects of patient care, offering a valuable complement to administrative data. Harnessing the rich clinical data in EMRs offers a unique opportunity to improve detection, identify possible risk factors of AE and enhance surveillance. However, the methodological tools for detection of AEs within EMR need to be developed and validated. The objectives of this study are to develop EMR-based AE algorithms from hospital EMR data and assess AE algorithm’s validity in Canadian EMR data.

Methods

Patient EMR structured and text data from acute care hospitals in Calgary, Alberta, Canada will be linked with discharge abstract data (DAD) between 2010 and 2020 (n~1.5 million). AE algorithms development. First, a comprehensive list of AEs will be generated through a systematic literature review and expert recommendations. Second, these AEs will be mapped to EMR free texts using Natural Language Processing (NLP) technologies. Finally, an expert panel will assess the clinical relevance of the developed NLP algorithms. AE algorithms validation: We will test the newly developed AE algorithms on 10,000 randomly selected EMRs between 2010 to 2020 from Calgary, Alberta. Trained reviewers will review the selected 10,000 EMR charts to identify AEs that had occurred during hospitalization. Performance indicators (e.g., sensitivity, specificity, positive predictive value, negative predictive value, F₁ score, etc.) of the developed AE algorithms will be assessed using chart review data as the reference standard.

Discussion

The results of this project can be widely implemented in EMR based healthcare system to accurately and timely detect in-hospital AEs.

P15.11.A 18F-Fluciclovine PET/CT to distinguish radiation necrosis from tumour progression in brain metastases treated with stereotactic radiosurgery: results of a prospective pilot study

Background

Amino acid PET radiopharmaceutical, 18F-fluciclovine, shows increased uptake in brain tumors relative to normal tissue and may be a useful tool for detecting recurrent brain metastases. Here, we report results from a prospective pilot study evaluating the use of 18F-fluciclovine PET/CT to distinguish radiation necrosis from tumour progression among patients with brain metastases treated with stereotactic radiosurgery (SRS).

Material and Methods

The primary objective was to estimate the accuracy of 18F-fluciclovine PET/CT in distinguishing radiation necrosis from tumour progression. The trial included adults with brain metastases who underwent SRS and presented with a follow up MRI brain (with DSC MR perfusion) which was equivocal for radiation necrosis versus tumour progression. Within 30 days of equivocal MRI brain, patients underwent an 18F-fluciclovine PET/CT (Siemens mCT) acquired 5-15 min post-injection with images generated by PSF reconstruction. Quantitative metrics for each lesion were documented and lesion to normal brain SUVmean ratios were calculated. The reference standard for diagnosis of radiation necrosis vs tumour progression was clinical follow up with MRI brain every 2-4 months until multidisciplinary consensus or tissue confirmation.

Results

Of 16 patients enrolled between 7/2019-11/2020, 1 patient died prior to diagnosis, allowing 15 evaluable subjects with 20 lesions. Primary histology was NSCLC in 9 (45%) lesions, breast in 7 (35%), melanoma in 3 (15%), and endometrial in 1 (5%). The final diagnosis was radiation necrosis in 16 (80%) lesions and tumour progression in 4 (20%). SUVmax was a statistically significant predictor of tumour progression (P = 0.011), with higher SUVmax values indicative of tumour progression. The area under the ROC curve was 0.833 (95% CI: 0.590, 1.0). A cutoff of 4.3 provided a sensitivity to identify tumour progression of 1.0 (4/4) and specificity to rule out tumour progression of 0.63 (10/16). SUVmean (P = 0.018), SUVpeak (P = 0.007), and SUVpeak/normal (P = 0.002) also reached statistical significance as predictors of tumour progression, with higher SUVmax values indicative of tumour progression. SUVmax/normal (P = 0.1) and SUVmean/normal (P = 0.5) were not statistically significant. The AUC for SUVmax was not significantly higher than the AUCs for the other quantitative variables (P-values &gt; 0.2).

Conclusion

In this prospective pilot study, 18F Fluciclovine PET/CT demonstrated promising accuracy to distinguish radiation necrosis from tumour progression among patients with brain metastases previously treated with SRS. Using SUVmax, a cutpoint of 4.3 provided a sensitivity of 1.0 and specificity of 0.63. Confirmatory phase II and III studies are ongoing.

3D-Stacked Multistage Inertial Microfluidic Chip for High-Throughput Enrichment of Circulating Tumor Cells

Whether for cancer diagnosis or single-cell analysis, it remains a major challenge to isolate the target sample cells from a large background cell for high-efficiency downstream detection and analysis in an integrated chip. Therefore, in this paper, we propose a 3D-stacked multistage inertial microfluidic sorting chip for high-throughput enrichment of circulating tumor cells (CTCs) and convenient downstream analysis. In this chip, the first stage is a spiral channel with a trapezoidal cross-section, which has better separation performance than a spiral channel with a rectangular cross-section. The second and third stages adopt symmetrical square serpentine channels with different rectangular cross-section widths for further separation and enrichment of sample cells reducing the outlet flow rate for easier downstream detection and analysis. The multistage channel can separate 5 μm and 15 μm particles with a separation efficiency of 92.37% and purity of 98.10% at a high inlet flow rate of 1.3 mL/min. Meanwhile, it can separate tumor cells (SW480, A549, and Caki-1) from massive red blood cells (RBCs) with a separation efficiency of >80%, separation purity of >90%, and a concentration fold of ~20. The proposed work is aimed at providing a high-throughput sample processing system that can be easily integrated with flowing sample detection methods for rapid CTC analysis.

Validated algorithms for identifying timing of second event of oropharyngeal squamous cell carcinoma using real-world data

BACKGROUND

Understanding occurrence and timing of second events (recurrence and second primary cancer) is essential for cancer specific survival analysis. However, this information is not readily available in administrative data.

METHODS

Alberta Cancer Registry, physician claims, and other administrative data were used. Timing of second event was estimated based on our developed algorithm. For validation, the difference, in days between the algorithm estimated and the chart-reviewed timing of second event. Further, the result of Cox-regression modeling cancer-free survival was compared to chart review data.

RESULTS

Majority (74.3%) of the patients had a difference between the chart-reviewed and algorithm-estimated timing of second event falling within the 0-60 days window. Kaplan-Meier curves generated from the estimated data and chart review data were comparable with a 5-year second-event-free survival rate of 75.4% versus 72.5%.

CONCLUSION

The algorithm provided an estimated timing of second event similar to that of the chart review.

Molecular simulation of linear octacosane via a CG10 coarse grain scheme

Following our previous work on the united-atom simulation on octacosane (C₂₈H₅₈) (Dai et al., Phys. Chem. Chem. Phys., 2021, 23, 21262-21271), we developed a coarse grain scheme (CG10), which is able to reproduce the pivotal phase characteristics of octacosane with highly improved computational efficiency. The CG10 octacosane chain was composed of 10 consecutive beads, maintaining the fundamental zigzag chain morphology. When the potential functions were set up and the coefficients were parameterized, our CG10 models yielded solid phase diagrams and transitions during an annealing process. We also detected the melting point by various means: direct observation, bond order, density tracking, and an enthalpy plot. Furthermore, our CG10 successfully reproduced the liquid density with only 2% underestimation, indicating its applicability across the solid and liquid phases. Therefore, with the ability to reproduce critical structure and property characteristics, our CG10 scheme provides an effective means of numerically modelling octacosane with highly improved computational efficiency.

Large Culprit Plaque and More Intracranial Plaques Are Associated with Recurrent Stroke: A Case-Control Study Using Vessel Wall Imaging

BACKGROUND AND PURPOSE

Intracranial atherosclerotic plaque features are potential factors associated with recurrent stroke, but previous studies only focused on a single lesion, and few studies investigated them with perfusion impairment. This study aimed to investigate the association among whole-brain plaque features, perfusion deficit, and stroke recurrence.

MATERIALS AND METHODS

Patients with ischemic stroke due to intracranial atherosclerosis were retrospectively collected and categorized into first-time and recurrent-stroke groups. Patients underwent high-resolution vessel wall imaging and DSC-PWI. Intracranial plaque number, culprit plaque features (such as plaque volume/burden, degree of stenosis, enhancement ratio), and perfusion deficit variables were recorded. Logistic regression analyses were performed to determine the independent factors associated with recurrent stroke.

RESULTS

One hundred seventy-five patients (mean age, 59 [SD, 12] years; 115 men) were included. Compared with the first-time stroke group (n = 100), the recurrent-stroke group (n = 75) had a larger culprit volume (P = .006) and showed more intracranial plaques (P < .001) and more enhanced plaques (P = .003). After we adjusted for other factors, culprit plaque volume (OR, 1.16 per 10-mm³ increase; 95% CI, 1.03-1.30; P = .015) and total plaque number (OR, 1.31; 95% CI, 1.13-1.52; P < .001) were independently associated with recurrent stroke. Combining these factors increased the area under the curve to 0.71.

CONCLUSIONS

Large culprit plaque and more intracranial plaques were independently associated with recurrent stroke. Performing whole-brain vessel wall imaging may help identify patients with a higher risk of recurrent stroke.

Comparison of clinical outcome between stereotactic body radiotherapy and radiofrequency ablation for unresectable hepatocellular carcinoma

Stereotactic body radiotherapy (SBRT) is a novel noninvasive treatment for unresectable hepatocellular carcinoma (HCC). Whether its efficacy is comparable to radiofrequency ablation (RFA), a recommended therapy for unresectable HCC, is unknown. The present study aims to compare the clinical outcome between SBRT and RFA for patients with unresectable HCC.The clinical data of 60 patients with unresectable HCC from January 2018 to January 2021 were retrospectively reviewed. There were 22 cases treated by SBRT and 38 cases by RFA. The short-term and long-term clinical outcomes were compared.There was no significant difference in the baseline demographic characteristics between two groups. The complete remission rate at 3 months was comparable between SBRT group (81.8%) and RFA group (89.4%). Local tumor control rate was also similar between two groups (90.9% vs. 94.7%). There was no severe complication (grade IIIa or above) in both groups. The 1-year and 2-year overall survival rates were 88.2% and 85.7% in SBRT group and 100% and 75% in RFA group, respectively. There was no statistical significant difference between groups (P = .576).SBRT can achieve similar short and long-term clinical outcome as RFA for unresectable HCC. Future prospective clinical study is needed to justify its role in patients with HCC.

Validity of ICD-10 codes for COVID-19 patients with hospital admissions or ED visits in Canada: a retrospective cohort study

OBJECTIVE

To evaluate the validity of COVID-19 International Classification of Diseases, 10th Revision (ICD-10) codes and their combinations.

DESIGN

Retrospective cohort study.

SETTING

Acute care hospitals and emergency departments (EDs) in Alberta, Canada.

PARTICIPANTS

Patients who were admitted to hospital or presented to an ED in Alberta, as captured by local administrative databases between 1 March 2020 and 28 February 2021, who had a positive COVID-19 test and/or a COVID-19-related ICD-10 code.

MAIN OUTCOME MEASURES

The sensitivity, positive predictive value (PPV) and 95% CIs for ICD-10 codes were computed. Stratified analysis on age group, sex, symptomatic status, mechanical ventilation, hospital type, patient intensive care unit (ICU) admission, discharge status and season of pandemic were conducted.

RESULTS

Two overlapping subsets of the study population were considered: those who had a positive COVID-19 test (cohort A, for estimating sensitivity) and those who had a COVID-19-related ICD-10 code (cohort B, for estimating PPV). Cohort A included 17 979 ED patients and 6477 inpatients while cohort B included 33 675 ED patients and 18 746 inpatients. Of inpatients, 9.5% in cohort A and 8.1% in cohort B received mechanical ventilation. Over 13% of inpatients were admitted to ICU. The length of hospital stay was 6 days (IQR: 3-14) for cohort A and 8 days (IQR: 3-19) for cohort B. In-hospital mortality was 15.9% and 38.8% for cohort A and B, respectively. The sensitivity for ICD-10 code U07.1 (COVID-19, virus identified) was 82.5% (81.8%-83.2%) with a PPV of 93.1% (92.6%-93.6%). The combination of U07.1 and U07.3 (multisystem inflammatory syndrome associated with COVID-19) had a sensitivity of 82.5% (81.9%-83.2%) and PPV of 92.9% (92.4%-93.4%).

CONCLUSIONS

In Alberta, ICD-10 COVID-19 codes (U07.1 and U07.3) were coded well with high validity. This indicates administrative data can be used for COVID-19 research and pandemic management purposes.

Evolving Factors in Hospital Safety: A Systematic Review and Meta-Analysis of Hospital Adverse Events

OBJECTIVE

This study aimed to estimate the frequency of hospital adverse events (AEs) and explore the rate of AEs over time, and across and within hospital populations.

METHODS

Validated search terms were run in MEDLINE and EMBASE; gray literature and references of included studies were also searched. Studies of any design or language providing an estimate of AEs within the hospital were eligible. Studies were excluded if they only provided an estimate for a specific AE, a subgroup of hospital patients or children. Data were abstracted in duplicate using a standardized data abstraction form. Study quality was assessed using the Newcastle-Ottawa Scale. A random-effects meta-analysis estimated the occurrence of hospital AEs, and meta-regression explored the association between hospital AEs, and patient and hospital characteristics.

RESULTS

A total of 45,426 unique references were identified; 1,265 full-texts were reviewed and 94 studies representing 590 million admissions from 25 countries from 1961 to 2014 were included. The incidence of hospital AEs was 8.6 per 100 patient admissions (95% confidence interval [CI], 8.3 to 8.9; I2 = 100%, P < 0.001). Half of the AEs were preventable (52.6%), and a third resulted in moderate/significant harm (39.7%). The most evaluated AEs were surgical AEs, drug-related AEs, and nosocomial infections. The occurrence of AEs increased by year (95% CI, -0.05 to -0.04; P < 0.001) and patient age (95% CI = -0.15 to -0.14; P < 0.001), and varied by country income level and study characteristics. Patient sex, hospital type, hospital service, and geographical location were not associated with AEs.

CONCLUSIONS

Hospital AEs are common, and reported rates are increasing in the literature. Given the increase in AEs over time, hospitals should reinvest in improving hospital safety with a focus on interventions targeted toward the more than half of AEs that are preventable.