Capacity for large language model chatbots to aid in orthopedic management, research, and patient queries

Large language model (LLM) chatbots possess a remarkable capacity to synthesize complex information into concise, digestible summaries across a wide range of orthopedic subject matter. As LLM chatbots become widely available they will serve as a powerful, accessible resource that patients, clinicians, and researchers may reference to obtain information about orthopedic science and clinical management. Here, we examined the performance of three well-known and easily accessible chatbots-ChatGPT, Bard, and Bing AI-in responding to inquiries relating to clinical management and orthopedic concepts. Although all three chatbots were found to be capable of generating relevant responses, ChatGPT outperformed Bard and BingAI in each category due to its ability to provide accurate and complete responses to orthopedic queries. Despite their promising applications in clinical management, shortcomings observed included incomplete responses, lack of context, and outdated information. Nonetheless, the ability for these LLM chatbots to address these inquires has largely yet to be evaluated and will be critical for understanding the risks and opportunities of LLM chatbots in orthopedics.

Improved Utilization of Serial Testing Without Increased Admissions after Implementation of High-Sensitivity Troponin I: a Controlled Retrospective Cohort Study

BACKGROUND

Guidelines recommend high-sensitivity cardiac troponin (hs-cTn) for diagnosis of myocardial infarction. Use of hs-cTn is increasing across the U.S., but questions remain regarding clinical and operational impact. Prior studies have had methodologic limitations and yielded conflicting results.

OBJECTIVE

To evaluate the impact of transitioning from conventional cardiac troponin (cTn) to hs-cTn on test and resource utilization, operational efficiency, and patient safety.

DESIGN

Retrospective cohort study in two New York City hospitals during the months before and after transition from conventional cTn to hs-cTn at Hospital 1. Hospital 2 served as a control.

PARTICIPANTS

Consecutive emergency department (ED) patients with at least one cTn test resulted.

INTERVENTION

Multifaceted hs-cTn intervention bundle, including a 0/2-h diagnostic algorithm for non-ST-elevation myocardial infarction, an educational bundle, enhancements to the electronic medical record, and nursing interventions to facilitate timed sample collection.

MAIN MEASURES

Primary outcomes included serial cTn test utilization, probability of hospital admission, ED length of stay (LOS), and among discharged patients, probability of ED revisit within 72 h resulting in hospital admission. Multivariable regression models adjusted for age, sex, temporal trends, and interhospital differences.

KEY RESULTS

The intervention was associated with increased use of serial cTn testing (adjusted risk difference: 48 percentage points, 95% CI: 45-50, P < 0.001) and ED LOS (adjusted geometric mean difference: 50 min, 95% CI: 50-51, P < 0.001). There was no significant association between the intervention and probability of admission (adjusted relative risk [aRR]: 0.99, 95% CI: 0.89-1.1, P = 0.81) or probability of ED revisit within 72 h resulting in admission (aRR: 1.1, 95% CI: 0.44-2.9, P = 0.81).

CONCLUSIONS

Implementation of a hs-cTn intervention bundle was associated with an improvement in serial cTn testing, a neutral effect on probability of hospital admission, and a modest increase in ED LOS.

The performance of artificial intelligence chatbot large language models to address skeletal biology and bone health queries

Artificial intelligence (AI) chatbots utilizing large language models (LLMs) have recently garnered significant interest due to their ability to generate humanlike responses to user inquiries in an interactive dialog format. While these models are being increasingly utilized to obtain medical information by patients, scientific and medical providers, and trainees to address biomedical questions, their performance may vary from field to field. The opportunities and risks these chatbots pose to the widespread understanding of skeletal health and science are unknown. Here we assess the performance of 3 high-profile LLM chatbots, Chat Generative Pre-Trained Transformer (ChatGPT) 4.0, BingAI, and Bard, to address 30 questions in 3 categories: basic and translational skeletal biology, clinical practitioner management of skeletal disorders, and patient queries to assess the accuracy and quality of the responses. Thirty questions in each of these categories were posed, and responses were independently graded for their degree of accuracy by four reviewers. While each of the chatbots was often able to provide relevant information about skeletal disorders, the quality and relevance of these responses varied widely, and ChatGPT 4.0 had the highest overall median score in each of the categories. Each of these chatbots displayed distinct limitations that included inconsistent, incomplete, or irrelevant responses, inappropriate utilization of lay sources in a professional context, a failure to take patient demographics or clinical context into account when providing recommendations, and an inability to consistently identify areas of uncertainty in the relevant literature. Careful consideration of both the opportunities and risks of current AI chatbots is needed to formulate guidelines for best practices for their use as source of information about skeletal health and biology.

Faithful AI in Medicine: A Systematic Review with Large Language Models and Beyond

Objective

While artificial intelligence (AI), particularly large language models (LLMs), offers significant potential for medicine, it raises critical concerns due to the possibility of generating factually incorrect information, leading to potential long-term risks and ethical issues. This review aims to provide a comprehensive overview of the faithfulness problem in existing research on AI in healthcare and medicine, with a focus on the analysis of the causes of unfaithful results, evaluation metrics, and mitigation methods.

Materials and Methods

Using PRISMA methodology, we sourced 5,061 records from five databases (PubMed, Scopus, IEEE Xplore, ACM Digital Library, Google Scholar) published between January 2018 to March 2023. We removed duplicates and screened records based on exclusion criteria.

Results

With 40 leaving articles, we conducted a systematic review of recent developments aimed at optimizing and evaluating factuality across a variety of generative medical AI approaches. These include knowledge-grounded LLMs, text-to-text generation, multimodality-to-text generation, and automatic medical fact-checking tasks.

Discussion

Current research investigating the factuality problem in medical AI is in its early stages. There are significant challenges related to data resources, backbone models, mitigation methods, and evaluation metrics. Promising opportunities exist for novel faithful medical AI research involving the adaptation of LLMs and prompt engineering.

Conclusion

This comprehensive review highlights the need for further research to address the issues of reliability and factuality in medical AI, serving as both a reference and inspiration for future research into the safe, ethical use of AI in medicine and healthcare.

Generalizability of a Machine Learning Model for Improving Utilization of Parathyroid Hormone-Related Peptide Testing across Multiple Clinical Centers

BACKGROUND

Measuring parathyroid hormone-related peptide (PTHrP) helps diagnose the humoral hypercalcemia of malignancy, but is often ordered for patients with low pretest probability, resulting in poor test utilization. Manual review of results to identify inappropriate PTHrP orders is a cumbersome process.

METHODS

Using a dataset of 1330 patients from a single institute, we developed a machine learning (ML) model to predict abnormal PTHrP results. We then evaluated the performance of the model on two external datasets. Different strategies (model transporting, retraining, rebuilding, and fine-tuning) were investigated to improve model generalizability. Maximum mean discrepancy (MMD) was adopted to quantify the shift of data distributions across different datasets.

RESULTS

The model achieved an area under the receiver operating characteristic curve (AUROC) of 0.936, and a specificity of 0.842 at 0.900 sensitivity in the development cohort. Directly transporting this model to two external datasets resulted in a deterioration of AUROC to 0.838 and 0.737, with the latter having a larger MMD corresponding to a greater data shift compared to the original dataset. Model rebuilding using site-specific data improved AUROC to 0.891 and 0.837 on the two sites, respectively. When external data is insufficient for retraining, a fine-tuning strategy also improved model utility.

CONCLUSIONS

ML offers promise to improve PTHrP test utilization while relieving the burden of manual review. Transporting a ready-made model to external datasets may lead to performance deterioration due to data distribution shift. Model retraining or rebuilding could improve generalizability when there are enough data, and model fine-tuning may be favorable when site-specific data is limited.

AI Chatbots in Clinical Laboratory Medicine: Foundations and Trends

BACKGROUND

Artificial intelligence (AI) conversational agents, or chatbots, are computer programs designed to simulate human conversations using natural language processing. They offer diverse functions and applications across an expanding range of healthcare domains. However, their roles in laboratory medicine remain unclear, as their accuracy, repeatability, and ability to interpret complex laboratory data have yet to be rigorously evaluated.

CONTENT

This review provides an overview of the history of chatbots, two major chatbot development approaches, and their respective advantages and limitations. We discuss the capabilities and potential applications of chatbots in healthcare, focusing on the laboratory medicine field. Recent evaluations of chatbot performance are presented, with a special emphasis on large language models such as the Chat Generative Pre-trained Transformer in response to laboratory medicine questions across different categories, such as medical knowledge, laboratory operations, regulations, and interpretation of laboratory results as related to clinical context. We analyze the causes of chatbots' limitations and suggest research directions for developing more accurate, reliable, and manageable chatbots for applications in laboratory medicine.

SUMMARY

Chatbots, which are rapidly evolving AI applications, hold tremendous potential to improve medical education, provide timely responses to clinical inquiries concerning laboratory tests, assist in interpreting laboratory results, and facilitate communication among patients, physicians, and laboratorians. Nevertheless, users should be vigilant of existing chatbots' limitations, such as misinformation, inconsistencies, and lack of human-like reasoning abilities. To be effectively used in laboratory medicine, chatbots must undergo extensive training on rigorously validated medical knowledge and be thoroughly evaluated against standard clinical practice.

Elevated levels of renal function tests conferred increased risks of developing various pregnancy complications and adverse perinatal outcomes: insights from a population-based cohort study

OBJECTIVES

Physiological changes during pregnancy can affect the results of renal function tests (RFTs). In this population-based cohort study, we aimed to establish trimester-specific reference intervals (RIs) of RFTs in singleton and twin pregnancies and systematically investigate the relationship between RFTs and adverse pregnancy outcomes.

METHODS

The laboratory results of the first- and third-trimester RFTs, including blood urea nitrogen (BUN), serum uric acid (UA), creatinine (Crea) and cystatin C (Cys C), and the relevant medical records, were retrieved from 29,328 singleton and 840 twin pregnant women who underwent antenatal examinations from November 20, 2017 to January 31, 2021. The trimester-specific RIs of RFTs were estimated with both of the direct observational and the indirect Hoffmann methods. The associations between RTFs and pregnancy complications as well as perinatal outcomes were assessed by logistic regression analysis.

RESULTS

Maternal RFTs showed no significant difference between the direct RIs established with healthy pregnant women and the calculated RIs derived from the Hoffmann method. In addition, elevated levels of RFTs were associated with increased risks of developing various pregnancy complications and adverse perinatal outcomes. Notably, elevated third-trimester RFTs posed strong risks of preterm birth (PTB) and fetal growth restriction (FGR).

CONCLUSIONS

We established the trimester-specific RIs of RFTs in both singleton and twin pregnancies. Our risk analysis findings underscored the importance of RFTs in identifying women at high risks of developing adverse complications or outcomes during pregnancy.

Epigenetic memory of coronavirus infection in innate immune cells and their progenitors

Inflammation can trigger lasting phenotypes in immune and non-immune cells. Whether and how human infections and associated inflammation can form innate immune memory in hematopoietic stem and progenitor cells (HSPC) has remained unclear. We found that circulating HSPC, enriched from peripheral blood, captured the diversity of bone marrow HSPC, enabling investigation of their epigenomic reprogramming following coronavirus disease 2019 (COVID-19). Alterations in innate immune phenotypes and epigenetic programs of HSPC persisted for months to 1 year following severe COVID-19 and were associated with distinct transcription factor (TF) activities, altered regulation of inflammatory programs, and durable increases in myelopoiesis. HSPC epigenomic alterations were conveyed, through differentiation, to progeny innate immune cells. Early activity of IL-6 contributed to these persistent phenotypes in human COVID-19 and a mouse coronavirus infection model. Epigenetic reprogramming of HSPC may underlie altered immune function following infection and be broadly relevant, especially for millions of COVID-19 survivors.

Faithful AI in Medicine: A Systematic Review with Large Language Models and Beyond

Artificial intelligence (AI), especially the most recent large language models (LLMs), holds great promise in healthcare and medicine, with applications spanning from biological scientific discovery and clinical patient care to public health policymaking. However, AI methods have the critical concern for generating factually incorrect or unfaithful information, posing potential long-term risks, ethical issues, and other serious consequences. This review aims to provide a comprehensive overview of the faithfulness problem in existing research on AI in healthcare and medicine, with a focus on the analysis of the causes of unfaithful results, evaluation metrics, and mitigation methods. We systematically reviewed the recent progress in optimizing the factuality across various generative medical AI methods, including knowledge-grounded LLMs, text-to-text generation, multimodality-to-text generation, and automatic medical fact-checking tasks. We further discussed the challenges and opportunities of ensuring the faithfulness of AI-generated information in these applications. We expect that this review will assist researchers and practitioners in understanding the faithfulness problem in AI-generated information in healthcare and medicine, as well as the recent progress and challenges in related research. Our review can also serve as a guide for researchers and practitioners who are interested in applying AI in medicine and healthcare.

Explore the impact of abnormal coagulation test results on pregnancy complications and perinatal outcomes by establishing the trimester-specific reference intervals of singleton and twin pregnancies

BACKGROUND

During pregnancy, complex physiological changes take place in the hemostatic system, resulting in a hypercoagulable state. With the established trimester-specific reference intervals (RIs) of the coagulation tests, we investigated the associations between disturbance of hemostasis and adverse pregnant outcomes in a population-based cohort study.

METHODS

The first- and third-trimester coagulation tests results were retrieved from 29,328 singleton and 840 twin pregnant women for regular antenatal check-ups from November 30th, 2017 to January 31st, 2021. The trimester-specific RIs for fibrinogen (FIB), prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), d-dimer (DD) were estimated using both the direct observational and the indirect Hoffmann methods. The associations between the coagulation tests and the risks of developing pregnancy complications as well as adverse perinatal outcomes were assessed using the logistic regression analysis.

RESULTS

Increased FIB, DD and decreased PT, APTT and TT were observed as the gestational age increases in the singleton pregnancy. An enhanced procoagulant state, marked by significant elevation of FIB, DD and reduction of PT, APTT and TT, was observed in the twin pregnancy. The subjects with anormal PT, APTT, TT, DD, tend to have increased risks of developing peri- and postpartum complications such as preterm birth, fetal growth restriction.

CONCLUSIONS

The incidence of adverse perinatal outcomes was remarkably associated with the maternal increased levels of FIB, PT, TT, APTT and DD in the third trimester, which may be applied in early identification of women at high risk of adverse outcomes due to coagulopathy.

[Role of imaging classification in the diagnosis and management of orbital inflammatory pseudotumor]

Orbital inflammatory pseudotumor (OIP) is a kind of orbital idiopathic benign space-occupying lesion with no clear etiology and mainly characterized by inflammatory response. The clinical diagnosis of OIP should be based on exclusion of other diseases or surgical biopsy. Medication and surgical excision are both diagnostic and therapeutic methods. The choice of which is a problem that baffles clinicians. This article discusses a new strategy basing on the imaging features and classifications of OIP. It is expected to be further discussed and promoted in clinical practice to improve the diagnosis and treatment of OIP.

Development of a Machine Learning Algorithm for Drug Screening Analysis on High-Resolution UPLC-MSE/QTOF Mass Spectrometry

BACKGROUND

Ultra-performance liquid chromatography (UPLC)-MSE/quadrupole time-of-flight (QTOF) high-resolution mass spectrometry employs untargeted, data-independent acquisition in a dual mode that simultaneously collects precursor ions and product ions at low and ramped collision energies, respectively. However, algorithmic analysis of large-scale multivariate data of comprehensive drug screening as well as the positivity criteria of drug identification have not been systematically investigated. It is also unclear whether ion ratio (IR), the intensity ratio of a defined product ion divided by the precursor ion, is a stable parameter that can be incorporated into the MSE/QTOF data analysis algorithm.

METHODS

IR of 91 drugs were experimentally determined and variation of IR was investigated across 5 concentrations measured on 3 different days. A data-driven machine learning approach was employed to develop multivariate linear regression (MLR) models incorporating mass error, retention time, number of detected fragment ions and IR, accuracy of isotope abundance, and peak response using drug-supplemented urine samples. Performance of the models was evaluated in an independent data set of unknown clinical urine samples in comparison with the results of manual analysis.

RESULTS

IR of most compounds acquired by MSE/QTOF were low and concentration-dependent (i.e., IR increased at higher concentrations). We developed an MLR model with composite score outputs incorporating 7 parameters to predict positive drug identification. The model achieved a mean accuracy of 89.38% in the validation set and 87.92% agreement in the test set.

CONCLUSIONS

The MLR model incorporating all contributing parameters can serve as a decision-support tool to facilitate objective drug identification using UPLC-MSE/QTOF.

Serum peptidomic screening identified circulating peptide biomarkers predictive for preeclampsia

Background

Reliable biomarkers are needed to improve preeclampsia (PE) prediction accuracy. With the investigational tool of peptidomics, we aimed to identify and validate potential serum peptide biomarkers in cohorts suspected for PE development in middle or late pregnancy.

Methods

Totally 195 serum samples were prospectively collected from pregnant women with PE-related syndromes who were followed up for PE development until delivery. Serum peptidomic analysis was performed in the discovery cohort of 115 samples using matrix-assisted laser desorption ionization-time of flight coupled with Linear Trap Quadropole Orbitrap mass spectrometry. The candidate biomarkers were further validated using an in-house developed liquid chromatography tandem mass spectrometry (LC-MS/MS) method in an independent validation cohort of 80 serum samples.

Results

We identified 8 peptides that were differentially expressed and originated from fibrinogen alpha chain (FGA), inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4) and complement component 3. In the subsequent LC-MS/MS quantitation analysis, the levels of the three peptides (FGA-1033.4, ITIH4-2026.9, ITIH4-2051.1) exhibited a significant difference between the PE-positive and PE-negative groups. Further, the three-peptide panel yielded an area under the ROC curve (AUC) of 0.985 [95% confidence interval (CI) 0.965-1.000] and 0.923 (95% CI 0.845-1.000) in the discovery and validation cohorts respectively, with negative predictive values of 98.1-98.8% and positive predictive values of 73.1-85.3% that were much improved when compared with that of soluble fms-like tyrosine kinase-1/placental growth factor (sFlt-1/PlGF) ratio.

Conclusions

We have discovered and validated a novel three-peptide biomarker panel predictive for the occurrence PE in pregnant women.

Building the Model

CONTEXT.—

Machine learning (ML) allows for the analysis of massive quantities of high-dimensional clinical laboratory data, thereby revealing complex patterns and trends. Thus, ML can potentially improve the efficiency of clinical data interpretation and the practice of laboratory medicine. However, the risks of generating biased or unrepresentative models, which can lead to misleading clinical conclusions or overestimation of the model performance, should be recognized.

OBJECTIVES.—

To discuss the major components for creating ML models, including data collection, data preprocessing, model development, and model evaluation. We also highlight many of the challenges and pitfalls in developing ML models, which could result in misleading clinical impressions or inaccurate model performance, and provide suggestions and guidance on how to circumvent these challenges.

DATA SOURCES.—

The references for this review were identified through searches of the PubMed database, the US Food and Drug Administration white papers and guidelines, conference abstracts, and online preprints.

CONCLUSIONS.—

With the growing interest in developing and implementing ML models in clinical practice, laboratorians and clinicians need to be educated in order to collect sufficiently large and high-quality data, properly report the data set characteristics, and combine data from multiple institutions with proper normalization. They will also need to assess the reasons for missing values, determine the inclusion or exclusion of outliers, and evaluate the completeness of a data set. In addition, they require the necessary knowledge to select a suitable ML model for a specific clinical question and accurately evaluate the performance of the ML model, based on objective criteria. Domain-specific knowledge is critical in the entire workflow of developing ML models.

Integrative metabolomic and proteomic signatures define clinical outcomes in severe COVID-19

The coronavirus disease-19 (COVID-19) pandemic has ravaged global healthcare with previously unseen levels of morbidity and mortality. In this study, we performed large-scale integrative multi-omics analyses of serum obtained from COVID-19 patients with the goal of uncovering novel pathogenic complexities of this disease and identifying molecular signatures that predict clinical outcomes. We assembled a network of protein-metabolite interactions through targeted metabolomic and proteomic profiling in 330 COVID-19 patients compared to 97 non-COVID, hospitalized controls. Our network identified distinct protein-metabolite cross talk related to immune modulation, energy and nucleotide metabolism, vascular homeostasis, and collagen catabolism. Additionally, our data linked multiple proteins and metabolites to clinical indices associated with long-term mortality and morbidity. Finally, we developed a novel composite outcome measure for COVID-19 disease severity based on metabolomics data. The model predicts severe disease with a concordance index of around 0.69, and shows high predictive power of 0.83-0.93 in two independent datasets.

Chronic superphysiologic AMH promotes premature luteinization of antral follicles in human ovarian xenografts

Anti-Müllerian hormone (AMH) is produced by growing ovarian follicles and provides a diagnostic measure of reproductive reserve in women; however, the impact of AMH on folliculogenesis is poorly understood. We cotransplanted human ovarian cortex with control or AMH-expressing endothelial cells in immunocompromised mice and recovered antral follicles for purification and downstream single-cell RNA sequencing of granulosa and theca/stroma cell fractions. A total of 38 antral follicles were observed (19 control and 19 AMH) at long-term intervals (>10 weeks). In the context of exogenous AMH, follicles exhibited a decreased ratio of primordial to growing follicles and antral follicles of increased diameter. Transcriptomic analysis and immunolabeling revealed a marked increase in factors typically noted at more advanced stages of follicle maturation, with granulosa and theca/stroma cells also displaying molecular hallmarks of luteinization. These results suggest that superphysiologic AMH alone may contribute to ovulatory dysfunction by accelerating maturation and/or luteinization of antral-stage follicles.

Rapid, robust, and sustainable antibody responses to mRNA COVID-19 vaccine in convalescent COVID-19 individuals

Longitudinal studies are needed to evaluate the SARS-CoV-2 mRNA vaccine antibody response under real-world conditions. This longitudinal study investigated the quantity and quality of SARS-CoV-2 antibody response in 846 specimens from 350 patients, comparing BNT162b2-vaccinated individuals (19 previously diagnosed with COVID-19, termed RecoVax; and 49 never diagnosed, termed NaiveVax) with 122 hospitalized unvaccinated (HospNoVax) and 160 outpatient unvaccinated (OutPtNoVax) COVID-19 patients. NaiveVax experienced delay in generating SARS-CoV-2 total antibodies (TAb) and surrogate neutralizing antibodies (SNAb) after the first vaccine dose (D1) but rapid increase in antibody levels after the second dose (D2). However, these never reached RecoVax's robust levels. In fact, NaiveVax TAb and SNAb levels decreased 4 weeks after D2. For the most part, RecoVax TAb persisted, after reaching maximal levels 2 weeks after D2, but SNAb decreased significantly about 6 months after D1. Although NaiveVax avidity lagged behind that of RecoVax for most of the follow-up periods, NaiveVax did reach similar avidity by about 6 months after D1. These data suggest that 1 vaccine dose elicits maximal antibody response in RecoVax and may be sufficient. Also, despite decreasing levels in TAb and SNAb over time, long-term avidity may be a measure worth evaluating and possibly correlating to vaccine efficacy.

TOP-Plus Is a Versatile Biosensor Platform for Monitoring SARS-CoV-2 Antibody Durability

BACKGROUND

Low initial severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody titers dropping to undetectable levels within months after infection have raised concerns about long-term immunity. Both the antibody levels and the avidity of the antibody-antigen interaction should be examined to understand the quality of the antibody response.

METHODS

A testing-on-a-probe "plus" panel (TOP-Plus) was developed to include a newly developed avidity assay built into the previously described SARS-CoV-2 TOP assays that measured total antibody (TAb), surrogate neutralizing antibody (SNAb), IgM, and IgG on a versatile biosensor platform. TAb and SNAb levels were compared with avidity in previously infected individuals at 1.3 and 6.2 months after infection in paired samples from 80 patients with coronavirus disease 2019 (COVID-19). Sera from individuals vaccinated for SARS-CoV-2 were also evaluated for antibody avidity.

RESULTS

The newly designed avidity assay in this TOP panel correlated well with a reference Bio-Layer Interferometry avidity assay (r = 0.88). The imprecision of the TOP avidity assay was <10%. Although TAb and neutralization activity (by SNAb) decreased between 1.3 and 6.2 months after infection, the antibody avidity increased significantly (P < 0.0001). Antibody avidity in 10 SARS-CoV-2 vaccinated individuals (median: 28 days after vaccination) was comparable to the measured antibody avidity in infected individuals (median: 26 days after infection).

CONCLUSIONS

This highly precise and versatile TOP-Plus panel with the ability to measure SARS-CoV-2 TAb, SNAb, IgG, and IgM antibody levels and avidity of individual sera on one sensor can become a valuable asset in monitoring not only patients infected with SARS-CoV-2 but also the status of individuals' COVID-19 vaccination response.

Elemental Testing Using Inductively Coupled Plasma Mass Spectrometry in Clinical Laboratories

OBJECTIVES

This review aims to describe the principles underlying different types of inductively coupled plasma mass spectrometry (ICP-MS), and major technical advancements that reduce spectral interferences, as well as their suitability and wide applications in clinical laboratories.

METHODS

A literature survey was performed to review the technical aspects of ICP-MS, ICP-MS/MS, high-resolution ICP-MS, and their applications in disease diagnosis and monitoring.

RESULTS

Compared to the atomic absorption spectrometry and ICP-optical emission spectrometry, ICP-MS has advantages including improved precision, sensitivity and accuracy, wide linear dynamic range, multielement measurement capability, and ability to perform isotopic analysis. Technical advancements, such as collision/reaction cells, triple quadrupole ICP-MS, and sector-field ICP-MS, have been introduced to improve resolving power and reduce interferences. Cases are discussed that highlight the clinical applications of ICP-MS including determination of toxic elements, quantification of nutritional elements, monitoring elemental deficiency in metabolic disease, and multielement analysis.

CONCLUSIONS

This review provides insight on the strategies of elemental analysis in clinical laboratories and demonstrates current and emerging clinical applications of ICP-MS.

Machine Learning Highlights Downtrending of COVID-19 Patients with a Distinct Laboratory Profile

BACKGROUND

New York City (NYC) experienced an initial surge and gradual decline in the number of SARS-CoV-2-confirmed cases in 2020. A change in the pattern of laboratory test results in COVID-19 patients over this time has not been reported or correlated with patient outcome.

METHODS

We performed a retrospective study of routine laboratory and SARS-CoV-2 RT-PCR test results from 5,785 patients evaluated in a NYC hospital emergency department from March to June employing machine learning analysis.

RESULTS

A COVID-19 high-risk laboratory test result profile (COVID19-HRP), consisting of 21 routine blood tests, was identified to characterize the SARS-CoV-2 patients. Approximately half of the SARS-CoV-2 positive patients had the distinct COVID19-HRP that separated them from SARS-CoV-2 negative patients. SARS-CoV-2 patients with the COVID19-HRP had higher SARS-CoV-2 viral loads, determined by cycle threshold values from the RT-PCR, and poorer clinical outcome compared to other positive patients without the COVID12-HRP. Furthermore, the percentage of SARS-CoV-2 patients with the COVID19-HRP has significantly decreased from March/April to May/June. Notably, viral load in the SARS-CoV-2 patients declined, and their laboratory profile became less distinguishable from SARS-CoV-2 negative patients in the later phase.

CONCLUSIONS

Our longitudinal analysis illustrates the temporal change of laboratory test result profile in SARS-CoV-2 patients and the COVID-19 evolvement in a US epicenter. This analysis could become an important tool in COVID-19 population disease severity tracking and prediction. In addition, this analysis may play an important role in prioritizing high-risk patients, assisting in patient triaging and optimizing the usage of resources.

Cytokine signatures of end organ injury in COVID-19

Increasing evidence has shown that Coronavirus disease 19 (COVID-19) severity is driven by a dysregulated immunologic response. We aimed to assess the differences in inflammatory cytokines in COVID-19 patients compared to contemporaneously hospitalized controls and then analyze the relationship between these cytokines and the development of Acute Respiratory Distress Syndrome (ARDS), Acute Kidney Injury (AKI) and mortality. In this cohort study of hospitalized patients, done between March third, 2020 and April first, 2020 at a quaternary referral center in New York City we included adult hospitalized patients with COVID-19 and negative controls. Serum specimens were obtained on the first, second, and third hospital day and cytokines were measured by Luminex. Autopsies of nine cohort patients were examined. We identified 90 COVID-19 patients and 51 controls. Analysis of 48 inflammatory cytokines revealed upregulation of macrophage induced chemokines, T-cell related interleukines and stromal cell producing cytokines in COVID-19 patients compared to the controls. Moreover, distinctive cytokine signatures predicted the development of ARDS, AKI and mortality in COVID-19 patients. Specifically, macrophage-associated cytokines predicted ARDS, T cell immunity related cytokines predicted AKI and mortality was associated with cytokines of activated immune pathways, of which IL-13 was universally correlated with ARDS, AKI and mortality. Histopathological examination of the autopsies showed diffuse alveolar damage with significant mononuclear inflammatory cell infiltration. Additionally, the kidneys demonstrated glomerular sclerosis, tubulointerstitial lymphocyte infiltration and cortical and medullary atrophy. These patterns of cytokine expression offer insight into the pathogenesis of COVID-19 disease, its severity, and subsequent lung and kidney injury suggesting more targeted treatment strategies.

A rare case of persistent pseudohypobicarbonatemia arising from chemistry analyzer-specific interference

BACKGROUND

Major discrepancies between concentrations of serum total carbon dioxide (tCO₂) obtained from chemistry analyzers and calculated bicarbonate from blood gas analyzers should prompt laboratory investigation. Here, we present a rare case of pseudohypobicarbonatemia unrelated to the common causes such as hypertriglyceridemia and hyperproteinemia, but was caused by a low concentration of paraproteins.

CASE

A 75-year-old man with persistent fevers was found to have a low concentration of serum tCO₂ (<10 mmol/l) with a normal pH and calculated bicarbonate concentrations (23.5 mmol/l) from the blood gas analyzer. His serum tCO₂ concentrations remained critically low throughout hospitalization without any evidence of acidosis. Serum tCO₂ levels were measured via Siemens ADVIA Chemistry XPT system.

RESULTS

Mixing studies revealed non-linearity of serum tCO₂, suggesting the presence of interfering substances. Triglyceride concentrations were normal. Serum electrophoresis revealed a 0.4 mg/dl M-protein. The patient's serum tCO₂ concentrations were repeated on different chemistry analyzer platforms - including Siemens, Roche, and Abbott - which demonstrated that the interference was specific to the Siemens chemistry analyzer. Serum tCO₂ was significantly elevated after ultrafiltration of paraprotein, which confirmed the root cause of pseudohypobicarbonatemia.

CONCLUSION

Laboratory professionals should be aware that spuriously low serum tCO₂ concentrations may result from unique interfering substances, such as paraproteins, that are both patient- and chemistry analyzer-specific.

Postconvalescent SARS-CoV-2 IgG and Neutralizing Antibodies are Elevated in Individuals with Poor Metabolic Health

PURPOSE

Comorbidities making up metabolic syndrome (MetS), such as obesity, type 2 diabetes, and chronic cardiovascular disease can lead to increased risk of coronavirus disease-2019 (COVID-19) with a higher morbidity and mortality. SARS-CoV-2 antibodies are higher in severely or critically ill COVID-19 patients, but studies have not focused on levels in convalescent patients with MetS, which this study aimed to assess.

METHODS

This retrospective study focused on adult convalescent outpatients with SARS-CoV-2 positive serology during the COVID-19 pandemic at NewYork Presbyterian/Weill Cornell. Data collected for descriptive and correlative analysis included SARS-COV-2 immunoglobin G (IgG) levels and history of MetS comorbidities from April 17, 2020 to May 20, 2020. Additional data, including SARS-CoV-2 IgG levels, body mass index (BMI), hemoglobin A1c (HbA1c) and lipid levels were collected and analyzed for a second cohort from May 21, 2020 to June 21, 2020. SARS-CoV-2 neutralizing antibodies were measured in a subset of the study cohort.

RESULTS

SARS-CoV-2 IgG levels were significantly higher in convalescent individuals with MetS comorbidities. When adjusted for age, sex, race, and time duration from symptom onset to testing, increased SARS-CoV-2 IgG levels remained significantly associated with obesity (P < 0.0001). SARS-CoV-2 IgG levels were significantly higher in patients with HbA1c ≥6.5% compared to those with HbA1c <5.7% (P = 0.0197) and remained significant on multivariable analysis (P = 0.0104). A positive correlation was noted between BMI and antibody levels [95% confidence interval: 0.37 (0.20-0.52) P < 0.0001]. Neutralizing antibody titers were higher in COVID-19 individuals with BMI ≥ 30 (P = 0.0055).

CONCLUSION

Postconvalescent SARS-CoV-2 IgG and neutralizing antibodies are elevated in obese patients, and a positive correlation exists between BMI and antibody levels.

Sensitive tracking of circulating viral RNA through all stages of SARS-CoV-2 infection

BACKGROUNDCirculating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA may represent a more reliable indicator of infection than nasal RNA, but quantitative reverse transcription PCR (RT-qPCR) lacks diagnostic sensitivity for blood samples.METHODSA CRISPR-augmented RT-PCR assay that sensitively detects SARS-CoV-2 RNA was employed to analyze viral RNA kinetics in longitudinal plasma samples from nonhuman primates (NHPs) after virus exposure; to evaluate the utility of blood SARS-CoV-2 RNA detection for coronavirus disease 2019 (COVID-19) diagnosis in adults cases confirmed by nasal/nasopharyngeal swab RT-PCR results; and to identify suspected COVID-19 cases in pediatric and at-risk adult populations with negative nasal swab RT-qPCR results. All blood samples were analyzed by RT-qPCR to allow direct comparisons.RESULTSCRISPR-augmented RT-PCR consistently detected SARS-CoV-2 RNA in the plasma of experimentally infected NHPs from 1 to 28 days after infection, and these increases preceded and correlated with rectal swab viral RNA increases. In a patient cohort (n = 159), this blood-based assay demonstrated 91.2% diagnostic sensitivity and 99.2% diagnostic specificity versus a comparator RT-qPCR nasal/nasopharyngeal test, whereas RT-qPCR exhibited 44.1% diagnostic sensitivity and 100% specificity for the same blood samples. This CRISPR-augmented RT-PCR assay also accurately identified patients with COVID-19 using one or more negative nasal swab RT-qPCR results.CONCLUSIONResults of this study indicate that sensitive detection of SARS-CoV-2 RNA in blood by CRISPR-augmented RT-PCR permits accurate COVID-19 diagnosis, and can detect COVID-19 cases with transient or negative nasal swab RT-qPCR results, suggesting that this approach could improve COVID-19 diagnosis and the evaluation of SARS-CoV-2 infection clearance, and predict the severity of infection.TRIAL REGISTRATIONClinicalTrials.gov. NCT04358211.FUNDINGDepartment of Defense, National Institute of Allergy and Infectious Diseases, National Institute of Child Health and Human Development, and the National Center for Research Resources.

Association of Age With SARS-CoV-2 Antibody Response

Importance

Accumulating evidence suggests that children infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are more likely to manifest mild symptoms and are at a lower risk of developing severe respiratory disease compared with adults. It remains unknown how the immune response in children differs from that of adolescents and adults.

Objective

To investigate the association of age with the quantity and quality of SARS-CoV-2 antibody responses.

Design, Setting, and Participants

This cross-sectional study used 31 426 SARS-CoV-2 antibody test results from pediatric and adult patients. Data were collected from a New York City hospital from April 9 to August 31, 2020. The semiquantitative immunoglobin (Ig) G levels were compared between 85 pediatric and 3648 adult patients. Further analysis of SARS-CoV-2 antibody profiles was performed on sera from 126 patients aged 1 to 24 years.

Main Outcomes and Measures

SARS-CoV-2 antibody positivity rates and IgG levels were evaluated in patients from a wide range of age groups (1-102 years). SARS-CoV-2 IgG level, total antibody (TAb) level, surrogate neutralizing antibody (SNAb) activity, and antibody binding avidity were compared between children (aged 1-10 years), adolescents (aged 11-18 years), and young adults (aged 19-24 years).

Results

Among 31 426 antibody test results (19 797 [63.0%] female patients), with 1194 pediatric patients (mean [SD] age, 11.0 [5.3] years) and 30 232 adult patients (mean [SD] age, 49.2 [17.1] years), the seroprevalence in the pediatric (197 [16.5%; 95% CI, 14.4%-18.7%]) and adult (5630 [18.6%; 95% CI, 18.2%-19.1%]) patient populations was similar. The SARS-CoV-2 IgG level showed a negative correlation with age in the pediatric population (r = -0.45, P < .001) and a moderate but positive correlation with age in adults (r = 0.24, P < .001). Patients aged 19 to 30 years exhibited the lowest IgG levels (eg, aged 25-30 years vs 1-10 years: 99 [44-180] relative fluorescence units [RFU] vs 443 [188-851] RFU). In the subset cohort aged 1 to 24 years, IgG, TAb, SNAb and avidity were negatively correlated with age (eg, IgG: r = -0.51; P < .001). Children exhibited higher median (IQR) IgG levels, TAb levels, and SNAb activity compared with adolescents (eg, IgG levels: 473 [233-656] RFU vs 191 [82-349] RFU; P < .001) and young adults (eg, IgG levels: 473 [233-656] RFU vs 85 [38-150] RFU; P < .001). Adolescents also exhibited higher median (IQR) TAb levels, IgG levels, and SNAb activity than young adults (eg, TAb levels: 961 [290-2074] RFU vs 370 [125-697]; P = .006). In addition, children had higher antibody binding avidity compared with young adults, but the difference was not significant.

Conclusions and Relevance

The results of this study suggest that SARS-CoV-2 viral specific antibody response profiles are distinct in different age groups. Age-targeted strategies for disease screening and management as well as vaccine development may be warranted.

TOP-Plus is a Versatile Biosensor Platform for Monitoring SARS-CoV-2 Antibody Durability

BACKGROUND

There is a concern that low initial SARS-CoV-2 antibody titers in individuals may drop to undetectable levels within months after infection. Although this may raise concerns over long term immunity, both the antibody levels and avidity of the antibody-antigen interaction should be examined to understand the quality of the antibody response.

METHODS

A testing-on-a-probe-plus panel (TOP-Plus) was developed, which included a newly developed avidity assay built into the previously described SARS-CoV-2 TOP assays that measured total antibody (TAb), surrogate neutralizing antibody (SNAb), IgM and IgG on a versatile biosensor platform. TAb and SNAb levels were compared with avidity in previously infected individuals at 1.3 and 6.2 months post-infection in paired samples from 80 COVID-19 patients.

RESULTS

The newly designed avidity assay in this TOP panel correlated well with a reference Bio-Layer Interferometry avidity assay (R=0.88). The imprecision of the TOP avidity assay was less than 9%. Although TAb and neutralization activity (by SNAb) decreased between 1.3 and 6.2 months post infection, the antibody avidity increased significantly (P < 0.0001).

Testing-on-a-probe biosensors reveal association of early SARS-CoV-2 total antibodies and surrogate neutralizing antibodies with mortality in COVID-19 patients

The association of mortality with the early humoral response to SARS-CoV-2 infection within the first few days after onset of symptoms (DAOS) has not been thoroughly investigated partly due to a lack of sufficiently sensitive antibody testing methods. Here we report two sensitive and automated testing-on-a-probe (TOP) biosensor assays for SARS-CoV-2 viral specific total antibodies (TAb) and surrogate neutralizing antibodies (SNAb), which are suitable for clinical use. The TOP assays employ an RBD-coated quartz probe using a Cy5-Streptavidin-polysacharide conjugate to improve sensitivity and minimize interference. Disposable cartridges containing pre-dispensed reagents require no liquid manipulation or fluidics during testing. The TOP-TAb assay exhibited higher sensitivity in the 0-7 DAOS window than a widely used FDA-EUA assay. The rapid and automated TOP-SNAb correlated well with two well-established SARS-CoV-2 virus neutralization tests. The clinical utility of the TOP assays was demonstrated by evaluating early antibody responses in 120 SARS-CoV-2 RT-PCR positive adult hospitalized patients. Higher TAb and SNAb positivity rates and more robust antibody responses at patient's initial hospital presentation were seen in inpatients who survived COVID-19 than those who died in the hospital. Survival analysis using the Cox Proportional Hazards Model showed that patients who had negative TAb and/or SNAb at initial hospital presentation were at a higher risk of in-hospital mortality. Furthermore, TAb and SNAb levels at presentation were inversely associated with SARS-CoV-2 viral load based on concurrent RT-PCR testing. Overall, the sensitive and automated TAb and SNAb assays allow the detection of early SARS-CoV-2 antibodies which associate with mortality.

Testing-on-a-probe biosensors reveal association of early SARS-CoV-2 total antibodies and surrogate neutralizing antibodies with mortality in COVID-19 patients

The association of mortality with early humoral response to SARS-CoV-2 infection within the first few days after onset of symptoms (DAOS) has not been thoroughly investigated partly due to a lack of sufficiently sensitive antibody testing methods. Here we report two sensitive and automated testing-on-a-probe (TOP) biosensor assays for SARS-CoV-2 viral specific total antibodies (TAb) and surrogate neutralizing antibodies (SNAb), which are suitable for clinical use. The TOP assays employ an RBD-coated quartz probe using a Cy5-Streptavidin-polysacharide conjugate to improved sensitivity and minimize interference. Disposable cartridge containing pre-dispensed reagents requires no liquid manipulation or fluidics during testing. The TOP-TAb assay exhibited higher sensitivity in the 0-7 DAOS window than a widely used FDA-EUA assay. The rapid (18 min) and automated TOP-SNAb correlated well with two well-established SARS-CoV-2 virus neutralization tests. The clinical utility of the TOP assays was demonstrated by evaluating early antibody responses in 120 SARS-CoV-2 RT-PCR positive adult hospitalized patients. Higher baseline TAb and SNAb positivity rates and more robust antibody responses were seen in patients who survived COVID-19 than those who died in the hospital. Survival analysis using the Cox Proportional Hazards Model showed that patients who were TAb and SNAb negative at initial hospital presentation were at a higher risk of in-hospital mortality. Furthermore, TAb and SNAb levels at presentation were inversely associated with SARS-CoV-2 viral load based on concurrent RT-PCR testing. Overall, the sensitive and automated TAb and SNAb assays allow detection of early SARS-CoV-2 antibodies which associate with mortality.

Routine Laboratory Blood Tests Predict SARS-CoV-2 Infection Using Machine Learning

Background

Accurate diagnostic strategies to rapidly identify SARS-CoV-2 positive individuals for management of patient care and protection of health care personnel are urgently needed. The predominant diagnostic test is viral RNA detection by RT-PCR from nasopharyngeal swabs specimens, however the results are not promptly obtainable in all patient care locations. Routine laboratory testing, in contrast, is readily available with a turn-around time (TAT) usually within 1-2 hours.

Method

We developed a machine learning model incorporating patient demographic features (age, sex, race) with 27 routine laboratory tests to predict an individual’s SARS-CoV-2 infection status. Laboratory test results obtained within two days before the release of SARS-CoV-2-RT-PCR result were used to train a gradient boosted decision tree (GBDT) model from 3,356 SARS-CoV-2 RT-PCR tested patients (1,402 positive and 1,954 negative) evaluated at a metropolitan hospital.

Results

The model achieved an area under the receiver operating characteristic curve (AUC) of 0.854 (95% CI: 0.829-0.878). Application of this model to an independent patient dataset from a separate hospital resulted in a comparable AUC (0.838), validating the generalization of its use. Moreover, our model predicted initial SARS-CoV-2 RT-PCR positivity in 66% individuals whose RT-PCR result changed from negative to positive within two days.

Conclusion

This model employing routine laboratory test results offers opportunities for early and rapid identification of high-risk SARS-CoV-2 infected patients before their RT-PCR results are available. It may play an important role in assisting the identification of SARS-COV-2 infected patients in areas where RT-PCR testing is not accessible due to financial or supply constraints.

Routine Laboratory Blood Tests Predict SARS-CoV-2 Infection Using Machine Learning

BACKGROUND

Accurate diagnostic strategies to identify SARS-CoV-2 positive individuals rapidly for management of patient care and protection of health care personnel are urgently needed. The predominant diagnostic test is viral RNA detection by RT-PCR from nasopharyngeal swabs specimens, however the results are not promptly obtainable in all patient care locations. Routine laboratory testing, in contrast, is readily available with a turn-around time (TAT) usually within 1-2 hours.

METHOD

We developed a machine learning model incorporating patient demographic features (age, sex, race) with 27 routine laboratory tests to predict an individual's SARS-CoV-2 infection status. Laboratory testing results obtained within 2 days before the release of SARS-CoV-2 RT-PCR result were used to train a gradient boosting decision tree (GBDT) model from 3,356 SARS-CoV-2 RT-PCR tested patients (1,402 positive and 1,954 negative) evaluated at a metropolitan hospital.

RESULTS

The model achieved an area under the receiver operating characteristic curve (AUC) of 0.854 (95% CI: 0.829-0.878). Application of this model to an independent patient dataset from a separate hospital resulted in a comparable AUC (0.838), validating the generalization of its use. Moreover, our model predicted initial SARS-CoV-2 RT-PCR positivity in 66% individuals whose RT-PCR result changed from negative to positive within 2 days.

CONCLUSION

This model employing routine laboratory test results offers opportunities for early and rapid identification of high-risk SARS-CoV-2 infected patients before their RT-PCR results are available. It may play an important role in assisting the identification of SARS-CoV-2 infected patients in areas where RT-PCR testing is not accessible due to financial or supply constraints.

NGS-based profiling reveals a critical contributing role of somatic D-loop mtDNA mutations in HBV-related hepatocarcinogenesis

BACKGROUND

Somatic mutations of mitochondrial DNA (mtDNA) have been extensively identified mainly by traditional Sanger sequencing technology in various cancer types. However, low detection sensitivity of traditional methods greatly limits the comprehensive profiling of mtDNA somatic mutations in cancers, especially in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). Moreover, the functional roles of mtDNA mutation in HBV-related hepatocarcinogenesis have not been systematically revealed.

PATIENTS AND METHODS

Next-generation sequencing (NGS) platform was applied to profile the somatic mtDNA mutations of HCC and paired paratumor (non-HCC) tissues from a large cohort of 156 HBV-HCC patients.

RESULTS

Our data revealed the common existence of mtDNA mutation in both inflammatory and cancer tissues with significantly different mutation pattern. The mutation density (mutation number/region length) of D-loop region was much higher than that of other regions in both HCC and non-HCC tissues. Unexpectedly, the average mutation number in D-loop region of HCC tissues was significantly less than that of non-HCC tissues. In contrast, the heteroplasmy level of D-loop region mutations was significantly increased in HCC tissues, implying that the D-loop mutations might be positively selected in HCC tissues. Furthermore, our results indicated that the patients with D-loop mutations had a significantly lower mtDNA copy number and were more likely to relapse. In vitro experiments demonstrated that proliferation, invasion and metastasis ability of HCC cells with D-loop region mutations were significantly higher than those without D-loop region mutations.

CONCLUSION

These results emphasize the critical contributing role of somatic mtDNA D-loop mutations in HBV-related hepatocarcinogenesis.

[Whether lowering intraocular pressure is needed for thyroid associated ophthalmopathy with intraocular hypertension]

Patients with thyroid associated ophthalmopathy often have elevated intraocular pressure. Patients and doctors are often confused about whether intraocular hypertension in thyroid associated ophthalmopathy needs to be lowered. There are several theories on the possible causes of this kind of increased intraocular pressure: restriction and compression of the globe by fibrotic and enlarged rectus muscles, increased episcleral venous pressure resulting from orbital congestion and venous outflow obstruction, and increased resistance to trabecular outflow. In addition, the patient's eye position and the device for measuring intraocular pressure also have great impacts on the accuracy of intraocular pressure measurement. At the same time, there are very few patients with thyroid associated ophthalmopathy combined with primary glaucoma. Therefore, whether patients with elevated intraocular pressure need to be treated depends on the specific clinical manifestations of the thyroid associated ophthalmopathy. Intraocular pressure of most patients can be lowered by active treatment for thyroid associated ophthalmopathy; antiglaucoma medical therapy may be necessary for patients whose intraocular pressure cannot be lowered; only very few cases of glaucoma require antiglaucoma drugs or surgery. (Chin J Ophthalmol, 2019, 55:811-813).

Review: The roles and functions of glutamine on intestinal health and performance of weaning pigs

The gut is composed of a single layer of intestinal epithelial cells and plays important roles in the digestion and absorption of nutrients, immune and barrier functions and amino acid metabolism. Weaning stress impairs piglet intestinal epithelium structural and functional integrities, which results in reduced feed intake, growth rates and increased morbidity and mortality. Several measures are needed to maintain swine gut development and growth performance after weaning stress. A large body of evidence indicates that, in weaning piglets, glutamine, a functional amino acid, may improve growth performance and intestinal morphology, reduce oxidative damage, stimulate enterocyte proliferation, modulate cell survival and death and enhance intestinal paracellular permeability. This review focuses on the effects of glutamine on intestinal health in piglets. The aim is to provide evidentiary support for using glutamine as a feed additive to alleviate weaning stress.

Health-related quality-of-life among patients with premature ovarian insufficiency: a systematic review and meta-analysis

PURPOSE

To systematically review studies investigating health-related quality-of-life (HrQoL) in patients with premature ovarian insufficiency (POI), to examine questionnaires used and to conduct a meta-analysis of control studies with normal ovarian function.

METHODS

Data sources: PubMed, Embase, Web of science, CNKI, and CQVIP, searched from inception until June 2018. The search strategy was a combination of medical (e.g. POI), subjective (e.g. well-being) and methodological (e.g. questionnaires) keywords. PRISMA guidelines were used to assess outcome data quality/validity by one reviewer, verified by a second reviewer. Risk of bias within studies was evaluated. A meta-analysis compared HrQoL in patients and non-patients. Due to measurement differences in the studies, the effect size was calculated as standard mean difference.

RESULTS

We identified 6869 HrQoL studies. Nineteen geographically diverse studies met inclusion criteria, dated from 2006, using 23 questionnaires. The meta-analysis included six studies with 645 POI participants (age 33.3 ± 5.47) and 492 normal-ovarian control subjects (age 32.87 ± 5.61). Medium effect sizes were found for lower overall HrQoL (pooled SMD = - 0.73, 95% CI - 0.94, - 0.51; I² = 54%) and physical function (pooled SMD = - 0.54, 95% CI - 0.69, - 0.39; I² = 55%). Heterogeneity was investigated. Effect sizes varied for sexual function depending on the measure (SMD = - 0.27 to - 0.74), overall HrQoL (SF-36) had the largest effect size (- 0.93) in one study. The effect sizes for psychological and social HrQoL were small.

CONCLUSION

POI is associated with low-to-medium effect size on HrQoL compared to normal ovarian controls. The greatest effects are found in general HrQoL and most sexual function areas. Condition-specific questionnaires and RCTs are recommended for further investigation.

[Orbital decompression for thyroid associated ophthalmopathy: transnasal endoscopic approach or external orbital approach?]

External orbital decompression, including medial wall, inferior wall, lateral wall and orbital fat decompression alone or in combination, has long been considered to be the standard treatment for thyroid related eye diseases. Deep lateral wall orbital decompression has better effect in the balance of eye position, correction of serious exophthalmos and severe oppression optic neuropathy. Recently, however, endoscopic orbital decompression is becoming increasingly popular with the development of endoscopic surgery technique in naso-orbit related diseases. Endoscopic orbital decompression has the advantages of avoiding an external incision scar. Nevertheless, the new method also has some disadvantages, for example, application limited to medial and inferior orbital wall orbital decompression, high incidence of esotropia, need for external lateral wall decompression and expensive cost for equipment. Both surgical approaches have advantages and disadvantages respectively for medial wall and inferior wall decompression. The operative result depends on the individualized surgical design and the experience of the surgeon rather than the choice of the surgical approach. As a result, the choice of the surgical approaches should be specifically based on the patient's conditions, patient's acceptance of the operation, experience of the surgeon and available resources. (Chin J Ophthalmol, 2018, 54: 484-487).

Seven Years of Experiences of Preclinical Experiments of Xeno-Heart Transplantation of Pig to Non-Human Primate (Cynomolgus Monkey)

BACKGROUND

The absolute shortage of donors compared with patients requiring transplantation is currently an unsolved problem, and the only possible solution may be xenotransplantation. To establish a successful clinical trial, a preclinical study using nonhuman primates is essential. Starting in November 2011, our team initiated heterotopic abdominal heart xenotransplantation, the first in the Republic of Korea. We present here the initial 7-year results.

METHODS

A total of 22 xenotransplantation procedures have been performed since 2011. Single transgenic pig (alpha-galactosidase transferase knockout [GalT KO], n = 16), double transgenic pig (GalT KO + CD46, n = 3, and GalT KO + CD39, n = 2), and triple transgenic pig (GalT KO + CD46 + CD70, n = 1) models were used. Our baseline regimen of immunosuppressants comprised CD154 ab, rituximab, anti-thymocyte globulin, tacrolimus, mycophenolate mofetil, and steroids.

RESULTS

The mean graft survival was 16 ± 16.27 days, and the mean graft survival was significantly longer in cases performed since 2014 (7.5 ± 8.03 days vs 24.67 ± 17.50; P = .01). Although the donor heart ischemic time was decreased per annum, no correlations could be found between ischemic time and survival days of the graft. Double or triple genetic manipulated hearts exhibited significantly better survival (11.63 ± 11.29 days vs 30.83 ± 20.34 days; P = .03). When the ratio of heart weight (grams) to nonhuman primate weight (kilograms) was lower, the results tended to be better (P < .05). The rate of immediate postoperative bleeding (9%, n = 2) causing death was relatively high in the earlier period, but there have been no serious surgical complications affecting graft survival since 2013.

CONCLUSIONS

Investigation of effective and optimal target genes for each organ to further progression toward better results is important. In addition, the immunosuppressive regimen needs to be further studied and constantly refined.

[Clinical diagnosis and management of cervical spondylotic amyotrophy]

Objective: To investigate the clinical characteristics and surgical treatment of cervical spondylotic amyotrophy. Methods: Thirteen patients(13 man) with proximal (10) and distal(3) cervical spondylotic amyotrophy between November 2014 and September 2016 were included in this study. The average age of the patients was 55 (range, 47-66) years. The sex, age, clinical course, type of amyotrophy, lesion segment and postdecompression improvement in muscle power were reviewed. Results: Of 13 cervical spondylotic amyotrophy patients, 9 were performed on with cervical disectomy, 2 were performed on with cervical posterior operation, 2 remainding patients received nonoperative treatment. Cervical spondylotic amyotrophy patients were followed up 6-22 (average 10.6) months, muscle power of 4 patients (all proximal-type)were improved completely (the average recovery time were 4.4 months), muscle power of 6 patients were improved uncompletely, 1 patients failed to improve, the 2 remainding patients received nonoperative treatment had no change. Conclusion: Cervical spondylotic amyotrophy as a rare type of cervical spondylotic disorder, It should distinguish cervical spondylotic amyotrophy from amyotrophic lateral sclerosis, especially in the early stage of amyotrophic lateral sclerosis. A surgical treatment is recommended as the first line of proximal-type CSA, especially those with serious compression. It is important that clinicians should be aware that distal-type CSA had a poor results, resulting in a lower lower satisfaction, especially those with no, or insignificant, sensory disturbance.

[Evaluation of a low dose imaging protocol on radiation exposure reduction in pediatric supraventricular tachycardia ablation procedure]

Objective: To evaluate the feasibility and efficiency of a low dose imaging protocol on reducing X-ray dose level in pediatric supraventricular tachycardia (SVT) ablation procedure. Method: Data were collected from 103 patients who underwent catheter ablation for SVT in Children's Hospital of Fudan University from January 2014 to October 2016 in terms of body weight, body surface area (BSA), SVT types, accessory pathway location, fluoroscopy time and the radiation dose (including AIR KERMA and dose area product) in a case observational study.The fluoroscopy protocols were operated at 36 nGy/frame and 10 frames/s (Standard group, n=47) from January 2014 to September 2015, 36 nGy/frame and 10 frames/s with removal of the grid (Grid-out group, n=24) from October 2015 to April 2016, as well as 23 nGy/frame and 4.0-7.5 frames/s without the grid (Grid-out plus low dose group, n=32) from May 2016 to October 2016, respectively.Comparisons among groups were performed by independent-sample t-test or one-way analysis of variance for normally distributed continuous variables, and χ(2) test for categorical variables. Result: The average body weight, BSA, fluoroscopy time and AIR KERMA of the three groups was (34±14) kg, (1.14±0.33) m(2,) (11±8) minutes and (12.97±12.43) mGy, respectively.No significant differences in body weight (F=2.551), BSA (F=2.359), SVT types (χ(2)=6.15), and accessory pathway location (χ(2)=3.438) were observed among these three groups (P>0.05). Images acquired by low dose protocol could provide enough information for procedures, and no complication occurred.The acute success rates were 100% in all of these three groups, and there was no significant difference in mean fluoroscopy time (F=0.004, P>0.05) among them.However, the radiation dose (AIR KERMA) in the Grid-out plus low dose group was much lower than that in the Standard group ((7.54±7.31) mGy vs. (16.25±12.08) mGy, F=6.112, P<0.01)). Conclusion: The new strategy of combination of low dose fluoroscopy protocol with removal of grid markedly reduced radiation exposure to children undergoing supraventricular tachycardia ablation while maintaining procedural efficacy and safety.

A systems approach identifies networks and genes linking sleep and stress: implications for neuropsychiatric disorders

Sleep dysfunction and stress susceptibility are comorbid complex traits that often precede and predispose patients to a variety of neuropsychiatric diseases. Here, we demonstrate multilevel organizations of genetic landscape, candidate genes, and molecular networks associated with 328 stress and sleep traits in a chronically stressed population of 338 (C57BL/6J × A/J) F2 mice. We constructed striatal gene co-expression networks, revealing functionally and cell-type-specific gene co-regulations important for stress and sleep. Using a composite ranking system, we identified network modules most relevant for 15 independent phenotypic categories, highlighting a mitochondria/synaptic module that links sleep and stress. The key network regulators of this module are overrepresented with genes implicated in neuropsychiatric diseases. Our work suggests that the interplay among sleep, stress, and neuropathology emerges from genetic influences on gene expression and their collective organization through complex molecular networks, providing a framework for interrogating the mechanisms underlying sleep, stress susceptibility, and related neuropsychiatric disorders.

Cardiac transplantation and concomitant coronary artery bypass grafting: our experiences in 11 cases

INTRODUCTION

The shortage of donor hearts for transplantation could be alleviated by including the hearts of older donors. Previous literature revealed similar early and medium-term survival outcomes compared with those of younger donors. This study presents our experience with patients who underwent orthotopic heart transplantation and concomitant coronary artery bypass grafting at our institution.

METHODS

We present our experience with 11 patients with end-stage cardiomyopathy (8 men and 3 women) undergoing orthotopic heart transplantation and concomitant coronary artery bypass grafting from September 2002 to November 2011 at our institute.

RESULTS

All 11 donor organs would otherwise have been rejected, depriving potential recipients of organ transplantation. Two patients received concurrent 2-coronary-artery bypass, and the other 9 patients received concurrent single-coronary-artery bypass during orthotopic heart transplantation. All patients had an uneventful postoperative course, with follow-up completed 3 to 128 months after cardiac transplantation and concomitant coronary artery bypass grafting surgery.

CONCLUSIONS

Our experiences suggest that donor hearts requiring coronary artery bypass grafting, which form a small but significant donor subgroup, can be used effectively and safely when matched to the recipients' age and medical condition.

Cloning and expression analysis of Wnt6 and Hox6 during intestinal regeneration in the sea cucumber Apostichopus japonicus

Many developmental genes play important roles in regeneration. Here, we cloned the two developmental genes, Wnt6 and Hox6, from Apostichopus japonicus by rapid amplification of cDNA ends (RACE) polymerase chain reaction (PCR). The Wnt6 full-length cDNA is 1140 bp long with a 1029-bp open reading frame encoding 342 amino acids. The deduced Wnt6 protein contained a 22-amino acid signal peptide and a 274-amino acid mature peptide. The Hox6 (AjHBOX6) full-length cDNA contained 1312 bp with a 966-bp open reading frame encoding 321 amino acids. Its deduced amino acid sequence included one homeodomain (60 amino acids) and three domains with low compositional complexity. Comparison and phylogenetic analysis revealed that Wnt6 and Hox6 in A. japonicus had the nearest relationship to those in sea urchins. Further expression analysis by real-time PCR showed that Wnt6 and Hox6 were apparently upregulated during intestine regeneration, which suggested that they were involved in the intestinal regeneration of sea cucumbers.

Dietary supplementation with N-carbamylglutamate increases the expression of intestinal amino acid transporters in weaned Huanjiang mini-pig piglets

Weaning is associated with reduced intestinal absorptive capacity in piglets. Our previous study indicated that dietary supplementation with N-carbamylglutamate (NCG) enhanced growth performance and improved intestinal function in weaned piglets. The present study was conducted to test the hypothesis that dietary supplementation with NCG may increase the growth performance of weaned piglets by regulating the expression of intestinal nutrient transporters, thus enhancing nutrient absorption. Twenty-four Huanjiang mini-pig piglets weaned at 21 d of age (3.17 ± 0.21 kg average BW) were randomly assigned to 2 dietary treatments consisting of a basal diet and the basal diet with 0.1% NCG supplementation for a 14-d period with 6 pens per treatment and 1 male and 1 female per pen. On d 14, 1 piglet was randomly selected from each pen for blood and tissue sampling. Dietary NCG supplementation enhanced (P < 0.05) growth rate and the efficiency of feed use in weaned Huanjiang mini-pig piglets. The NCG-supplemented diet increased (P < 0.05) mRNA expression levels of Slc6a19, Slc7a9, and Slc1a1 and the protein abundance of ASCT2, B(0)AT1, b(0,+)AT, y(+)LAT1, and EAAC1 in the jejunum. Furthermore, the contents of low density lipoprotein, ammonia, urea nitrogen, and AA as well as the activity of alkaline phosphatase in plasma were all altered (P < 0.05) by supplementation with NCG. These findings indicate that dietary supplementation with NCG may improve intestinal absorptive function in weaned piglets by increasing the expression of AA transporters in the intestine.