Add-On Chinese Medicine for Coronavirus Disease 2019 (ACCORD): A Retrospective Cohort Study of Hospital Registries

Deep representation learning from electronic medical records identifies distinct symptom based subtypes and progression patterns for COVID-19 prognosis

OBJECTIVE

Symptoms are significant kind of phenotypes for managing and controlling of the burst of acute infectious diseases, such as COVID-19. Although patterns of symptom clusters and time series have been considered the high potential prediction factors for the prognosis of patients, the elaborated subtypes and their progression patterns based on symptom phenotypes related to the prognosis of COVID-19 patients still need be detected. This study aims to investigate patient subtypes and their progression patterns with distinct features of outcome and prognosis.

METHODS

This study included a total of 14,139 longitudinal electronic medical records (EMRs) obtained from four hospitals in Hubei Province, China, involving 2,683 individuals in the early stage of COVID-19 pandemic. A deep representation learning model was developed to help acquire the symptom profiles of patients. K-means clustering algorithm is used to divide them into distinct subtypes. Subsequently, symptom progression patterns were identified by considering the subtypes associated with patients upon admission and discharge. Furthermore, we used Fisher's test to identify significant clinical entities for each subtype.

RESULTS

Three distinct patient subtypes exhibiting specific symptoms and prognosis have been identified. Particularly, Subtype 0 includes 44.2% of the whole and is characterized by poor appetite, fatigue and sleep disorders; Subtype 1 includes 25.6% cases and is characterized by confusion, cough with bloody sputum, encopresis and urinary incontinence; Subtype 2 includes 30.2% cases and is characterized by dry cough and rhinorrhea. These three subtypes demonstrate significant disparities in prognosis, with the mortality rates of 4.72%, 8.59%, and 0.25% respectively. Furthermore, symptom cluster progression patterns showed that patients with Subtype 0 who manifest dark yellow urine, chest pain, etc. in the admission stage exhibit an elevated risk of transforming into the more severe subtypes with poor outcome, whereas those presenting with nausea and vomiting tend to incline towards entering the milder subtype.

CONCLUSION

This study has proposed a clinical meaningful approach by utilizing the deep representation learning and real-world EMR data containing symptom phenotypes to identify the COVID-19 subtypes and their progression patterns. The results would be potentially useful to help improve the precise stratification and management of acute infectious diseases.

Research Progress of Immunomodulation on Anti-COVID-19 and the Effective Components from Traditional Chinese Medicine

SARS-CoV-2 has posed a threat to the health of people around the world because of its strong transmission and high virulence. Currently, there is no specific medicine for the treatment of COVID-19. However, for a wide variety of medicines used to treat COVID-19, traditional Chinese medicine (TCM) plays a major role. In this paper, the effective treatment of COVID-19 using TCM was consulted first, and several Chinese medicines that were frequently used apart from their huge role in treating it were found. Then, when exploring the active ingredients of these herbs, it was discovered that most of them contained flavonoids. Therefore, the structure and function of the potential active substances of flavonoids, including flavonols, flavonoids, and flavanes, respectively, are discussed in this paper. According to the screening data, these flavonoids can bind to the key proteins of SARS-CoV-2, 3CLpro, PLpro, and RdRp, respectively, or block the interface between the viral spike protein and ACE2 receptor, which could inhibit the proliferation of coronavirus and prevent the virus from entering human cells. Besides, the effects of flavonoids on the human body systems are expounded on in this paper, including the respiratory system, digestive system, and immune system, respectively. Normally, flavonoids boost the body's immune system. However, they can suppress the immune system when over immunized. Ultimately, this study hopes to provide a reference for the clinical drug treatment of COVID-19 patients, and more TCM can be put into the market accordingly, which is expected to promote the development of TCM on the international stage.

Willingness to accept COVID-19 vaccine and its determinants in Ethiopia: A systematic review and meta-analysis

Introduction

Vaccination is one of the most crucial strategies in the control of pandemics such as COVID-19. Although a couple of research has been conducted to assess the willingness of the population to accept the COVID-19 vaccine, the findings are inconsistent and inconclusive. This study aimed to assess the pooled willingness to uptake the COVID-19 vaccine and its determinants in Ethiopia.

Methods

Published and unpublished articles were accessed from various electronic databases and digital libraries. A random-effects model was used to estimate the pooled effect size with a 95% confidence interval. Inverse variance (I2) was used to visualize the presence of heterogeneity. Publication bias was assessed using funnel plots and Egger’s statistical test.

Results

A total of 2345 studies were identified from several databases and 16 studies fulfilled the eligibility criteria and were included in the final meta-analysis. The pooled magnitude of willingness to accept the COVID-19 vaccine in Ethiopia was 55.19% (95% CI: 42.91, 67.48). The current meta-analysis indicated that age greater than 25 years (OR=1.49, 95% CI: 1.12, 1.98) and having a good attitude towards the COVID-19 vaccine (3.57, 95% CI: 1.46, 8.72) were significantly associated with the COVID-19 vaccine uptake.

Conclusions and recommendations

In general, the magnitude of the COVID-19 vaccine acceptance rate among the public is unacceptably low in Ethiopia. Therefore, there is a need to build public trust through the provision of reliable and consistent information about vaccines using different media outlets.

Add-on Chinese medicine for hospitalized chronic obstructive pulmonary disease (CHOP): A cohort study of hospital registry

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death globally. The effect of Chinese medicine (CM) on mortality during acute exacerbation of COPD is unclear. We evaluated the real-world effectiveness of add-on personalized CM in hospitalized COPD patients with acute exacerbation.

METHODS

This is a retrospective cohort study with new-user design. All electronic medical records of hospitalized adult COPD patients (n = 4781) between July 2011 and November 2019 were extracted. Personalized CM exposure was defined as receiving CM that were prescribed, and not in a fixed form and dose at baseline. A 1:1 matching control cohort was generated from the same source and matched by propensity score. Primary endpoint was mortality. Multivariable Cox regression models were used to estimate the hazard ratio (HR) adjusting the same set of covariates (most prevalent with significant inter-group difference) used in propensity score calculation. Secondary endpoints included the change in hematology and biochemistry, and the association between the use of difference CMs and treatment effect. The prescription pattern was also assessed and the putative targets of the CMs on COPD was analyzed with network pharmacology approach.

RESULTS

4325 (90.5%) patients were included in the analysis. The mean total hospital stay was 16.7 ± 11.8 days. In the matched cohort, the absolute risk reduction by add-on personalized CM was 5.2% (3.9% vs 9.1%). The adjusted HR of mortality was 0.13 (95% CI: 0.03 to 0.60, p = 0.008). The result remained robust in the sensitivity analyses. The change in hematology and biochemistry were comparable between groups. Among the top 10 most used CMs, Poria (Fu-ling), Citri Reticulatae Pericarpium (Chen-pi) and Glycyrrhizae Radix Et Rhizoma (Gan-cao) were associated with significant hazard reduction in mortality. The putative targets of the CM used in this cohort on COPD were related to Jak-STAT, Toll-like receptor, and TNF signaling pathway which shares similar mechanism with a range of immunological disorders and infectious diseases.

CONCLUSION

Our results suggest that add-on personalized Chinese medicine was associated with significant mortality reduction in hospitalized COPD patients with acute exacerbation in real-world setting with minimal adverse effect on liver and renal function. Further randomized trials are warranted.

Ginseng as a Key Immune Response Modulator in Chinese Medicine: From Antipandemic History to COVID-19 Management

The cytokine storm plays an indispensable role in the severe and critical illness and death of the COVID-19 vulnerable population. Thus, suppressing the cytokine storm is of great significance. Ginseng is a traditional Chinese herb originally used for improving physiological conditions and ameliorating disease. Common throughout the history of ancient Chinese medicine is utilizing ginseng as a major ingredient to successfully fight various pandemics, and the most famous decoction is Renshen Baidu powder. In recent years, ginseng has been observed to provide preventive and therapeutic benefits in the treatment of various conditions by suppressing hyper-inflammation, inhibiting virus intrusion, and balancing the host's immunity. This paper summarizes the ancient Chinese medicine books' recordings of, the clinical practice of, and the laboratory exploration of ginseng for the treatment of pandemics and COVID-19. Ginseng and its active ingredients were found to downregulate inflammatory cytokines, upregulate anti-inflammatory cytokines, stimulate the secretion of the antiviral cytokine IFN-[Formula: see text], prevent viral entry and replication, and improve viral clearance. Furthermore, ginseng modulates both natural and acquired immunity during viral infection. Collectively, we propose that ginseng can act as a key immune response modulator against the cytokine storm of COVID-19. This paper may provide a new approach to discover specific medications using ginseng to combat COVID-19.

Practicing traditional Chinese medicine in the COVID-19 pandemic in Switzerland – an exploratory study

Background

To curb the spread of the first wave of the COVID-19 pandemic, the Swiss government declared a state of health emergency and ordered a legal restriction concerning the opening of healthcare institutions. In this study, we aimed to assess the proportion of traditional Chinese medicine (TCM) physicians and therapists who consulted patients regarding COVID-19 during the first wave of the pandemic in 2020 in Switzerland, as well as the extent to which COVID-19 affected their practices during the same period.

Methods

A retrospective study was performed by using a questionnaire from January to April 2021 among a random sample of TCM physicians and therapists based in Switzerland. The survey included questions on demographic characteristics, opening status of practices, channels of communication used for the medical encounter, and experience in managing the prevention, acute, and recovery stages of COVID-19 infection.

Results

Among the 320 participants, 76% consulted a patient regarding COVID-19 at least once. Overall, physicians and therapists consulted more patients during recovery (76.3%) and prevention (67.8%) than during the acute stage (19.8%) of the disease. Acupuncture was the most frequently used technique among TCM therapists and physicians consulting for prevention (80.4%) and recovery (92.5%), whereas Chinese pharmacopeia was the most used technique among those consulting for the acute stage (59.3%). Of those who closed their practices from March to April 2020 but kept consulting, telephone (30.4%) and home visits (29.9%) were the two principal methods of consultation.

Conclusions

The restriction concerning the opening of practices induced a loss of the health workforce, especially among TCM therapists. Nonetheless, TCM therapists and physicians consulted patients regarding COVID-19, especially during the recovery stage. As there is a demand for the use of TCM in the context of COVID-19, it raises the need for a better consideration of TCM in the Swiss health care system.

Plant Metabolites as SARS-CoV-2 Inhibitors Candidates: In Silico and In Vitro Studies

Since it acquired pandemic status, SARS-CoV-2 has been causing all kinds of damage all over the world. More than 6.3 million people have died, and many cases of sequelae are in survivors. Currently, the only products available to most of the world’s population to fight the pandemic are vaccines, which still need improvement since the number of new cases, admissions into intensive care units, and deaths are again reaching worrying rates, which makes it essential to compounds that can be used during infection, reducing the impacts of the disease. Plant metabolites are recognized sources of diverse biological activities and are the safest way to research anti-SARS-CoV-2 compounds. The present study computationally evaluated 55 plant compounds in five SARS-CoV-2 targets such Main Protease (Mpro or 3CL or MainPro), RNA-dependent RNA polymerase (RdRp), Papain-Like Protease (PLpro), NSP15 Endoribonuclease, Spike Protein (Protein S or Spro) and human Angiotensin-converting enzyme 2 (ACE-2) followed by in vitro evaluation of their potential for the inhibition of the interaction of the SARS-CoV-2 Spro with human ACE-2. The in silico results indicated that, in general, amentoflavone, 7-O-galloylquercetin, kaempferitrin, and gallagic acid were the compounds with the strongest electronic interaction parameters with the selected targets. Through the data obtained, we can demonstrate that although the indication of individual interaction of plant metabolites with both Spro and ACE-2, the metabolites evaluated were not able to inhibit the interaction between these two structures in the in vitro test. Despite this, these molecules still must be considered in the research of therapeutic agents for treatment of patients affected by COVID-19 since the activity on other targets and influence on the dynamics of viral infection during the interaction Spro x ACE-2 should be investigated.

Role of Traditional Chinese Medicine in Treating Severe or Critical COVID-19: A Systematic Review of Randomized Controlled Trials and Observational Studies

Background: The coronavirus disease 2019 (COVID-19) continues to spread globally. Due to the higher risk of mortality, the treatment of severe or critical patients is a top priority. Traditional Chinese medicine (TCM) treatment has played an extremely important role in the fight against COVID-19 in China; a timely evidence summary on TCM in managing COVID-19 is crucial to update the knowledge of healthcare for better clinical management of COVID-19. This study aimed to assess the effects and safety of TCM treatments for severe/critical COVID-19 patients by systematically collecting and synthesizing evidence from randomized controlled trials (RCTs) and observational studies (e.g., cohort).

Methods: We searched nine databases up to 19th March 2022 and the reference lists of relevant publications. Pairs of reviewers independently screened studies, extracted data of interest, and assessed risk of bias. We performed qualitative systematic analysis with visual presentation of results and compared the direction and distribution of effect estimates for each patient’s important outcome. We performed sensitivity analyses to observe the robustness of results by restricting analysis to studies with low risk of bias.

Results: The search yielded 217,761 records, and 21 studies (6 RCTs and 15 observational studies) proved eligible. A total of 21 studies enrolled 12,981 severe/critical COVID-19 patients with a mean age of 57.21 years and a mean proportion of men of 47.91%. Compared with usual supportive treatments, the effect estimates of TCM treatments were consistent in direction, illustrating that TCM treatments could reduce the risk of mortality, rate of conversion to critical cases, and mechanical ventilation, and showed significant advantages in shortening the length of hospital stay, time to viral clearance, and symptom resolution. The results were similar when we restricted analyses to low-risk-bias studies. No serious adverse events were reported with TCM treatments, and no significant differences were observed between groups.

Conclusion: Encouraging evidence suggests that TCM presents substantial advantages in treating severe/critical COVID-19 patients. TCM has a safety profile that is comparable to that of conventional treatment alone. TCMs have played an important role in China’s prevention and treatment of COVID-19, which sets an example of using traditional medicine in preventing and treating COVID-19 worldwide.

Potential Therapeutic Targets of Rehmannia Formulations on Diabetic Nephropathy: A Comparative Network Pharmacology Analysis

Background: Previous retrospective cohorts showed that Rehmannia-6 (R-6, Liu-wei-di-huang-wan) formulations were associated with significant kidney function preservation and mortality reduction among chronic kidney disease patients with diabetes. This study aimed to investigate the potential mechanism of action of common R-6 variations in a clinical protocol for diabetic nephropathy (DN) from a system pharmacology approach.

Study Design and Methods: Disease-related genes were retrieved from GeneCards and OMIM by searching “Diabetic Nephropathy” and “Macroalbuminuria”. Variations of R-6 were identified from a published existing clinical practice guideline developed from expert consensus and pilot clinical service program. The chemical compound IDs of each herb were retrieved from TCM-Mesh and PubChem. Drug targets were subsequently revealed via PharmaMapper and UniProtKB. The disease gene interactions were assessed through STRING, and disease–drug protein–protein interaction network was integrated and visualized by Cytoscape. Clusters of disease–drug protein–protein interaction were constructed by Molecular Complex Detection (MCODE) extension. Functional annotation of clusters was analyzed by DAVID and KEGG pathway enrichment. Differences among variations of R-6 were compared. Binding was verified by molecular docking with AutoDock.

Results: Three hundred fifty-eight genes related to DN were identified, forming 11 clusters which corresponded to complement and coagulation cascades and signaling pathways of adipocytokine, TNF, HIF-1, and AMPK. Five variations of R-6 were analyzed. Common putative targets of the R-6 variations on DN included ACE, APOE, CCL2, CRP, EDN1, FN1, HGF, ICAM1, IL10, IL1B, IL6, INS, LEP, MMP9, PTGS2, SERPINE1, and TNF, which are related to regulation of nitric oxide biosynthesis, lipid storage, cellular response to lipopolysaccharide, inflammatory response, NF-kappa B transcription factor activity, smooth muscle cell proliferation, blood pressure, cellular response to interleukin-1, angiogenesis, cell proliferation, peptidyl-tyrosine phosphorylation, and protein kinase B signaling. TNF was identified as the seed for the most significant cluster of all R-6 variations. Targets specific to each formulation were identified. The key chemical compounds of R-6 have good binding ability to the putative protein targets.

Conclusion: The mechanism of action of R-6 on DN is mostly related to the TNF signaling pathway as a core mechanism, involving amelioration of angiogenesis, fibrosis, inflammation, disease susceptibility, and oxidative stress. The putative targets identified could be validated through clinical trials.

Efficacy and mechanisms of traditional Chinese medicine for COVID-19: a systematic review

Since the outbreak of coronavirus disease 2019 (COVID-19), traditional Chinese medicine (TCM) has made an important contribution to the prevention and control of the epidemic. This review aimed to evaluate the efficacy and explore the mechanisms of TCM for COVID-19. We systematically searched 7 databases from their inception up to July 21, 2021, to distinguish randomized controlled trials (RCTs), cohort studies (CSs), and case–control studies (CCSs) of TCM for COVID-19. Two reviewers independently completed the screening of literature, extraction of data, and quality assessment of included studies. Meta-analysis was performed using Review Manager 5.4 software. Eventually, 29 RCTs involving 3060 patients and 28 retrospective studies (RSs) involving 12,460 patients were included. The meta-analysis demonstrated that TCM could decrease the proportion of patients progressing to severe cases by 55% and the mortality rate of severe or critical patients by 49%. Moreover, TCM could relieve clinical symptoms, curtail the length of hospital stay, improve laboratory indicators, and so on. In addition, we consulted the literature and obtained 149 components of Chinese medicinal herbs that could stably bind to antiviral targets or anti-inflammatory or immune-regulating targets by the prediction of molecular docking. It suggested that the mechanisms involved anti-virus, anti-inflammation, and regulation of immunity. Our study made a systematic review on the efficacy of TCM for COVID-19 and discussed the possible mechanisms, which provided clinical reference and theoretical basis for further research on the mechanism of TCM for COVID-19.

Natural products as a source of novel drugs for treating SARS-CoV2 infection

COVID-19, the infectious disease caused by the beta-corona virus SARS-CoV2, has posed a global health threat causing more than five million of deaths in the last two years in the world. Although the disease often presents with mild cold-like symptoms, it may have lethal consequences following thromboembolisms, hyperinflammation and cytokine storm eventually leading to pulmonary fibrosis and multiple organ failure.

Despite the progress made in the understanding of the SARS-CoV2 pathology and the clinical management of COVID-19, the viral illness is still a health concern since outbreaks continue to resurge due to the emergence of mutant variants of the virus that resist the vaccines.

Therefore, there is an urgent need for therapeutics that can block SARS-CoV2 viral transmission and the progression from infection to severe symptomatic illness.

Natural products could be a valuable source of drugs for the management of COVID-19 disease, particularly because they can act on multitargets and through different mechanisms including inhibition of biochemical pathways, epigenetic regulation of gene expression, modulation of immune response, regulation of pathophysiological stress response.

Here we present an overview of the natural products that possess SARS-CoV2 antiviral activity and the potential to benefit the management of COVID-19.

Efficacy and Safety of "Three Chinese Patent Medicines and Three TCM Prescriptions" for COVID-19: A Systematic Review and Network Meta-Analysis

Objective

To systematically evaluate the efficacy, safety, and precision of TMTP for COVID-19.

Methods

Randomized controlled trials and retrospective studies were searched in 11 electronic databases. This network meta-analysis included trials using TMTP to treat patients with COVID-19. The traditional pairwise meta-analysis was done by using Stata 15, and Bayesian network meta-analysis was done with WinBUGS.

Results

18 trials were included with 2036 participants and 7 drugs. The results showed that LHQW had the most significant effects on improving expectoration, shortness of breath, sore throat, nausea, emesis, inappetence, muscle soreness, and headache, and it could produce the least adverse reactions. XBJ was the best drug for fever, fatigue, and diarrhea, which showed great advantages in lowering WBC levels. XFBD was the most effective drug for cough and chest distress, which had the least exacerbation rate. JHQG was the most effective for rhinobyon and rhinorrhea, while QFPD was the best drug in decreasing CRP levels.

Conclusion

This study was the first most large-scale and comprehensive research of TMTP for COVID-19. The results showed that LHQW had good efficacy without obvious adverse reactions. Therefore, we believe that it should be firstly recommended for COVID-19 treatment. In addition, XBJ is recommended for patients with a severe fever, fatigue, and diarrhea, and JHQG is recommended for patients with obvious rhinobyon and rhinorrhea; then, XFBD is recommended for patients with cough and chest tightness as the main manifestation. Our findings will help experts develop new COVID-19 treatment guidelines to better guide clinical medication for protecting the health of COVID-19 patients.

Diversity and molecular network patterns of symptom phenotypes

Symptom phenotypes have continuously been an important clinical entity for clinical diagnosis and management. However, non-specificity of symptom phenotypes for clinical diagnosis is one of the major challenges that need be addressed to advance symptom science and precision health. Network medicine has delivered a successful approach for understanding the underlying mechanisms of complex disease phenotypes, which will also be a useful tool for symptom science. Here, we extracted symptom co-occurrences from clinical textbooks to construct phenotype network of symptoms with clinical co-occurrence and incorporated high-quality symptom-gene associations and protein-protein interactions to explore the molecular network patterns of symptom phenotypes. Furthermore, we adopted established network diversity measure in network medicine to quantify both the phenotypic diversity (i.e., non-specificity) and molecular diversity of symptom phenotypes. The results showed that the clinical diversity of symptom phenotypes could partially be explained by their underlying molecular network diversity (PCC = 0.49, P-value = 2.14E-08). For example, non-specific symptoms, such as chill, vomiting, and amnesia, have both high phenotypic and molecular network diversities. Moreover, we further validated and confirmed the approach of symptom clusters to reduce the non-specificity of symptom phenotypes. Network diversity proposes a useful approach to evaluate the non-specificity of symptom phenotypes and would help elucidate the underlying molecular network mechanisms of symptom phenotypes and thus promotes the advance of symptom science for precision health.

He-Jie-Shen-Shi Decoction as an Adjuvant Therapy on Severe Coronavirus Disease 2019: A Retrospective Cohort and Potential Mechanistic Study

Combination therapy using Western and traditional Chinese medicines has shown notable effects on coronavirus disease 2019 (COVID-19). The He-Jie-Shen-Shi decoction (HJSS), composed of Bupleurum chinense DC., Scutellaria baicalensis Georgi, Pinellia ternata (Thunb.) Makino, Glycyrrhiza uralensis Fisch. ex DC., and nine other herbs, has been used to treat severe COVID-19 in clinical practice. The aim of this study was to compare the clinical efficacies of HJSS combination therapy and Western monotherapy against severe COVID-19 and to study the potential action mechanism of HJSS. From February 2020 to March 2020, 81 patients with severe COVID-19 in Wuhan Tongji Hospital were selected for retrospective cohort study. Network pharmacology was conducted to predict the possible mechanism of HJSS on COVID-19-related acute respiratory distress syndrome (ARDS). Targets of active components in HJSS were screened using the Traditional Chinese Medicine Systems Pharmacology (TCMSP) and PharmMapper databases. The targets of COVID-19 and ARDS were obtained from GeneCards and Online Mendelian Inheritance in Man databases. The key targets of HJSS in COVID-19 and ARDS were obtained based on the protein–protein interaction network (PPI). Kyoto Encyclopedia of Genes and Genomes analysis (KEGG) was conducted to predict the pathways related to the targets of HJSS in COVID-19 and ARDS. A “herb-ingredient-target-pathway” network was established using Cytoscape 3.2.7. Results showed that the duration of the negative conversion time of nucleic acid was shorter in patients who received HJSS combination therapy. HJSS combination therapy also relieved fever in patients with severe COVID-19. Network pharmacology analysis identified interleukin (IL) 6, tumor necrosis factor (TNF), vascular endothelial growth factor A (VEGFA), catalase (CAT), mitogen-activated protein kinase (MAPK) 1, tumor protein p53 (TP53), CC-chemokine ligand (CCL2), MAPK3, prostaglandin-endoperoxide synthase 2 (PTGS2), and IL1B as the key targets of HJSS in COVID-19-related ARDS. KEGG analysis suggested that HJSS improved COVID-19-related ARDS by regulating hypoxia-inducible factor (HIF)-1, NOD-like receptor, TNF, T cell receptor, sphingolipid, PI3K-Akt, toll-like receptor, VEGF, FoxO, and MAPK signaling pathways. In conclusion, HJSS can be used as an adjuvant therapy on severe COVID-19. The therapeutic mechanisms may be involved in inhibiting viral replication, inflammatory response, and oxidative stress and alleviating lung injury. Further studies are required to confirm its clinical efficacies and action mechanisms.

SYmptom-Based STratification of DiabEtes Mellitus by Renal Function Decline (SYSTEM): A Retrospective Cohort Study and Modeling Assessment

Background: Previous UK Biobank studies showed that symptoms and physical measurements had excellent prediction on long-term clinical outcomes in general population. Symptoms and signs could intuitively and non-invasively predict and monitor disease progression, especially for telemedicine, but related research is limited in diabetes and renal medicine. Methods: This retrospective cohort study aimed to evaluate the predictive power of a symptom-based stratification framework and individual symptoms for diabetes. Three hundred two adult diabetic patients were consecutively sampled from outpatient clinics in Hong Kong for prospective symptom assessment. Demographics and longitudinal measures of biochemical parameters were retrospectively extracted from linked medical records. The association between estimated glomerular filtration rate (GFR) (independent variable) and biochemistry, epidemiological factors, and individual symptoms was assessed by mixed regression analyses. A symptom-based stratification framework of diabetes using symptom clusters was formulated by Delphi consensus method. Akaike information criterion (AIC) and Bayesian information criterion (BIC) were compared between statistical models with different combinations of biochemical, epidemiological, and symptom variables. Results: In the 4.2-year follow-up period, baseline presentation of edema (-1.8 ml/min/1.73m2, 95%CI: -2.5 to -1.2, p < 0.001), epigastric bloating (-0.8 ml/min/1.73m2, 95%CI: -1.4 to -0.2, p = 0.014) and alternating dry and loose stool (-1.1 ml/min/1.73m2, 95%CI: -1.9 to -0.4, p = 0.004) were independently associated with faster annual GFR decline. Eleven symptom clusters were identified from literature, stratifying diabetes predominantly by gastrointestinal phenotypes. Using symptom clusters synchronized by Delphi consensus as the independent variable in statistical models reduced complexity and improved explanatory power when compared to using individual symptoms. Symptom-biologic-epidemiologic combined model had the lowest AIC (4,478 vs. 5,824 vs. 4,966 vs. 7,926) and BIC (4,597 vs. 5,870 vs. 5,065 vs. 8,026) compared to the symptom, symptom-epidemiologic and biologic-epidemiologic models, respectively. Patients co-presenting with a constellation of fatigue, malaise, dry mouth, and dry throat were independently associated with faster annual GFR decline (-1.1 ml/min/1.73m2, 95%CI: -1.9 to -0.2, p = 0.011). Conclusions: Add-on symptom-based diagnosis improves the predictive power on renal function decline among diabetic patients based on key biochemical and epidemiological factors. Dynamic change of symptoms should be considered in clinical practice and research design.

Global REnal Involvement of CORonavirus Disease 2019 (RECORD): A Systematic Review and Meta-Analysis of Incidence, Risk Factors, and Clinical Outcomes

Introduction: The quantitative effect of underlying non-communicable diseases on acute kidney injury (AKI) incidence and the factors affecting the odds of death among coronavirus disease 2019 (COVID-19) AKI patients were unclear at population level. This study aimed to assess the association between AKI, mortality, underlying non-communicable diseases, and clinical risk factors. Methods: A systematic search of six databases was performed from January 1, 2020, until October 5, 2020. Peer-reviewed observational studies containing quantitative data on risk factors and incidence of renal manifestations of COVID-19 were included. Location, institution, and time period were matched to avoid duplicated data source. Incidence, prevalence, and odds ratio of outcomes were extracted and pooled by random-effects meta-analysis. History of renal replacement therapy (RRT) and age group were stratified for analysis. Univariable meta-regression models were built using AKI incidence as dependent variable, with underlying comorbidities and clinical presentations at admission as independent variables. Results: Global incidence rates of AKI and RRT in COVID-19 patients were 20.40% [95% confidence interval (CI) = 12.07-28.74] and 2.97% (95% CI = 1.91-4.04), respectively, among patients without RRT history. Patients who developed AKI during hospitalization were associated with 8 times (pooled OR = 9.03, 95% CI = 5.45-14.94) and 16.6 times (pooled OR = 17.58, 95% CI = 10.51-29.38) increased odds of death or being critical. At population level, each percentage increase in the underlying prevalence of diabetes, hypertension, chronic kidney disease, and tumor history was associated with 0.82% (95% CI = 0.40-1.24), 0.48% (95% CI = 0.18-0.78), 0.99% (95% CI = 0.18-1.79), and 2.85% (95% CI = 0.93-4.76) increased incidence of AKI across different settings, respectively. Although patients who had a kidney transplant presented with a higher incidence of AKI and RRT, their odds of mortality was lower. A positive trend of increased odds of death among AKI patients against the interval between symptom onset and hospital admission was observed. Conclusion: Underlying prevalence of non-communicable diseases partly explained the heterogeneity in the AKI incidence at population level. Delay in admission after symptom onset could be associated with higher mortality among patients who developed AKI and warrants further research.