Canis lupus) to dogs (Canis lupus familiaris) is a debated ecological topic. Changes in food and environment are major divergences in the domestication of dogs. Gut microbes play an important role in animal adaptation to the food and environmental changes. In this study, shotgun sequencing was performed to compare the species diversity and functional diversity of gut microbes in wild wolves , captive wolves , and domestic dogs . The results found that Bacteroidetes, Firmicutes, Fusobacteria, Proteobacteria and Actinobacteria were the most abundant phyla and Bacteroides, Fusobacterium, Prevotella, Megamonas, Paraprevotella, Faecalibacterium, Clostridium were the most abundant genera in the gut of wolves and dogs. Groups CLW, CLC and CLF have shown significant difference in gut microbial species diversity and functional diversity. Bacteroides, Fusobacterium and Faecalibacterium were most abundant genera in groups CLW, CLC and CLF, respectively. Their abundance varied significantly among groups. Compared to the wild wolves, the intestinal microbiol genes of domestic dogs were significantly enriched in the carbohydrate metabolism pathway of KEGG database. One hundred and seventy-seven enzymes were detected with significantly higher abundance in group CLF than that in group CLW, and 49 enzymes showed extremely significant higher abundance in group CLF than that in group CLW (q < 0.01) base on the function abundance annotated in CAZy database. It is noteworthy that there were also significant differences in the abundance of 140 enzymes between groups CLC and CLW (q < 0.05). Clustering analysis based on both the species and the function abundance of intestinal microbiota all found that groups CLC and CLF clustered into one branch, while samples from group CLW clustered into the other branch. This result suggests that captive wolves are more similar to domestic dogs than wild wolves in both species composition and function composition of intestinal microbiota.Adaptation during the domestication from wolves ( Canis lupus familiaris) is the first known domesticated animal. Genetic, behavioral and morphological studies have shown that the domestic dog is descended from wolves , 4 captive wolves  and 4 domestic dogs  were collected in winter in Hulun Lake Nature Reserve in Inner Mongolia, China . Wild woGenomic DNA was extracted from fecal samples using the QIAamp DNA Fecal Genomic DNA Extraction Kit (Qiagen). The quality and concentration of DNA were quantified using NanoDrop 2000c. The purity and integrity of DNA were examined by agarose gel electrophoresis. The qualified DNA samples were randomly cut into fragments of approximately 350 bp in length by Covaris ultrasonic fragmentation, and the libraries were prepared by PCR amplification. Agilent 2100 was used to detect the INSERT size of the library. Qubit 3.0 and Q-PCR were used to accurately quantify the effective concentration of the library (library effective concentration >3 nM). After the library inspection, different libraries were pooling according to the effective concentration and target data amount and sequenced by using Illumina HiSeq 2500.Reads with low quality base and high N-base ratio and with an adapter overlap exceeding the threshold were removed from raw data. SoapAligner software was used for alignment with the host database to filter out the reads that may come from the host and to filter for the clean data. Assembly was performed using SOAP denovo assembly software. For a single sample, K-mer = 55 was selected for assembly to obtain the assembly sequence (Scaffolds). Scaffolds were disrupted from the N junction to obtain N-free sequence fragments (Scaftigs). The clean data of each sample after quality control was aligned to the Scaftigs of each sample to filter out the PE reads that were not utilized. The unused PE reads of each sample were pooled together, and K-mer = 55 was selected for mixed assembly (NOVO_MIX). The N-free Scaftigs sequence was obtained by interrupting the mixed assembled Scaffolds from the N junction. For Scaftigs generated by single sample and hybrid assembly, fragments below 500 bp were filtered out for statistical analysis and subsequent gene prediction.Open reading frames (ORFs) were predicted by using MetaGeneMark software from Scaftigs (≥500 bp), and ORFs less than 100 nt in length were filtered out. CD-HIT software was used to remove the redundant ORFs and to obtain the non-redundant initial gene catalogue. Clustering was performed with identity = 95% and coverage = 90%, and the longest sequence was selected as the representative sequence. SoapAligner was used to align the clean data of each sample to the initial gene catalogue, and the number of aligned reads in each sample were calculated. The genes whose supporting reads ≤2 in each sample were filtered out to obtain the gene catalogue (unigenes) for subsequent analysis. Based on the number of reads and the length of the alignment, the abundance information of each gene in each sample were calculated with the formula The DIAMOND software was used to align unigenes to bacteria, fungi, archaea and viruses sequences selected from the NR database of NCBI . The alignment results of evalues ≤  were selected for species annotation. The LCA algorithm of MEGAN software took the taxonomic level before the first branch as the species annotation information of the sequence. Based on the LCA annotation results and gene abundances, the abundance information of each sample at each taxonomic level  was obtained. The abundance of a species in a sample was the sum of the abundance of genes annotated to that species. Alpha diversity (Shannon index and Simpson index) test of each group was performed by using Qiime software. Beta diversity, estimated with Bray-Curtis metrics, was calculated using R (version 2.15.3) to compare the composition of microbial communities among different groups. The relative abundance of different groups at each taxonomic level were compared by Wilcoxon signed-rank test and MetaStat test. Anosim analysis, PCA and NMDS dimensionality reduction analysis, cluster analysis based on Bray-Curtis distance were performed to test for the similarity among the groups. Linear discriminant analysis effect size (LEfSe) analysis was performed to search for the representative biomarkers.The Unigenes was aligned to the KEGG, eggNOG, and CAZy databases using the DIAMOND software . The KEGG database was divided into 6 levels , the eggNOG database was divided into 3 levels , and the CAZy database was divided into 3 levels . The comparison result with the highest score (one HSP >60 bits) was selected for subsequent analysis. The relative abundances of different functional levels were counted . The differences in functional abundance between the groups were compared by MetaStat test. The similarity of annotation function between groups was compared by PCA, NMDS and cluster analysis based on Bray-Curtis distance.A total of 58,820.98 Mbp clean data was obtained by Illumina HiSeq sequencing and preprocessing. Data effective was above 99.96%. By SOAP denovo assembly, a total length of 761.93Mbp and a total number of 453,461 Scaftigs were obtained for statistical analysis and subsequent gene prediction. By using MetaGeneMark for ORF prediction, a total of 418,264 ORFs were obtained and the total length of the ORFs  was 264.15 Mbp .p < 0.05; The abundance of annotated unigenes in group CLF  was higher than that of group CLC  and significantly higher than that of group CLW . The abundance of Fusobacteria in group CLC (16.49%) was higher than that in group CLW (12.14%) and was significantly higher than that in group CLF .The phyla with the highest abundance were Bacteroidetes, Firmicutes, Fusobacteria, Proteobacteria and Actinobacteria. Bacteroidetes accounted for more than 40% in each sample while Firmicutes (7–37%) and Fusobacteria (1–25%) showed great differences in each sample . Wilcoxop > 0.05). The abundance of Fusobacteriaceae in group CLC was higher than that in group CLW and significantly higher than that in group CLF (p < 0.05). The abundance of Ruminococcaceae in group CLF was significantly higher than that in groups CLC and CLW (p < 0.05).The highest abundant families were Bacteroidaceae, Prevotellaceae, Fusobacteriaceae, Selenomonadaceae, Ruminococcaceae . WilcoxoBacteroides, Fusobacterium, Prevotella, Megamonas, Paraprevotella, Faecalibacterium, Clostridium, Campylobacter, Sutterella, Escherichia were the genera with higher abundance (Bacteroides in group CLW was higher than that in groups CLC and CLF (p > 0.05). The abundance of Fusobacterium in group CLC was higher than that in group CLW and significantly higher than that in group CLF (p < 0.05). The abundance of Paraprevotella in group CLW was significantly higher than that in groups CLC and CLF (p < 0.05). The abundance of Faecalibacterium in group CLF was significantly higher than that in groups CLC and CLW (p < 0.05).bundance . The abuPrevotella sp. CAG:891 and Fusobacterium perfoetens were the most abundant bacteria in the gut of wolves and domestic dogs . At the same time, the abundance of a variety of bacteria with high abundance in genera Clostridium and Collinsella were significantly lower in group CLW. For instance, the abundance of Clostridium sp. AT4 in group CLF was higher than that in group CLC and significantly higher than that in group CLW (p < 0.05). The abundance of the Collinsella intestinalis was higher in the group CLC than in the group CLF and significantly higher than that in the group CLW (p < 0.05). On the contrary, the overall abundance of genus Bacteroides in group CLW was higher than that in the other two groups. However, the relative abundance of several bacteria in the genus Bacteroides was not consistent among the three groups. For example, the relative abundance of Bacteroides massiliensis in group CLW was higher than that in group CLC and significantly higher than that in group CLF (p < 0.01). The relative abundance of Bacteroides vulgatus and Bacteroides fragilis in group CLW was significantly higher than that in group CLC and group CLF (p < 0.05). On the contrary, the relative abundances of Bacteroides stercoris and Bacteroides uniformis in groups CLF and CLC were significantly higher than those in group CLW (p < 0.05). In addition, the abundance of Anaerobiospirillum succiniciproducens with a higher abundance in group CLW was higher than that in the group CLF and significantly higher than that in the group CLC (p < 0.05). The abundance of Faecalibacterium prausnitzii in group CLF was significantly higher than that in groups CLC and CLW (p < 0.05). It was intersting that the abundance of Escherichia coli in groups CLC and CLF was higher than that in group CLW, although the difference was not significant , including Bacteroides caecimuris, Bacteroides fragilis, Bacteroides helcogenes, Bacteroides oleiciplenus and Bacteroides sartorii. Biomarkers of group CLF were mainly in phylum Firmicutes, included genus Faecalibacterium in the family Ruminococcaceae , genus Megamonas in the family Selenomonadaceae , as well as Blautia hansenii in the family Lachnospiraceae and Clostridium sp. AT4 in the family Clostridiaceae. Biomarkers of group CLC were mainly the genus Fusobacterium in the family Fusobacteriaceae, phylum Fusobacteria, including Fusobacterium ulcerans and Fusobacterium varium , genetic information processing (4.53%) and environmental information processing (3.79%). Among them, carbohydrate metabolism, amino acid metabolism, nucleotide metabolism, metabolism of cofactors and vitamins and energy metabolism in metabolism pathway, membrane transport in environmental information processing pathway and translation in genetic information processing pathway enriched the highest number of genes .In the eggNOG database, a large number of genes were functionally unknown (28.37% of unigenes). Functional clusters with a higher number of enriched genes included Replication, recombination and repair, cell wall/membrane/envelope biogenesis, amino acid transport and metabolism, carbohydrate transport and metabolism, translation, ribosome structure and biogenesis, transcription, inorganic ion transport and metabolism and energy production and conversion . In the q < 0.05); the abundance of environmental adaptation in organic systems and infectious diseases: bacterial pathway in human diseases was significantly higher in group CLW than in group CLC (q < 0.05); the abundance of carbohydrate metabolism, lipid metabolism, amino acid metabolism, biosynthesis of other secondary and metabolism of other amino acids in metabolism, signal transduction in environmental information processing, cell growth and death in cellular processes, endocrine and metabolic diseases in human diseases, and endocrine system in organismal systems were significantly higher in group CLF than in group CLW , the abundance of carbohydrate metabolism, biosynthesis of other secondary metabolites, metabolism of other amino acids in metabolism, signal transmission in environmental information processing, transcription in genetic information processing, cardiovascular diseases, drug resistance: antimicrobial and neurodegenerative diseases in human diseases, and aging and endocrine system pathways in organic systems were significantly higher in CLC group than in CLW group  was unique to the CLF group, which was mainly involved in the metabolism of cysteine and methionine and amino acid biosynthesis. In the carbon metabolism pathway, malate synthase (EC:2.3.3.9), glutamate--glyoxylate aminotransferase (EC:2.6.1.4 2.6.1.2 2.6.1.44), isocitrate lyase (EC:4.1.3.1), acetoacetyl-Coa Reductase (EC:1.1.1.36) and some other enzymes were only annotated in group CLF, but 3-hydroxyButyryl-Coa dehydratase (EC:4.2.1.55) was only annotated in the group CLW . In the q < 0.05), but no significant difference was detected between groups CLC and CLF and between groups CLC and CLW (q < 0.05).Among the functions annotated in the eggNOG database (level 1), the annotation results of groups CLW and CLF were significantly different in the pathways of carbon transport and metabolism, amino acid transport and metabolism, nucleoside transport and metabolism, inorganic ion transport and metabolism, signal transmission mechanisms and transcription, and posttranslational modification . Sixty enzymes were extremely significantly different between groups CLF and CLW (MetaStat test q < 0.01). The abundances of 49 enzymes in the group CLF, such as alpha-L-arabinofuranosidase (EC 3.2.1.55), beta-xylosidase (EC 3.2.1.37), alpha-glucosidase (EC 3.2.1.20), alpha-1,2-L-arabinofuranosidase (EC 3.2.1.-), beta-1,3-xylosidase (EC 3.2.1.-), beta-glucosidase (EC 3.2.1.21), beta-primeverosidase (EC 3.2.1.149), beta-galactosidase (EC 3.2.1.23), endoglucanase (EC 3.2.1.4), were extremely significantly higher than that of the group CLW (MetaStat test q < 0.01). Significant differences in the abundance of 140 enzymes were detected between groups CLC and CLW, and 108 of these enzymes had a significantly higher abundance in the group CLC than in the group CLW (MetaStat test q < 0.05). Only 27 enzymes were significantly different between groups CLF and CLC , the abundance of 244 enzymes were significantly different between the groups CLF and CLW, and 177 of these enzymes had a significantly higher abundance in the group CLF than in the group CLW  and Fusobacterium were biomarkers of group CLW and group CLC, respectively, while the biomarkers of group CLF were mainly Faecalibacterium and Megamonas. Bacteroides maintain a complex and generally beneficial relationship with the host when retained in the gut, but when they escape this environment they can cause pathology in humans . Faecalibacterium associated to glucose fermentation was significantly increased in the feces of domestic dogs, which may be related to the complex polysaccharide diet of domestic dogs . In addition, the annotated genes in group CLF were also significantly enriched in the amino acid metabolism, glycan biosynthesis and metabolism pathways. In contrast, more genes annotated by gut microbes of wild wolves were enriched in immune system, environmental adaptation and other pathways. This reflected the adaption of gut microbes to living environment. Wild wolves likely have periods of starvation, encounter a higher pathogen load, and have significant more exercise compared to the wild counterparts, all of which can influence the microbiome. Annotation results in the professional carbohydrate metabolism database (CAZy database) further revealed the differences in carbohydrate metabolism among gut microbiota of wild wolves, captive wolves and domestic dogs. In the level ec of CAZy database, 177 enzymes were detected with significantly higher abundance in group CLF than that in group CLW (q < 0.05) and 48 enzymes of them showed extremely significant differences between groups CLF and CLW . This fully indicated that due to the increase of starch compounds in food, the intestinal microbiota of domestic dogs showed significant adaptation to the increase of carbohydrate. Interestingly, significant differences in the abundance of 140 enzymes were detected between the groups CLC and CLW (q < 0.05). However, there were few differences between the groups CLC and the CLF. This indicated that the intestinal microbiome of wolves in captivity may have changed significantly from that in the wild due to the differences in the living environment and food.Previous studies found that because the canine diet contained more complex polysaccharides than the wolf’s diet, the abundance of functional genes involved in valine, leucine and isoleucine biosynthesis and nitrogen metabolism in the canine gut microbiota and the abundance of genes encoding glycosyltransferase family 34, rum-binding Module family 25 and GH family 13 were significantly higher than those of captive wolves. At the same time, the abundances of six glycosyltransferases and five GHs which mainly act on the metabolic pathways of starch and sucrose in domestic dogs were also significantly higher than those in captive wolves . In thisSeveral previous studies explored the differences of gut microbiota between wild and captive mammals  and discThe ability of wild animals to survive on food that may be infected by pathogens, and to show immunity to various diseases, is inseparable from their complex gut microbial community . By specSample collection is difficult due to the small population, large habitat and covert activity of wild carnivores. Therefore, the small sample size is a major limitation of this study. In order to minimizing environmental differences on gut microbes, the samples of captive wolves living on the same grassland as wild wolves were collected. To reduce differences in gut microbes due to sample numbers, sample numbers for captive wolves and domestic dogs were designed with reference to the number of wild wolves. The small sample number and the lack of a standardized diet of animals have limited the further in-depth analysis of the data obtained here. However, as the first attempt to compare the gut microbial species and functional diversity of wild wolves, captive wolves and domestic dogs, this study provide a scientific reference for future studies to explore the ecological adaptive mechanism in the captive and domestic process of wild predators.https://www.ncbi.nlm.nih.gov/, PRJNA871950.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found at: The animal study was reviewed and approved by Bioethics Committee of Qufu Normal University.LC: conceived, designed, performed the experiments and collected samples. LC and MS: wrote the paper. MS, DX, ZG, YS, SW, and YZ: analyzed the data and modify the manuscript. All authors contributed to the article and approved the submitted version.This study is supported by the National Natural Science Foundation of China (31400473).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The purpose of this article is to assess the relationship between serum albumin level and long length of stay (LOS) of inpatients with acute heart failure (AHF) in the intensive care unit (ICU).We retrospectively analyzed data of 2280 patients with AHF from the medical information mart for intensive care IV (the MIMIC-IV) database. Multivariate logistic regression was performed to evaluate the association between serum albumin and long LOS, and the development of the predictive model was based on independent predictors of long LOS.P for trend <0.001), and serum albumin could predict long LOS . Based on independent predictors, including respiratory failure , WBC , creatinine , glucose , lactic acid , and albumin , identified by multivariable logistic regression analysis, we developed the nomogram to predict the probability of long LOS of AHF patients in the ICU. The nomogram accurately predicted the probability of long LOS . The calibration suggested the predictive probability was highly consistent with the actual probability of long LOS. Decision curve analysis (DCA) also suggested that the nomogram was applicable in the clinic.According to the statistical results, A negative linear relationship was presented between albumin and long LOS of AHF patients in the ICU (Serum albumin level was negatively associated with LOS among AHF patients. The predictive model based on serum albumin has predictive value for evaluating the length of stay in AHF patients. As a common and growing medical problem, heart failure (HF) is one of the most frequent causes of admission and hospital mortality . The limAs an inexpensive and powerful indicator, serum albumin is an essential protein in the human body produced by the liver and often used to evaluate the prognosis of a variety of diseases, such as HF, acute pulmonary embolism, diabetic nephropathy, and patients with severe illness in ICU –8. CurreTherefore, In the present study, we analyzed the association between serum albumin level and LOS of patients with AHF from the medical information mart for intensive care IV (the MIMIC-IV) database. what’s more, based on albumin, we developed a prediction model that can predict the length of hospital stay.Fig 1. This study was approved by the Institutional Review Boards of Beth Israel Deaconess Medical Center  and the Massachusetts Institute of Technology , and the requirement for patient informed consent was waived due to the study design.Two thousand, and two hundred and eighty AHF patients whose years more than 18 were enrolled from the MIMIC-IV database  in our study. The data provided by the above database was the original data. Thus, data used for the study was retrieved from MIMIC-IV by author Liu (ID: 9008147), who had completed the online training course of the National Institutes. The selection process of study participants is shown in The exposure variable of the present study was serum albumin, and it was defined as the first serum albumin level at the time of admission to ICU. The outcome variable was the LOS of ICU, A "long length of stay" in the ICU was considered when more than 7 days. Categorical variables  and continuous variables were collected for all patients, including relevant demographic variables  and blood biomarkers . For patients who had been admitted to the ICU more than once, the clinical data of their first admission to the ICU was collected.X2 test. Multivariate logistic regression with a significant difference of 0.05 was used to build the final models, and nomogram was developed by results of multivariate logistic regression. Discriminative capacity, calibration ability, and clinical effectiveness were used to evaluate nomogram. The concordance index (C-index) was measured to quantify the discrimination capacity of the nomogram, and C-index is equal to the area under the receiver operating characteristics curve (AUC-ROC) in logistic regression analysis. A calibration plot was drawn to evaluate the prediction accuracy of the nomogram. Decision curve analysis (DCA) was performed to evaluate Clinical effectiveness. All statistical analyses were performed using the software Stata15  and package R (http://www.Rproject.org). All P-value <0.05 were significant.Continuous variables were represented by mean ± standard deviation or median  in the table. If the test of normality and the homogeneity test of variance is performed, the T-test is appropriate, otherwise, the Kruskal Wallis test is appropriate. Categorical variables are presented as a percentage in the tables and compared using the P < 0.05), all variables were not significant (P > 0.05) (Table 1).The mean age of 2280 patients were 69.88 ± 13.72, and men made up 56.80% of the total. Compared with the group with ICU stay less than 7 days, patients of the group with ICU stay longer than 7 days were more likely to have respiratory failure, sepsis, and high use ratio of nitroglycerin, and increased levels of blood glucose, creatinine, Bun, WBC, calcium, lactic acid value, and decreased level of albumin value . Except for the above variables (P <0.001). the OR (95% CI) for long LOS across the albumin quartile were 0.558 (0.402–0.774), 0.532 (0.370–0.765), and 0.455 (0.312–0.662), compared with the first quartile of albumin (P for trend <0.001). Both unadjusted and adjusted only age, gender, and ethnicity models showed statistically similar significance to the above (Table 2). Fig 2A showed that serum albumin could predict a long length of stay in the ICU .We further analyzed the relationship between serum albumin and long LOS in the ICU. In the final adjusted model, serum albumin could be a protective factor for LOS shortening of patients with AHF , sepsis , nitroglycerin , WBC , hemoglobin , creatinine , Bun , calcium , glucose , lactic acid , and albumin , were selected by the univariate analysis results (Table 3). Finally, the independent influencing factors for long LOS for AHF patients in the ICU were selected by multivariate regression analysis, including respiratory failure , WBC , creatinine , glucose , lactic acid , and albumin  (Table 4).The predictors with P<0.001), which suggested that the predictive model has a better discriminative capacity . The predictive model has high consistency for predicted and actual probability for predicting long LOS . When the threshold probability is greater than 5%, the predictive model has a high net benefit in assessing the prognosis of AHF patients, which suggests that the predictive model was clinically useful . Finally, the predictive model was visualized by nomogram .Based on the above independent influencing factors, we developed a predictive model. The AUC of the predictive model for predicting the long LOS of AHF patients was 0.740  in the hypoalbuminemia group was higher than that in the normal group, their data revealed statistically that increased serum albumin levels did not shorten LOS or decrease clinical mortality . HoweverSerum albumin not only plays an important role in their nutritional statue, but also maintains the colloidal osmotic pressure. For AHF patients, hypoalbuminemia will reduce the patient’s blood volume, which will lead to insufficient perfusion of important organs, thereby aggravating the patient’s clinical symptoms. Previous studies have shown that hypoalbuminemia significantly affected prognosis and LOS of various diseases, such as patients with severe sepsis, acute decompensated chronic obstructive pulmonary disease, and requiring surgery –18, but In addition, the results of the present study also found respiratory failure, WBC, creatinine, glucose, and lactic acid were independent risk factors for long LOS among AHF patients. The related reasons are as follows. For AHF patients, respiratory failure increases hypoxia symptoms and internal environmental disturbances, which leads to a long LOS. Previous studies have shown that patients with respiratory failure have low albumin levels due to severe metabolic depletion . Severe Finally, the present study found that high serum albumin level was beneficial to LOS shortening of AHF patients, and the result could guide clinicians to reduce LOS of AHF patients by changing albumin levels. In addition, the predictive model we developed could identify high-risk patients. However, our study also has some limitations. Firstly, the maximum serum albumin level included in our study was 5.1 g/dl. When the albumin level is greater than 5.1 g/dl, whether the relationship between serum albumin and LOS is still negative has not been studied. Secondly, we only focus on the development of the model without external verification. Additional experiments may be required for external verification. Finally, we might not adjust other potential confounding factors.Serum albumin level was negatively associated with long LOS among AHF patients. The predictive model based on serum albumin has predictive value for evaluating the long LOS in AHF patients.


Coronavirus is an infectious disease that has affected sexual life. Sexual activity has decreased for many people, and couples' physical contact has reduced. The present study aimed to determine the sexual relationship of Iranian people and related factors during the Corona home quarantine by focusing on all constructs of the protective motivation theory.This cross-sectional online survey was conducted on Iranian people under in-home quarantine from July to December 2020 during the Covid-19 pandemic. Seven hundred sixteen people were selected by the convenience sampling method. The data was gathered by an ad-hoc tool consisting of demographic information and sexual relationship regarding protection motivation behavior in the Covid-19 pandemic. Participants should be able to complete the online questionnaire because the questionnaires were completed online. One-way ANOVA, independent T, and Pearson correlation tests were used to analyze the data in SPSS 16 software.p = 0.031). Perceived response efficiency with an average of 79.12 had the highest, and perceived self-efficacy with an average of 69.92 had the lowest mean score among the areas of sexual relationship. Among the protection motivation domains of sexual behavior that all had significant correlations, there was no significant correlation between perceived severity and perceived self-efficacy (p = 0.067).Findings indicate the average age of the participants was 37.78 + 8.34 years. Most of them were women (%85.1), married (%91.3) and had a university education (%90.2). In addition, %42.5% of participants had Full-time jobs and %34.2 lived in Tehran. 49.9% obtained information about corona from TV. 63.3% of the participants and their spouses did not catch Covid-19. Employment status was the only variable that was significantly different from sexual relationships regarding protection motivation (Perceived vulnerability is associated with employment status, place of residence, and age. Sexual relationships regarding protection motivations are only associated with employment status. Overall, participants in the present study reported high levels of perceived severity, perceived vulnerability, perceived response efficiency, and perceived costs Therefore, they reported a high level of motivation for protective and preventive behaviors in their sexual relationship. Our findings suggest that future interventions should focus on general cognition by developing appropriate knowledge about the severity and vulnerability of Covid-19 and sexual behaviors, improving perceived response efficiency, and self-efficacy of protective behavior through skills training. Coronavirus is an infectious disease that has affected all aspects of human life as well as sexual life. Sexual activity has decreased for many people, and couples' physical contact has reduced –3. HowevBecause the global approach to the disease is prevention, quarantine in various ways is the first strategy to combat Covid-19. The Ministry of Health of Iran, which is the main trustee of public health, proposed the home quarantine plan, and with the cooperation of departments and inter-organizations, this plan started from the end of February 2020 and has been emphasized and supported so far . ConcernOne of the theories used to study the factors affecting motivation and ultimately the health behavior of individuals is the Protection Motivation Theory. This theory was proposed by Rogers in 1975 based on the value expectation model to explain the effects of fear on health attitudes and behaviors . Here itAccording to various studies, the constructs of this theory have predicted different types of preventive and protective behaviors, including smoking cessation behaviors , protectIt seems that public health efforts to combat the high prevalence of human diseases should focus on preventing and changing the awareness, attitude, and intent to change people's behavior at risk, which indicates the role of awareness in performing preventive behaviors. Since the body of current knowledge about Covid-19 is not very strong in all aspects of health, especially couples' sexual relations, and on the other hand, it seems that the constructs of protection motivation theory provide a good basis for studying this issue, the present study focused on all constructs of protective motivation theory and was performed to determine sexual relationship of Iranian people regarding protection motivation and related factors during home quarantine of COVID-19 pandemic. The present study aimed to answer research questions following from two main perspective:First, “are there differences between the sociodemographic variables in the constructs of protection motivation in sexual relationships?”.Second, “are the protective motivation constructs in sexual relationships related to each other?”.This cross-sectional online survey was conducted in Iranian people in home quarantine from July to December 2020 during the Covid-19 pandemic. Sampling was done by convenience method, and all men and women who received the online questionnaire link could participate in the study. Using the Cochran formula , the minimum sample size was estimated to be 600. Considering 10% of the sample loss probability, the sample size was taken to be 650, and finally, 716 participants completed the questionnaire.All samples should be Iranian men and women with the experience of a home quarantine period  who could read and write Persian. The sample did not include both members of the couple but they have to be experienced in sexual relationship and have sexual partner. Their marital status could be permanent marriage, temporary marriage, divorce, and widowhood. But all participants had to have a sexual partner during the quarantine period. Participants should be able to complete the online questionnaire because the questionnaires were completed online.The data collection tool included two sections with sociodemographic variables and the ad-hoc questionnaire about Protection Motivation behavior in COVID-19.In part one sociodemographic variables consisted of information about COVID-19 sources of information gathering, history of exposure to COVID-19, gender, age, educational status, marital status, living location, job, and spouse' education.Part two of tool included ad-hoc questionnaire entitled Protection “Protective Motivation Motivative Sexual Relationship Questionnaire in COVID-19” or “PMSRQ-COVID-19”. It was consisted 23 five-point Likert-scale response items (from 'strongly disagree' to 'strongly agree') in 6 dimensions; perceived vulnerability  can cause illness.), perceived severity, perceived costs , perceived response efficacy .), perceived self-efficacy , and protection motivation  .The scale's score ranged from 23 to 115, where the higher the score, the greater the protective motivated sexual behavior in Covid-19. Each domain's scores were standardized based on 0 to 100.The developers reported the content validity ratio (CVR) and content validity index (CVI) of the instrument to be 0.66–0.83 and 0.91–1, respectively. Moreover, Cronbach's alpha reliability and intra-cluster homogeneity of the questionnaire based on the ICC coefficient were calculated 0.64–0.81, and 0.731–0.975, respectively.After receiving the code of ethics from the Faculty of Nursing and Midwifery of Tehran University of Medical Sciences (IR.TUMS.REC.2020.545), the target group received an online questionnaire through accessible social networks, e.g., WhatsApp, Telegram, and Instagram. Data collection was carried out with an online questionnaire. The questionnaire could be completed only once by the user. In line with the Helsinki Declaration of Ethical Principles for Medical Research, the participants' confidentiality was preserved. The collected data was not linked to any individual, and personal identifiers were not used during data storage. Therefore, this study's collected data can only be accessed by the research team.The collected data were analyzed by SPSS 16 software, and the significance level was considered less than 0.05. Descriptive statistics  and inferential statistics were used to analyze the data in line with the research objectives. ANOVA and t-tests were also utilized to evaluate the Protection Motivation based on the demographic characteristics. A Pearson correlation test was used to investigate the relationship between Protection Motivation and it’s dimensions. The normality of the variables was tested by the Kolmogorov–Smirnov test.p = 0.031; Table The mean age of 716 samples was 37.78 ± 8.34 years. 85.1% were women, 91.3% were married, 42.5% had full-time employment, and 89.8% had a university education. 61.5% were residents the cities other than Tehran, and 49.9% obtained information about Corona from the national media. 69.3% of the subjects and their spouses did not catch Covid-19  and place of residence (p = 0.021); Post hoc analysis revealed that in people with part-time job significantly less than people with a full-time job (p = 0.001), unemployed (p = 0.013), self-employed (p = 0.045), housewife (p = 0.029) and other jobs (p = 0.028). Also, people who lived in the city were significantly more than people living in Tehran (p = 0.028), and people who lived in the city and their spouses lived in Tehran (p = 0.017). Perceived vulnerability also had a significant positive correlation with age; with age, perceived vulnerability also increased (p = 0.049). Other domains did not have a significant relationship with any of the studied units' demographic characteristics  and non-permanent residence during the Corona pandemic provided a sense of confusion among participants in terms of sensitivity to protective behaviors.In this study, the perceived vulnerability domain was most associated with preventive sexual behaviors in Corona. Consistent with the present study, Grunfeld argues that the components of Threat-Appraisal (perceived vulnerability and perceived severity) and then the components of Coping-Appraisal  are strong predictors of intent to engage in protective behaviors . If peopAccording to the present study, preventive sexual behaviors in the Corona period and perceived severity are positively and significantly related. Therefore, if people are aware of this disease's consequences, they will take more protective behaviors. This is consistent with Ezzati Rad et al. and Tazval et al. , 30 but According to the present study, preventive sexual behaviors in the Corona period and perceived cost were positively and significantly related to each other, consistent with Gong et al. . If peopThe present study showed that protective motivated sexual relationship had the highest mean score in the area of perceived response efficiency, which is consistent with Sharifi Rad et al.'s study on the prevention of influenza A and Leigh et al.'s study of Ebola and preventive behaviors against SARS, avian influenza, and swine flu , 32. A pIn the present study, protective behaviors are shown at an optimal level that is consistent with Bashirian et al. on Covid-19 protective behaviors based on protection motivation theory among hospital staff, Ezzati Rad on predicting Covid-19 preventive behaviors based on protection motivation , 35.Several studies have reported information on the positive consequences of perceived severity and perceived vulnerability of infectious diseases on individuals' goals of adhering to protective and preventive behaviors , 37. SigUsing online polls as the main source of data collection due to the current social distance needs may limit access to all people in the community, as it excludes people with low digital literacy or lack of smartphones. However, many studies have reported that online questionnaires have significantly higher responses than e-mail questionnaires and higher quality data in online surveys than e-mail surveys . AnotherPerceived vulnerability is associated with employment status and place of residence, and age. protective motivated sexual relationship is only associated with employment status. Overall, participants in the present study reported high levels of perceived severity, perceived vulnerability, perceived response efficiency, and perceived costs. Therefore, they reported a high level of motivation for protective and preventive behaviors in all situations. From a practical point of view, the predictive validity of protection motivation theory showed that infrastructures have a significant relationship with the intention of protective and preventive behavior. This finding suggests that future interventions should focus on general cognition by developing appropriate knowledge about the severity and vulnerability of Covid-19, improving perceived response efficiency, and self-efficacy of protective behavior through skills training.


Hospice and palliative care (HPC) aims to improve end-of-life quality and has received much more attention through the lens of an aging population in the midst of the coronavirus disease pandemic. However, several barriers remain in China due to a lack of professional HPC providers with positive behavioral intentions. Therefore, we conducted an original study introducing machine learning to explore individual behavioral intentions and detect factors of enablers of, and barriers to, excavating potential human resources and improving HPC accessibility.A cross-sectional study was designed to investigate healthcare providers' behavioral intentions, knowledge, attitudes, and practices in hospice care (KAPHC) with an indigenized KAPHC scale. Binary Logistic Regression and Random Forest Classifier (RFC) were performed to model impacting and predict individual behavioral intentions.The RFC showed high sensitivity . Attitude could directly or indirectly improve work enthusiasm and is the most efficient approach to reveal behavioral intentions. Continuous practice could also improve individual confidence and willingness to provide HPC. In addition, scientific knowledge and related skills were the foundation of implementing HPC.Individual behavioral intention is crucial for improving HPC accessibility, particularly at the initial stage. A well-trained RFC can help estimate individual behavioral intentions to organize a productive team and promote additional policies. An aging population is a great challenge for healthcare systems, especially for hospice and palliative care (HPC) aiming to improve end-of-life quality. The number of people aged 65 years or over was 703 million globally in 2019 and is projected to reach 1.5 billion by 2050 , 5. HPC Existing studies mostly used traditional statistical methods to analyze the KAPHC among healthcare providers –15. TherWe conducted a cross-sectional study using the indigenized healthcare provider KAPHC scale, which proved to have good reliability . The scaShanghai had received continuous support to improve HPC research and practices and achieve universal coverage of HPC among community health service centers (CHC) by 2020 . TherefoThe indicators were divided into two components: the target vector and the feature matrix. Behavioral intentions, a binary variable, were selected as the target vector, with the label (1/yes) suggesting positive behavioral intentions to work in HPC and the negative label (0/no) without behavioral intentions. The feature matrix includes demographic characteristics, career experience, and measure data of KAPHC. A higher score means better personal performance. Descriptive statistics for the feature matrix were based on full samples to analyze the situation of participation. Categorical variables were reported as frequency distribution and percentage, whereas continuous variables were reported as average values, standard deviations, median, and IQR (Inter Quartile Range). IBM SPSS Statistics for Windows, version 21.0  software was used for the statistical analysis.Binary Logistic Regression (BLR) was performed to analyze the correlation between a dependent variable and independent variables to identify which variables can influence the willingness of healthcare providers to work in HPC. BLR could provide several key information points, namely, which explanatory variables show statistical significance with Wald's test, which variables are the risk or protective factors, and how important they are by odds ratio (OR). The goodness-of-fit is compared using the likelihood ratio test, the Hosmer–Lemeshow test, and Pearson's chi-squared test . BLR wasRandom Forest (RF) lowers the variance of a single regression tree by averaging the prediction of multiple DTs. The DT is a non-parametric supervised learning method used for classification and regression analysis. The DT predicts the value of a target variable by learning simple decision rules inferred from the data features, which can be seen as a piecewise constant approximation . Each DTIn our study, the variable types of latent factors include nominal variables and skewed continuous variables. Related studies have proven the applicability of RF in assembling learning algorithms and machine learning methods with the advantages of no restrictions on variable conditions and higher accuracy, sensitivity, and specificity. In addition, RF could be utilized to predict continuous variables and obtain predictions without obvious deviations . Therefon = 2,804) and the 20% test dataset (n = 701)  . Considen = 701) . Model vn = 701) . Once prn = 701) .The predictive abilities of RFC were assessed using the following measures:Accuracy: The proportion of the correctly classified samples. In multilabel classification, this function computes subset accuracy, meaning the set of labels predicted for a sample must match the corresponding set of labels in positive (positive .Precision: The ratio of “tp/(tp + fp)” where “tp” is the number of true positives and “fp” the number of false positives. The precision is intuitively the ability of the classifier not to label as positive a sample that is negative.Recall: The ratio of “tp/(tp + fn)” where “tp” is the same as above and “fn” is the number of false negatives. The recall is intuitively the ability of the classifier to find all the positive samples.F1 score: The weighted average of the precision and recall. The relative contribution of precision and recall to the F1 score are equal. F1 score = 2 *  /   .AUC: The area under the Receiver Operating Characteristic curve (ic curve .Average Precision (AP): The Precision-Recall curve shows the tradeoff between precision and recalls for different thresholds. A high area under the curve represents high recall and high precision. The AP summarizes a Precision-Recall curve as the weighted mean of precisions achieved at each threshold  were women, and 76.3% were married. Additionally, 68.8% held a bachelor's degree (or above), and 16.1% had religious beliefs. For career experience, approximately half (49.6%) worked downtown and the others (50.45%) in the countryside. The majority were employed in CHC (64.5%), and most participants were doctors (36.7%) and nurses (39.25%). The government funded most medical institutions (82.7%). Among all the participants with certain working experience in HPC, only half (56.1%) still work in HPC positions at the time of the investigation. Details are given in The individual scores for attitude, practice, and requirement of training were more dispersed than those of knowledge and confidence. The average attitude was 91.7 points, and the standard deviation and IQR of attitude score were the highest among the five items. The average knowledge score was 8.9 points, with the lowest standard deviation and IQR. More details are reported in P = 0.031), location of medical institution (P = 0.050), type of medical institution (P < 0.001), fund or supply of medical institution (P = 0.014), occupation (P < 0.001), profession title (P = 0.021), “Working in hospice care now” (P < 0.001), attitude (P < 0.001), knowledge (P = 0.001), confidence (P < 0.001), and practice (P = 0.059) showed statistical significance; these factors were selected as potential features fitting in RFC analysis. Meanwhile, it should be noted that KAPHC showed a positive impact on behavioral intentions, especially knowledge , which is higher than others. Meanwhile, profession title, marital status 2 (Divorced or widow), medical institution 2 (CHCs), and occupation 2 (doctor) showed a negative impact on behavioral intentions, especially the medical institution of CHCs .Overall, most measures were over 0.75. The recall performance (average of 0.92) was the best, followed by AP and F1-score of about 0.85. Additionally, the average accuracy, precision, and AUC values were between 0.75 and 0.80. Details are given in RFC was compared with three widely used machine learning models, including DT, K-Nearest Neighbor (KNN), and Support Vector Machine (SVM), to prove its superiority. Generally, RFC performed better for most measures, while the recall of SVM was higher than that of RFC. More details are given in The feature importance was computed as the  total reduction of the criterion brought by that feature, also known as the Gini importance . It was The result of RFC showed high sensitivity, suggesting that a majority of the samples were correctly classified into a positive label. However, the AUC (0.65) was still far from that of a perfect classification. It is considered that the class imbalance of the target variable caused the capacity of the discrimination to be poor, suggesting that we could not evaluate our classification models completely based on the accuracy and AUC. The Precision-Recall curve is a widely used measure of prediction for imbalanced classes . The AP According to the outcome of RFC and BLR, attitude was the most significant enabler. A positive attitude was a crucial facilitator to improving the quality of HPC services and important for building teamwork and interpersonal relationship , 45. It In our further analysis, aside from its own influence, attitude was associated with other features that affect behavioral intentions . ConfideBLR and RFC provided similar evidence suggesting that practice experience would enhance the development of behavioral intentions. It has been illustrated that healthcare providers at CHCs show a lack of behavioral intentions, partly due to assigned work tasks by the government instead of by active participation, without sufficient financial support and an effective incentive mechanism. Worse still, in many CHCs, there are rare opportunities to practice since the public are unaware of HPC . FurtherBLR and RFC highlighted that knowledge was an undeniable facilitator of behavioral intentions. The impact of knowledge includes two aspects: whether healthcare providers understand the concept of HPC and whether they have a good knowledge of the essential skills and apply them to HPC practice. For the former, we noticed that doctors showed negative behavioral intentions compared with other professionals. Most doctors would rarely consider HPC when cancer patients first visited; however, they agreed with the value of HPC . DoctorsFor the latter, we found that healthcare providers working in the countryside showed negative behavioral intentions due to a lack of knowledge and essential skills of HPC. As previously reported, most providers lack the professional training, skills, and principles in HPC practice, particularly pain control, symptom management, and psychological care . Also, oRFC outperformed other machine learning models and avoided the overfitting phenomenon; however, it is not a perfect classification. Therefore, we will keep working to develop more excellent methods. Additionally, evidence from Shanghai could not represent the situation of other provinces in China. Therefore, we will try to expand our samples to other areas to get stable evidence.HPC has become a topic of interest owing to the rising burden of NCDs, population aging, and the COVID-19 pandemic. However, due to several barriers to implementing HPC, most patients cannot access the needed professional services. Therefore, it is significant to understand the real-world situation at the initial stage of the HPC movement in China, particularly the individual behavioral intentions to improve the accessibility of HPC. Our study was designed to predict the behavioral intentions of HPC providers using RF, which presented a first attempt in this area to automatically identify the relationship between behavioral intentions and other parameters of KAPHC. RFC showed high sensitivity, which suggested a well-trained RFC could help to estimate individual behavioral intentions to organize a productive team. Moreover, attitude is considered the most significant facilitator, implying the most efficient approach to encourage behavioral intentions. Reasonable HPC knowledge and practices in caring for terminal patients are of potential interest and stimulate the behavioral intentions of healthcare providers. Ultimately, the study has provided evidence that the government and HPC organizations should scale up standardized training, sustained financial support, and long-term incentives to attract providers to engage actively and enthusiastically in HPC. This will ensure its long-term sustainable development in China.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.This study was approved by the Ethics Committees of Shanghai Ninth People's Hospital (Ref: SH9H-2021-T11-1). Written informed consent from the participants was not required to participate in this study in accordance with the national legislation and the institutional requirements.TC contributed to the original draft's conceptualization, formal analysis, and writing. YX contributed to the investigation and data curation. HZ contributed to visualization. XT contributed to the investigation and data curation. LJ contributed to writing—review and editing, supervision, and project administration. All authors contributed to the article and approved the submitted version.This work was supported by grants from the Nature Science Foundation of Shanghai (No. 22ZR1461400), Humanities and Social Science Research Planning Fund of the Ministry of Education (No. 20YJAZH045), Philosophy and Social Science Planning Project of Shanghai (No. 2019BGL032), and Pujiang Talent Program of Shanghai (No. 2019PJC099).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Benzodiazepines (BZD), Z-drugs (ZD), and opioids share a high risk of abuse. This study assessed and characterised adverse events (AEs) related to BDZ, ZD, and opioids leading to emergency department (ED) visits in the Italian setting.ED accesses related to BDZ, ZD, and/or opioids were analysed from the MEREAFaPS database. Information on AEs, suspected and concomitant medications was retrieved. Multivariate logistic regression was used to estimate the reporting odds ratios (RORs) of hospitalisation according to the different treatments.n = 3,106), opioids , or their combination (n = 97) were analysed. Compared to opioids, patients with BZD/ZD-related AEs were often younger (51 vs 64 years), more frequently presented 2+ suspected medications (13 vs 3%), and often had a history of abuse (4%). Twenty-three percent of BZD/ZD-related AEs were related to drug abuse (vs 2% of opioid-related ones) and frequently required patient hospitalisation (52% vs 24%), despite the significantly lower clinical complexity of these patients as compared to those on opioids. An increased risk of hospitalisation was found for flurazepam , prazepam , lorazepam , and morphine .A total of 5,970 pharmacovigilance reports involving BZD/ZD (These results indicate that, in Italy, the inappropriate use of BZD/ZD is a relevant heath issue, often leading to serious AEs requiring patients’ ED visits and hospitalisation, especially in young women and patients with a history of substance abuse.The online version contains supplementary material available at 10.1007/s00228-022-03354-7. Drug abuse in the world has been a growing problem. In the past two decades, the USA has seen a surge in opioid use and abuse that has led to an increase in the number of overdose deaths estimated at 42 thousand individuals in 2016 , there hTo date, guidelines discourage the initiation of therapy with long-acting opioids and their use at high doses, and criteria for prescribing opioids suggest remaining on dosages lower than 50 mg/day of oral morphine equivalents (OME), and in any case not exceeding 90 mg/day. In fact, the risk of mortality appears to increase consistently above 40 mg/die of OME, and is even greater when benzodiazepines (BZDs) are used in combination [Abuse of BZD or Z-drugs (ZD) is another growing problem in high-income countries. Between 2.3 and 18% of Americans report to have abused sedatives or tranquillisers for nonmedical use during their lifetime .Osservatorio Nazionale sull'Impiego dei Medicinali, OsMed), BZD and ZD are the most purchased medications belonging to the class C category of drug prescriptions, i.e. medications fully paid by the citizen (representing 18.5% of expenditure and 26% of DDD/1000 inhabitants die for the year 2018) [Consequently, concomitant with the increase in the prescription of these drugs and their abuse, an increase in the number of emergency department (ED) visits for adverse events (AEs) has been observed in both the USA , 8 and Ear 2018) .While BZD and ZD are far more used than opioids in Italy, in the period between 2013 and 2018, there has been an increase in the prescription of drugs for pain therapy (from 6.7 DDD/1000 inhabitants die in 2013 to 7.3 in 2018: +9.2%) and an increase in the prevalence of use of 12% . In particular, tramadol and fentanyl are the active substances with the highest average DDD/1000 inhabitants per day, 0.8 and 0.6, respectively .Moreover, considering data of ED visits collected in Italy through the MEREAFaPS study between 2007 and 2018, it is possible to observe that the frequency of hospitalisation is always much higher for BZD and ZD than for all other classes of medications that can induce tolerance and dependence, such as opioids , 12–16.In light of this, this post hoc analysis aimed to assess and characterise AEs related to the use of BDZ, ZD, and opioids that led to ED visits and/or hospitalisations in the Italian setting.A retrospective study was conducted on the MEREAFaPS database, an Italian database of pharmacovigilance report forms of suspected AEs requiring ED visits, actively collected between January 1st, 2007, and December 31st, 2018, in ED , 12–16. Only pharmacovigilance reports with BZD , ZD (N05CF*), and/or opioids  as suspected medications were considered . PatientSuspected medications were classified in terms of pharmacological class and active substance. BZD and ZD were classified based on their plasma half-life as short-, intermediate-, or long-acting , 18, 19,When available, information on drug misuse, abuse, medication error, or overdose, defined according to the Good Pharmacovigilance Practices (GVP)—Module VI (Rev 2) , was alsAEs were coded using the Medical Dictionary for Regulatory Activities (MedDRA) and reported as System Organ Class (SOC) and Preferred Term (PT) . The totDescriptive statistics were used to summarise data. Categorical data were reported as frequencies and percentages and compared using the chi-square test, while continuous data were reported as median values with the related interquartile ranges (IQR) and compared using the Mann–Whitney test for unpaired data.Within the BZD/ZD group, univariate logistic regression models were fitted to estimate the reporting odds ratios (RORs) of hospitalisation with 95% confidence intervals (CIs) associated with short-, intermediate-, and long-acting BZD or with ZD, respectively, as compared to the other four pharmacological classes. Moreover, RORs of hospitalisation were estimated for each considered active substance, each one compared to all other active substances belonging to BZD/ZD.Similarly, for the opioids group, univariate logistic regression models were fitted to estimate the RORs of hospitalisation with 95% CIs associated with strong, weak opioids or fixed associations containing opioids, respectively, each one compared to the other two pharmacological classes.Multivariate logistic regression models were also computed, adjusting for age, sex, ethnicity, presence of concomitant medications, and presence of concomitant conditions.p < 0.05. Data management and statistical analysis were performed using the software STATA 17 .All results were considered to be statistically significant at n = 3,106, BZD/ZD group), opioids , or their combination  were collected (Table p = 0.0001). Overall, female sex was significantly more represented, particularly in the OP group. In most cases, only one suspected medication was involved, mostly administrated by oral route. The presence of two or more suspected medications was significantly more frequent in reports related to BZD/ZD (12.7% in the BZD/ZD group vs 3.1% in the OP group); in the BZD/ZD + OP group (where at least two suspected medications were involved by definition), the co-presence of a third (or more) agent was reported in 22.7%. Of major note, in around one-fourth of AE reports related to BZD/ZD or to BZD/ZD + OP, a drug abuse or misuse was reported ; this percentage was significantly lower for the OP group . Also overdose and therapeutic errors were more frequently reported in the BZD/ZD group, though their frequency was overall low . Notably, more than half of AEs related to BZD/ZD or to BZD/ZD + OP required patient’s hospitalisation ; this proportion was significantly lower in the OP group . In all groups AEs usually ended with an improvement or with a complete resolution of symptoms. Of particular interest, four cases of “death” have been observed in the BZD/ZD group and one case in the OP group. In the first group, deceased patients were all females aged ≥ 75 years (mean age 84 years), for whom the causality assessment was consistent with a “possible” relationship between the events and the suspected drugs . In all cases an overdose or abuse of BZD/ZD was reported, and two of them also presented a psychiatric comorbidity. In the second group, the patient who died was a 55-year-old woman of unspecified ethnicity, treated with morphine and oxycodone for the management of cancer pain. No abuse/medication error/overdose was reported.During the study period 2007–2018), 5,970 AE reports involving BZD or ZD  of these events led to hospitalisation. Most AEs were retrievable to gastrointestinal symptoms , to neurological , or to generalised symptoms .As for the BZD/ZD + OP group, 252 AEs reported as PT were detectable from the 97 AE reports. A not negligible proportion of AEs were related to drug abuse (9.9%), self-harm (2.8%), or to attempted suicide (1.6%).Information on concomitant (non-suspected) medications and concomitant conditions is available in Supplementary Table Table Table This study aimed to describe the frequency and pharmacological characteristics of BZD, ZD, and opioid-related AEs leading to ED visits and/or hospitalisations.In terms of age, subjects who experienced AEs from BZD and/or ZD were significantly younger than those who experienced AEs from opioids with a median age of 51.3 (39.1–70.7) and 63.8 (47.1–77.7) years, respectively. This finding allows us to frame the latter as older subjects. As for gender, the female sex was the prevalent one, especially among subjects experiencing opioid-related AEs. These results are comparable with those published by Bushnell and colleagues in their study characterising BZD poisoning ED visits in young people by sex . In partWhen considering concomitant conditions, results underlined a more severe clinical complexity for subjects in the OP group, which resulted to be frequently affected by hypertension and diabetes. Conversely, in the BZD/ZD group we found anxiety, depressive, and psychiatric disorders (i.e. sleep disorder) among the most frequently reported concomitant conditions, which generally represent some of the therapeutic indications of these medications. Also, history of substance abuse was reported in around 4% of patients in the BZD/ZD group. It is worth mentioning that the presence of substance abuse as a common concomitant condition could indicate poor appropriateness, both in the prescription and use of BZD/ZD, as the use of BZD/ZD is generally contraindicated among these subjects . Our eviRegarding concomitant medications, we found that, in the BZD/ZD group, antidepressants and antipsychotics were frequently co-administered, due to the common therapeutic practice of associating BZD to antidepressants in the first 2–3 weeks of the treatment of some mood disorders . On the Particular attention should be paid to the concomitant use of BZD/ZD and opioids. Despite that in our analysis the concomitant use of both drug classes accounted for a small amount of cases and did not show an increase of hospitalisations or poor outcomes of AEs, a study published in 2017 highlighted that, from 2001 to 2013, concurrent BZD/opioids use suddenly increased in the USA and significantly contributed to the overall population risk of opioid overdose . ConversIn this context, it is worth remembering that, while opioids are mostly paid by the National Health System, in Italy BZD/ZD are always paid by patients, exposing them to a less strict monitoring by physicians, especially in terms of regular ambulatory follow-up. Coherently, our results indicated that abuse and misuse of BZD/ZD was much more frequent than for opioids, accounting for around 20% of AEs requiring ED visit in the BZD/ZD group, as compared to 2% in the OP group. Similarly, overdose and therapeutic errors were significantly more frequent in the BZD/ZD group . Furthermore, BZDs are the only class of medications reported among a range of drug harms in the UK by Nutt and colleagues through their multicriteria decision analysis performed . In the Of note, we also found that the hospitalisation rate for subjects in the BZD/ZD group was about twofold higher than the rate observed for subjects in the OP group (>50% vs <25% in the OP group). Particularly, within the BZD/ZD group, an increased risk of hospitalisation was found for two long-acting BZDs (flurazepam and prazepam) and for an intermediate-acting BDZ (lorazepam), while the short-term-acting midazolam was associated with a lower risk. As reported in our previous study , the assRegarding opioids, an increased risk of hospitalisation was found for strong opioids (particularly morphine) as compared to weak opioids or fixed associations (particularly tramadol/dexketoprofen). These results are likely to be mostly driven by the high clinical complexity of patients receiving strong opioids, whose complications need to be mostly managed in an in-hospital setting.In light of this, is BZD/ZD misuse the next drug epidemic? Healthcare professionals, patients, and customers continue to view BZD/ZD use as less harmful than that of opioids. The National Institute on Drug Abuse (NIH) reported 8,791 overdose deaths in 2015 involving BZD, more than 7,600 overdose deaths since 1999. Such a significant increase in the number of deaths should raise alarm worldwide, not only in the USA .In the near future, clinical pharmacologists and toxicologists should take into account the harmful effects of substance use disorder also associated with BZD and ZD . To miniThe results from this study suffer some limitations, mostly related to its retrospective and observational nature, which might have led to an underestimation of the number of AEs analysed. Indeed, not all patients with an AE refer to the ED or spontaneously report the event. However, considering that AEs leading to ED visit were collected through an active pharmacovigilance project, the problem of underreporting, particularly for serious AEs, was minimised in this post hoc analysis. In addition, analyses are based on the collection of pharmacovigilance report forms that could be affected by inaccurate or incomplete information, mainly due to the lack of demographic and/or clinical data. In particular, data on dosages of suspected medications were not available in all pharmacovigilance report forms. Thus, the impact of BZD/ZD or OP dosages on the risk of hospitalisation was not evaluated. Considering cases of misuse, abuse, overdose, or medication errors, these covariates were only considered categorical variables when reported in the pharmacovigilance report form.Despite these limitations, this study is strengthened by the fact that it involved numerous EDs of hospitals equally distributed throughout the National territory, so we can say that the data collected and the evidence described can be considered representative of all Italian EDs. Moreover, since BZD and ZD are not reimbursed by the Italian National Health Service, it is currently very difficult to conduct safety studies based on prescription data of these drugs. In this context, the use of data related to ED visits and/or hospitalisations represent a unique opportunity to estimate the true impact of BZD/ZD abuse and inappropriate use in the Italian population.In the ED setting, active pharmacovigilance studies appear to be a valid scientific approach, enabling both healthcare providers and systems to detect and characterise AEs, particularly those associated with inappropriate use of central nervous system medications, such as BZD, ZD, and opioids. This approach is also useful in the monitoring of the safety of medications which are generally paid for by patients. In fact, for such medications the analysis based on administrative data (i.e. administrative database of reimbursed medicines and/or insurance database) could not be performed.The results from this study indicate that, while in the USA the opioid epidemic is a major health issue, in Italy the inappropriate use of BZD and ZD is a much more relevant challenge, often leading to serious AEs requiring patients’ ED visits and, eventually, hospitalisation, especially in young women.The results from this study provide interesting hints for prescribers and emergency physicians for the recognition and management of AEs associated with these pharmacological classes. In particular, specific attention should be paid to young BZD and ZD users with a history of substance abuse.Increasing the awareness of the potential public health consequences of inappropriate use of BZD and ZD can substantially reduce the number and costs associated with AE-related ED visits and/or hospitalisations, as well as improve patients’ quality of life across all age groups.Supplementary file1 (DOCX 25 kb)Below is the link to the electronic supplementary material.


Patients with incomplete revascularization (ICR) tend to develop refractory angina despite optimal medical therapy. The Compound Danshen Dripping Pills (CDDP) is a widely used antianginal drug in China and is shown to significantly alleviate myocardial ischemia. Previous studies showed dose-efficacy tendency when increasing doses of CDDP. This study aims to investigate the efficacy and safety of intensive doses of CDDP in patients with refractory angina with ICR.2 peak) and other parameters as measured by CPET, and the levels of plasma C-reactive protein, homocysteine, and N-terminal pro-B-type natriuretic peptide. Safety events related to CDDP use will be monitored.The INCODER study is a multicenter, double-blind, randomized controlled, superiority trial. We plan to recruit 250 patients aged 18–85 years with a diagnosis of refractory angina with ICR. Patients will be randomized (1:1) to intensive treatment group (CDDP 20 pills three times per day) or standard treatment group (10 pills CDDP and 10 pills placebo three times per day). Patients will have a 6-week medication period and be followed up every 2 weeks. The primary endpoint is the change of total exercise time from baseline to week 6 as assessed by cardiopulmonary exercise testing (CPET). Secondary endpoints include changes in the frequency of angina, Canadian Cardiovascular Society angina class, nitroglycerin use, Seattle Angina Questionnaire scores, peak oxygen uptake . The results will be reported through peer-reviewed journals, seminars, and conference presentations.www.chictr.org.cn (ChiCTR2000032384). Registered on 27 April 2020. Multivessel coronary artery disease (CAD), which is defined as stenosis of >50% affecting more than one epicardial vessel, is found in about 50% of patients on diagnostic angiography and is significantly associated with a worse prognosis than single-vessel CAD , 2. Due Salvia miltiorrhiza, notoginseng, and borneol at a ratio of 450:141:8 (p = 0.18) and 43 s in high-dose group (p = 0.005). No serious adverse drug reactions (ADRs) were observed (Compound Danshen dripping pills (CDDP) or Dantonic, an herbal patent medicine, is widely used in China for the clinical treatment of CAD. CDDP contains three medicinal herbs, 50:141:8 . Its mai50:141:8 . Accordi50:141:8 . A meta-50:141:8 . Another50:141:8 . The rec50:141:8 . In the observed . AlthougAs for the safety issue, according to the reports from China FDA (CFDA) center for ADRs, the incidence rate of ADRs for CDDP is only 0.0018%, most of which were gastrointestinal symptoms, non-specific hemorrhage, and non-specific purpura . Most ofvs. standard treatment of COmpound DanshEn dripping pills in Refractory angina patients with ICR (INCODER study).Therefore, we designed the study to evaluate the efficacy and safety of INtensive treatment The INCODER study is a multicenter, randomized, double-blind, parallel controlled, superiority clinical trial. Patients will be randomly divided into two groups: intensive treatment group (CDDP 20 pills three times per day) or standard treatment group (CDDP 10 pills three times per day). The administration of CDDP 20 pills three times per day is superior to 10 pills three times per day with respect to efficacy and safety in patients with refractory angina with ICR.Patients aged 18–85 years with a diagnosis of stable refractory angina with ICR are eligible for participation. Patients are eligible for inclusion in the study if they had a history of CAD with refractory angina (Canadian Cardiovascular Society [CCS] class II to III) despite OMT for at least 1 month. OMT is defined as a guideline-recommended treatment including secondary prevention and at least two antianginal drugs: one is nitrates and the other is a beta-blocker or calcium channel blocker, except for medication contraindications . ICR is The exclusion criteria are detailed in The study will be conducted in 7 medical centers in China. Patients will be recruited by local physicians using posters and advertisements in the hospital and nearby communities. Posters and advertisements contain brief introductions about the study and the contact information of the investigators. The study will be explained in detail to the potential participants, and informed written consent will be obtained prior to enrolment.Randomization is generated using computer-generated random permuted blocks by a designated statistician not involved in study operations using SAS V9.4 software. Either CDDP or placebo will be packaged identically and labeled with a number according to the randomization list. The treatment kit numbers will be obtained by the investigators at the time of patients' randomization, and treatment kits will be strictly sequentially allocated to patients according to the randomization list. In accordance with the double-blind design, the sponsor, study patients, investigators, and study site personnel will remain blinded to study treatment.The randomization code will be kept in opaque sealed envelopes and secured by both the sponsor and the principal investigator and can only be broken in exceptional circumstances when knowledge of the investigational drug is essential for treating the patient. If the randomization code is uncovered, the investigator should document the reason for unblinding, and the administration of the investigational drug will be discontinued.The intensive treatment group is administered with CDDP  at a dose of 20 pills three times per day while the standard treatment group takes a standard dose of 10 pills CDDP and 10 pills placebo three times per day orally after meals. All the patients will be treated for 6 weeks. CDDP or placebo pills are identical in size and smell. All the 20 pills (20 pills CDDP for intensive treatment group or 10 pills CDDP and 10 pills placebo for the standard treatment group) are stored in one identical bottle. Patients take one bottle three times per day.Study participants should be treated with standard CAD therapies as per recommended guidelines. The following drugs are prohibited during the whole study including ivabradine, ranolazine, nicorandil, trimetazidine, and other antianginal Chinese traditional medicine . However, other kinds of medications are taken as needed. The concomitant medication will be recorded throughout the trial and analyzed if necessary.The primary outcome is the change in total exercise time evaluated by CPET from baseline to week 6 in the intention-to-treat (ITT) population.2 peak), frequency of angina, nitroglycerin use, CCS angina class improvement, Seattle Angina Questionnaire (SAQ) scores, other CPET indexes, as well as plasma C-reactive protein (CRP), homocysteine, and N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels. Safety assessment includes adverse events during the whole study period, vital signs, physical examination, 12-lead ECG, laboratory tests, and the use of rescue medication  and are encouraged to keep exercising until exhaustion or symptoms of chest tightness, chest pain, and shortness of breath, or inability to maintain the pedal frequency of 60 rpm. (2 achieved during active exercise or early recovery. Heart rate and respiratory exchange ratio (RER) are objective indicators for peak exercise. Peak VO2 was determined as the highest mean VO2 over 20 s  using a ramp protocol according to the statement from the American Heart Association , 24. Exp 60 rpm. . Peak exCompliance will be evaluated by counting the number of bottles returned at every follow-up visit . Of note, the denominator  will be calculated over the actual duration when the subject is in the study. Subjects will be informed of the intention to monitor compliance in the informed consent form.Adverse events will be assessed and recorded in the case report forms during the whole study. Given the nature of the intervention, the most common adverse reactions related to CDDP including gastrointestinal symptoms, headache, and facial flushing will be monitored. Although CPET is fairly safe with a serious complications rate of <1–5 per 10, 000 tests and a death rate of around 0.5 per 10,000 tests, complications do occur and should be paid attention , 26. MajAll serious adverse events (SAEs) will be assessed and reported to the ethics committee in accordance with the International Council for Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use Good Clinical Practice (GCP) guidelines .http://www.researchdata.org.cn/, where it can be accessed and traced securely via a specialized administration panel by members of the research team using an encrypted password.Data will be collected by trained research staff at each site and recorded in case report forms. This will then be entered into the INCODER database, which is located in the clinical research unit in the Department of Cardiology in the First Affiliated Hospital, Sun Yat-sen University, and supervised by the trial data manager. Data from the INCODER study will be transferred securely to the Research Data Deposit at The INCODER study will be overseen by the trial steering committee (TSC) in accordance with the GCP guidance. The TSC, which consists of the chief investigator, study coordinator, site investigators, and statisticians, will independently monitor the process of the study and give advice on the continuation, termination, or amendments of the trial protocol. The study is sponsored by Tasly Pharmaceutical Group Co. Ltd. and will be subject to regular monitoring visits and audits.Patients were neither involved in the design or the recruitment and conduct of the study, nor in the assessment of the burden of the intervention. Results will be disseminated to participants on request.http://www.chictr.org.cn; Registration number: ChiCTR-IIR-17013662), the change of total exercise time is 62.5±19.6 s and 54.5±18.8 s from baseline to week 6 in intensive treatment group and standard treatment group, respectively. We, therefore, assumed the changes of total exercise time as 62.5 s and 54.5 s in the two groups, respectively, and combined standard deviations as 20. The sample size was calculated based on the following formulaThis is a superiority study. Sample size calculation is based on the primary outcome of change in total exercise time from baseline to follow-up at 6 weeks. According to the unpublished results of Phase II clinical trial conducted in the United States  and our Nc and Nt denote the sample size of the standard treatment group and the intensive treatment group, respectively. In the equation, σ is the combined standard deviation, and α and β are type I and type II errors, respectively. Here, r is the allocation ratio between the two groups, and μE and μC are the average changes of the total exercise time before and after treatment among the intensive treatment group and the standard treatment group, respectively. The superiority margin is Δ. In our study, α = 0.025, β = 0.2, μE − μC = 62.5–54.5 = 8, σ ≈ 20, r = 1, and Δ = 0. A sample size of 100 per group will yield 80% power to obtain a significant difference between the 2 groups, using a 2-sample t-test at a 1-sided 0.025 level of significance. Considering an ~20% dropout rate, a total of 250 subjects (125 subjects for each group) will be enrolled.where Statistical analysis will be conducted by the SAS V9.4 software using a two-tailed 0.05 significance level.t-test or rank sum test will be used for continuous variables and the chi-square or Fisher's exact test will be applied for categorical variables.Baseline demographic characteristics of the two groups will be presented using descriptive statistics. Continuous variables will be presented with median and interquartile range or mean ± SD. Categorical variables will be expressed as frequencies and percentages. For comparisons between the two groups, p-values. Missing data will be imputed by using the last observation carried forward method.The primary outcome, changes of total exercise time between the intensive treatment group and the standard treatment group, will be estimated based on the ITT population consisting of all the randomized patients. The general linear model will be used for the primary outcome with covariates of center and baseline exercise time using a 1-sided 0.025 significance level. Data will be presented as mean differences and corresponding We will further conduct ITT and per-protocol analysis to evaluate the differences in certain secondary outcomes between the two groups. Safety analyses will also be conducted based on a safety set in which all randomized subjects receive ≥1 dose of study medication.www.chictr.org.cn (ChiCTR2000032384) prior to trial commencement.The protocol was approved by the Clinical Research and Laboratory Animal Ethics Committee of the First Affiliated Hospital, Sun Yat-sen University ([2019]65), and all participants provided their written informed consent. All study procedures were followed with the ethical standards of the Helsinki Declaration. The study protocol was registered at www.chictr.org.cn.Changes to the study protocol are documented in amendments. Amendments are submitted for approval to the Ethics Committee of the First Affiliated Hospital, Sun Yat-sen University. Major changes will be updated on the trial registration website of After completion, the results will be published in a peer-reviewed journal.Over the past decades, there have been great advances in interventional therapy and medical therapy in CAD. However, still a large proportion of patients cannot achieve CR owing to patient comorbidities, anatomical factors, and technical or procedural considerations , 29. Deshttp://www.chictr.org.cn; Registration number: ChiCTR-IIR-17013662). However, due to the difficulties in the patients' recruitment and enrollment, we expanded the scope of the inclusive patients to those with ICR. During the preliminary study, we also found it very important to unify the criteria for termination of the CPET test. Therefore, we optimized the termination criteria . The patients/participants provided their written informed consent to participate in this study.YD and YC conceived and instructed the study. ZW, DX, and ZW designed the study. LLin and YL provided statistical expertise and supported the development of the statistical analysis plan. AC, LLiu, YZ, and DL contributed to recruitment, trial oversight, intervention implementation, and the follow-up of the subjects. All the authors contributed to the design and development of the study protocol and have reviewed the manuscript.The INCODER study was sponsored by Tasly Pharmaceutical Group Co. Ltd (Grant number: K0601461). The study design, data collection, statistical analysis, or publications are not influenced by the sponsors and are exclusive responsibility of the investigators.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.