The polygenic risk score (PRS) is calculated as the weighted sum of an individual’s genotypes and their estimated effect sizes, which is often used to estimate an individual’s genetic susceptibility to complex traits and disorders. It is well known that some complex human traits or disorders have sex differences in trait distributions, disease onset, progression, and treatment response, although the underlying mechanisms causing these sex differences remain largely unknown. PRSs for these traits are often based on Genome-Wide Association Studies (GWAS) data with both male and female samples included, ignoring sex differences. In this study, we present a benchmark study using both simulations with various combinations of genetic correlation and sample size ratios between sexes and real data to investigate whether combining sex-specific PRSs can outperform sex-agnostic PRSs on traits showing sex differences. We consider two types of PRS models in our study: single-population PRS models  and multiple-population PRS models (PRScsx). For each trait or disorder, the candidate PRSs were calculated based on sex-specific GWAS data and sex-agnostic GWAS data. The simulation results show that applying LDpred2 or PRScsx to sex-specific GWAS data and then combining sex-specific PRSs leads to the highest prediction accuracy when the genetic correlation between sexes is low and the sample sizes for both sexes are balanced and large. Otherwise, the PRS generated by applying LDpred2 or PRScs to sex-agnostic GWAS data is more appropriate. If the sample sizes between sexes are not too small and very unbalanced, combining LDpred2-based sex-specific PRSs to predict on the sex with a larger sample size and combining PRScsx-based sex-specific PRSs to predict on the sex with a smaller size are the preferred strategies. For real data, we considered 19 traits from Genetic Investigation of ANthropometric Traits (GIANT) consortium studies and UK Biobank with both sex-specific GWAS data and sex-agnostic GWAS data. We found that for waist-to-hip ratio (WHR) related traits, accounting for sex differences and incorporating information from the opposite sex could help improve PRS prediction accuracy. Taken together, our findings in this study provide guidance on how to calculate the best PRS for sex-differentiated traits or disorders, especially as the sample size of GWASs grows in the future. In this article, we focus on three such PRS models, including PRScs (Many traits or complex diseases result from the combined influence of many genetic variants and other risk factors. The polygenic risk score (PRS) is a measure of an individual’s genetic susceptibility to a trait or complex disorder. It is calculated as the weighted sum of an individual’s genotypes and their estimated effect sizes. The PRS is developed to use genetic information to predict complex disorders and can also be informative to assess genetic overlap between traits . Becauseng PRScs , LDpred2ng PRScs , and PRSng PRScs  that havng PRScs . Two of ng PRScs , are sinng PRScs  is a mulIn the applications of the PRS to different traits and disorders, the input is the summary statistics from genome-wide association studies (GWAS), which often combines female and male samples with the implicit assumption that the effect sizes are the same between the two sexes. However, many investigations have suggested sex differences in traits and in the risk of developing complex disorders in recent years. For example, in the context of Alzheimer’s disease, females acquire verbal memory impairments later but exhibit decline faster than in males . There aTo address sex-specific genetic effects, sex-specific PRSs have been developed and evaluated . HoweverThe PRS methods considered in our work can be classified into two categories: those designed for one population [PRScs  and LDprrg) set to 1, 0.8, and 0.5, respectively. We also considered the situation when only a subset of causal variants was shared across sexes. We conducted a simulation with 80% of causal variants shared across sexes and their effect sizes following a bivariate normal distribution with genetic correlation (rg) set to 0.8 and 0.5. The squared correlation (R-squared) between simulated traits and predicted traits was calculated to evaluate the performance of the PRSs, and each simulation setting was repeated ten times.We first conducted simulations to evaluate the prediction performance of sex-agnostic PRSs, sex-specific PRSs, and combined sex-specific PRSs derived from various PRS methods. We simulated individual-level genotypes of the white British population from the UK Biobank data for HapMap3 variants whose minor allele frequencies are larger than 1% . We chose 1 KG Phase 3 European samples as our reference panel for all PRS methods. With balanced female and male sample sizes, we considered three sample sizes  as the training data set to construct sex-specific and sex-agnostic GWAS summary statistics. We also conducted a simulation with unbalanced heritability between sexes when the sample sizes were 25,000 females and 25,000 males. In the unbalanced sample size settings, we considered three scenarios: females/males: 2,500/12,500, females/males: 10,000/50,000, and females/males: 50,000/10,000. We simulated 5,000 females and 5,000 males to form the validation data set, and another 5,000 females and 5,000 males as the testing data set. There was no overlap among the training, validation, and testing data sets. Among all the SNPs, we randomly sampled ∼0.1% HapMap3 variants  as causal variants for each sex and assumed that the causal variants were shared across sexes and their effect sizes followed a bivariate normal distribution with genetic correlation  showed the best prediction performance for both sexes and in all genetic correlation settings . When thThere are situations when the sample sizes are unbalanced between males and females. In the UK Biobank (UKB) data set, for example, there are more females than males. For the Million Veteran Program, males account for 92% of the study subjects . TherefoWe obtained sex-specific GWAS summary statistics and sex-agnostic GWAS summary statistics for 12 traits  from the GIANT study . For allWe applied sex-agnostic PRS methods, sex-specific PRS methods, and combined sex-specific PRS methods to the sex-specific GWAS summary statistics and sex-agnostic GWAS summary statistics of each trait. We first investigated the PRS performance of WHR, WHRadjBMI, HIP, HIPadjBMI, WC, and WCadjBMI. Among these six traits, WHR and WHRadjBMI showed the benefit of sex-specific PRS and combined sex-specific PRS on both sexes . For femWe also obtained sex-specific GWAS summary statistics and sex-agnostic GWAS summary statistics of BMI, WHRadjBMI, and WCadjBMI after adding physical activity levels  or smoking status  as covariant. Sex-agnostic LDpred2  still outperformed other methods when predicting BMI for both females and males . As for Based on prior knowledge , we studThe sex-specific and sex-agnostic GWAS summary statistics were obtained from the Genetic Investigation of ANthropometric Traits (GIANT) collaboration . GIANT ip-value greater than 1e-6, and a minor allele frequency (MAF) greater than 0.05. We also eliminated all strand-ambiguous SNPs. To obtain sex-specific GWAS and sex-agnostic GWAS summary statistics, we used Bolt-LMM   is a majBolt-LMM  on the tLDpred2 is a new version of LDpred with a larger window size of 3 cM. It could better handle numerical errors when working with exponentials. With an efficient parallel implementation in C++ and restrictions to HapMap3 variants, LDpred2 could run with a larger hyper-parameter search space than LDpred but with a shorter time. There are two extensions of LDpred2: 1) sparsity option in LDpred2-grid which provides models that truly encourage sparsity and 2) LDpred2-auto which automatically estimates values for hyper-parameters p and heritability. We tested a grid of hyper-parameters with p from a sequence of 17 values from 10e−5 to 1 on a log scale; h2 within {0.7,1,1.4} times heritability estimates from LDSC and their sparsity option.PRS-CS is also a Bayesian method that calculates the posterior mean effect size of each variant based on GWAS summary statistics and linkage disequilibrium (LD). It employs a continuous shrinkage prior to SNP effect sizes, with one hyper-parameter, the global shrinkage parameter. This hyper-parameter represents the genetic architecture’s overall sparsity. The 1 KG LD reference panel used in this study was pre-calculated and built for HapMap3 variants with MAF >0.01. Though PRScs could automatically estimate the parameter, we use the version that tunes the parameter and the global shrinkage parameter is range from 1e-8 to 1e-6, 1e-4, 1e-2, to 1.PRS-CSx is an extension of PRS-CS which enables the integration of GWAS summary statistics from multiple populations to improve cross-population prediction performance. We also use the version that tunes the parameter and the global shrinkage parameter that ranges from 1e-8 to 1e-6, 1e-4, 1e-2, to 1.In all the PRS analyses, we applied PRS methods to sex-specific and sex-agnostic GWAS summary statistics to estimate the effect sizes of genetic variants. Then, the validation data set, with individual-level genotypes and phenotypes, was used to tune hyperparameters for different PRS methods. After we selected the best PRS for each method using the validation data set, we used the testing data set to evaluate their prediction accuracy and computed performance metrics which is the square of correlation for quantity phenotypes. For all the PRS methods, we used the 1000 Genomes Project (1 KG) Phase 3 super-population samples as the LD reference panels .The PRS models in this work can be broadly grouped into two categories: the single population methods (LDpred2 and PRScs), which train PRS using one set of GWAS summary statistics, and the multi-population method (PRScsx), which uses GWAS summary statistics from several populations. First, sex-agnostic  and sex-specific GWAS summary statistics  are derived from the training samples. We obtained female-specific PRScs/LDpred2, male-specific PRScs/LDpred2, and sex-agnostic PRScs/LDpred2 by applying PRScs and LDpred2 to these three sets of GWAS summary statistics. The female-specific PRScsx and male-specific PRScsx are generated by inputting both female-specific and male-specific GWAS summary statistics to PRScsx. We tuned sex-specific PRSs and sex-agnostic PRSs on the validation samples whose sex was the same as that of the testing data set which we were going to predict on. The combined sex-specific PRSs are created by linearly combining sex-specific PRSs on the target validation data set. The hyper-parameters and weights of each sex-specific PRS are validated simultaneously.via simulation studies, that when the sample sizes are small, even though there is a relatively small genetic correlation between sexes, the increase in sample size contributes more than sex differences in PRS prediction. With an increase in sample size, the combined sex-specific PRSs gradually improve their relative performance and the majority part of the information for combined sex-specific PRSs is from the corresponding sex-specific PRSs. When the sample sizes are large enough, PRScs and PRScsx provide better performance than LDpred2. Besides, combined sex-specific PRScsx always performs better than combined sex-specific PRScs, which indicates the benefits of jointly modeling multiple GWAS summary statistics. When there is a difference in heritability between the sexes, combined sex-specific PRSs can be an option for the sex with higher heritability. In unbalanced sample size simulations, we found that female-specific PRScsx consistently outperformed other female-specific PRSs in both sexes, where there were fewer females than males. This could imply that sex-specific PRS of the smaller sample size could benefit from information from the opposite sex with a larger sample size by PRScsx. When the sample size is unbalanced between sexes, the combined sex-specific PRScsx may be a good candidate PRS to predict on the sex with smaller sample size and combined sex-specific LDpred2 may be a good candidate PRS on the sex with larger sample size. However, in real data analysis, there are limited sex-specific GWAS summary statistics, and sex-agnostic LDpred2 gave the best prediction for most of the traits we investigated, with the exception of traits related to WHR, where we observed that combined sex-specific PRSs performed better than the sex-agnostic PRSs.In this article, we have presented a comprehensive study to investigate what would be the most effective way to develop PRS that can adequately address sex differences in genetic associations for traits/disorders with demonstrated sex differences, such as different heritability and/or low genetic correlation between sexes. We considered sex-agnostic PRS, sex-specific PRS, and combined sex-specific PRS that are built from PRScs, LDpred2, and PRScsx. We have shown, However, our study only used autosomes to generate polygenic risk scores, ignoring sex chromosomes, particularly the X chromosome. The X-chromosome has two copies in females, but only one in males. In females, one of the two copies may even be silenced, a process known as X-chromosome inactivation (XCI) , and theIn conclusion, although there are sex differences in the genetic architecture for some traits, considering these differences, for example, through building models from sex-specific GWAS summary statistics, PRS prediction does not lead to improved prediction accuracy in most traits in our analysis of real data for the time being. Sex-agnostic PRSs remain the best option for most cases. When the sample size is large and the genetic correlation is relatively small between males and females, there may be some benefit to considering sex-specific information for PRS. When there is a big difference in heritability or the sample sizes of the two sexes are very unbalanced, combined sex-specific PRSs are worth considering. A guidance on how to select the optimal PRSs based on simulation results is also shown on


To promote an acceptance rate of COVID-19 immunization among Thai children, concerns about parental vaccination hesitancy should be urgently studied. This study aimed to examine the parental COVID-19 vaccination hesitancy (PVh) level and influencing factors among Thai parents of children 5–18 years of age.U test was used to compare the differences among groups of parents based on EC&V and FC. The factors influencing PVh were assessed by multiple regression analysis.This cross-sectional survey was conducted in Thailand during May and June of 2022. The Google forms for data collection were distributed to parents  via various online social media. Data regarding PVh level, relevant attitudes, experiences of COVID-19 and COVID-19 vaccination (EC&V), and family contexts (FC) were collected and analyzed using descriptive statistics. Mann–Whitney p value < 0.001). Conversely, the parents who had finished the initial COVID-19 vaccine had lower PVh levels with statistical significance . Attitude towards COVID-19 (AC), attitude towards COVID-19 vaccine (AV), and perceived behavioral control (PC) of the parents negatively influenced PVh with statistical significance, according to the results of the multiple regression analysis .Four hundred and eighty-eight parents completed the online questionnaire. Their median (IQR) age was 41 (35–47) years. They lived in different provinces from all regions across Thailand. Ninety percent of them were authorized persons to make decision about children vaccination. Fifty-eight percent of the respondents had vaccine hesitancy, defined as PVh level at moderate or above. Parents who had ever refused COVID-19 vaccination for themselves or refused to vaccinate their children against any other diseases had statistically significant higher levels of PVh (COVID-19 vaccination hesitancy was commonly found among Thai parents. The factors of the hesitancy were multifaceted. Different experiences regarding COVID-19 vaccination for themselves and any vaccinations for their children were associated with different PVhs. The attitudes especially AC, AV, and PC statistically influenced PVh. These findings should be exploited for national and local policy planning as well as public campaigns. The oveAlthough the perceived severity of COVID-19 in children is less than in adults, long-term serious complications of COVID-19 in children have been increasingly reported including long-COVID symptoms and multisystem inflammatory syndrome in children (MIS-C). These complications could be prevented by COVID-19 vaccines. As a result, every child should be managed to receive the vaccine timely . On JanuVaccine hesitancy has long been one of the major obstacles to immunization among people of all age groups. The WHO defined vaccine hesitancy as “a delay in acceptance or refusal of vaccination even though vaccination services are available”. Factors that determine individual vaccine hesitancy consists of (1) complacency which indicates a low perceived risk of disease (2) confidence in the safety and efficacy of the vaccine 3) convenience in acquiring and accessing vaccines –12. In t convenieThis research was a cross-sectional survey study conducted in Thailand. The data were collected between May and June 2022 after being approved by the Human Experimentation Committee Research Institute for Health Sciences, Chiang Mai University, Chiang Mai, Thailand (No. 22/2022).The parent in this study means a father, a mother, or one who nurtures and raises a child. The inclusion criteria of the study were Thai parents of children aged between 5 and 18 years old that are eligible for the COVID-19 vaccination. [The main outcome of this study was the prevalence of PVh. Based on a previous survey in Japan, 57.1% of parents expressed hesitation to vaccinate their children against COVID-19 . A formuThe data were collected online using Google forms for survey. The authors distributed a QR code and a link to the questionnaire and informed consent form via online social media including Facebook and LINE applications, for institutional alumni groups, general online marketplaces and stores, and provincial news channels, where the public was members. The data collection was conducted between May and June 2022.The authors developed a questionnaire based on a literature review from previous studies , 19, 20.U test for non-normally distributed data sets was used to compare the hesitancy score between groups with different experiences towards COVID-19, COVID-19 vaccination, and family context. The multiple regression analysis (MRA) was used to estimate the impact of the attitude domain on the hesitancy level. The enter technique with statistical significance at p value < 0.05 was applied in the MRA. All analyses were performed using SPSS version 22.0 .Quantitative data from the survey were interpreted using descriptive statistics consisting of percentages, means, standard deviations (SD), medians, and interquartile range (IQR). The prevalence of PVh was calculated based on the PVh level at moderate or above. The Mann–Whitney A total of 488 people completed the survey. Most of them (70.5%) were females. The median (IQR) age was 41 (35–47) years and 66.6% of survey respondents had a bachelor's degree or higher. They lived in different provinces across Thailand, which were primarily in Southern, Eastern, and Western regions. Altogether, 72.3% were not healthcare professionals. Over 90% of respondents were parents who hold the right to make a final decision regarding their child’s vaccination. About two-thirds of respondents were a father or a mother of the children, while the remaining were relatives of the children. About one-fourth of their children had a history of vaccine refusal, since they were extremely trpanophobic . The refusal rate of COVID-19 vaccine or any other vaccines for themselves or their children were low (between 12.7% to 15%). The result showed that 96.7% of respondents had completed the initial COVID-19 vaccination with a median (IQR) of 3 (2–3) shots. Around 80% of the children were living in areas, where COVID-19 was prevalent at the time of the survey. Most of the respondents (90.4%) did not have children with a high risk of serious COVID-19 complications due to congenital diseases. However, nearly all of them (94.3%) had at least one senior family member. Besides, 27% of the respondents had family members with a high risk of serious COVID-19 complications due to comorbidities, such as diabetes mellitus, asthma, chronic obstructive pulmonary disease, cardiovascular diseases, chronic kidney disease, or immunosuppression . Contrarily, the parents who had completed the initial COVID-19 vaccination had a statistically significant lower level of PVh than others (3 (IQR 2–3) vs. 4 (IQR 2–5); p value < 0.001). The statistically significant difference between median PVh level among parents with yes or no answer to other EC&V and FC questionnaire items were not found  vs. 3 (IQR 2–3), and 3 (IQR 2–4) vs. 3 (IQR 2–3), respectively; Although the respondents had a neutral attitude towards COVID-19, they had high levels of positive attitude towards COVID-19 vaccine, attitude towards the vaccination program, parental subjective norm, and parental perceived behavioral control Table .Table 4PThis online survey examined the parental COVID-19 vaccination hesitancy among parents of children aged 5–18 years in Thailand. Most of the respondents were parents who hold the right to make a final decision regarding their child’s vaccination. They probably had a high acceptance level of the COVID-19 vaccination, since 96.7% of them had completed the vaccine program, and the average number of the vaccines they received was around 3 shots which included the initial and booster doses.Even though their children were living in an outbreak area and there were senior or at-risk family members, our findings revealed that 58% of Thai parents had moderate to extremely high levels of PVh. This result was in line with earlier studies conducted in other countries, such as Turkey , Japan , Italy  and SaudPrevious refusal to receive the COVID-19 vaccine for themselves and completing the initial COVID-19 vaccination were associated with higher and lower PVh, respectively. Those results indicated that the direct experience of the parents with their COVID-19 vaccination was one of the key factors influencing PVh. This hypothesis was supported by previous studies which found that there was an inverse relationship between COVID-19 vaccination history of the parents and PVh , 28, 30.Our study also found that PVh was higher with statistical significance among parents who previously refused any other vaccinations for their children. These parents may have misunderstandings, distrust, excessive fear, and concerns about any vaccination, especially COVID-19 vaccines which had been manufactured by newly invented platforms for an unfamiliar emerging disease . As a reIn previous studies, parents who had a family member who suffered or died from the disease showed a lower level of PVh . AlthougParental subjective norm (SN), perceived behavioral control (PC2), and attitude towards vaccine regarding the unavailability of long-term safety (AV4) were rated with high levels of agreement in our study. However, the multiple regression analysis found that only attitude towards COVID-19, attitude towards COVID-19 vaccine, and parental perceived behavioral control statistically influenced PVh with negative beta values indicating the inverse relationship between those factors and the level of hesitancy. As a result, communication to increase the perceived risk of COVID-19, the perceived benefit of COVID-19 vaccine, and the perceived behavioral control could be the most effective directions to reduce the level of parental COVID-19 hesitancy , 37.To our knowledge, this is the first study to explore the parental COVID-19 vaccine hesitancy in Thailand. Most of the respondents were parents who hold the right to make a final decision regarding their child’s vaccination. The questionnaire was systematically developed in Thai language and tested for its validity and reliability. Therefore, their opinions collected in our study could be highly correlated with the actual decision for their children in the near future.Although our study was conducted in various living regions which improved the generalizability of our results, some limitations require consideration. First, the study was an online survey. This could be of concern that only parents who were familiar with an online questionnaire and well-equipped can participate in the data collection. Thanks to several national projects of the Thai government such as Thai-Cha-Na (mobile application for tracking COVID-19 contact persons) and Mor-Prompt (mobile application for COVID-19 vaccine services) which most Thai people used in everyday life, nowadays, Thai parents could participate in the online survey without any limitations as aforementioned. Secondly, we conducted this study during a period when the incidence of severe COVID-19 was relatively low. The parental vaccine hesitancy was sensitive to the context of data collection, e.g., outbreak situation and trend, news, rumors on public and social media, national and local policy, as well as local availability of the vaccine. The prevalence of PVh in this study was calculated based on the PVh level at moderate or above. Different cutoff PVh levels for data transformation, such as determining only high and extremely high PVh levels could lead to remarkably different prevalence . TherefoThe parental COVID-19 vaccination hesitancy among Thai parents of children aged 5–18 years was prevalent. The hesitancy level was higher among parents who refused their COVID-19 vaccination or denied any other vaccinations for their children. Contrarily, parents who had completed the initial COVID-19 vaccination had lower vaccine hesitancy. Past experiences regarding the parents and children vaccination could be considered as a screening tool for the risk of vaccine hesitancy. Factors influencing the hesitancy of Thai parents were multifactorial, especially attitudes towards COVID-19, attitudes towards COVID-19 vaccine, and perceived behavioral control. Parents and public education should emphasize on threats and consequences of COVID-19 and the risk–benefit ratio of COVID-19 vaccine as well as inspire the confidence of the parents regarding their child’s vaccination.


Treatment discontinuation is a major challenge in routine clinical settings. Despite poor adherence to antipsychotic medication, long acting injectable (LAI) formulations are an underutilized option in psychotic disorders. Recently, an earlier and broader use of LAIs has been emphasized. However, few studies have evaluated the factors associated with LAI antipsychotic discontinuation in ordinary clinical practice. The main purpose of the present study was, therefore, to identify the factors associated with LAI discontinuation in a real-world setting. Patients in treatment with LAI antipsychotics were recruited. A Cox regression analysis was applied considering a 12-month follow-up period. Moreover, a Kaplan-Meier survival analysis was applied to compare the single treatment LAI antipsychotic groups in terms of time to discontinuation. Our analysis showed an LAI discontinuation rate at 12 months, corresponding to 28.8%, with olanzapine and aripiprazole having a longer time to discontinuation compared to zuclopenthixol. The results of the present study can help clinicians with their choice of LAI antipsychotic according to patients’ characteristics and in a context of precision medicine. Increasing knowledge about factors affecting discontinuation of LAI antipsychotics can improve the prescribing practices of these compounds. Individualized approaches may ameliorate long-term patients’ treatment adherence, thus preventing the long-term disability caused by psychotic disorders. The progressive aging of the world population, particularly in Western countries, is associated with an increase of the prevalence of different chronic conditions. Chronic diseases are generally defined as physical or mental disorders that last more than one year, requiring ongoing care . ChronicThe psychopharmacological treatment of schizophrenia and other psychotic disorders includes the use of antipsychotics, which are traditionally divided into two classes: first generation antipsychotics (FGA) and second-generation antipsychotics (SGA). Both classes of drugs are effective in treating positive symptoms , whilst data about the efficacy on negative, cognitive and affective dimensions are contrasting and FGAs may even worsen these symptoms. Nevertheless, antipsychotics may also induce different types of side-effects . CurrentDrop-out rates from LAI antipsychotics are observed in the real world. However, current data show that discontinuation rates of second generation antipsychotic LAIs (SGA-LAIs) seem similar to those of first-generation compounds (FGA-LAIs) , althougIn this framework, the objectives of the present study are: (1) to identify clinical and demographic predictors of LAI antipsychotic discontinuation during the first year of treatment in patients suffering from psychotic disorders; (2) to investigate potential differences in the time of discontinuation between the LAI compounds ; (3) to evaluate other clinical factors (including tolerability) possibly associated with the prescription of a specific LAI antipsychotic. Therefore, using real world data, our main research questions were: (1) What is the rate of LAI antipsychotic discontinuation in a sample of every-day patients with psychotic disorders during a 12 month follow-up period? (2) Are there some potential clinical and demographic predictors of LAI discontinuation in patients with psychotic disorders? (3) Are there some differences in terms of discontinuation between different LAI antipsychotic drugs? (4) Are there some clinical factors associated with the prescription of specific LAI antipsychotics? Therefore, factors associated with LAI antipsychotic discontinuation should be identified in order to implement personalized medicine .Patients with a diagnosis of schizophrenia, schizoaffective disorder or bipolar disorder type I (with lifetime psychotic features) according to DSM   criteriaThe data of the following demographic and clinical variables (referred to the visit before starting LAI) were collected: age, gender, marital status, work status, history of criminal acts, age at onset and duration of illness (years), duration of untreated illness (DUI), presence and number of previous suicide attempts, presence and number of previous hospitalizations, type of LAI medication with mean monthly dosage, presence of personality disorders, family history of psychiatric disorders, multiple family history of psychiatric disorders, pre-onset and post-onset psychiatric comorbidity and poly-comorbidity, pre-onset and post-onset substance misuse and poly-misuse, pre-onset and post-onset medical comorbidity and poly-comorbidity, current poly-pharmacotherapy, current or lifetime psychotherapy, reason for discontinuation of LAI antipsychotic, side effects of therapy and presence of multiple side effects.Duration of untreated illness was considered as the time elapsing between the onset of the disorder and the prescription of a proper treatment  ,26.Descriptive statistics on the total sample were performed. A Cox regression analysis was applied considering a 12-month follow-up period. This model was realized to identify the predictors of LAI antipsychotic discontinuation . The evep ≤ 0.05. All statistical analyses were performed using SPSS .The level of statistical significance was set at p < 0.01), paliperidone (p < 0.01) and olanzapine (p < 0.01).The total sample consisted of 382 patients: 221 males (57.9%) and 161 females (42.1%) with a mean age of 45.430 years (±12.795). One hundred and one subjects (26.4%) were affected by psychotic bipolar disorder, 59 by schizoaffective disorder (15.5%) and 222 by schizophrenia (58.1%). The mean dose of LAI antipsychotics was: 96.790 ± 40.434 mg/4 weeks for haloperidol (N = 150), 215.800 ± 100.420 mg/4 weeks for zuclopenthixol (N = 44), 111.679 ± 32.859 mg/4 weeks for paliperidone (N = 77), 340.318 ± 79.042 mg/4 weeks (N = 22) for olanzapine, 371.80 ± 50.253 mg/4 weeks (N = 56) for aripiprazole, 39.46 ± 11.656 mg/2 weeks for risperidone. If these doses are converted in olanzapine equivalents: the 4-week dose of zuclopenthixol resulted to be less than that of haloperidol . A trend to statistical significance was found also for the presence of pre-onset poly-substance use disorders (p = 0.058). The results were practically the same when duration of illness was removed from the model . Proportionality of hazards was satisfied for age (p = 0.070) and duration of illness (p = 0.444). Patients with pre-onset poly-substance use disorder had a shorter time of discontinuation (8.760 months ± 3.673) compared to the others (10.300 months ± 3.194). With regard to survival analysis, patients treated with olanzapine  and aripiprazole  had a longer time to discontinuation with respect to those treated with zuclopenthixol (p = 0.539).The Cox regression  showed tenthixol . No statp < 0.001). Sedation  and sexual dysfunction  were more frequently reported in patients treated with olanzapine than the other treatment groups (p < 0.05), while motor symptoms emerged more often in patients treated with haloperidol  than in those in treatment with other compounds (p < 0.05). This latter result was also confirmed by the analysis comparing FGA versus SGA-LAIs . Patients reporting side effects were older , more frequently women , more often treated with poly-therapy , with less frequent pre-onset medical poly-comorbidity  and with less frequent pre-onset poly-substance use disorders  than the counterpart. Duration of illness was not significantly different in the two groups identified by the presence or absence of treatment side effects when co-variating for the type of compound . Furthermore, patients with poor compliance resulted to have a shorter duration of untreated illness , a lower number of lifetime suicide attempts , reported less multiple side effects  and had a more frequent history of criminal acts  than their counterparts. The frequency of prescription of the compounds was different among diagnoses: patients affected by schizophrenia were more likely to receive haloperidol and less likely to receive aripiprazole compared to subjects suffering from schizoaffective or bipolar disorder type I with psychotic features . This latter result was also confirmed by the analysis comparing FGA versus SGA-LAIs . The frequency of prescription of the compounds was different among genders : zuclopenthixol was preferentially prescribed in males compared to females (p < 0.05). In addition, patients in treatment with paliperidone or olanzapine showed less pre-onset medical comorbidity than the other treatment groups . The distribution of treatments was also significantly different according to the lifetime administration of psychotherapy : patients who received psychotherapy during the course of life were more likely in treatment with aripiprazole or paliperidone (p < 0.05). In addition, patients treated with SGA-LAIs were more likely to have received lifetime psychotherapy than those in treatment with FGA-LAIs . Specifically supportive psychotherapy had been more frequently administered in patients treated with SGA-LAIs than in those in treatment with FGA-LAIs . In addition, the patients treated with SGAs received psychotherapy more frequently than the others , while those in treatment with FGAs more frequently had post-onset psychiatric comorbidity than their counterparts . On the contrary, pre-onset substance use disorders were more frequent in patients treated with atypical antipsychotics than those in treatment with typical ones . Finally, patients treated with zuclopenthixol had a significantly longer duration of illness with respect to subjects in treatment with aripiprazole (p = 0.029), and generally, patients treated with FGA-LAIs had a longer duration of illness than those to whom SGA-LAIs were prescribed . Patients in treatment with olanzapine showed a longer treatment duration compared to those in treatment with zuclopenthixol (p = 0.019) and risperidone (p = 0.012), as shown by univariate analysis weighted for duration of illness.The frequency of side effects (moderate in intensity) was different in the treatment groups .No other significant differences were found between treatment groups (both considering the single compounds and SGA versus FGA-LAIs) with regard to the other variables . Second, from our point of view, the observed few prescriptions of SGA-LAIs may further stimulate the ongoing discussion whether the newer LAI antipsychotics should be the preferential choice in first-episode patients. Third, it would be relevant to develop LAI formulations for the other atypical antipsychotics.The study presents different limitations related to its naturalistic, non-interventional design. First, we acknowledge that although time to discontinuation could be considered a pragmatic outcome measure, the lack of a randomized controlled design prevents us from drawing definitive conclusions related to the comparative efficacy of the different LAIs. Nevertheless, a strength of the present study includes the large number of patients (n = 382) with affective and non-affective psychotic disorders, enrolled in outpatient services and day hospital of two different Mental Health Departments (one in urban and the other in sub-urban environment), thus offering a comprehensive overview and complexity of a real-world clinical setting. Second, for some LAIs, including olanzapine and risperidone-LAI, the number of patients was relatively small, limiting the precision of our findings. Moreover, paliperidone 3-monthly LAI has recently become available in Italy. Third, rating scale scores were not collected to assess symptom severity and side effects. Moreover, no subjective questionnaires regarding satisfaction or quality of life with therapy were provided to patients, as reported in other studies . NeverthDespite such limitations, we believe that the present study is important since it can provide insight into the practical consequences of starting different LAI antipsychotics in real world settings.This study provides important information about predictors of discontinuation of LAI antipsychotic treatment and patterns of prescription. Approximately 30% of patients stopped pharmacotherapy soon after initiation of a LAI antipsychotic, mainly as a result of lack of compliance or side effects. However, some SGA-LAIs, including aripiprazole and olanzapine-LAIs, showed a longer time to discontinuation than zuclopenthixol depot. The type of prescribed LAI antipsychotic at baseline as well as pre-onset poly-substance abuse seems to affect treatment continuation of a LAI antipsychotic. Furthermore, our research showed that patients’ characteristics influence prescription patterns. The choice of a specific LAI antipsychotic needs to be carefully discussed with the patient, taking into account individual features and possible barriers. A regular and careful assessment of adherence levels before and in the course of LAI treatment could be helpful to predict and monitor the risk of discontinuation. Nevertheless, it should be taken into account that the first relapse is a strong predictor of a rapid progression of both bipolar disorder and schizophrenia  and that


The aim of this project was to implement long-read sequencing for BCR-ABL1 TKI resistance mutation screening in a clinical setting for patients undergoing treatment for chronic myeloid leukemia.https://github.com/pharmbio/clampProcesses were established for registering and transferring samples from the clinic to an academic sequencing facility for long-read sequencing. An automated analysis pipeline for detecting mutations was established, and an information system was implemented comprising features for data management, analysis and visualization. Clinical validation was performed by identifying BCR-ABL1 TKI resistance mutations by Sanger and long-read sequencing in parallel. The developed software is available as open source via GitHub at The information system enabled traceable transfer of samples from the clinic to the sequencing facility, robust and automated analysis of the long-read sequence data, and communication of results from sequence analysis in a reporting format that could be easily interpreted and acted upon by clinical experts. In a validation study, all 17 resistance mutations found by Sanger sequencing were also detected by long-read sequencing. An additional 16 mutations were found only by long-read sequencing, all of them with frequencies below the limit of detection for Sanger sequencing. The clonal distributions of co-existing mutations were automatically resolved through the long-read data analysis. After the implementation and validation, the clinical laboratory switched their routine protocol from using Sanger to long-read sequencing for this application.Long-read sequencing delivers results with higher sensitivity compared to Sanger sequencing and enables earlier detection of emerging TKI resistance mutations. The developed processes, analysis workflow, and software components lower barriers for adoption and could be extended to other applications. The parallel nature of NGS can transform large projects into routine activities. With all its advantages, NGS can have difficulties with highly-repetitive or other problematic regions. It can be difficult to stitch together a consensus sequence from very similar short read fragments. Long-read single-molecule sequencing (LR-SMS) ameliorates this problem by producing fragments long enough to unambiguously read through difficult regions.5 Because of these advantages, LR-SMS is increasingly being used for human medical research, for example to identify previously uncharacterized structural variation, determine the clonal distribution of mutations, and to sequence through repetitive regions. However, there is today a lack of established workflows and analysis tools which focus on LR-SMS for routine clinical diagnostics.Next-generation sequencing (NGS) technologies are a dramatic improvement over traditional Sanger sequencing in terms of throughput, cost, and accuracy.BCR-ABL1 fusion gene, which is the intended target for the TKI’s. BCR-ABL1 TKI resistance is also relevant for the related disease Acute Lymphoblastic Leukemia (ALL). The multi-resistant substitution T315I is of particular importance for clinical investigations, but other nucleotide substitutions in BCR-ABL1 can also confer resistance. In other clinical cases, the reason for resistance is still unknown.Chronic Myeloid Leukemia (CML) is a well-studied disease. Efficient drug treatments using tyrosine kinase inhibitors (TKIs) are available, but some patients develop drug resistance. This resistance can in many cases be explained by point mutations in the  this is limiting the detection of emerging drug-resistant mutations. Short read NGS makes it possible to detect mutations at lower frequency, but does not generally provide information about clonal composition of co-occurring mutations since the sequence information is broken into small pieces. LR-SMS resolves all of these issues and when obtaining high-accuracy reads, which are currently enabled by PacBio circular consensus sequencing, false positive mutations due to sequencing errors can essentially be removed.As part of the treatment process, Sanger sequencing has traditionally been used to identify T315I and other mutations. This has worked reasonably well but since the sensitivity to detect low-frequency mutations using Sanger sequencing is 15% to 20%, Moreover, a dilution series was performed demonstrating that low frequency mutations (<1%) are detectable. As a relatively new technology, there are fewer bioinformatics packages available for LR-SMS analysis and no turn-key solutions. This presents difficulties for clinical organizations or any organization with established routines where this expertise is not available. To facilitate translation of LR-SMS into clinical applications, there is a need for processes as well as informatics and decision support systems to assist with organizing and automating the analysis work needed for LR-SMS.Our previous work demonstrated that LR-SMS can be applied to studying BCR-ABL1 mutations in CML patients.Here we illustrate how these challenges have been overcome at Uppsala University Hospital for an application in BCR-ABL1 TKI resistance mutation screening. We present how this transition was made via parallel studies using Sanger and PacBio single molecule real-time (SMRT) sequencing with summary statistics from 39 patients. We also resolved a number of logistical issues such as long turnaround for the analyses, inefficient communication through email and written reports with little tractability to samples from the same or other patients. To this end, a web-based system to organize and automate data management, analysis, and visualization was developed.Data were collected from 39 samples analyzed through Uppsala University Hospital. The patients were being treated for Chronic Myeloid Leukemia  or Acute Lymphocytic Leukemia  and suspected to be resistant to the therapy. Treatments, responses, and disease status varied.This study was performed in accordance with the Declaration of Helsinki. The Ethical Committee at Uppsala University, Dnr 2014/233, approved this study. Written informed consent was obtained from the patients.® (Invitrogen), standard protocol and quantified by NanoDrop™ 2000/2000c Spectrophotometers . cDNA was synthesized using the SMARTer™ PCR cDNA synthesis kit , using 1000 ng total RNA.RNA was extracted from peripheral blood or bone marrow samples using a TRIzol The cDNA amplicons underwent end-repair and adaptor ligation to generate SMRTbell™ libraries for PacBio sequencing. SMRTbell™ libraries were quantified using the Qubit assay and library size was confirmed using the Agilent DNA 12000 Kit. Each SMRTbell™ amplicon library was loaded on to 1 SMRT cell and sequenced on the PacBio RS II instrument using C4 chemistry and a 120-minute movie time. Circular consensus sequence (CCS) reads were generated for each sample. The CCS reads in FASTQ format were used as input for the automated analysis pipeline.Long range PCR amplification of the BCR-ABL1 transcript was performed using the Clontech Advantage PCR kit as previously described.https://github.com/pharmbio/clamp). The analysis can be divided into 7 main steps, described below:An analysis workflow was developed to process PacBio sequencing data according to the general procedure described below and summarized in (1) Filter primers. In the first step, all CCS reads are filtered so that only reads having the expected primer sequences both at the 5′ and 3′ ends are kept. In this way, only reads corresponding to the BCR-ABL1 fusion gene are used for further analysis.(2) Assign reference sequence. Next, the filtered reads are used to determine the main isoform of BCR-ABL1 present in the sample. The reason for this analysis is that there can be some small variation in exon usage between different samples. Once the dominant isoform has been determined, this isoform is assigned as a reference sequence for the subsequent steps.(3) Quality check. A quality control is performed to make sure the entire sequence is covered by at least 100 reads, to ensure that no mutation sites are missed. If the quality check fails, then the analysis is aborted.(4) Search for novel mutations. After having passed the quality control, the sample is screened for previously unreported (de novo) mutations. The reads are compared to the reference sequence and all sites with potential nucleotide substitutions are reported.(5) Analyze novel and known resistance mutations. Next, all previously known and potentially novel TKI resistance mutations in BCR-ABL1 are analyzed and their variant allele frequencies (VAF) determined. The results are compiled into a table.(6) Determine clonal composition of positive mutations. In cases where least 2 positive mutations are found, an additional analysis is performed to determine the clonal distribution of all mutations in the sample.(7) Record results in local database. After processing, the raw data files, quality control data, and mutation results are stored in a custom developed information system.https://github.com/pharmbio/clamp).An information system was developed to sustain registration of samples of the clinical side, automated analysis of the produced sequencing data, storage of results in a database, and communication of results to clinicians. The database was implemented on top of SQLite and the interfaces consisting of custom Perl scripts are served over a private intranet with Apache HTTPD. Searches can be made through various fields and a summary of the matches is returned . DetailsAt the Clinical Genetics Division at Uppsala University Hospital (UUH), TKI resistance mutations have traditionally been detected using Sanger sequencing of the BCR-ABL1 fusion gene. We set out to link UUH to the sequencing facility National Genomics Infrastructure (NGI) at Science for Life Laboratory (SciLifeLab) in Sweden.We established a process according to the following: (i) Clinicians register the sample and perform RNA extraction and cDNA synthesis; (ii) Samples are transferred between the hospital and the NGI sequencing facility in Uppsala; (iii) Long-read single molecule sequencing is carried out at the facility; (iv) An automated analysis pipeline is executed; (v) Results are stored in a shared database; (vi) Clinicians are informed of new results and can view and download actionable reports. The process is illustrated in  we were able to identify BCR-ABL1 TKI resistance mutations with variant allele frequencies (VAFs) as low as 0.5%, which is far below the detection limit for routine Sanger analysis. Since early detection of emerging mutations is important to guide treatment and to avoid resistance development, this highlights a major advantage of LR-SMS. Based on our previous work, the cutoff for a positive mutation was set to 0.5%. However, only mutations above 1% were considered relevant by the clinicians to reduce the risk of false positives.In a previous dilution series experiment,The LR-SMS analysis workflow is simple and automated. Technicians need only to run a single script and upload the resulting files to produce quality control reports and mutation results. Result retrieval by clinicians was similarly simplified over the former practice of exchanging static documents. Feedback from clinicians helped design a data analysis system that they can and want to use. These small changes in procedure helped ease the transition away from Sanger to PacBio SMRT sequencing.LR-SMS was run in parallel with routine Sanger sequencing for a period of 25 months. During this period, 39 samples from patients not responding to TKI treatment were collected to determine the presence of BCR-ABL1 resistance mutations . A totalIn 21 samples, no mutations were reported by either Sanger or LR-SMS. Of the 18 samples which did show mutations, 5 had complete agreement between the methods. Of the remaining 13 samples, LR-SMS found more mutations than Sanger. No mutations identified by Sanger were missed by LR-SMS. LR-SMS reported this mutation as strongly dominating . In addition, LR-SMS detected a modest amount (1.7%) of mutation E255V in sample 4. This mutation, also associated with imatinib resistance, was not identified by Sanger, probably due to its low prevalence.Samples 4 and 7 were found by both methods to include mutation Y253H, which is associated with imatinib resistance.In Sample 15, both methods identified mutations L273M and T315I but LR-SMS also reported the rare mutation K247R. T315I is the well-known “gatekeeper” mutation associated with imatinib and secondary resistance.One of the benefits of long-read sequencing is that phasing of mutations separated by several kilo bases becomes a trivial task, whereas this information is more difficult to obtain from other sequencing technologies. This is exemplified in In Samples 1, 12, 14, 24, and 29, LR-SMS found the Sanger mutations but also reported others, undetected by Sanger. These additional mutations were near or below Sanger’s detection limit but could still be of clinical significance see . In someIn Sample 33, both methods found the 2 mutations L298V and E255K. The methods agreed on mutation T315I for Samples 10 and 16, with values approaching 100% for LR-SMS. Sample 2 showed mutations F359I and T315I with both methods.In Samples 3, 5, 18, 26, 28 and 35, LR-SMS found mutations where Sanger reported only wild-type. In these samples, LR-SMS reported mutation levels well below Sanger’s practical detection limit but these were also below the 1% limit considered relevant for the clinic. Some of these low-level mutations are associated with resistance (T315I and M244V) and others are of uncertain significance . 15 samples showed fewer or no mutations with Sanger. Overall, LR-SMS found every mutation reported by Sanger sequencing and revealed many more missed by Sanger.In summary, LR-SMS discovered mutations which were not found by Sanger. All (9) samples with Sanger reported mutations show (at least) these same mutations with LR- SMS. All mutations found by Sanger were also found by LR-SMS. At a conservative cutoff of 5% for LR-SMS, 5 samples showed fewer or no mutations with Sanger. At the practical detection limit for LR-SMS,https://ukneqas.org.uk). Within this program, control samples with mutations at specific sites in the BCR-ABL1 transcript were supplied by UK-NEQAS to us and to other clinical laboratories across Europe. After having reported our results back to UK-NEQAS, we can conclude that our analysis has obtained a 100% success rate in all test rounds. This means that all true positive mutations have been found, while no false positives mutations have been reported, in any of the analyzed control samples. We are thus confident that our analysis method has an acceptable false positive rate and meets all requirements for clinical reporting.After these encouraging results, the method was further validated and eventually introduced into clinical routine. Since 2015, our implementation has been validated twice every year in the UK-NEQAS program “BCR::ABL1 Kinase Domain Variant Mutation Status.” UK-NEQAS performs independent monitoring of laboratory tests, and is used by many clinical labs in Europe to ensure the quality of their accredited analyses  data analysis. If the entire data analysis is not automated, it presents additional challenges to incorporate in clinical practice.New technological developments and applications can be found in academic settings, such as in core facilities serving the scientific community. It is not uncommon that these technologies mature over a period of years, and ultimately make their way into the clinic. In our work, we bridged the gap and allowed Uppsala University Hospital to make use of the academic sequencing facility for performing long-read sequencing. The main components to enable this were processes to prepare and exchange samples between the clinic and the facility, automated workflows for the sequence analysis, and a system for storing and reporting results back to clinicians for interpretation. One of the keys to helping clinicians switch over to a new technology was to get their input in the design process of reports and interfaces.In this manuscript we present the first fully integrated solutions for long-read sequencing comprising the complete workflow, from sample registration via long-read sequencing at a core facility to clinical decision aid on the hospital side, to detect low-frequency mutations in high coverage long-read amplicon data, such as in this BCR-ABL1 project. Although it would have been possible to perform alignment using standard tools such as minimap2 followed by variant calling by DeepVariant, it is important to note that such analyses have been developed for germline variation but have not been optimized for detection of low-frequency somatic variation. Since many of the variant calling tools for long-read are based on machine learning, it would be a non-trivial task to apply these for somatic variant calling and with uncertain outcomes. Moreover, our analysis strategy contains specific steps fine-tuned for the BCR-ABL1 region; for example, filtering is performed in order to only analyze reads originating from the BCR-ABL1 molecules while filtering out reads originating from ABL1 (not fused with BCR). We also perform specific quality control steps to ensure that all clinically relevant mutation positions can be assigned either as a negative or a positive call. To the best of our knowledge, no other existing pipelines can detect cancer mutations down to a frequency of 1% from the long-read data generated within this project.The possibility to take advantage of long-read sequencing via a core facility includes no up-front costs for sequencing instruments, which currently are quite expensive, at least for PacBio SMRT sequencing. Further, costs are kept lower as utilization of sequencing instruments is higher when shared with academic researchers. Finally, the clinical organization is not required to build up and maintain state-of- the-art expertise in bioinformatics. The information system developed in this project can be directly reused to serve as a blueprint for other long-read sequencing applications.We present an example where long-read sequencing was implemented for BCR-ABL1 TKI resistance mutation screening, as a clinical routine analysis. The process comprised linking the clinic to an academic sequencing facility where sequencing of samples was carried out, the development of a supportive information system, and validation steps to verify the methodology. Key components in the translation were the processes for sample preparation and transfer, automated data analysis pipelines, and a shared system for storage and reporting. Long-read sequencing was shown to have advantages over previous methods, such as higher sensitivity, and ultimately replaced Sanger sequencing as the routine method for detection of BCR-ABL1 mutations.Click here for additional data file.Supplemental material, sj-pdf-1-cix-10.1177_11769351221110872 for Migrating to Long-Read Sequencing for Clinical Routine BCR-ABL1 TKI Resistance Mutation Screening by Wesley Schaal, Adam Ameur, Ulla Olsson-Strömberg, Monica Hermanson, Lucia Cavelier and Ola Spjuth in Cancer InformaticsClick here for additional data file.Supplemental material, sj-pdf-2-cix-10.1177_11769351221110872 for Migrating to Long-Read Sequencing for Clinical Routine BCR-ABL1 TKI Resistance Mutation Screening by Wesley Schaal, Adam Ameur, Ulla Olsson-Strömberg, Monica Hermanson, Lucia Cavelier and Ola Spjuth in Cancer InformaticsClick here for additional data file.Supplemental material, sj-pdf-3-cix-10.1177_11769351221110872 for Migrating to Long-Read Sequencing for Clinical Routine BCR-ABL1 TKI Resistance Mutation Screening by Wesley Schaal, Adam Ameur, Ulla Olsson-Strömberg, Monica Hermanson, Lucia Cavelier and Ola Spjuth in Cancer InformaticsClick here for additional data file.Supplemental material, sj-pdf-4-cix-10.1177_11769351221110872 for Migrating to Long-Read Sequencing for Clinical Routine BCR-ABL1 TKI Resistance Mutation Screening by Wesley Schaal, Adam Ameur, Ulla Olsson-Strömberg, Monica Hermanson, Lucia Cavelier and Ola Spjuth in Cancer InformaticsClick here for additional data file.Supplemental material, sj-pdf-5-cix-10.1177_11769351221110872 for Migrating to Long-Read Sequencing for Clinical Routine BCR-ABL1 TKI Resistance Mutation Screening by Wesley Schaal, Adam Ameur, Ulla Olsson-Strömberg, Monica Hermanson, Lucia Cavelier and Ola Spjuth in Cancer Informatics


Since its first appearance in Wuhan December 2019, SARS-CoV2 virus received great attention due to its severe symptoms and high spread causing COVID-19 disease which spread all over the world like a pandemic. The causative virus is capable of human-to-human transmission via droplet and direct contact suggesting that upper respiratory tract is the main site to virus manifestations.There is a great diversity in its clinical picture, although the severe respiratory and neurological symptoms are commonly present; however, other symptoms are present. Although otological manifestations are reported in many COVID-19 patients even in asymptomatic cases, they did not receive much attention compared with other critical manifestations. In this article, we paid our attention specifically to the otological manifestations of COVID-19 and their relevance either to the virus infection, treatment, or vaccination through literature review.COVID-19 disease has a deleterious effect on the inner ear. This effect is not only due to SARS-Cov-2 infection, but it could be also due to the ototoxic drugs used for treatment. The COVID-19 vaccinations are found to be implicated in the otological symptoms in some cases. Coronavirus disease 2019 (COVID-19) is a contagious respiratory and vascular disease that was found to be caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 virus). Patients of COVID-19 are presented with many symptoms and signs with great variability in their clinical pictures, and clinical findings were noticed worldwide. However, the most common symptoms are fever, shortness of breath, cough, sore throat, headache, muscle pain, and taste and smell disturbance. The incidence of otological symptoms is quite small including hearing loss, vestibular symptoms, tinnitus, and otitis media in addition to rare symptoms as facial palsy or migraine. Some asymptomatic cases with positive polymerase chain reaction (PCR) for COVID-19 showed evidence of inner ear affection. This might indicate that the prevalence of otological signs of auditory damage related to SARS-CoV-2 infection is much more than we thought. In this review, we tried to highlight the otological manifestations reported in different studies and their relevance to treatment or vaccination.In this review, English-language studies were searched in PubMed and the Cochrane databases about COVID-19 published in 2019, 2020, and 2021. These studies included meta-analyses, systematic reviews, randomized clinical trials (RCTs), practical guidelines, and case reports. The references of the selected articles were searched for additional data.By the end of 2019, a new coronaviruses family member appeared in Wuhan-China where several cases of pneumonia appeared with unidentified etiology. The new coronavirus was identified on 6 January 2020 as the cause of these cases and was named as SARS-CoV-2, and on 30 January 2020, WHO declared the coronavirus disease as COVID-19 and declared the pandemic state with public health emergency of international concern  hPhases b and c are often grouped together and referred to as long COVID with common symptoms of dizziness, tinnitus, and otalgia .SARS-CoV-2 is characterized by its infectious abilities. Viral pneumonia is the most frequent serious clinical picture of COVID-19 with sever manifestation such as fever, dry cough, dyspnea, hypoxemia, and bilateral infiltrates on chest radiography in addition to fatigue, shortness of breath, anosmia, and loss of taste. However, some cases had no symptoms . A wide The estimated prevalence of hearing loss in COVID-19 infection is about 7.6% which should be interpreted with caution as most studies used medical records or self-reported symptoms through telephone call or questionnaires without appropriate audio-vestibular evaluation due to home isolation of patients , 23. JeoSeveral authors reported sudden SNHL (SSNHL) in COVID-19 patients without prior otologic problems or use of ototoxic medication , 25–27. The elderly people have high incidence of comorbidity such as hypertension, atherosclerosis, and diabetes mellitus which increase their risk for thrombosis and the occurrence of HL with their COVID-19 infection . In an iThe neurotrophic and neuro-invasive characteristics of SAR-Cov-2 virus can lead to peripheral neuropathy including the auditory neuropathy (AN). Sedaghat and Karimi  reportedVertigo or dizziness has recently been described as a clinical manifestation of neuro-invasive characteristics of COVID-19 as a result of acute labyrinthitis, vestibular neuritis, acute otitis media, or secondary to stroke following COVID-19 .Viola et al.  reportedUranaka et al.  reportedThe data of tinnitus in COVID-19 were collected using self-reported questionnaires such as Tinnitus Handicap Inventory . ThroughRegarding the tinnitus onset, there is a lack of consistency where it could be reported with the diagnosis of COVID-19 , after dThe neuro-invasive properties of coronaviruses are responsible for acute facial palsy in COVID-19 patients either isolated or unilateral  or bilatExposure to viruses may lead to upper respiratory tract infection with mucus secretions and damage to the ciliated columnar epithelium in the middle ear, Eustachian tubes, and sinuses. Fidan  reportedMady et al.  reportedOtalgia was reported in case reports and cross-sectional studies in COVID-19 patients. This symptom was attributed mainly to acute otitis media and otitis externa in those patients. The incidence is unknown due to small sample size of studies, however. Earache could be the clinical symptoms during the early phase of the coronavirus infection .There is an association between otoneurological manifestation of COVID-19 and migraine which was present in 30.8% of COVID-19 cases studied by Viola et al. . Those aMany of previously or currently used drugs in treating COVID-19 have known ototoxicity Table . These dAzithromycin which is a macrolide antibiotic with known anti-inflammatory properties and inhibits viral replication of human influenza virus H1N1 in vivo. It is documented that azithromycin can cause HL, tinnitus, and imbalance. HL is usually irreversible and range from mild to severe SNHL even at standard oral doses of 250 mg [Other types of treatment protocols used multiple drugs for COVID-19 including f 250 mg . Althougf 250 mg .Interferons (IFNs) are natural antiviral and immunoregulatory agents that react to viral infections and determine the immune response to the viral infection. In COVID-19 disease, IFN-α therapy significantly reduced rates of viral shedding and levels of inflammatory markers, whereas IFN-β therapy improved virologic clearance . Accordilopinavir–ritonavir . Few reports described anecdotal cases of hearing loss associated with their use, postulating possible mitochondrial toxicity as a potential etiologic mechanism. Moderate, bilateral HL was confirmed by audiologic testing in a patient 4 weeks after initiation of lopinavir-ritonavir therapy which was reversible after discontinuation of treatment [Ribavirin is another antiviral agent that interferes with viral replication through inhibition of viral mRNA synthesis. Minimal data exists on the ototoxic effects of ribavirin alone as it is usually combined with INF for treating COVID-19 patients. Data from several case report studies showed that this combination was followed by HL which could be unilateral or bilateral, permanent, or reversible in addition to tinnitus [Some antiviral drugs are listed among current treatments against SARS-CoV-2 including the drug combination of reatment . Ribavirtinnitus . Interestinnitus .Ivermectin is a broad spectrum antiparasitic drug that has been used recently as a treatment of COVID-19 due to its inhibitory effect on the replication of the SARS-CoV-2 virus in vitro [in vitro . It is uin vitro .Most drugs used in the treatment of COVID-19 are usually administrated in combination and all of them have ototoxic effects. The condition is worsened additional factors like aging, underlying hearing impairment, comorbidity, genetic factors, and renal impairment. Renal impairment occurred in 20 to 40% of critically ill COVID-19 patients, and this will reduce the rate of elimination of ototoxic drugs from the body and increase the risk of ototoxicity. Additionally, hypoxia (which is a defining feature of serious COVID-19 disease) and the hypercoagulable state associated with COVID-19 may exacerbate the ototoxic effects of drugs and increase the risk of HL due to microthrombi formation in these patients .So, the American Speech–Language–Hearing Association  guidelines are used for all patients with COVID-19 who should be audiologically monitored during the treatment course, receive post treatment audiologic evaluations at 3 months and 6 months after cessation of treatment, and receive prompt aural rehabilitation if ototoxic effects should manifest .Different vaccines were used in COVID-19 disease such as BNT162b2 mRNA Pfizer-BioNTech COVID-19 and the mRNA-1273 SARS-CoV-2Moderna COVID-19. During the early release of the vaccines, otologic symptoms were not listed as common potential adverse effects. But later, there was an increase in the frequency of patients presenting with SSNHL, tinnitus, aural fullness, and/or the exacerbation of previously stable Menière’s in addition to autoimmune inner ear disease (AIED) .The House Ear Clinic developed a study in subjects within 30 days after they received COVID-19 vaccination. The study was conducted along 3 years . They reported an increase in the incidence of SSNHL from 1.60% in 2019 to 2.44 and 3.85% in 2020 and 2021, respectively. They also reported that hearing loss as the most common symptom followed by tinnitus, dizziness, and aural fullness. The mean time to onset of symptoms was 10.2 ± 9  days after vaccination . In anotThe exacerbation of AIED diseases including Meniere’s were noted after the first COVID-19 vaccination with further decrease of hearing noticed at the time of follow-up following the second COVID vaccine dose . AbouzarThere is growing evidence that audiovestibular symptoms may represent atypical manifestation of COVID-19 or even the only presentation so COVID-19 should be taken in consideration in patients presented with audiovestibular manifestations for early diagnosis and better prognosis and also decrease the potential infection risks to ENT specialists. The exact pathogenesis of audiovestibular manifestations in COVID-19 patients is not well known. Audiovestibular manifestations may be sequalae of the SARS-CoV-2 virus or as side effects of the ant COVID-19 medications; these manifestations may be reversible or not according to the severity of the condition. There is an increase in frequency of the audiovestibular symptoms after COVID-19 vaccinations. More large-scaled studies are needed to understand the pathogenesis and the audiovestibular complications, the risk factors for developing this challenging disease, and audiovestibular manifestations after vaccination and the relation to different medications.


In intensive care unit (ICU) settings, the transmission risk of carbapenem-resistant, gram-negative bacteria (CRGNB) is high. There is a paucity of data regarding the effectiveness of interventions, including active screening, preemptive isolation, and contact precautions, to reduce transmission of CRGNB.We conducted a pragmatic, cluster-randomized, non-blinded cross-over study in 6 adult ICUs in a tertiary care center in Seoul, South Korea. ICUs were randomly assigned to perform active surveillance testing with preemptive isolation and contact precautions (intervention) or standard precautions (control) during the initial 6-month study period, followed by a 1-month washout period. During a subsequent 6-month period, departments that used standard precautions switched to using interventional precautions and vice versa. The incidence rates of CRGNB were compared between the two periods using Poisson regression analysis.During the study period, there were 2268 and 2224 ICU admissions during the intervention and control periods, respectively. Because a carbapenemase-producing Enterobacterales outbreak occurred in a surgical ICU (SICU), we excluded admissions to the SICU during both the intervention and control periods and performed a modified intention-to-treat (mITT) analysis. In mITT analysis, a total of 1314 patients were included. The acquisition rate of CRGNB was 1.75 cases per 1000 person-days during the intervention period versus 3.33 cases per 1000 person-days during the control period  0.23–1.11]; P = 0.07).Although this study was underpowered and showed borderline significance, active surveillance testing and preemptive isolation could be considered in settings with high baseline prevalence of CRGNB.Trial registration Clinicaltrials.gov Identifier: NCT03980197.The online version contains supplementary material available at 10.1186/s13756-023-01222-2. Pseudomonas aeruginosa, Acinetobacter baumannii, and Enterobacterales, have been leading causes of healthcare-associated infections and intensive care unit (ICU)-acquired infections [A. baumannii (CRAB) and P. aeruginosa (CRPA) have increased; in a 2015 surveillance program by the Korea Centers for Disease Control and Prevention, 85% of A. baumannii and 35% of P. aeruginosa were carbapenem-resistant [Staphylococcus aureus (MRSA), several studies found that screening and isolation were not effective for reducing its transmission [Carbapenem-resistant, gram-negative bacteria (CRGNB), including fections . In Koresmission  with gooWe conducted a pragmatic, cluster-randomized, nonblinded cross-over study in the included randomized ICUs between June 2019 and June 2020. We included 6 adult ICUs in a tertiary care hospital, Seoul, South Korea: two medical ICUs (23 beds), two surgical ICUs (26 beds), a cardiac ICU (16 beds), and a cardiothoracic surgery ICU (15 beds) in a tertiary care hospital. The study was approved by the physicians and nurse team leaders of each ICU and the institutional review board (IRB no. 2019–0274). The requirements for informed consent were waived. ICUs were randomly assigned to perform active surveillance testing (intervention) or use standard precautions (control) during the initial 6-month study period (period 1), followed by a 1-month washout period, and alternative during the second 6-month period (period 2). Randomization of ICU was performed by SPSS for Windows software, version 21 . The microbiology laboratory processed surveillance specimens using standard culture-based identification of CRGNB. Patients with histories of CRGNB colonization or infection were placed under contact precautions at the time of admission.In the intervention period, stool or perirectal swabs for CRPA, CRAB, and CRE surveillance cultures and sputum, or endotracheal cultures for CRPA or CRAB, were obtained from patients within 2 days of their admission to the ICU and weekly thereafter. In the intervention period, preemptive isolation and contact precautions were implemented at admission, and if the initial surveillance test was negative, contact precautions were ceased, and standard precautions were continued. If the initial surveillance test or subsequent surveillances or clinical culture tests were positive for CRGNB, isolation and contact precautions were continued until 3 negative consecutive test results were obtained. In the control period, surveillance testing was not performed, and if clinical specimens were positive for CRGNB, contact precautions were implemented. During both the intervention and control periods, daily chlorhexidine-bathing was performed in all ICUs, and contact precautions were required in patients with MRSA and VRE colonization or infection. In period 2 (from April to June 2020), universal use of personal protective equipment (PPE)  was implemented for response to COVID-19 pandemic when caring patients in ICUs. During the whole study period, hand hygiene compliance was observed 4 times by a year by the infection control team staff, and the results by units were disclosed to all hospital staffs. Promotions for improving the compliance of hand hygiene included frequent monitoring and real-time feedback by infection control leader in ICU nursing team, and hospital-wide rewards given to the units with high hand hygiene compliance.If outbreaks of CRGNB occurred, surveillance and post-outbreak surveillance in the control period were permitted.An event was defined as a positive result for CRGNB from a clinical culture. The event date was the date of the earliest positive clinical culture. A patient was classified as having a new event if they had stayed in the ICU > 2 days, had no history of colonization or infection during the previous year, had no positive clinical culture within 2 days after admission to the ICU, and if admitted to an intervention ICU, a negative surveillance culture was obtained within 2 days of admission. Days at risk were calculated from the date of the third day in the ICU through the event date or the date two days after discharge from the ICU, whichever was later.The primary outcome was the ICU-level incidence of new events per 1000 ICU patient-days at risk. Secondary ICU-level outcomes were the incidences of new events with CRPA, CRAB, or CRE calculated separately and the incidences of hospital-acquired bloodstream infections, catheter-related bloodstream infections, urinary tract infections, catheter-associated urinary tract infections, pneumonia, ventilator-associated pneumonia, and in-ICU mortality. We also performed subgroup analysis of individual ICUs for new events per 1000 ICU patient-days at risk. In addition, we compared new events per 1000 ICU patient-days at risk between periods 1 and 2. For the evaluation of economic impacts, we also compared the lengths of hospital and ICU stays and the costs of hospitalization between the intervention and control periods.Outbreak was defined as ≥ 3 cases of acquisition of CRGNB within 2 weeks. If surveillance and post-outbreak surveillance were performed in the control period because of a CRGNB outbreak, we excluded the ICU in the modified intention-to-treat (mITT) analysis.Based on the acquisition rate of CRGNB from 2016 to 2018 in ICUs of our hospital, we assumed a mean baseline incidence of CRGNB colonization or infection of 8 per 1000 patient-days; between-cluster variance would be 0.4, and the average amount of time a patient spent in the ICU would be 10 days. This study was designed to achieve 80% power for detecting a reduction in acquisition of 40% in the intervention period with a 2-sided type I error of 5%. According to these assumptions, the estimated sample size was 2400 patients  [t test and the Mann–Whitney U test, respectively. The primary analysis was a comparison of the primary outcomes between the intervention and control periods using an unadjusted Poisson regression model according to the mITT. All statistical analyses were performed using SPSS for Windows software, version 21  and MedCalc Statistical Software version 18.10.2  with P < 0.05 considered statistically significant.Categorical variables were analyzed using the chi-square or Fisher’s exact test, as appropriate. Normally and non-normally distributed continuous variables were analyzed by Student’s A total of 4492 admissions to the 6 ICUs occurred during the study period, and 1884 (42%) with ICU stays ≥ 3 days were enrolled in this study      cases in intervention period were detected in surveillance culture. Of these, 31 were detected in surveillance culture only, and 8 were detected in both surveillance and clinical culture. Five were detected in surveillance culture earlier than in clinical culture. Therefore, 36 (6%) were actually detected in surveillance culture .$5666 for hospitalization in the intervention period than in the control period, the cost difference was also not statistically significant (P = 0.43).For the economic impact evaluation of active surveillance testing of CRGNB, we compared the lengths of hospital and ICU stays and the total cost of hospitalization between the intervention and control periods in the mITT population Table . The meaThis pragmatic, cluster-randomized, cross-over study showed that active surveillance testing to identify patients colonized with CRGNB was associated with non-statistically significant decrease in the acquisition of CRGNB in clinical specimens.Enterococcus [Early detection of patients colonized or infected with CRGNB is important for implementing timely interventions to prevent subsequent spread. However, active surveillance testing is a complicated and resource-intensive intervention that has the potential for several adverse consequences, including reduced contact between healthcare workers and patients due to contact precautions . Previourococcus –9. Howevrococcus –13. We cThe incidence of CRGNB acquisition was higher in the period 1 (before COVID-19 pandemic) than in period 2 (after COVID-19 pandemic). The lower acquisition rate in period 2 may be associated with additional infection prevention measure to respond COVID-19 pandemic, especially universal donning of gown and glove. Previous cluster randomized study showed that universal glove and gown use was associated with decrease in acquisition of antibiotic-resistant gram-negative bacteria, although it was not statistically significant . As we eIn our subgroup analysis, the CRGNB acquisition rate was higher in the intervention period than in the control period in MICU1 and SICU2. Although a CPE outbreak occurred in SICU2, there was no outbreak of CRGNB in MICU1, and the reason for this unanticipated finding is unclear. It may be a seasonal effect, or more enhanced environmental cleaning might have been performed during the control period due to the COVID-19 pandemic, which occurred in the latter 6-month period (Additional file The acquisition rates of CRPA, CRAB, and CRE did not differ between the intervention and control periods. Because this trial was designed to identify the effectiveness of reducing the total CRGNB acquisition rate, further study is needed to identify the effectiveness of active surveillance testing for each organisms.Our study has some limitations. First, it was a single-center study with a low prevalence of CRGNB. A multicenter study with variable prevalences of CRGNB is warranted to generalize our findings. Despite this limitation, well-monitored infection control practices and policies to minimize unmeasured confounding factors by different centers during the study period is a strength of our study. Second, as this study was not blinded, the difference in the number of clinical specimens submitted to the laboratory may be present, and this may have affected the chance to detect CRGNB. However, the number of clinical specimen was not different between intervention and control periods in mITT analysis. Third, we did not perform surveillance testing during the control period, which may have biased our findings. However, we performed a pragmatic trial that reflects actual clinical practices, and we evaluated the outcomes of CRGNB acquisition in clinical specimens. Fourth, data regarding immunosuppressant use was absent. Use of immunosuppressant is associated with exposure to antimicrobials and acquisition of MDR gram-negative organism –17. HoweIn conclusion, active surveillance testing for CRGNB may reduce its acquisition in clinical specimens in the ICU without additional costs. Individual hospitals should consider the cost-effectiveness of the intervention based on the baseline acquisition rate of CRGNB and the cost of intervention when they decide whether to adopt active surveillance testing.Additional file 1. Supplemental Figure and Tables.


Objective: This study evaluated whether COVID-19 pandemic-related health, healthcare and economic factors during pregnancy are associated with prenatal depression and anxiety.Methods: We conducted a cross-sectional study of 6,628 pregnant members of Kaiser Permanente Northern California who responded to a survey between 22 June and 30 September 2020. The survey included questions about depression  and anxiety  symptoms and COVID-19-related health and healthcare  and economic  factors.Results: Over one third of individuals reported depression  or anxiety  symptoms. In multivariable analyses, COVID-19 during pregnancy, employment with greater risk of COVID-19, distress over changes in prenatal care, job loss, changes in childcare and food insecurity were associated with greater odds of prenatal depression or anxiety.Conclusion: Findings suggest the COVID-19 pandemic may have severe mental health repercussions for pregnant individuals. Support services for pregnant individuals experiencing these COVID-19-related factors and monitoring of those who had moderate/severe prenatal depression and anxiety symptoms during the COVID-19 pandemic is warranted. The coronavirus pandemic COVID-19) has had a tremendous impact worldwide. At the time of publication of this paper, there have been >76 million confirmed cases and nearly 900,000 deaths in the US alone 9 has had–4.The potential impact of the COVID-19 pandemic on the mental health of pregnant individuals is important to understand. Pregnancy is an extremely vulnerable period given the increased susceptibility to adverse health effects for both the mother and offspring. Pregnant individuals have experienced distinct concerns and challenges during the pandemic. Concerns about fewer prenatal visits, cancellation of labor and delivery classes, virtual visits, and the possibility of heightened risks of adverse pregnancy and child outcomes associated with COVID-19  may leadDepression and anxiety during pregnancy can have significant negative consequences for both the parent and baby –16. ThusThis cross-sectional study was conducted in Kaiser Permanente Northern California (KPNC), a large integrated health care delivery system that provides comprehensive medical care to over 4.5 million members. All 15 regional service centers (with 48 associated office facilities) have Obstetrics and Gynecology and Behavioral Medicine/Psychiatry Departments. KPNC members include individuals covered by employer-sponsored insurance plans, the insurance exchange and Medicaid. Coverage is provided for approximately 30% of the northern California population. KPNC members are socio-demographically similar to the population living in the geographic area . KPNC maBeginning on June 22, 2020 pregnant KPNC members were invited to participate in a KPNC COVID-19 Pregnancy Study (18). The survey collected information on depression and anxiety symptoms, as well as COVID-19-related health, healthcare and economic factors. Pregnant individuals 18 years of age or older and English-speaking were identified from the EHR and recruited via email. At the initial survey launch, all eligible individuals were contacted via email and invited to complete a brief, web-based survey. Every 2 weeks thereafter, all newly eligible individuals were emailed a study invitation. Individuals who did not respond to the initial email invitation received email reminders 7 and 14 days after the initial emails were sent. Participants who started but did not complete the survey received two email reminders, at 7 and 14 days after starting the survey. While study recruitment is ongoing, this study reports on data collected from 6,628 individuals who were at any stage of pregnancy between 1 January 2020 through 30 September 2020.The Institutional Review Board of KPNC approved all study procedures and individuals indicated informed consent by completing the survey after reviewing the consent information in the recruitment email (protocol number 1600113-11).Depression: The Patient Health Questionnaire (PHQ-8)  is a depAnxiety: General Anxiety Disorder Scale (GAD-7)  has beenHealth and healthcare factors: Individuals were asked if a healthcare provider had told them that they had or likely had COVID-19 during their pregnancy ; if a member of their household had or probably had COVID-19 ; whether their job put them at increased risk of COVID-19 ; and how distressed they were about changes to their prenatal care due to the COVID-19 pandemic .Economic factors: All questions addressing economic factors referred to the time frame of “since becoming aware of the COVID-19 pandemic”. Individuals were asked if they lost their job permanently, temporarily or reduced their work hours , if their spouse lost their job permanently, temporarily or reduced their work hours , if their childcare was impacted such that they had difficulty arranging childcare or had to pay more . The validated 2-item Hunger Vital Sign screener was used to assess food insecurity . Food inDemographic and health characteristics were ascertained from KPNC’s electronic health records (EHR) and include: race/ethnicity  maternal age at delivery , insurance status , trimester at survey completion (trimester one/ two or three), parity , and history of a depression or anxiety disorder in the 3 years prior to pregnancy [anxiety  or depression ].Inverse probability weighting was used to account for survey non-response (21% response rate). Inverse probability weights for survey response were calculated using predicted probabilities from a logistic regression model including variables expected to be associated with survey response , additional variables strongly associated with depression or anxiety symptoms , and an interaction term for race/ethnicity category and insurance type. Weights ranged from 1.74 to 40.24 in individuals who completed the survey. For the 14 individuals with weights greater than 20, weights were truncated at 20.n = 36 for prenatal depression and n = 44 for prenatal anxiety). Results were combined using Rubin’s rules   with 100’s rules . Crude pOf the individuals in our study, 66% were 30 years of age or older, 8% had Medicaid insurance, and 18% had a history of depression or anxiety. Individuals reported several COVID-19 pandemic-related health and healthcare factors  and economic factors  .n = 1,559) of the individuals reported mild to severe symptoms of both depression and anxiety.Overall, 36% of the individuals reported depression symptoms  and severe anxiety symptoms (13% vs. 4%)  had a higher prevalence of depression and anxiety overall compared to individuals not impacted by these factors there were few differences by severity , 2. HoweCrude estimates are reported in Individuals who reported having COVID-19 during pregnancy had increased odds of anxiety symptoms  compared to individuals without COVID-19 during pregnancy . IncreasIndividuals who lost their job had higher odds of depression, but not anxiety compared to individuals who did not lose their job; however, the estimate for severe depression was less precise  . There wThis cross-sectional study examined the associations of several COVID-19 pandemic-related health, healthcare and economic factors with depression and anxiety symptoms in pregnant individuals during the first 6 months of the COVID-19 pandemic and height of stay-at-home orders. More severe symptoms of prenatal depression and/or anxiety were associated with self-report of COVID-19, employment increasing the risk of COVID-19, distress over changes in prenatal care, job loss, childcare challenges, and food insecurity. This study evaluated a larger number of COVID-19-related factors than previously assessed. In addition, previous research has not assessed the impact of COVID-19-related factors on prenatal depression and anxiety symptom severity, which is important for identifying those at greatest risk.Elucidating risk factors for adverse mental health during pregnancy is of extreme significance as prenatal depression and anxiety can have detrimental impacts on the health of both mother and child. For example, individuals with prenatal depression and anxiety are at increased risk for unhealth maternal behaviors  , 27–29, Our finding of the associations of self-reported COVID-19 and employment in a job with high-risk of COVID-19 exposure with prenatal depression and anxiety severity is consistent with other reports in pregnant individuals  and otheWe documented escalating severity of depression and anxiety symptoms associated with distress over COVID-19-related changes in prenatal care. These findings are similar to other studies documenting COVID-19-related changes in prenatal care and greater psychological distress , 36–38. Previous research on the association of job loss or loss of source of income due to COVID-19 with prenatal depression and anxiety has reported mixed results , 38, 39.Changes in childcare was also significantly related to increased odds of depression and anxiety. Other studies of pregnant individuals during the COVID-19 pandemic have documented similar findings , 38 highThe low survey response rate raises concerns about non-response bias. However, our analyses were weighted to account for these differences. It is possible individuals with higher psychological distress were less likely to participate in the study and may explain why the prevalence of depression and anxiety was lower in our sample than has been reported in some, but not all , samplesWhile there have been several studies on the mental health of pregnant individuals during the COVID-19 pandemic, few studies have contextualized the impact of COVID-19-related factors on prenatal depression and anxiety. Additional strengths include the study’s large sample size, diversity across sociodemographic characteristics, stages in pregnancy, and capture of COVID-19-related factors and psychological distress during the first 6 months of the pandemic and height of stay-at-home orders.This study contributes to the growing body of research documenting the adverse impact of public health emergencies experienced during pregnancy on maternal mental health –45. Find