To assess the relationship between empathic communication, shared decision-making, and patient sociodemographic factors of income, education, and ethnicity in patients with diabetes.This was a cross-sectional study from five primary care practices in the Greater Toronto Area, Ontario, Canada, participating in a randomized controlled trial of a diabetes goal setting and shared decision-making plan. Participants included 30 patients with diabetes and 23 clinicians , with a sample size of 48 clinical encounters. Clinical encounter audiotapes were coded using the Empathic Communication Coding System (ECCS) and Decision Support Analysis Tool (DSAT-10).p=0.030) and ethnicity (p=0.03), but not income. Patients with only a college degree received more empathic communication than patients with bachelor’s degrees or more, and South Asian patients received less empathic communication than Asian patients. DSAT varied with ethnicity (p=0.07) but not education or income. White patients experienced more shared decision-making than those in the “other” category.The most frequent empathic responses among encounters were “acknowledgement with pursuit” (28.9%) and “confirmation” (30.0%). The most frequently assessed DSAT components were “stage” (86%) and knowledge of options (82.0%). ECCS varied by education (We identified a new relationship between ECCS, education and ethnicity, as well as DSAT and ethnicity. Limitations include sample size, heterogeneity of encounters, and predominant white ethnicity. These associations may be evidence of systemic biases in healthcare, with hidden roots in medical education.The online version contains supplementary material available at 10.1007/s11606-021-07230-5. For example, citizens living in the 1% or 5% highest income counties in the USA had better health outcomes compared to average US citizens3. In contrast, those with lower socio-economic status had a greater prevalence of psychological and chronic health conditions4. These health disparities arise from historical inequities that result in decreased access to clean environments, housing, quality nutrition, and health care. This in turn predisposes to chronic stress and chronic disease development5.Despite advances in medicine, social and economic factors contribute to 50% of a population’s health status6. Shared decision-making, a component of patient-centered care6, involves assessing the patient’s decision-making needs, providing individualized support and evaluating patient goals to arrive at a quality decision informed by evidence and patients’ values and preferences7. Shared decision-making is associated with improved patient satisfaction and engagement in care8. Shared decision-making is facilitated by empathic communication9; it encompasses the cognitive capacity to understand a patient’s needs, an affective sensitivity to the patient’s feelings, and a behavioral ability to convey this to the patient10. A 2002 meta-analysis of medical interactions in primary care demonstrated that increased physician empathy was associated with increased patient satisfaction, adherence, comprehension, and perception of a good interpersonal relationship11.Patient-centered care is a vital component of health care that improves the physical and psychosocial well-being of patients5. For example, in the USA, the risk of type 2 diabetes is 66% higher in Hispanic people and 77% higher in Black people12 than white people. In Canada, Indigenous people are three to five times more likely to have type 2 diabetes than non-Indigenous people13. Both low income and education are also associated with increased prevalence of diabetes: individuals with lower income and education are two to four times more likely to develop diabetes than more advantaged individuals14. In those with diabetes, low socioeconomic status was associated with a two-fold greater risk of all-cause, cardiovascular- and diabetes-related death compared to high-income counterparts15. A recent population-based study in the UK by Riley et al. (2021) showed that social deprivation is an independent risk factor for developing diabetic foot disease and related complications16.Diabetes is a complex chronic disease that disproportionately affects racialized groups and those of lower socioeconomic status worldwide, with these groups experiencing increased prevalence, lower life expectancy, and increased complications of diabetes17. Similarly, people living in areas of high deprivation  in Scotland perceive their physicians as less empathic and had less desire for shared decision-making18. A survey study found that physicians viewed Black patients and patients of low and middle socioeconomic status as less intelligent, less rational, and less likely to adhere to medical advice or follow-up, than White and high socioeconomic status patients19. Additional studies using audiotapes and videotapes of patient-clinician encounters, as well as patient self-report, demonstrate that clinicians exhibit less empathic and participatory communication (characterized by information sharing and patient involvement in discussion) towards racialized and low income patients20. These implicit biases impact physicians’ communication and clinical decision-making20, and may impact patient outcomes.Health disparities also exist in the receipt of patient-centered care, which may then worsen care gaps. National survey data demonstrate that racialized low-income patients in the USA perceive that they receive less patient-centered care, including less shared decision-making, trust and empathic communication, and as a result are less satisfied with their care21. However, little is known about the relationship between social determinants of health, clinician empathy, and shared decision-making in a diabetes-specific population.Specific to diabetes care, clinician empathy has been associated with increased patient satisfaction, quality of life, reduced HbA1c, LDL cholesterol, and fewer diabetes complicationsThus, we sought to quantify the relationship between empathic communication, shared decision-making, and sociodemographic factors of income, education, and ethnicity, using validated scales. Our primary objective was to evaluate the relationship between empathic communication and patient education, income, and ethnicity in individuals with diabetes attending primary care clinics in the Greater Toronto Area. The secondary objective was to evaluate the relationship between shared decision-making and patient education, income, and ethnicity in this same population. We hypothesized that patients with lower education, income and from ethnic minorities would experience less empathic communication and shared decision-making compared to those with high education, income, and patients who identified as white.10 — an observer-rated measure of empathy, which has not been studied in this context before. Shared decision-making will be quantified by with the Decision Support Analysis Tool-10 (DSAT-10)22 — an observer-rated measure of a clinician’s ability to engage a patient in shared decision-making.Specifically, empathic communication will be quantified by the Empathic Communication Coding System (ECCS)23. Sample size was based on 48 available audiotapes from the original study. We reported according to Strengthening the Reporting of Observational Studies (STROBE) guidelines for a cross-sectional study , or were not available for a follow-up. In order to assess intervention fidelity during the trial , 48 clinical encounters were audio-recorded then transcribed. This constituted the data source for the current study.The previous study was a 10-site cluster randomized-controlled trialThe primary outcome was empathic communication, measured using ECCS. The secondary outcome was shared decision-making, measured using DSAT-10.We used patient-reported sociodemographic information and transcripts of clinical encounters. Patients self-reported their ethnicity, education, and income through an online or mailed survey at the start of the prior trial. In the original study, clinical encounters were audiotaped for qualitative analysis to inform future iterations of the shared decision-making intervention. Of note, the prior study also consisted of patient questionnaires for patient-reported outcomes of decisional conflict, diabetes distress, assessment of care, and quality of life; however, these were not used in the present study.We conducted qualitative coding of the clinical encounter transcripts to derive a score for empathic communication, using ECCS. ECCS is an observer-rated measure of clinician empathy that measures empathy by examining clinician empathic responses to patient-created opportunities, with responses subsequently categorized on a scale from 0  to 6 (shared experience) , we used 2 independent sample t-test. For the secondary outcome, we used the Kruskal-Wallis test to examine the effect of the categorical independent variables (income and education) on our ordinal dependent variable DSAT28. If there was a significant effect of any factor, we conducted exploratory post hoc Dunn tests to determine which groups differed from each other27. For ethnicity, we used Mann-Whitney test. We conducted a Benjamini-Hochberg procedure to correct for multiple comparisons, a moderate false discovery rate of 0.15, given the exploratory nature of this study29. All analyses were done using SPSS Statistics for Windows, Version 20.030.We used descriptive statistics to describe the characteristics of participants (patients and clinicians) and clinical encounters. For the primary outcome, we used one-way ANOVA to examine the effect of the categorical independent variables (income and education) entered as between-subjects factors, on our continuous dependent variable ECCS. If there was a significant effect of any factor, we conducted exploratory post hoc Tukey’s to determine which groups differed from each otherWe analyzed a total of 48 clinical encounters, involving 30 unique patients and 23 unique clinicians. Sociodemographic characteristics of patients and clinicians are indicated in Table Clinical encounters ranged in length from 3 min 55 s to 1 h 30 min, with a mean length of 31 min 26 s (SD 15 min 33 s). Mean ECCS score across all clinical encounters was 3.5 (standard deviation (SD) = 0.8). The most frequent empathic responses were “acknowledgement with pursuit” (29 %) and “confirmation” (30.0%) (Table p=0.030) and ethnicity (p=0.030), but not income (Table We found that ECCS was varied by education (me Table . Post home Table .Table 4p=0.07) but not education or income (Table We found that DSAT varied with ethnicity (me Table . Post home Table .P (=0.07) that was less than its critical Benjamini-Hochberg value (0.08), thus confirming that all preceding comparisons  were significant. The rank table is included in Supplemental File To correct for multiple comparisons, we conducted a Benjamini-Hochberg procedure using a conservative false discovery rate of 0.15. The comparison between DSAT and patient ethnicity had the highest Our study demonstrated that ECCS was varied by education and ethnicity, such that patients with only a college degree received more empathic communication than patients with bachelor degrees or higher, and South Asian patients received less empathic communication than Asian patients. In addition, we found that DSAT varied by ethnicity, such that white patients received more shared decision-making than non-white patients/“other.”31. However, we found that patients with only college education received more empathic communication compared to those with a bachelor degree or higher, which reveals a new finding that is contrary to the overarching trend in the literature, despite controlling for income and ethnicity32. Although several studies have demonstrated that individuals with low income, education and from ethnic minorities experience less empathic communication and shared decision-making, we provide objectively assessed, quantitative evidence of these relationships, in a clinical population — individuals with type 2 diabetes — that is characterized by ethnic and socioeconomic diversity; these relationships existed despite the study being conducted in a multicultural geographic setting during an era with growing awareness of considerations for equity, diversity, and inclusion.These findings are consistent with the existing literature that racialized individuals and those with lower SES perceive less empathy and shared decision-making in healthcare interactions33. Further, studies of medical trainees’ attitudes towards racialized populations have demonstrated a “pro-white” bias in empathic communication and treatment, in that medical trainees held false beliefs regarding black patients’ perception of pain which led to under-treatment20. This was confirmed in a systematic review by Hall and colleagues, which showed that healthcare providers have implicit biases in terms of negative attitudes towards people of color, which impacted patient-provider interactions, treatment decisions, and patient health outcomes34. Similarly, patients of lower socioeconomic status perceive less access to care, altered physician-patient interaction (feeling like they are listened to), and differences in management plan (such as reduced diagnostic testing)35. Taken together, strategies must be implemented at the medical education level to foster empathy and address these biases that are often part of the hidden curriculum. Examples of strategies to enhance empathic communication include assessing provider patient-centered communication at the point-of-care, education among peers, and mentorship by clinicians who score highly on patient-rated scales of patient-centered communication36. Strategies to address systemic bias in medical education include standardized anti-racism and anti-bias training37 as well as implementation of a structural competency framework, including improving recruitment, promotion and retention processes of faculty, “stop the line” processes for racism, and the use of a community council to review health equity initiatives and provide feedback on performance38.These associations are concrete evidence of systemic bias in healthcare, with roots in medical education. Empathy decreases throughout medical training18. Third, heterogeneity of appointment type  may have resulted in differing levels of empathic communication and shared decision-making, given that shared decision-making is longitudinal in nature occurring over several appointments8. We tried to account for this heterogeneity by adjusting for the number of empathic opportunities per encounter; however, we could not adjust the overall DSAT score based on encounter length because of scale properties. Fourth, we did not examine the impact of clinician factors on empathy or shared-decision-making, including burnout, workload, gender, and training32, which may have influenced our results.First, our study was limited by small predominantly white sample; however, this was a hypothesis-generating exploratory study wherein we a priori selected specific outcomes and statistically controlled for multiple comparisons. Second, because our findings were based on audio-recordings of clinical encounters alone, we were unable to assess non-verbal empathic communication, a key component of empathic communicationStudy strengths include our use of objective third-party observer-rated scales not previously used in this context that reduce bias associated with patient or clinician self-report. Second, we captured representative clinical encounters with different clinicians, including physicians, nurses, and dietitians, consistent with interprofessional diabetes care.39, and incorporating critical reflection and dialogue into curriculum to address biases and assumptions that shape healthcare interactions40. In terms of clinical implications, our research underscores the importance of clinical interventions such as shared decision-making tools to empower patients — in particular racialized individuals and those of lower income and educational attainment — to become involved in their healthcare. Additional supports such as interprofessional teams and peer coaches36 should be leveraged to enable patients in vulnerable groups to play an active role in their care. In terms of implications for research, future studies should confirm our findings, and specifically assess the trend of education level and empathy in a larger and more diverse patient population during chance encounters. Triangulation of objective rating of empathic communication (as in our study) with patient self-report of empathy as well as the patient lived experience using qualitative methodology would enhance our understanding. Future studies could also test the impact of patient-directed interventions (such as peer coaches) as well as clinician-directed interventions  in specific vulnerable populations.Our research has implications for medical education, clinical practice, and research. That empathy declines with medical training and that racial biases are prevalent in medical trainees call into question the adequacy of medical education in preparing physicians to care for patients with a lens of social justice. Several professional organizations have advocated for education interventions to prepare medical trainees to care for the needs of a culturally diverse population including cultural competency trainingSupplementary file1 (DOCX 21.1 KB)Supplementary file2 (DOCX 15 KB)Below is the link to the electronic supplementary material.


RSV was the leading pathogen responsible for bronchiolitis before the national lockdown in March 2020 (70.0% of cases), while Rhinovirus was the leading pathogen responsible for bronchiolitis (62.5%) during the pandemic while strict restrictions were ongoing. As Italy approached the COVID-19 vaccination target, the national government lifted some COVID-19-related restrictions. A surprising rebound of bronchiolitis (particularly cases caused by RSV) was observed in October 2021. (4) Conclusions: In this study, we describe for the first time the fluctuations over time of RSV bronchiolitis among newborns and young infants in Italy in relation to the restrictive measures containing the spread of the COVID-19 pandemic. Our results are in line with other countries’ reports. Italy was the first European country to announce severe nationwide restrictions in March 2020 to prevent the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) after the first clusters in the Northern regions. The response to the pandemic caused many important changes in daily lifestyle, with the activation of social measures of distancing, teleworking, closing of schools and kindergartens, closing of commercial activities, strict hygiene behaviors, widespread use of face masks, limitations of travel, and avoidance of activities associated with gathering. All nonessential activities were prohibited until May 2020. Activities were gradually reopened, and free movements within the nation were restored in June 2020. Unfortunately, a new rise in detected Coronavirus disease 2019 (COVID-19) cases was observed: stricter rules were reintroduced in October 2020 to fight the so-called “second” and “third” waves. Respiratory viruses such as influenza, respiratory syncytial virus (RSV), and SARS-CoV-2 have three similar routes of transmission: contact (direct or indirect), droplets, and aerosol transmission. All three viruses replicate in the respiratory tract from where they are subsequently shed and transmit via respiratory secretions . FurtherIn the last two years, in our tertiary children’s hospital, we observed a significant decrease in the number of children referred to the emergency department , partialBronchiolitis is a common lower respiratory tract infection that affects neonates and infants, usually from October–November to March–April. This infection is characterized by coryza, persistent cough, and respiratory distress in the presence of wheezing or crackles during chest auscultation. During recent winter seasons (2018–2019), bronchiolitis crowded our hospital wards, often with no beds to manage children with mild-to-moderate respiratory infections. The situation was dramatically changed with the COVID-19 pandemic and related restriction measures, with an evident decrease in the number of cases of bronchiolitis.This study aims to describe and compare the number of neonates hospitalized for bronchiolitis in the pre-COVID-19 era and the pandemic period in Rome .Our internal database was used to attain data for neonates and infants aged up to three months who were admitted to the Medical and Surgical Department of Fetus, Newborn, and Infant in our hospital due to bronchiolitis in the quarters (quarter 1 (Q1)—January–March; quarter 2 (Q2)—April–June; quarter 3 (Q3)—July–September; quarter 4 (Q4)—October–December) of 2018–2020 and the first months of 2021 to compare admissions in the pre-COVID-19 period (January 2018–March 2020) and in the pandemic period (April 2020–February 2022).In all selected cases, we performed a broad investigation of respiratory viruses by using a multiplex panel capable of simultaneously detecting and identifying 19 clinically relevant virus subtypes: influenza virus , respiratory syncytial virus (A/B), adenovirus, enterovirus, parainfluenza virus (1–4), metapneumovirus, bocavirus, rhinovirus, and human coronaviruses (NL63/229E/OC43). These were detected on nasopharyngeal aspirates (NPA) by multiplex one-step real-time polymerase chain reaction (RT-PCR) using “AllplexTM Respiratory Panel Assays”  on an automated instrumental workflow as previously described . In addiData are presented as numbers and percentages for categorical variables. Statistical analysis was performed using Microsoft Excel’s software (release 2016 for Windows).From 1 January 2018 to 28 February 2022, we admitted 354 infants with bronchiolitis: 243 were admitted in the pre-COVID-19 period and 111 were admitted in the pandemic period. A viral pathogen was found in 342/354 (96.6%) patients. RSV was found to be the virus which was most frequently responsible for diseases (71.2%), followed by rhinovirus (23.6%) and parainfluenza virus (3.9%). Just two cases of bronchiolitis were observed to be caused by SARS-CoV-2; a third patient tested positive for SARS-CoV-2 and RSV simultaneously, but the primary pathogen was considered to be RSV  .In 2018, 96 infants required hospitalization because of bronchiolitis; during 2019, the number of patients hospitalized increased to 120, while in 2020, only 33 infants were hospitalized .Of these 33 cases, only 6 occurred after the first national Italian lockdown (9 March 2020). In the first quarter of 2021, we observed a similar trend, and only two patients required hospitalization for bronchiolitis . From September 2021, the number of patients with bronchiolitis started to increase   in 2018, with 80 RSV infections (66.7%) in 2019 and 25 (75.8%) in 2020. The majority of the latter RSV cases (24/25: 96.0%) occurred before the introduction of lockdown. We hospitalized only 1 infant with RSV in the first nine months of 2021, whereas during October 2021 and February 2022, we admitted 80 infants with RSV (79.2%) , while rhinovirus was the most prevalent (5/8 patients: 62.5%) during the pandemic when strict restrictions were ongoing (from April 2020 to June 2021) . From thFor the first time, we accurately report all the pathogens identified to cause bronchiolitis in neonates and infants up to three months of age in the periods before the COVID-19 pandemic and afterwards. Preventive interventions against SARS-CoV-2 implemented in the northern part of the globe have led to a decrease in pediatric, droplet-borne, and contact infections . Conversely, a coincidental reduction in conditions that are not transmitted through droplets and contact, i.e., urinary tract infections, has not been observed .In June 2021, Van Brusselen et al. described bronchiolitis as “a nearly absent disease”, without hiding the fear of a “delayed” peak occurring once most NPIs become more relaxed and pre-pandemic life restarts . Indeed,Concerning the Italian situation, after the first national lockdown, the government decided to change its strategy to avoid an economic disaster. It imposed the Traffic Light Approach, a set of stop–start restrictions based on indicators  . In thisGood anti-COVID-19 vaccination coverage has been reached in Italy, and the restrictive measures have been lifted for those with an immunity passport . However, SARS-CoV-2 vaccines do not protect against other respiratory viral infections that have started to spread in a seemingly more aggressive way than in the pre-COVID-19 era. As COVID-19 vaccines became more publicly accessible, the Italian government extended the requirement of the EUDCC, also known as a “Green Pass”, to attend sports events and concerts and for access to indoor places, such as bars, restaurants, and gyms, as well as for travel. Meanwhile, cases of bronchiolitis were reported to rise globally.In Japan, the comparison of 2021 weekly RSV activity with activity in 2017–2020 from the Tokyo Metropolitan Infectious Disease Surveillance Center demonstrated the most significant annual increase in cases for 2021 , may havAlthough the association between SARS-CoV-2 and bronchiolitis has been reported , we founHospitalization in bronchiolitis usually only occurs with the presence of hypoxia, moderate–severe respiratory distress, dehydration, or apnea; other criteria to be considered are comorbidities  and unfavorable social and environmental factors . TherefoRecently, Camporesi et al. explored the epidemiology, microbiology, and severity of bronchiolitis in four pediatric referral centers located in different geographical areas in Italy during 2021–2022 . Their rWe observed a dramatic drop in admissions of infants with bronchiolitis due to RSV with the implementation of SARS-CoV-2-related social restrictions. We noted fluctuations were related to the intensity of restrictive measures at a given time: we learned that bronchiolitis in neonates and small infants could be drastically contained when non-pharmaceutical interventions hinder transmission from adults and older children. Indeed, since the restrictions were relaxed, cases have started to rise again with a significant trend.A lesson learned during lockdowns tells us that simple preventive measures should not be forgotten, because they can markedly reduce bronchiolitis-related hospitalization of neonates and infants. This is especially the case among those younger than three months or with pre-existing risk factors  who thus have a higher risk of severe illness and hospitalization which goes beyond the protection provided by RSV prophylaxis.


SARS-CoV-2 disease, COVID-19 infection, is a multi-system illness that has afflicted people all over the world. A number of vaccines have been produced to combat the current COVID-19 pandemic, and a variety of side effects have been recorded following the vaccination. However, there are limited data on the negative effects of immunological reactivation following vaccination. We report 10 incidences of herpes zoster reactivation within 7-21 days of getting the COVID-19 vaccination. Transient immunomodulation following vaccination, similar to that seen in COVID-19 illness, could be one explanation for this reactivation. These cases highlight the significance of continuing to examine vaccine safety during the COVID-19 pandemic's ongoing mass vaccination campaign. We also underline the importance of peripheral health professionals in the management and reporting of any vaccination-associated adverse event. In view of the current COVID-19 pandemic, World Health Organisation (WHO) issued the first emergency use for the COVID-19 vaccine in December 2020 . HoweverVaricella zoster virus (VZV) is a commonly encountered infectious disease in dermatology outpatient departments (OPDs) presenting as varicella/chickenpox or herpes zoster. VZV, a DNA virus of the Herpes family, is a neurotropic virus that causes chickenpox as a primary infection, which is a relatively mild, self-limiting childhood illness with a characteristic exanthem, following which VZV remains dormant in dorsal root ganglion for life. Upon reactivation, there is anterograde axonal migration of the virus to the periphery, causing a characteristic painful dermatomal rash with unilateral involvement, which is known as herpes zoster or shingles . ReactivWe present a study of patients who developed reactivation of VZV after receiving the Covishield vaccine to fight against SARS-CoV-2. Few cases in our study were misdiagnosed by the peripheral health workers, severely affecting their quality of life due to delay in treatment and landing them up in post-herpetic neuralgia, a herpes zoster complication.These cases highlight the significance of continuing to check vaccine safety while mass vaccination for the COVID-19 pandemic is ongoing, as well as the importance of documenting and communicating any vaccination-related adverse events, especially at the level of peripheral health workers. The need to enlist the help of atypical health professionals in acquiring data for the development of control strategies is emphasized.We present a case series of 10 patients who presented with herpes zoster reactivation after COVID-19 vaccination, with two cases in detail focussing on the role of peripheral health worker. Demographic details, comorbidities, clinical features, history of COVID-19 vaccination, and treatment history were noted down, and pictures were taken after obtaining consent from the patients.Case 1A 73-year-old woman went to her local community healthcare center complaining of painful skin rashes that had been bothering her for the past three days, starting with pain and burning sensations on the right side of her forehead and right eye, followed by multiple painful eruptions in the same area the next day. She was given a five-day course of 5 mg levocetirizine tablets at night and a topical steroid formulation for local application. Antivirals were not administered. According to the patient, no history of COVID-19 immunization was taken. After five days, she alerted the peripheral health worker that the pills were not providing any relief, and she was instructed to remain on the same medications for another five days. After ten days of treatment, she was still unsatisfied, which compelled her to visit our dermatology OPD because of the excruciating pain and burning sensation. Her medical history was taken, and she was examined thoroughly. She did not give any past history of similar complaints and has been a known case of diabetes mellitus and hypertension for 15 years, with regular medications. She had no previous history of COVID-19 infection, and she had had her first dose of COVID-19 immunization seven days before she presented to the peripheral health center. This history was overlooked by a peripheral health provider, who only provided symptomatic therapy without considering it to be a COVID-19 vaccination problem. Multiple clustered vesicles with crusting over an erythematous base were found on examination in the right frontotemporal area, spreading to the periocular area below; V1 dermatome was involved  were conducted and found to be within normal limits. Only two of 10 patients gave a history of varicella infection in their childhood. Other patients were unable to recall properly any past history of varicella infection. None of our patients had any past episodes of herpes zoster. Two patients were known cases of diabetes mellitus and were on medication for the same. Their HbA1C was within normal limits. The rest of the patients were free of any associated comorbidity and were immunocompetent.For a period of 5-7 days, all patients were given oral antiviral drugs: 1 gm of valacyclovir thrice daily or 800 mg tablet of acyclovir five times daily for five days, and symptomatic care with antihistamines, nonsteroidal anti-inflammatory drugs (NSAIDs), and topical antibiotics with calamine lotion. None of the patients had received a zoster virus vaccine. Patients were observed for two-three months. Two out of 10 patients developed postherpetic neuralgia after two months.Herpes zoster (HZ) incidence rises with age, from 3.1 per 1000 person-years for those 45-54 years old to 5.7 for those 55-64 years old and 11.8 per 1000 person-years for those over 65 years old .Postherpetic neuralgia is the most common HZ consequence, followed by HZ ophthalmicus, acute retinal necrosis, Ramsay Hunt syndrome, Bell's palsy, aseptic meningitis, encephalitis, peripheral motor neuropathy, myelitis, Guillain-Barre syndrome, and bacterial skin infection . In addiThe COVID-19 infection produces an immunosuppressive state due to functional impairment and a concomitant quantitative decrease in T lymphocytes, particularly CD4+ T cells, CD8+ T cells, and natural killer cells which could be the plausible mechanism for the increased susceptibility to herpes zoster reactivation in COVID-19 patients . Few stuTo prevent this infection, several nations have begun vaccination with inactivated or live vaccines, and a variety of side effects have been observed following COVID-19 inoculation. Mild-to-moderate pain at the injection site, headache, and weariness characterize the safety profile of the COVID-19 mRNA vaccine, while the incidence of major, long-term side effects is still being assessed.HZ after vaccination is a rare occurrence in the literature. Following inactivated influenza, hepatitis A, rabies, and Japanese encephalitis vaccines, Walter et al. documented three cases of herpes virus reactivation , while BAt the time of writing, the United States Vaccine Adverse Event Report System (VAERS) has already reported 2512 cases of HZ (1.3%) of total reported events after tozinameran vaccine, 1763 cases (0.9%) after mRNA-1273, and 302 (0.7%) after AD26.COV2.S . HZ is uVaccination initiatives for COVID-19 are in full swing. Given the large number of people who will be vaccinated against SARS-CoV-2, a possible causal link could result in a large number of cases among the elderly, with devastating consequences. Post-marketing surveillance procedures must be in place, and ongoing vaccination safety assessments are critical for detecting any occurrence that could reduce the projected benefits and, as a result, taking obligatory action to reduce hazards amongst vaccinated people. HZ appears to be a "possible" yet uncommon adverse event following immunization (AEFI). Our findings necessitate a further investigation of the possible relationship between COVID-19 and herpes zoster in the context of vaccinating elderly and/or immunocompromised people.In most impoverished nations, data for designing disease prevention initiatives is unavailable due to the high cost of gathering it. This study looked into using community key informants and peripheral health personnel to collect data on post-COVID-19 vaccination problems. Even in the poorest sections of the country, primary health care providers' prior knowledge can aid in the identification, quick treatment, and reporting of these potential problems following COVID-19 immunization. Antivirals work best if started within 2-3 days of the onset of HZ symptoms; therefore, the two individuals mentioned in our case series might not have ended up with postherpetic neuralgia if they had been diagnosed and managed promptly by peripheral health practitioners.Fortunately, HZ is a manageable condition that is commonly associated with disability, particularly among the elderly, and existing therapy only affects the degree and length of pain, reduces viral shedding, and avoids postherpetic neuralgia. Because of the increased awareness of this complication, more HZ cases are being reported and communicated after the COVID-19 vaccination. Furthermore, these findings will help clinicians decide whether to give prophylactic valacyclovir before immunization for people who are at a higher risk of VZV reactivation after receiving the SARS-CoV-2 vaccine.The comprehensive evaluation will determine whether more should be done to raise awareness about potential dermatological complications such as VZV reactivation and how to remain prepared to manage them efficiently. However, the complication we report after the Covishield vaccination could just be a one-of-a-kind, isolated instance, and each person should have no hesitations about receiving the COVID-19 vaccine.


There are known differences in vaccine reactogenicity and immunogenicity by sex. Females have been shown to report greater reactogenicity and generate higher humoral and cellular immune responses than males following vaccination with several different vaccines. Whether this is also the case for COVID-19 vaccines is currently unknown, as COVID-19 vaccine study data disaggregated by sex are not routinely reported. Therefore, we have assessed the influence of sex on reactogenicity, immunogenicity and efficacy of COVID-19 vaccine ChAdOx1 nCoV-19.Vaccine efficacy was assessed in 15169 volunteers enrolled into single-blind randomised controlled trials of ChAdOx1 nCoV-19 in Brazil and the UK, with the primary endpoint defined as nucleic acid amplification test (NAAT)-positive symptomatic SARS-CoV-2 infection. All participants were electronically randomised to receive two standard doses of vaccine or the control product. Logistic regression models were fitted to explore the effect of age and sex on reactogenicity, and linear models fitted to log-transformed values for immunogenicity data. Reactogenicity data were taken from self-reported diaries of 788 trial participants. Pseudovirus neutralisation assay data were available from 748 participants and anti-SARS-CoV-2 spike IgG assay data from 1543 participants.7619 participants received ChAdOx1 nCoV-19 and 7550 received the control. Vaccine efficacy in participants after two doses of ChAdOx1 nCoV-19  was 66.1% (95% CI 55.9-73.9%) in males and 59.9% (95% CI 49.8-67.9%) in females; with no evidence of a difference in efficacy between the sexes (vaccine by sex interaction term P=0.3359). A small, statistically significant difference in anti-spike IgG was observed , with higher titres in females than males, but there were no statistically significant differences in other immunological endpoints. Whilst the majority of individuals reported at least one systemic reaction following a first dose of ChAdOx1 nCoV-19, females were twice as likely as males to report any systemic reaction after a first dose . Measured fever of 38°C or above was reported in 5% of females and 1% of males following first doses. Headache and fatigue were the most commonly reported reactions in both sexes.Our results show that there is no evidence of difference in efficacy of the COVID-19 vaccine ChAdOx1 nCoV-19 in males and females. Greater reactogenicity in females was not associated with any difference in vaccine efficacy.Studies were registered with ISRCTN 90906759 (COV002) and ISRCTN 89951424 (COV003) and follow-up is ongoing. Funding was received from the UK Research and Innovation, Engineering and Physical Sciences Research Council, National Institute for Health Research, Coalition for Epidemic Preparedness Innovations, National Institute for Health Research Oxford Biomedical Research Centre, Chinese Academy of Medical Sciences Innovation Fund for Medical Science, Thames Valley and South Midlands NIHR Clinical Research Network, the Lemann Foundation, Rede D'Or, the Brava and Telles Foundation, the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior, Brazil, and AstraZeneca. Sex differences in reactogenicity and immunogenicity in response to vaccines have previously been described for several vaccines. Females have been shown to repeatedly report greater reactogenicity and generate greater immune responses than males. The clinical relevance of higher immune responses in females is unclear as clinical data disaggregated by sex are infrequently reported and the quality of reported data on sex-differences is often poor. Whether this is also true for COVID-19 vaccine ChAdOx1 nCoV-19 is unclear.Phase 2/3 and real-world data for BNT162b2 (Pfizer/BioNTech), mRNA-1273 (Moderna) and Ad26.COV2-S (Janssen) vaccines describe greater reactogenicity in females than males. Phase 3 efficacy studies of the BNT162b2, mRNA-1273 and AD26.COV2-S vaccines have shown similar efficacy in males and females. Whether greater reactogenicity to COVID-19 vaccines in females is associated with any differences in immunogenicity or efficacy has not been evaluated.This study assessed reactogenicity, immunogenicity and efficacy of COVID-19 vaccine ChAdOx1 nCOV-19, using data from randomised controlled studies of the vaccine in the UK and Brazil, disaggregated by sex.Our results show that although females had higher reactogenicity than males, there was no evidence of a difference in efficacy of the COVID-19 vaccine ChAdOx1 nCoV-19 in males and females. Only one immune readout showed a higher response in females than males.Alt-text: Unlabelled boxBiological sex is known to impact immune responses, susceptibility to pathogens and outcome of infection.,Female sex has been associated with both greater reactogenicity and higher levels of humoral and cellular immunity in response to vaccination with non-COVID-19 vaccines, including those against influenza, yellow fever, pneumococcus and hepatitis B across a range of vaccine types.Studies suggest that sex differences also exist with regards to COVID-19 vaccine responses. Data from the COVID Symptom Study app developed by ZOE Global suggest that females are more likely to report both local and systemic reactions in response to COVID-19 vaccination with two doses of either BNT162b2 (Pfizer/BioNtech) or ChAdOx1 nCoV-19 than males,Data were taken from two single-blind, randomised controlled efficacy trials in the UK (COV002) and Brazil (COV003). Between May 28 and December 8 2020, informed written consent from 21227 healthy volunteers was obtained, who were then recruited and vaccinated across both trials. 15169 were included in the primary efficacy analysis in this paper (7619 receiving ChAdOx1 nCoV-19 and 7550 receiving control vaccine). 5777 were participants in the UK study, and 9392 participated in the Brazil study. Health and social care workers and those considered at higher risk of exposure to SARS-CoV-2 were targeted for recruitment. The data cutoff date for COVID-19 cases to be included in this paper was February 28 2021.,The studies have been previously described and extensively published in detail, including study protocols.10 vp, or two-doses of the control product . Computer randomisation was carried out within the secure web platform (REDCap v12.0.19) used for the electronic case report form. Study staff cleaned and checked data on an ongoing basis throughout the study. Randomisation lists, using block randomisation stratified by study group and site, were generated by the study statistician (MV). Participants were blinded to their allocation.Participants in the efficacy cohort  were ranA subset of participants were asked to complete a diary detailing solicited systemic and local adverse reactions for seven days after receiving their first and second doses of vaccine. Solicited systemic reactions included headache, fever , feverishness, chills, muscle ache, joint pain, malaise, fatigue, and nausea; and solicited local reactions included pain, tenderness, redness, warmth, induration, itch, and swelling. Participants categorised their reactions as mild, moderate or severe using pre-specified criteria (Table S1). The reactogenicity cohorts consisted of trial participants who received two doses of ChAdOx1 nCoV-19 with at least one day of diary data in their first-dose or second-dose diaries. Participants were enrolled into the reactogenicity cohorts from a limited number of study sites, depending upon research capacity.The immunogenicity cohort consisted of participants who had received two doses of ChAdOx1 nCoV-19 and also had available anti-SARS-CoV-2 spike IgG and/or antibody neutralisation data at 28 days after receiving the second dose of vaccine. Only participants with no positive nucleic acid amplification test (NAAT) tests prior to this timepoint were included in the immunogenicity cohort. Participants were removed from the immunogenicity cohort if they were unblinded or received any COVID-19 vaccinations outside of the trial prior to the 28 days post-second vaccination timepoint.Baseline serum samples were measured for nucleocapsid reactivity with the Roche Elecsys Anti-SARS-CoV-2 serology assay and a multiplexed immunoassay used to assess the spike-specific response to ChAdOx1 nCoV-19 vaccination and/or natural SARS-CoV-2 infection. Antibody neutralisation was measured with a lentivirus-based pseudovirus particle expressing the SARS CoV-2 spike protein as previously described.For comparison, convalescent plasma samples from non-trial participants were obtained from hospitalised patients with severe COVID-19 disease or healthcare workers with mild or asymptomatic infection. All participants were ≥18 years old and were enrolled into surveillance studies following a confirmed SARS-CoV-2 NAAT positive test.The primary efficacy outcome was symptomatic SARS-CoV-2 infection with positive NAAT from a nose and throat swab. Participants with at least one of the primary outcome symptoms  were included as primary outcome cases. Only primary outcome cases occurring more than 14 days after receiving a second dose were eligible for inclusion in efficacy analysis. Participants with positive NAAT swabs within 14 days after receiving their second dose were excluded from the efficacy cohort. Other exclusions included participants who were not seronegative at baseline, those who discontinued from the study with a follow-up time of less than 15 days after the second vaccination, and those not enrolled in efficacy cohorts. All cases were reviewed for inclusion by an independent blinded outcome adjudication committee. Participants were analysed according to vaccine received.The efficacy analysis presented here is an exploratory subgroup analysis by sex. There are similarities in the targeted recruitment populations for phase 3 cohorts in COV002 and COV003, therefore efficacy analyses have been combined from these two studies./SC/0179; ISARIC/WHO Clinical Characterisation Protocol for Severe Emerging Infections ; Oxford Tropical Research Ethics Committee (OxTREC Reference 36-20); Sepsis Immunomics Project ; Studies were registered with ISRCTN 90906759 (COV002) and ISRCTN 89951424 (COV003).Written informed consent was obtained from all participants. Studies were approved by the following committees: Brazilian National Research Ethics Committee (reference 4068113); Gastrointestinal Illness in Oxford: COVID substudy ; Health Research Authority and Health and Care Research WalesAn international data safety monitoring board reviewed the safety data for the studies.Baseline characteristics of each cohort were summarised by sex and presented as frequencies (%) or medians with IQRs for categorical or continuous variables, respectively. Distribution of sex and health/social care worker status was additionally explored in participants aged 18-65 years (considered to be of working age). The number of average daily COVID-19 patient contacts amongst participants working in a health/social care setting was collected. Proportions with 95% binomial confidence intervals, and P-values from Chi-squared tests, are presented to explore associations by sex.Vaccine efficacy (VE) was calculated as 1-aRR  computed using a robust Poisson regression model. The model contained terms for sex, country, vaccine received, BMI (linear and quadratic terms), health/social care worker status (yes/no), ethnicity (white/non-white), and age at randomisation (linear and quadratic terms). The model additionally contained interaction terms for age by health/social care worker status, and vaccine group by sex. The logarithm of the period at risk was used as an offset variable in the model to adjust for volunteers experiencing events at varying follow-up times. Participants were censored at the earliest occurrence of positive NAAT swab, discontinuation/withdrawal, unblinding, receiving a COVID-19 vaccination external to the trials, or data cutoff date. Severity of disease in primary symptomatic cases, measured by the WHO severity grading scale, was explored by sex using the Cochran-Armitage test for trend.Immune responses at 28 days post-second vaccination have been summarised as medians and IQRs, and geometric mean titres (GMTs) with 95% CIs for log-transformed data. Geometric mean ratios (GMRs) with 95% CIs and associated P-values, from Student's t-tests, are presented for comparison between females and males. Adjusted linear models of log-transformed immune responses were fit to produce GMRs adjusted for age at randomisation , country, health/social care worker status, ethnicity, and the interaction between age and health/social care worker status. Anti-spike antibody isotypes, subclasses and function data were compared between sexes using Bonferroni-adjusted P-values from Wilcoxon rank-sum tests. All other P-values are unadjusted for multiplicity.Levels of receptor binding domain (RBD), anti-spike, and anti-nucleocapsid antibodies in plasma samples from convalescent patients are presented by reported WHO severity grading scale rating. Linear models were fitted to assess the differences between males and females on each antibody response using the first sample taken for each patient, adjusting for severity of disease and age of patient.Solicited adverse events are presented as frequencies (%) with 95% binomial exact confidence intervals. Logistic regression models were fitted as exploratory analyses to observe the effect of age and sex on adverse events after first and second ChAdOx1 nCoV-19 vaccinations. For interpretation purposes, age was fit as a continuous variable, centered at 18 (the lower age bound of participants recruited to the studies). Models contained additional terms to adjust for the potentially confounding effects of country, health/social care worker status and ethnicity. Correlation matrices were produced to assess the associations between solicited adverse events in each sex.In all regression models, linearity assumptions for continuous variables were checked and transformations made as appropriate. A statistical analysis plan was prepared prior to the first efficacy analysis.Formal sample size calculations for efficacy were pre-specified for the main and interim efficacy analysis as previously published,There was no formal sample size calculation for immunogenicity outcomes as these were secondary or exploratory. Anti-spike IgG titres were measured on a subset of 15% of trial participants as required for regulatory submission, whereas other assays were run on smaller subsets.proc genmod” function, and logistic models were fitted using “proc logistic” function, in SAS.Data analysis was done using R version 3.6.1 or later and SAS version 9.4. Robust Poisson models were fitted using “Funders had no role in study design, data collection, data analyses, interpretation, or writing of this report.P<0.0001, Chi-squared test; Table S3) with 64% of females working in health or social care, compared with 36% of males. Average daily contact with COVID-19 patients in health/social care workers was not statistically significantly different between the sexes . However, there were country-specific differences, as female health/social care workers on average made fewer daily contacts with COVID-19 patients than males in the UK , but this was not so in Brazil .Baseline characteristics in the efficacy cohort were similar for vaccine and control groups . DiffereP=0.3359, robust Poisson regression). No statistically significant difference between males and females was found in the severity of breakthrough disease or disease in the control arm .663 cases of primary symptomatic COVID-19 occurred more than 14 days after a second dose, 109 (2.6%) in the 4243 female participants in the ChAdOx1 nCoV-19 group and 261 (6.3%) in the 4150 female participants in the control group, with adjusted efficacy of 59.9%  had anti-SARS-CoV-2 spike IgG data, and 748 participants  had available pseudovirus neutralising antibody data (Table S6). Anti-spike IgG responses 28 days after a second ChAdOx1 nCoV-19 vaccination were statistically significantly higher in females than males, both before and after adjustment for potential confounders . However, neutralising antibody levels were similar between the sexes . AdjustiP>0.5000 in each linear regression model; Figure S1).Convalescent plasma samples were available from 39 unvaccinated males and 74 females. A higher proportion of males had severe disease (67%) compared with females (19%). The majority of samples were collected from health/social care workers, the majority being female (82%), with asymptomatic and mild disease. The median age of males with convalescent plasma samples was 57 years (IQR 47–68 years) compared to 43 years (IQR 30–53 years) in females. Adjusting for both age and severity of disease, there were no statistically significant differences between males and females with regards to RBD, nucleocapsid, or spike antibody response to COVID-19 infection (The first-dose reactogenicity cohort included 788 participants (708 from the UK and 80 from Brazil) with diary data for their first ChAdOx1 nCoV-19 vaccination, and 676 participants in the second-dose cohort .Reported fever rates were higher in females 5%) than males (1%) after first doses. For each 10-year increase from 18 years of age, the odds of having any solicited systemic reaction after a first vaccination decreased by 35% , and by 48%  for any solicited local reaction ,5. This % than maAdjusting for age and other potentially confounding variables, females had almost twice the odds of experiencing a systemic reaction after first vaccination than males . Solicited systemic adverse reactions did not differ between males and females after a second dose; however, females had increased odds of a local reaction after a second dose . Interaction terms for age by sex and age by health/social care worker were explored, but were statistically insignificant in all models. Despite differences in frequency of reactions, both sexes reported fatigue and tenderness as the most common solicited systemic and local adverse reactions, respectively, after both first and second ChAdOx1 nCoV-19 doses . No differences between females and males were seen in correlations between solicited adverse reactions after either dose of ChAdOx1 nCoV-19 .This study shows that there is no evidence of a difference in efficacy of COVID-19 vaccine ChAdOx1 nCoV-19 between males and females. As observed for other vaccines, systemic reactions following the first dose were higher in females than males, and females were more likely to experience local reactions after a second dose. Whilst this trend was seen across age groups, reactogenicity in both sexes decreased with increasing age. Minor differences were also observed in binding antibody titres, which were higher in females, however this was not associated with any statistically significant difference in vaccine efficacy.In a large phase 3 efficacy study in the United States, ChAdOx1 nCoV-19 vaccine efficacy was similar in males and females.This study reports COVID-19 vaccine immune responses disaggregated by sex, showing a small difference in anti-spike IgG between males and females 28 days after receiving a second dose. However, no statistically significant differences were seen in neutralizing antibody titres, antibody isotypes or functionality profiles between the biological sexes. The sample sizes for neutralising antibody and systems serology assays were smaller than for SARS CoV-2 anti-spike IgG assays, and this may have affected our ability to detect statistically significant differences in these measures. To date, there are few reports of differing antibody functionality by biological sex after vaccination, though some differences are reported for measles vaccine.,Higher antibody titres are more commonly measured in females than males following vaccination but with no clear demonstration that these differences result in clinically meaningful variation in protection.Several mechanisms have been suggested to explain sex-differences in humoral responses to vaccination. Oestrogen receptors are present on lymphocytes and pre-menopausal adult females generally exhibit stronger immune responses than children, adult males or post-menopausal females.,,,,,The observation of greater reactogenicity in females following COVID-19 vaccination in our study is also seen for other COVID-19 vaccines. Both phase 2/3 clinical trial reports and real-world evidence gathered for BNT162b2, mRNA-1273 and Ad26.COV2-SWe adjusted for potential confounders to minimise potential bias in the analysis. Our models adjusted for health/social care worker status as a greater proportion of health/social care workers were female, and have potentially higher exposure to SARS-CoV-2. Health care workers were also younger than non-health care workers and so adjustment for age was important. This analysis includes clinical trial data collected from mid-2020 to early 2021. During this period, the alpha SARS-CoV-2 variant was the dominant variant in circulation in the UK and the gamma variant was emerging in Brazil. The observations of this study are limited to the UK and Brazil settings, and may not be representative of other ethnic groups or geographic settings.Our results show that there is no evidence of a difference in efficacy of the COVID-19 vaccine ChAdOx1 nCoV-19 in males and females, and efficacy is observed in both sexes. By disaggregating sex in our analysis of trial data we show that greater reactogenicity in females does not affect clinical vaccine efficacy.AJP is chief investigator. PA, SACC, SB-R, SB, CD, EAC, SF, HS, AF, PF, DJ, SG, JB, MR, SK, TL, EP, NS, ST, LW contributed to implementation of the study and/or laboratory experimentation. MV and NGM performed the statistical analysis and had full access to and verified the data. GL, NGM, AJP, and MV contributed to the preparation of the report. All authors critically reviewed and approved the final version.Anonymised participant data will be made available when the trials are complete, upon requests directed to the corresponding author. Proposals will be reviewed and approved by the sponsor, investigator, and collaborators on the basis of scientific merit. After approval of a proposal, data can be shared through a secure online platform after signing a data access agreement. All data will be made available for a minimum of 5 years from the end of the trial.Oxford University has entered into a partnership with AstraZeneca for further development of ChAdOx1 nCoV-19. AstraZeneca reviewed the final manuscript before submission, but the authors retained editorial control. SCG is a cofounder of and shareholder in Vaccitech (collaborators in the early development of this vaccine candidate) and named as an inventor on a patent covering use of ChAdOx1-vectored vaccines (PCT/GB2012/000467) and a patent application covering this SARS-CoV-2 vaccine. TL is named as an inventor on a patent covering use of ChAdOx1-vectored vaccines (PCT/GB2012/000467) and was a consultant to Vaccitech. PMF is a consultant to Vaccitech. AJP is Chair of the UK Department of Health and Social Care's JCVI, but does not participate in policy advice on coronavirus vaccines, and was a member of the WHO Strategic Advisory Group of Experts (SAGE) until 2022. MNR has acted as PI on commercial vaccine trials sponsored by Astra Zeneca and VBI vaccines but not personally received payment for this work. MV has received grants from the NIHR and Bill and Melinda Gates Foundation not related to this work and participated on Data Safety Monitoring Boards for NIHR funded projects not related to this paper.


Recent clinical guidelines have emphasized non-opioid treatments in lieu of prescription opioids for chronic non-cancer pain, exempting cancer patients from these recommendations. In this study, we determine trends in opioid and non-opioid treatment among privately insured adults with chronic non-cancer pain (CNCP) or cancer. Using administrative claims data from IBM MarketScan Research Databases, we identified privately-insured adults who were continuously enrolled in insurance for at least one calendar year from 2012 to 2019. We identified individuals with CNCP diagnosis, defined as a diagnosis of arthritis, headache, low back pain, and/or neuropathic pain, and a individuals with cancer diagnosis in a calendar year. Outcomes included receipt of any opioid, non-opioid medication, or non-pharmacologic CNCP therapy and opioid prescribing volume, MME-per-day, and days’ supply. Estimates were regression-adjusted for age, sex, and region. Between 2012 and 2019, the proportion of patients who received any opioid decreased across both groups . Non-opioid pain medication receipt remained steady for individuals with CNCP  and increased for individuals with cancer , while non-pharmacologic therapy use rose among individuals with CNCP . Among those prescribed opioids, there was a decrease in the receipt of at least one prescription with >90 MME/day ; >7 days of supply , the mean number of opioid prescriptions  and mean MME/day . Overall, from 2012–2019, opioid prescribing declined for CNCP and cancer, with larger reductions for patients with CNCP. For both groups, reductions in prescribed opioids outpaced increases in non-opioid alternatives. Over the past decade, the federal government, state governments, medical societies, health systems and insurers have issued clinical guidelines and policies designed to reduce opioid prescribing ,2. HighePain-related conditions associated with CNCP where opioids were historically considered acceptable first-line treatment and frequently prescribed include low back pain, arthritis, serious headache and neuropathic pain . In 2016Trends in opioid prescribing and delivery of non-opioid therapies among CNCP patients compared to cancer patients over the past decade are not well understood. Extant research on opioid prescribing patterns among CNCP patients has documented increases in opioid prescribing prior to 2010 using national samples and decreases in opioid prescribing after 2010 among non-national samples and populations with specific conditions, like arthritis –27. PrioWe conducted a retrospective cohort study using the IBM MarketScan Research Databases from 2012 to 2019, which included health insurance claims and encounters for privately insured employees and their dependents from approximately 100 insurance companies in the US covering 26.1 to 53.1 million enrollees, depending on the year.th Revision (ICD-10) codes , using International Classification of Diseases, Ninth Revision (ICD-9) and 10Codes in . These cFor both groups, we identified whether individuals received at least one opioid prescription, at least one clinical guideline-concordant non-opioid prescription pain medication, and, among individuals who were prescribed an opioid, the number of opioid prescriptions, duration, and strength of each prescription. For individuals with CNCP, we also identified if they received at least one guideline-concordant CNCP non-pharmacologic therapy.We identified opioid prescriptions using the 2018 CDC Opioid NDC and Oral MME Conversion File . We inclFor every individual that was prescribed an opioid, we also examined the number of opioid prescriptions, duration and strength of each prescription. The duration of the prescription was measured as the number of days of supply. To allow for comparison of strength across opioids of different types, we calculated the morphine milligrams equivalent (MME) by multiplying days of supply, dose and MME conversion factor. The dose and MME conversion factor for each drug was linked to Marketscan data from the 2018 CDC Opioid NDC and Oral MME Conversion File . We calcWe calculated regression-adjusted estimates of all outcomes separately for each group for each calendar year. Estimates were adjusted for age, sex, and region of residence. Standard errors were clustered at the individual level, and Wald tests were used to test for differences between estimates in a given year relative to the prior year and differences between 2012 and 2019 estimates.Given that clinical guidelines changed and began recommending non-opioid pain medications and non-pharmacologic therapies in place of opioids as first-line CNCP treatment during our study period, we conducted a secondary analysis assessing substitution of clinical guideline-concordant non-opioid therapies in place of opioid prescriptions among individuals with CNCP. We conducted this analysis among the subset of the sample with CNCP who were prescribed an opioid in the previous year. Among those individuals, we calculated the percentage of individuals who experienced reduced opioid prescribing. We defined reduced opioid prescribing using one of two benchmarks: 1) individuals whose yearly average MME/day reduced by at least 20 MME/day compared to the prior year or 2) individuals who received a lesser number of opioid prescriptions compared to the prior year. The 20 MME/day cutoff was chosen because CDC guidelines cited several studies that found increased overdose risk associated with higher opioid dosage comparing individuals with < 20 MME/day with higher dosage categories. Among CNCP patients with reduced opioid prescribing, we measured non-opioid substitution in four ways: 1) the percentage of CNCP patients who had an increase in the number of non-opioid pain medication prescriptions, but no increase in non-pharmacologic therapies, compared to the prior year; 2) the percentage of CNCP patients who had an increase in the number of non-pharmacologic therapies, but no increase in non-opioid pain medication prescriptions, compared to the prior year; 3) the percentage of CNCP patients who had increase in both the number of non-opioid prescriptions and the number of non-pharmacologic therapies compared to the prior year; and 4) no non-opioid substitution . We calculated unadjusted descriptive statistics of these percentages and chi-2 tests to test for differences across years.The number of individuals with CNCP in the sample ranged from 1,717,340 to 2,220,248 across years.  from 2012 to 2019 . The adjThe adjusted percentage of the group with cancer diagnoses prescribed an opioid decreased 7.3 percentage points from 2012 to 2019 . The adjusted percentage of this group prescribed a clinical guideline-concordant non-opioid pain medication increased 4.4 percentage points from 2012 to 2019 .The most commonly prescribed clinical guideline-concordant non-opioid pain medications among individuals with CNCP diagnoses were antidepressants , NSAIDs  and anticonvulsants   in the CNCP sample and 4.0 to 2.7 (p<0.01) in the cancer sample from 2012 to 2019 . From 20Among those who were prescribed an opioid, the percent of individuals who received at least one opioid prescription with >90 MME/day dropped 9 percentage points  in the CNCP sample and 18.6 percentage points  in the cancer sample. Among those who were prescribed an opioid, the percent of individuals who received at least one opioid prescription with >200 MME/day dropped 1.7 percentage points  in the CNCP sample and 2.2 percentage points  in the cancer sample.Among those who were prescribed an opioid, the percent of individuals who received at least one opioid prescription with >7 days of supply dropped 25.6 percentage points  in the CNCP sample and 24.8 percentage points  in the cancer sample. Among those who were prescribed an opioid, the percent of individuals who received at least one opioid prescription with >30 days of supply dropped 2.7 percentage points  in the CNCP sample and 0.9 percentage points  in the cancer sample. The unadjusted values of all outcomes  and sensAmong individuals with CNCP, the percentage of individuals that did not experience reduced opioid prescribing compared to the prior year decreased over time from 39.9% in 2013 to 32.9% in 2019 (p<0.001), meaning that the percentage that did experience reduced opioid prescribing increased over time from 60.1% in 2013 to 67.1% in 2019 (p<0.001) . We examIn a national sample of privately insured adults, opioid prescribing for individuals with CNCP decreased from 2012 to 2019, but delivery of guideline-concordant non-opioid CNCP treatments recommended by clinical guidelines –22 introWhile clinical guidelines continue to endorse prescription opioid treatment for cancer-related pain, declines in receipt of any opioid prescription were observed for people with cancer diagnoses, though these declines were smaller in magnitude than those observed among people with CNCP diagnoses. Future research is needed to understand the clinical implications of this decline, as well as observed decreases in MME/day and days’ supply of opioid prescriptions, among cancer patients. On the one hand, this finding may signal a cooling effect on opioid prescribing that could contribute to poorly controlled cancer pain. On the other hand, this finding may suggest reductions in high-risk opioid prescribing practices, such as high dosage prescribing, which are shown to contribute to increased risk of opioid overdose death among cancer patients .One potential unintended consequence of efforts to limit opioid prescribing is that providers may engage in “gaming” behavior and provide patients with multiple prescriptions, larger doses, or greater days of supply to avoid callbacks for refills . TherefoOur findings align with prior research suggesting that receipt of opioid prescriptions among the general population decreased following the release of the CDC guidelines in 2016 . HoweverThese results need to be taken in the context of several limitations. First, because our dataset was limited to administrative claims data. Therefore, we cannot determine the socioeconomic status of individuals in the sample, the clinical appropriateness of therapies, the consumption of opioids illegally or not paid for by insurance, or key clinical outcomes such as pain relief. Administrative claims data may also have data entry errors and misclassification, however to mitigate this we used measures of chronic non-cancer pain, cancer and therapies used in other claims analyses and guided by clinical guidelines. Second, our analytic sample included adults who were continuously enrolled in a self-insured employer-sponsored insurance plan for at least a full calendar year. Generalizability to other populations, such as Medicare and Medicaid beneficiaries and those without continuous insurance enrollment may be limited. Of particular note, these inclusion criteria led to a relatively small sample size of people with cancer diagnoses  Third, opioid prescribing in the general population varies widely by prescriber and geography, which was not examined in this study –49. FourFrom 2012–2019, individuals with CNCP and individuals with cancer have experienced declines in opioid prescribing without corresponding increases in receipt of non-opioid therapies. Further investigation is needed to examine how these changes influence the management of pain among patients with CNCP and/or cancer.S1 Appendix(PDF)Click here for additional data file.S2 Appendix(PDF)Click here for additional data file.S3 Appendix(PDF)Click here for additional data file.S4 Appendix(PDF)Click here for additional data file.S5 Appendix(PDF)Click here for additional data file.


The overall amount of social support increased from baseline to 1-week post-injury (p < 0.05) and then remained unchanged until RTP. The overall satisfaction with the support received increased from baseline to 1-week post-injury (p < 0.05) but decreased (p < 0.05) from 1-week post-injury to RTP. Increases in satisfaction with the support received were associated with decreases in post-injury depressive (β = −0.404), p < 0.0001) and anxiety symptoms (β = −0.406), p < 0.0001). Interventions involving social support may help hasten college-student athletes’ psychological recovery from injury.Social support can positively influence both physical and psychological recovery from sport-related injury. However, few studies have examined the influence of the quantity, quality, and timing of social support on athletes’ psychological health following injury. This study examined the effects of changes in social support on post-injury depressive and anxiety symptoms among college-student athletes. We conducted a prospective cohort study among Division I college-student athletes. Participants completed surveys at baseline and at multiple time points post-injury until return to play (RTP). A total of 597 injuries sustained by 389 student athletes ( Injuries are common among college-student athletes , with anSocial support, defined as individuals on whom a person can rely on during periods of stress , is an iDespite the body of literature highlighting the role of social support in psychological recovery from injury ,19,21,22Participants were male and female college-student athletes from two Big 10 Conference universities who were at least 18 years old and participated in 1 of 9 Division I NCAA-sponsored sports  between 1 August 2007 and 31 December 2011. Written informed consent was obtained immediately prior to participation in the study. A total of 957 college-student athletes (90.2% participation rate) were prospectively enrolled in the study between the 2007–2008 and 2011–2012 academic years. Of these, 389 (40.7%) sustained at least 1 injury during the study period. This study received ethical approval from the Institutional Review Boards at the participating universities (IRB ID #: 200507776).After receiving approval from the head coach of each team, the research team introduced the study to potential athlete participants during a scheduled team meeting at the beginning of the season and invited them to participate in the study. Athletes who expressed interest in the study provided written consent and completed a preseason baseline survey that assessed depressive and anxiety symptoms, social support, and other study measures. We then prospectively followed enrolled athletes to identify injury incidence using the Sports Injury Monitoring System (SIMS), an ongoing injury surveillance system established for Big 10 Conference universities . Injury We measured depressive symptoms at baseline  and post-injury using the 20-item Center for Epidemiological Studies Depression Scale (CESD) ,26, a wiWe measured anxiety using the 40-item State–Trait Anxiety Inventory (STAI), which includes separate measures of state anxiety (20 items) and trait anxiety (20 items) ,28. InteWe defined social support as college-student athletes’ appraisal of the support from their social network and how satisfied they were with that support. We measured 2 dimensions of social support using the 6-item Social Support Questionnaire (SSQ6) at each time point: ,30 (1) nData on college-student athletes’ demographic characteristics , class year when injured, type of injury, and injury severity were also collected and included as covariates in the analysis.Data analysis was conducted using SAS version 9.4 . We used descriptive statistics to describe participant’s demographic characteristics as well as their baseline depressive and anxiety scores. Because depressive and anxiety scores were not normally distributed, we conducted nonparametric tests  to compare mean differences in baseline depressive and anxiety scores across demographic characteristics. We conducted longitudinal analyses across the three time points  using linear models with repeated measures to assess changes in post-injury social support , including the amount of social support from each source and the degree of satisfaction with each source of social support.We used linear mixed models (LMMs) to assess the effects of changes in social support, including the amount of and satisfaction with the social support received, on changes in post-injury depressive and anxiety scores during recovery. The LMMs were constructed with a 3-level structure: repeated measures of mental health symptoms at follow-ups (level 1) nested within each injury (level 2), which were further nested within each athlete (level 3). Since the depressive and anxiety symptom scores were highly skewed at each data point, a log transformation was conducted to ensure approximate normality. To assess the effects of each of the 3 sources of social support  on changes in post-injury depressive and anxiety scores, we performed separate analyses for each source and adjusted for baseline depression and anxiety symptom scores, social support before injury, and other covariates . Due to the collinearity caused by high correlations between the 3 sources of social support, we first regressed the social support from each source against the other sources and then included and adjusted the residual obtained in our mixed models.n = 400, 67.0%), football players , and freshman  , and of these, sprains  were most common, followed by strains  and fractures . Approximately one-tenth of injuries  were concussions. Most athletes  returned to play within 1 week of injury, and 28.3% (n = 168) of athletes returned to play between 1-week and 1-month post-injury.A total of 597 injuries sustained by 389 athletes were included, accounting for an average of 1.53 injuries per athlete. Injuries were most common among male athletes  . Most inThe average baseline scores for depression and anxiety symptoms were 10.8 (SD = 8.9) and 41.0 (SD = 10.2), respectively . We founWhile the average amount of social support from all three sources increased from baseline to 1-week post-injury , no significant changes were observed from 1-week post-injury to RTP . The aveInjured athletes reported that family/friends were the primary source of social support throughout their recovery, with a higher average number of and a greater degree of satisfaction with the support received from family/friends, as compared to the other sources of support. Statistically significant changes were found in the amount of  and satisfaction with the support received  from family/friends from baseline to 1-week post-injury . InjuredInjured athletes also reported decreased satisfaction with the support received from family/friends , their team , and others  from 1-week post-injury to RTP. However, there were no statistically significant changes in the amount of social support received from each of the three sources of social support from 1-week post-injury to RTP .p = 0.01) and anxiety symptom scores , as was greater satisfaction with the social support received from one’s team . However, we found no statistically significant effects of changes in the amount of social support from each source on changes in post-injury depressive symptoms or anxiety, after adjusting for potential covariates (Greater satisfaction with the social support received from family/friends was associated with decreased post-injury depressive (β = −1.04, variates .This study investigated the effects of changes in social support on changes in depressive and anxiety symptoms post-injury among injured college-student athletes. The main results showed that greater levels of satisfaction with the social support received were associated with decreased depression and anxiety symptoms post-injury. Results also revealed that the amount of and satisfaction with the social support received increased from baseline to 1-week post-injury. However, while the amount of social support from all sources remained unchanged from 1-week post-injury to RTP, the satisfaction with the support received decreased during this period. The findings of this study highlight the importance of social support on the mental health of injured athletes from injury onset to full recovery. Our findings may help inform the development of proactive strategies, including those involving social support, that aim to improve the mental health of injured college-student athletes during recovery.An athlete’s level of social support is important to the recovery process ,32,33. SWe found that overall satisfaction with the social support received was associated with reduced post-injury depression and anxiety symptoms, as was the satisfaction with the support received from each of the three sources of social support. These findings, in line with others, ,32,35 suIt is important to recognize that injured college-student athletes need social support from the time of injury until RTP, in order to hasten both the physical and psychological recovery from injury, with needs being heightened at certain points during the recovery process ,36. Our Consistent with prior studies ,39, we fThis study had several limitations that warrant attention. First, our findings are limited by the collection of data from a sample of college-student athletes from two Big 10 universities. Therefore, our findings may not be generalizable to other universities, divisions, or leagues. Second, our sample was limited by the unbalanced distribution of participants by sex, sport played, and class year when injured. Third, we measured perceived social support as opposed to the actual social support received throughout recovery. While perceived support has a greater influence on the outcome, our results should be interpreted in this light. Fourth, it is important to acknowledge that some unmeasured factors, such as mental healthcare seeking or sport modality, may have influenced the observed relationships between social support and post-injury depressive and anxiety symptoms; thus, the findings of this study should be interpreted with caution. Fifth, depression and anxiety symptoms were based on self-reported data and may have been subject to social desirability bias. Finally, the data presented in this study were collected 10 years ago and may be outdated. It is important to note, however, that to the best of our knowledge, no similar studies have been conducted since the collection of our study data. Despite these limitations, this study provides important insight into the influence of social support on the mental health of Division I college-student athletes following injury.Our findings indicate that injured athletes reported an increase in the amount of social support and satisfaction with the social support received from baseline to 1-week post-injury. However, such a trend did not persist from 1-week post-injury to RTP. Our results also indicated that greater satisfaction with the social support received was associated with decreased post-injury depressive and anxiety symptoms. These findings suggest that interventions that involve social support may help injured college-student athletes manage depressive and anxiety symptoms post-injury. Future interventions could provide behavioral training to student athletes and coaches to equip them with the requisite skills to provide emotional/instrumental and informational support to injured athletes throughout the course of recovery.


Statin therapy can effectively reduce recurrent transient ischemic attack (TIA) risk. However, studies have reported that statin use is associated with incidence of diabetes mellitus (DM). Whether statin therapy remains associated with higher DM risk in patients with TIA remains unknown. This study investigated whether statin treatment influences incident DM risk in patients with TIA. We conducted a retrospective cohort study using the Longitudinal Health Insurance Database 2000. Participants who were newly diagnosed with TIA (ICD-9-CM code 435) from 1 January 1997 to 31 December 2011 were recruited. The Kaplan–Meier method and Cox proportional risk model of time-dependent covariance were used. We enrolled 8342 patients with newly diagnosed TIA from 1 January 1997 to 31 December 2011. Of these, 1255 patients were classified as statin users and 7087 as nonusers. During the 14-year follow-up, the incidence of newly diagnosed DM was 0.545-fold lower in the statins group compared with nonusers . According to cumulative defined daily doses (cDDDs), the adjusted hazard ratios for DM were 0.689, 0.594, and 0.463 when patients were treated with statins at cDDDs = 28–89, 90–180, and >180, respectively. In patients with TIA, statin use is associated with a lower incident DM risk compared with the nonuse of statins. Transient ischemic attack (TIA) is a common neurological disease. For patients exhibiting an acute loss of focal cerebral or ocular function attributable to vascular disease lasting under 24 h, TIA should be considered as the diagnosis . TIA is Atherosclerosis is a common risk factor for TIA. Patients with TIA caused by atherosclerosis should receive statin therapy . Statinsp < 0.001) [Statin use has been associated with increased insulin resistance and has been reported to elevate the risk of incident diabetes mellitus (DM) ,10. A re< 0.001) . One met< 0.001) .Research indicates that statin use contributes to the development of DM; however, the results of such studies vary widely. The risk of new-onset DM with statin use is between 0.1%  and 46% Whether statin treatment remains associated with increased DM risk in patients with specific health conditions, such as TIA, is unknown. The determination of the effect of statins on incident DM in patients with TIA will allow clinicians to optimize treatment plans.This study investigated whether statin treatment influences incident DM risk in patients with TIA using data from the Longitudinal Health Insurance Database 2000 (LHID 2000).In Taiwan, the National Health Insurance (NHI) program has been a compulsory, single-payer program since 1995, and more than 99% of the population is insured. The National Health Insurance Research Database (NHIRD) contains patient registry and claims data, including demographic characteristics, details of outpatient visits, hospitalizations, prescriptions, and diagnoses. The LHID 2000 is a subset of the NHIRD that contains reimbursement claims data of one million individuals randomly selected from the NHIRD. The NHI reported no difference in the sex and age distributions of participants in the LHID 2000 and NHIRD.This study used a retrospective cohort design. The sample was enrolled from the LHID 2000, from between 1 January 1997 and 31 December 2011. The definition of diseases was based on the International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM). To further validate the diagnoses of the study, only patients with at least three outpatient visits or who had ever been hospitalized because of their diagnosis were selected.Patients who were newly diagnosed with TIA (ICD-9-CM code 435) from 1 January 1997 to 31 December 2011 were included. The exclusion criteria were (1) a TIA or DM (ICD-9-CM code 250) diagnosis before 1 January 1997, (2) diabetic medical records before TIA diagnosis, (3) DM or stroke within 1 year following TIA diagnosis, and (4) statin medication records before the diagnosis of DM. The comorbidities of participants included hypertension (ICD-9-CM codes 401–405), dyslipidemia (ICD-9-CM code 272), atrial fibrillation (ICD-9-CM code 427.31), heart failure (ICD-9-CM code 428), coronary artery disease (ICD-9-CM codes 410–414), peripheral artery disease (ICD-9-CM code 443.9), chronic kidney disease (ICD-9-CM code 585.9), chronic obstructive pulmonary disease (ICD-9-CM codes 491 and 492), and alcohol-related diseases . A flow chart of participant enrollment is presented in Data relating to patient statin prescriptions were obtained from the medication records in the LHID 2000. Both hydrophilic and lipophilic statins were selected in the study, including pravastatin, fluvastatin, rosuvastatin, simvastatin, lovastatin, and atorvastatin. Exposure to statins was measured in terms of defined daily dose (DDD) as the unit of calculation, and the daily dose of each prescribed medicine was calculated using the following formula:To consider long-term exposure to changes in the exposure dose of each drug, we calculated the cumulative DDDs (cDDDs) for each participant under the tracking time of the study as the drug exposure dose of the individual. Statin exposure was grouped according to the cumulative definition of statins used as the previous research . The nonp < 0.05 was considered statistically significant.For descriptive statistics, Student’s t-test and chi-square tests were conducted to identify differences in demographic characteristics between the statin use and statin nonuse groups. The Kaplan–Meier (KM) method and Cox proportional risk model of time-dependent covariance were used to evaluate the association between statin use and incident DM in patients with TIA. Hazard ratios (HRs) and 95% confidence intervals were calculated to quantify DM risk. Statistical analyses were performed using SAS , and a two-tailed p < 0.0001). No differences in TIA diagnosis between male and female patients were observed (p = 0.3615). Approximately half of the participants were male (49.45%). The mean years of follow-up were 7.5 versus 6.1 for statin users and statin nonusers, respectively (see Patients (N = 8342) with newly diagnosed TIA, between 1997 and 2011, were selected for the study. Of these, 1255 were statin users and 7087 were statin nonusers. The mean age at TIA diagnosis was significantly lower for statin users than for statin nonusers  was observed. The results indicated that the incidence of DM in TIA patients was lower in the statin-use group than in the non-statin-use group during the first few years of statin use. However, the slope of KM curve was steeper in the statin-use group than in the non-statin group, which means the incidence of DM in the statin-use group increased faster than that of the non-statin group in the TIA patient. The incidence of DM in patients using statin in the TIA patient was lower than that of non-statin patients during the initial tracking time. However, if the tracking time was longer, the results were the opposite; in particular, when the tracking time was longer than 12 years, the incidence of DM was higher in statin nonusers than in statin users.The time-dependent covariate Cox model results are displayed in Compared with We observed that when the statin-use duration was less than 9.2 years, in patients with TIA, statin use was associated with a lower incident DM risk (adjusted HR = 0.545), and DM risk substantially decreased with an increase in the cDDDs of statins. Previous studies indicated that statin users exhibited a higher DM risk than statin nonusers ,12. ThisWe analyzed cohort data using a Cox proportional risk model of time-dependent covariance that is suitable for nonconstant exposure, such as nonconstant drug use, air pollution exposure, and temperature exposure. The drug dose that patients receive is adjusted according to their clinical situation, especially in Taiwan, where the health insurance system is convenient for the population. Therefore, the Cox proportional risk model of time-dependent covariance is suitable for situations where exposure is not constant. Some studies have reported decreasing trends in the incidence of DM for statin users , but othThe previous literature indicated that statin use has been associated with increased insulin resistance and has been reported to elevate the risk of incident DM ,10. HoweThe previous literature indicated that the incidence rate of the onset of type 2 diabetes increased by age . The KM One study reported that statin use is beneficial for cardiovascular disease prevention . This isThe exposure to statins, in terms of dose, does not remain constant clinically. The metabolism and absorption of each drug vary in different situations. Because drug dose is not constant and drug absorption is different for different people, research that combines big data and laboratory data should be undertaken in the future.This study has the following limitations. First, by using the LHID 2000, we defined the situations of patients only on the basis of ICD-9-CM code entered upon treatment in a hospital or clinic. Some information was lacking in the health insurance database, such as health examination data , daily life habits (such as smoking and drinking), family history (such as hereditary disease), and life environment (such as exposure to pollution). Because of the limited information available, potential confounders that might have influenced the relationship between statin use and DM could not be included in analysis. Second, the accuracy of the statin dosages might have been somewhat less than optimal, although we calculated the cumulative dose using a credible formula; nevertheless, compliance with the doctor’s orders for each patient could not be confirmed. Finally, we only recruited patients living in Taiwan. Some discrepancies in the incidence of diseases between ethnicities have been reported. Research using a multiethnic sample should be considered in the future.In patients with TIA, when the statin-use duration is less than 12 years, statin use is associated with a lower DM risk compared with the nonuse of statins. However, when the cohort was followed for longer than 12 years, the converse result was observed. It is important that the follow-up period in statin use contributes to determining whether there is a risk of development of DM in patients with TIA. In Taiwan, if cardiovascular disease patients have TC ≥ 160 or LDL-C ≤ 100, statin use is eligible through Taiwan’s health insurance. Those patients might not be diagnosed as dyslipidemia. Therefore, there will be a gap between the data of dyslipidemia-diagnosed and statin-using patients. The purpose of our research was to investigate whether statin treatment influences incident DM risk in patients with TIA. Therefore, we defined “statin treatment” via “the cases who actually use statin-drugs”.