To evaluate the extent to which dental health care visits in the past year differed among older adults with and without edentulism.We conducted a cross‐sectional study using the 2017 Medical Expenditure Panel Survey among participants aged ≥50 years . Two self‐reported outcome variables were used: loss of all teeth from upper and lower jaws (yes/no) and dental visit in the last 12 months (yes/no). Logistic models were used to estimate adjusted odds ratios (aOR) and 95% confidence intervals (CI).Overall, 11.4% of the non‐institutionalized U.S. population aged ≥50 years were edentulous; the prevalence was higher in those with advanced age. Adherence to annual oral health visits was 16% among those with edentulism, 52% among those without. The prevalence of dental care visits in the past year was higher among those with advanced age without edentulism, but for those with edentulism, the odds of visiting a dental care provider was lower in all age groups compared to those 50–59 years ((60–69 years): aOR: 0.58, CI:0.36–0.95; (70–79 years): aOR: 0.51, CI: 0.30–0.88; (≥ 80 years): aOR: 0.45, CI: 0.26–0.80)).Although the prevalence of edentulism was higher in those with advanced age, oral health visits during the last 12 months were less frequent in older adults with edentulism. Interventions to improve adherence to dental care recommendations in the growing aging population are warranted. The Center for Disease Control and the Agency for Healthcare Research and Quality sponsored the data collection for MEPS 2017. Questionnaires were administered to randomly selected persons for household reporting . Weighted respondents were cross‐checked with U.S. census estimates for 2017, which totaled 114,217,553 , born in the United States , marital status , family income as a percentage of the poverty line , dental insurance (yes/no), health insurance (private/public/none), dental visit in the last year (yes/no), active smoker in the last 12 months (yes/no). Education status was consolidated into three categories: no degree, high school diploma/general education diploma, and some college or greater. We categorized participants according to their race and ethnicity as Hispanic, non‐Hispanic Black, non‐Hispanic Asian, or non‐Hispanic White. Mixed race/ethnicity persons were included as Hispanic if they identified as such  or non‐Hispanic mixed race.3.6p‐Values <.05 were considered statistically significant (two‐sided tests). We then estimated the prevalence of edentulism by age (in years) and depicted this graphically (Figure MEPS provided survey weights and approaches for handling single unit datapoints in the weighted measurement were followed (Wun, Ezzati‐Rice, Diaz‐Tena, & Greenblatt, y Figure . LogistiFor the second aim, we first estimated the percent of participants who reported having an oral health care visit in the past 12 months, stratified by edentulism status and specific for each year of age Figure . We used4Data from MEPS 2017 indicate that 11.4% of U.S. persons aged ≥50 years of age were edentulous (Table Table Table Figure 5There were two main findings from our study. First, using population‐based contemporary data, this study confirms the association between advanced age and edentulism. Overall 11.4% of adults aged ≥50 years were edentulous; the prevalence increased in those with advanced age. While 6.2% of those aged 50–59 years were edentulous, 27.7% of those ≥80 years of age were edentulous. Second, adherence to guidelines regarding annual oral health provider visits was low with about half of those without edentulism and one in six of those with edentulism reporting a visit with an oral health provider in the past year. Furthermore, the relationship between age and use of oral health services in the past 12 months differed by edentulism status. Adherence to annual oral health care visits was less prevalent in older age groups among edentulous adults and was more prevalent in older age groups among non‐edentulous adults.Using contemporary data, our population‐based study confirmed the association between advanced age and edentulism. While there is some debate about the factors that contribute to complete tooth loss, people are more likely to lose their natural teeth as they age (Griffin et al., Adherence to recommendations for annual oral health visits is poor among older adults. As such, population‐level analyses examining the use of oral health services by age are important given the oral health care needs for this vulnerable population (Griffin et al., Edentulous persons require annual routine care from oral health providers (Felton et al., The study strengths and limitations must be considered. Data were drawn from a nationally representative sample that provides vital insight into the oral health status of aging persons in the United States, and oral health utilization of a vulnerable group of persons (Christian et al., 6Edentulism is affecting a significant portion of our non‐institutionalized persons aged ≥50 years and has a profound impact on diet, overall health, and pre‐existing conditions (Polzer, Schimmel, Mueller, & Biffar, Andriana M. Foiles Sifuentes and Kate L. Lapane and Maira A. Castaneda‐Avila made substantial contributions to the conception, design, analysis, and interpretation of study findings. Andriana M. Foiles Sifuentes wrote the original draft of the article and Kate L. Lapane and Maira A. Castaneda‐Avila critically revised the manuscript, providing important intellectual content. All authors approved the final version of the paper.


Previous studies examining the use of direct oral anticoagulants (DOACs) in atrial fibrillation (AF) have largely focused on patients newly initiating therapy. Little is known about the prevalence/patterns of switching to DOACs among AF patients initially treated with warfarin.To examine patterns of anticoagulation among patients chronically managed with warfarin upon the availability of DOACs and identify patient/practice‐level factors associated with switching from chronic warfarin therapy to a DOAC.Prospective cohort study of AF patients in the NCDR PINNACLE registry prescribed warfarin between May 1, 2008 and May 1, 2015. Patients were followed at least 1 year  through May 1, 2016 and stratified as follows: continued warfarin, switched to DOAC, or discontinued anticoagulation. To identify significant predictors of switching, a three‐level multivariable hierarchical regression was developed.P < .001). Switching was less likely with increased stroke risk , but more likely with increased bleeding risk . There was substantial variation at the practice‐level  and among providers within the same practice .Among 383 008 AF patients initially prescribed warfarin, 16.3% (n = 62 620) switched to DOACs, 68.8% (n = 263 609) continued warfarin, and 14.8% (n = 56 779) discontinued anticoagulation. Among those switched, 37.6% received dabigatran, 37.0% rivaroxaban, 24.4% apixaban, and 1.0% edoxaban. Switched patients were more likely to be younger, women, white, and have private insurance (all Among AF patients treated with warfarin between October 1, 2010 and May 1, 2016, one in six were switched to DOACs, with differences across sociodemographic/clinical characteristics and substantial practice‐level variation. In the context of current guidelines which favor DOACs over warfarin, these findings help benchmark performance and identify areas of improvement. AFatrial fibrillationDOACdirect oral anticoagulantACC/AHA/HRSAmerican College of Cardiology/American Heart Association/Heart Rhythm SocietyNCDRNational Cardiovascular Disease RegistryPINNACLEPractice Innovation and Clinical ExcellenceCKDchronic kidney diseaseGFRglomerular filtration rate1Anticoagulation significantly decreases stroke risk in atrial fibrillation (AF).Previous studies from the National Cardiovascular Disease Registry's (NCDR) Practice Innovation and Clinical Excellence (PINNACLE) registry have examined patterns of DOAC use in AF, and have noted disparities in DOAC use based on sex, race, and insurance status.Accordingly, we sought to examine patterns of anticoagulation among patients with AF treated with warfarin, determine predictors of switching from warfarin to DOACs, and identify potential disparities in care based on sociodemographic and clinical factors. We hypothesized that there would be significant disparities in switching patterns and substantial patient/practice‐level variations.22.1The NCDR PINNACLE registry is a prospective outpatient quality improvement registry that was created by the ACC in 2008.2.2The study cohort included all patients with nonvalvular AF, in the PINNACLE dataset with at least one warfarin prescription between January 1, 2008 and May 1, 2015. Patients were followed longitudinally in PINNACLE and stratified based upon their anticoagulation between October 1, 2010 and May 1, 2016 as follows: (a) continued warfarin, (b) switched to a DOAC, and (c) discontinued anticoagulation. Patients were substratified by the date of index visit  and time after index visit . Patients were considered to have switched if they had a DOAC recorded on two consecutive visits in the registry. Patients were excluded if they were younger than 18 years of age, or did not have a second encounter after the initiation of warfarin. Additionally, patients were excluded if they had a history of cardiac valve surgery  or systemic embolism recorded in the registry, in order to analyze patients who were potentially eligible to switch.2.32DS2‐VASc score . For the population of patients who were switched, demographic, clinical, laboratory, and medication information was compared across groups.The primary outcome of this study was the proportion of patients with AF treated with warfarin that were switched to a DOAC and the proportion switched to each specific agent. We calculated the proportion of patients with AF treated with warfarin that were switched to a DOAC, and then calculated the proportion switched to each specific agent . Among the patients who were switched, we calculated the proportion who were subsequently switched back to warfarin, to a different DOAC, or had all anticoagulation discontinued. The mean/median number of visits in the PINNACLE dataset and the mean/median time of follow‐up were also obtained. Additionally, patterns were determined after stratifying patients based on CHAt‐test for continuous variables and chi‐square test for categorical variables. To identify significant predictors of switching, a multivariate model was created, including all variables with P < .1 in bivariate testing.Categorical variables are reported as numbers (percentages) and continuous variables are reported as medians (25th and 75th percentiles) or means (SD). The significance of observed differences was tested using a Wilcoxon rank sum test or 2DS2‐VASc individually, (b) CH2ADS2‐VASc modeled per 1‐point increase along with noncomponent of the CHA2DS2‐VASc covariates, (c) CHA2DS2‐VASc modeled as 2‐6 vs 0 or 1 without HAS‐BLED score, and (d) including both CHA2DS2‐VASc scores and HAS‐BLED scores modeled per 1‐point increase. Since there are co‐linear variables in the risk scores, the CHA2DS2‐VASc score was modeled both with and without the HAS‐BLED score. Practice‐level analyses were conducted by aggregating patients initially managed with warfarin at the practice‐level. The distribution of the proportion of patients receiving warfarin who were switched to a DOAC was determined across practices. After the distribution was examined, additional practice‐level analyses were conducted by stratifying practices into tertiles based on the proportion of patients who were switched to a DOAC (tertiles were arranged from lowest switching rates to highest).The multivariate analyses of clinical variables were modeled in different ways: (a) each component of the CHATo measure practice variation, the median odds ratio (MOR) was used. The MOR is able to provide cluster‐level variance when a multilevel regression analysis is performed and can assess variation in a mixed effects model. An MOR >1.2 suggests clinically significant variation in the outcome among a unit after adjustment for fixed effects. In this analysis, an MOR >1.2 suggests clinically significant variation among practices in switching from warfarin to a DOAC.33.12DS2‐VASc score was 4.0 (IQR 3.0‐5.0) and HAS‐BLED score was 2.0 (IQR 2.0‐3.0). Practices were geographically distributed across the country, with 52.1% in the Southern region and 38.1% in urban locations.There were 485 986 patients in the PINNACLE registry with AF on warfarin between May 1, 2008 and May 1, 2015. Of these patients, 102 978 were excluded from the analysis due to cardiac valve surgery, systemic embolism, age less than 18, missing sex, or missing follow up encounters  were switched to a DOAC, while 68.8% (n = 263 609) were continued on warfarin and 14.8% (n = 56 779) had anticoagulation discontinued , 20.7% (n = 7083) were switched to DOAC, 58.8% (n = 20 077) were continued on warfarin, and 20.5% (n = 7003) had anticoagulation discontinued. For patients with a CHA2DS2‐VASc score of 2‐3 (n = 144 761), 17.1% (n = 24 769) were switched to DOAC, 68.4% (n = 99 064) were continued on warfarin, and 14.5% (n = 20 928) had anticoagulation discontinued. Among patients with a CHA2DS2‐VASc score of 4 or more (n = 204 084), 15.1% (n = 30 768) were switched to DOAC, 70.8% (n = 144 468) were continued on warfarin, and 14.1% (n = 28 848) had anticoagulation discontinued. Switching among patients with a GFR 15‐29 mL/min was 12.3% (n = 262) and among patients with a GFR < 15 mL/min was 6.4% (n = 35).Patterns of switching stratified by CHA3.3P < .001). The mean CHA2DS2‐VASc score for those switched was 3.5 (SD 1.7) and for those not switched 3.7 (SD 1.6); the mean HAS‐BLED score for those switched was 2.2 (SD 1.0) and for those not switched was 2.2 .Baseline demographic, clinical, and practice characteristics of the overall population with AF treated with warfarin Table , patient3.42DS2‐VASc score and noncomponent covariates  and at practices in the Midwest as compared with the Northeast region . A multivariate hierarchical regression model comparing CHA2DS2‐VASc scores to scores of 0‐1 showed that the odds of switching decreased as the CHA2DS2‐VASc score increased when modeled both with and without the HAS‐BLED score  were switched back to warfarin, 7.5% (n = 4692) were switched to another type of DOAC, and 4.6% (n = 2880) eventually discontinued all forms of anticoagulation Figure . A visua3.6There was substantial variation in switching patterns at the practice‐level  and for providers within the same practice . A graphical representation of practice variation in switching to DOACs among 355 practices  is shown in Figure The 355 practices were divided into tertiles (arranged from lowest switching rates to highest) based on the proportion of individuals switched from warfarin to DOACs Table , with te3.7As time progressed, the proportion of individuals switched from warfarin to DOACs increased Table . Among p4This analysis from a large, national outpatient registry demonstrates that approximately 1 in 6 AF patients treated with warfarin, who were eligible to be switched to a DOAC, were switched between October 1, 2010 and May 1, 2016. There were significant differences in switching based on clinical/sociodemographic factors, and substantial variation in care patterns across practices. This relatively low rate of switching represents an important target for improvement as DOACs have been established as first line therapy for most patients with nonvalvular AF.The updated ACC/AHA/HRS guidelines recommend DOAC therapy over warfarin given data demonstrating comparable efficacy with less bleeding. A meta‐analysis of randomized controlled trials demonstrated that DOACs provide significant reduction in stroke, intracranial hemorrhage, and mortality with similar major bleeding compared to warfarin.Potential explanations for the relatively low rate of switching include therapeutic inertia, where providers may not choose to make a change to anticoagulation therapy if a patient has been stable on warfarin without adverse events. Additionally, when DOACs were new, some providers may have waited for accumulating evidence of safety and benefit prior to changing therapy. This may explain why more switching occurred later in the study. Providers may have also chosen to not switch patients they believed had adequate Time in Therapeutic Range (TTR) on warfarin. European guidelines suggest that providers can consider continuing warfarin if patients are able to maintain a TTR on warfarin ≥70% of the time.Broadly speaking, the substantial practice level variation suggests that there are multiple mechanisms underlying these findings. Both at the practice level and among providers within the same practice, there was substantial variation in switching patterns, emphasizing a lack of a unified approach to switching patients from warfarin to DOACs. With some practices switching approximately 65% of patients, while others did not switch any, this highlights the need for additional performance improvement efforts to better align care with practice guidelines.Another key finding from our analysis is that switching was less prevalent among patients with increasing age, non‐white race, those without private insurance, and men. There have been numerous disparities in many aspects of AF management, including initiation of DOACs and ablation.2DS2‐VASc scores). We know from other studies that bleeding avoidance is an important driver of decision‐makingIt is also notable that switching was more prevalent with increased bleeding risk (based on HAS‐BLED scores) but less prevalent with increased stroke risk , household income, and drug benefit plans would be helpful to better define the role of cost in limiting switching. Additionally, as with any clinical management decision, there are often relevant factors that fall outside of information that can be collected in a registry, such as patient preference and unmeasured practice variation. Other factors such as nonadherence, or TTR with warfarin may have affected anticoagulation patterns and switching to DOACs, but were not collected in the PINNACLE registry. Another limitation is the relatively sparse data on renal function available for our analysis. Renal dysfunction is an important consideration in choosing anticoagulation for AF patients and previously was a limitation for DOAC use, although current guidelines now suggest it is reasonable to anticoagulate these patients with apixaban.5In a contemporary cohort of patients with AF treated with warfarin, switching from warfarin to DOACs was relatively uncommon. Switching was less likely with rising stroke risk, but more likely with higher bleeding risk. Additionally, there was significant practice variation in switching. In the context of the 2019 update to the ACC/AHA/HRS guidelines, which favor DOACs over warfarin, these findings may help benchmark performance and identify areas of improvement.The authors declare no potential conflict of interests.acc.org). James V. Freeman: Research Support: ACC NCDR; Modest consulting/advisory board: Medtronic, Boston Scientific, Biosense Webster, Janssen Pharmaceuticals. Nihar R. Desai: Research Support: Centers for Medicare and Medicaid Services; Consulting/advisory board: Amgen, Astra Zeneca, Boehringer Ingelheim, Relypsa. All other authors have no disclosures at this time.Salim S. Virani: American College of Cardiology Click here for additional data file.Figure S4 Multiple Anticoagulation Switches Flow ChartClick here for additional data file.Table S1 Patient Characteristics, Entire Population Initially Managed on WarfarinClick here for additional data file.Table S2 Patient Characteristics ‐ Switched to DOAC vs Not SwitchedClick here for additional data file.Table S3 Patients Characteristics ‐ by Switching CohortsClick here for additional data file.Table S4 Practice Characteristics ‐ All Analysis PopulationClick here for additional data file.Table S5 Switching from Warfarin to DOAC by Time PeriodClick here for additional data file.Table S6 Time from Initial Visit to First SwitchClick here for additional data file.


Spontaneous heart rate fluctuations contain rich information related to health and illness in terms of physiological complexity, an accepted indicator of plasticity and adaptability. However, it is challenging to make inferences on complexity from shorter, more practical epochs of data. Distribution entropy (DistEn) is a recently introduced complexity measure that is designed specifically for shorter duration heartbeat recordings. We hypothesized that reduced DistEn predicted increased mortality in a large population cohort.The prognostic value of DistEn was examined in 7631 middle‐older–aged UK Biobank participants who had 2‐minute resting ECGs conducted . During a median follow‐up period of 7.8 years, 451 (5.9%) participants died. In Cox proportional hazards models with adjustment for demographics, lifestyle factors, physical activity, cardiovascular risks, and comorbidities, for each 1‐SD decrease in DistEn, the risk increased by 36%, 56%, and 73% for all‐cause, cardiovascular, and respiratory disease–related mortality, respectively. These effect sizes were equivalent to the risk of death from being >5 years older, having been a former smoker, or having diabetes mellitus. Lower DistEn was most predictive of death in those <55 years with a prior myocardial infarction, representing an additional 56% risk for mortality compared with older participants without prior myocardial infarction. These observations remained after controlling for traditional mortality predictors, resting heart rate, and heart rate variability.Resting heartbeat complexity from short, resting ECGs was independently associated with mortality in middle‐ to older‐aged adults. These risks appear most pronounced in middle‐aged participants with prior MI, and may uniquely contribute to mortality risk screening. DistEndistribution entropyHRVheart rate variabilityNHSNational Health ServiceRHRresting heart rateRMSSDroot mean square of successive differencesRRIRR intervalTDITownsend deprivation indexUKBUK BiobankDistribution entropy—a measure of heartbeat complexity derived from a 2‐minute, resting ECG—predicts mortality independently of resting heart rate and heart rate variability in middle‐ to older‐aged adults.These risks appear most pronounced in middle‐aged patients with prior myocardial infarction, and may uniquely contribute to routine mortality risk screening.Our findings have the potential to be scaled‐up to remote monitoring in wearable devices, and opens up a new avenue of research for resting heartbeat complexity as a vulnerability marker for stress reactivity.With the exponential growth in noninvasive, passive monitoring of physiological function, there is burgeoning interest in extracting prognostic information from heart activity.In the past 2 decades, novel analytic tools derived from nonlinear dynamics have harnessed information imbedded in spontaneous physiological fluctuations; these are usually not obtainable through traditional, nonlinear signal processing approaches such as means/medians or frequency‐ and time‐domain analysis of heart rate variability (HRV). One of the predominant nonlinear methods is entropy, a measure of unpredictability or “complexity” of signals.A recently introduced distribution entropy (DistEn) measure considers a more integrated feature in the fluctuation patterns, thus allowing a reliable assessment of complexity from short recordings. It may fundamentally address the major limitation associated with short physiological recordings.UKB is a large‐scale biomedical database and research resource containing genetic, lifestyle, and health information from half a million UK participants. Between late 2009 and 2010, 8039 participants from across the United Kingdom recruited to the UKB undertook a 2‐minute resting ECG.Resting ECG data collection lasted 2 minutes with the patient in a seated position. Preprocessing steps are summarized in Figure RHR in bpm was calculated as the inverse of the mean RRI in milliseconds multiplied by the number of milliseconds per minute (60×1000) for each recording. Using established criteria, the root mean square of successive differences (RMSSDs), SD of NN intervals, and percentage >5, 10, and 20 milliseconds for differences between adjacent RRIs were calculated as measures of time‐domain HRV.A host of entropy measures for assessing physiological complexity have been established in the past decade; conceptually, they all share the same theoretical basis—the system is more complex (or unpredictable) if new information in its output  occurs at a higher rate. To assess such evolution of information in a time series, data are first reconstructed to a higher dimensional state space that is believed to best characterize the dynamic changes in the temporal structure of the fluctuations. A state, defined by a vector in the state space, renders new information if it appears far enough in distance from other states that already appear within the time series. With a threshold parameter for distance, approximate entropy and sample entropy essentially measure the log conditional probability that such a new state emerges.For traditional entropy measures, data length of 10 minutes to hours have been used.x=x(i), 1≤i≤N, its m‐dimensional state space reconstruction can be obtained by:i≤N−mτ; τ and m represent the time delay parameter and the dimension parameter, respectively. The Chebyshev distance between a pair of states mu(i), mu(j) can be calculated by:For an RRI time series B is used to estimate the empirical probability density function of the distance matrix d,1≤i,j≤N‐mτ except the main diagonal . Using {tp, t=1,2,…,B} to denote the probability of each bin, DistEn is defined by the following formula:Next, a histogram approach with a fixed bin number m=3, τ=1, and B=256 based on our prior studies using similar data.Further graphical representation of these methods are shown in Figure International Classification of Diseases, Tenth Revision (ICD‐10), codes by trained personnel. Secondary outcomes of cause‐specific mortality were grouped into cardiovascular‐ (I00‐I99), respiratory‐ (J00‐J99), and cancer‐ (C00‐D48) related primary causes of death.Our primary outcome was all‐cause mortality obtained from death certificates within the UK National Health Service (NHS) Information Center and the NHS Central Register for Scotland. All death certificate details were provided directly to the UKB. Primary cause of death was classified using Demographics included age, sex, ethnicity, and education. Age at baseline assessment was calculated in years based on their dates of birth. Sex (men/women) and ethnicity were self‐reported. Since the majority of participants self‐identified as British or “white” European descent (94%), we included ethnicity as European and non‐European. Education was college‐level (yes/no). For lifestyle factors, we included BMI , alcohol use , and smoking status , physical activity , hypertension, high cholesterol, atrial fibrillation (AF)/arrhythmias, diabetes mellitus, angina, myocardial infarction (MI), and peripheral vascular disease. CVD risk was split into low (no risks factors) and high (≥3 risk factors) for comparison purposes. Other comorbidities indicative of health status included cancer , respiratory diseases , psychiatric history , neurological disorders , musculoskeletal disorders , gastrointestinal disorders , renal disorders , endocrine disorders , hematological disorders , and number of medications taken.t tests for continuous variables and chi‐square tests for categorical variables. We determined the relationship between DistEn and dichotomized baseline variables (age >65 years versus ≤65 years), sex (men versus women), ethnicity (European versus non‐European), college attendance (yes versus no), BMI (>35 versus ≤35), TDI (fourth versus first quartiles), physical activity level (fourth versus first quartiles), CVD risk (high versus low), β‐blocker usage, AF/arrhythmias, and pacemaker presence using multivariable regression. Cox proportional hazards models were used to assess the predictive value of DistEn for all‐cause and cause‐specific mortality: (model A) a core model controlled for demographics; (model B) TDI and lifestyle factors; (model C) cardiovascular risks/diseases; (model D) other comorbidities; and (model E) final adjustment was made for autonomic measures . We also tested for interactions between DistEn and age, sex, and CVD risk factors. Hazards ratios (HRs) and corresponding 95% CIs represent a 1‐SD decrease in DistEn. The proportional hazards assumption was assessed using the global chi‐square test in R package cox.zph  incorporating methods described by Grambsch and Therneau.The characteristics of patients who died versus those who survived during follow‐up were assessed using Baseline characteristics of 7631 participants  are summarized in Table P<0.0001), men , non‐Europeans , low physical activity , and high socioeconomic deprivation (TDI) . The difference in DistEn was larger in patients with BMI >35  and those with the highest cardiovascular risk . DistEn was marginally lower in those taking β‐blockers , but was not different in those with previously reported AF/arrythmias (P=0.68).The median value for DistEn was 0.853  Figure . DiffereP<0.0001], equivalent to the effect of being 5.5 years older at baseline. After adjusting for lifestyle factors , the HR for mortality remained similar (Table P<0.0001]). DistEn remained predictive of mortality after further adjustment for CVDs/risk factors (Table P<0.0001]) and multiple comorbidities (Table P<0.0001]).DistEn was associated with all‐cause mortality using our core Cox proportional hazards model adjusted for demographics  Table ; model Aar Table ; model Brs Table ; model Ces Table ; model DP<0.0001). Full model results are shown in Table After controlling for autonomic‐related variables , DistEn still remained predictive of mortality (Table P<0.0001). We found DistEn to be negatively correlated with RHR  and positively correlated with RMSSD , but had no relationship with MAP (P>0.05). A 10‐bpm increase in RHR , and a 1‐SD decrease in RRI  or RMSSD , were separately predictive of mortality, but none of these associations remained after inclusion of DistEn . Table The mean RHR was 71.3 bpm  and significantly lower in those taking β‐blockers  or respiratory  disease–related; and remained after adjustment for confounders , but this was fully accounted for by inclusion of RHR and HRV measures .Of 451 deaths, the following primary causes were seen: 13.3% (60) cardiovascular, 10.0% (44) respiratory, and 42.8% (193) cancer. In Table P=0.006 for interaction) and prior MI  than those >65 years . Similarly, those with a prior MI  had a larger risk from every 1‐SD decrease in DistEn than those with none . Taken together, these interactions represented a 56% enhanced risk when comparing those <55 years with a history of MI, versus those >65 years without prior MI.We did find a significant interaction effect between DistEn and age , and those having already experienced an MI, is also particularly intriguing. We do note that a similar pattern was also observed for RHROthers have begun to explore heartbeat complexity as a novel approach to assessing cardiac stress reactivity,P values, which become less informative in these situations. The resting ECGs are readily obtained and effect sizes are significant, but whether DistEn can be influenced to make a clinical meaningful impact has yet to be tested. While all participants were conducting similar activities in answering questionnaires before their protocolized ECG recordings, we cannot control for the physical and mental state of the participant, in response to the multitude of mental tasks and recall requested of the participants by the UKB.Despite the strengths of this study, several limitations exist. The interpretation of these results from a clinically meaningful and statistically robust standpoint must be taken. With a large sample size, it can lead to tight CIs, so we have chosen not to make reference only to Resting heartbeat complexity from short, resting ECGs was independently associated with mortality in middle‐ to older‐aged adults. These risks appear most pronounced in middle‐aged patients with prior MI, and may uniquely contribute to routine mortality risk screening. Our findings have the potential to be scaled‐up to remote monitoring in smartwatch applications of beat‐to‐beat heart activity and opens up a new avenue of research for resting heartbeat complexity as a vulnerability marker for stress reactivity.This work was supported by the National Institutes of Health , the Foundation of Anesthesia Education and Research (MRTG‐02‐15‐2020‐Gao to L.G.) and the BrightFocus Foundation (A2020886S to P.L.). UKB is generously supported by its founding funders the Wellcome Trust and UK Medical Research Council, as well as the Department of Health, Scottish Government; the Northwest Regional Development Agency; and the British Heart Foundation and Cancer Research UK.Scheer has received lecture fees from Bayer HealthCare, Sentara HealthCare, Philips, Vanda Pharmaceuticals, and Pfizer Pharmaceuticals. The remaining authors have no disclosures to report.Tables S1–S2Figures S1–S3Click here for additional data file.


Anopheles gambiae sensu stricto (s.s.) from Tulukuyi village, Bungoma, Kenya, with differing permethrin resistance profiles were comparatively characterized.Insecticide resistance poses a growing challenge to malaria vector control in Kenya and around the world. Following evidence of associations between the mosquito microbiota and insecticide resistance, the microbiota of 1 progeny of field-caught An. gambiae s.s. were exposed to five times (107.5 µg/ml) the discriminating dose of permethrin. Post bioassay, 50 resistant and 50 susceptible mosquitoes were subsequently screened for kdr East and West mutations, and individually processed for microbial analysis using high throughput sequencing targeting the universal bacterial and archaeal 16S rRNA gene.Using the CDC bottle bioassay, 133 2–3 day-old, virgin, non-blood fed female Fkdr East and 1 % for kdr West. Overall, 84 bacterial taxa were detected across all mosquito samples, with 36 of these shared between resistant and susceptible mosquitoes. A total of 20 bacterial taxa were unique to the resistant mosquitoes and 28 were unique to the susceptible mosquitoes. There were significant differences in bacterial composition between resistant and susceptible individuals , with presence of Sphingobacterium, Lysinibacillus and Streptococcus , and the radiotolerant Rubrobacter, being significantly associated with resistant mosquitoes. On the other hand, the presence of Myxococcus, was significantly associated with susceptible mosquitoes.47 % of the samples tested (n = 133) were resistant, and of the 100 selected for further processing, 99 % were positive for An. gambiae s.s. associated with intense pyrethroid resistance. The findings highlight differentially abundant bacterial taxa between resistant and susceptible mosquitoes, and further suggest a microbe-mediated mechanism of insecticide resistance in mosquitoes. These results also indicate fixation of the kdr East mutation in this mosquito population, precluding further analysis of its associations with the mosquito microbiota, but presenting the hypothesis that any microbe-mediated mechanism of insecticide resistance would be likely of a metabolic nature. Overall, this study lays initial groundwork for understanding microbe-mediated mechanisms of insecticide resistance in African mosquito vectors of malaria, and potentially identifying novel microbial markers of insecticide resistance that could supplement existing vector surveillance tools.This is the first report of distinct microbiota in  Malaria remains an important global health problem, with 92 % of all deaths occurring in Africa . In KenyAnopheles albimanus across different geographical locations including Peru [Although insecticide resistance is increasingly prevalent , its unding Peru  and Guating Peru , these sing Peru .The mosquito microbiota has been shown to affect mosquito physiology . These mAnopheles stephensi, Anopheles albimanus and Anopheles arabiensis [Anopheles gambiae sensu stricto (s.s.) has, however, largely been unexplored in relation to insecticide resistance. Of particular importance is pyrethroid resistance—a major concern in Kenya, where this class of insecticide is predominantly used in LLINs and IRS [An. gambiae s.s. from an area with intense pyrethroid resistance in Western Kenya. Mosquitoes were also screened for gene mutations that mediate knockdown resistance (kdr) to pyrethroids, in order to characterize any associations between the mosquito microbiota and kdr genotype. We discuss these findings on An. gambiae s.s., and highlight their implications for insecticide resistance monitoring and management.Recent studies on the effects of insecticide exposure on microbes associated with mosquitoes and their habitats have so far focused on abiensis , 18, 19. and IRS , 20, 21.An. gambiae s.s. was the most predominant species in Bungoma and had high resistance levels to pyrethroids. Sampling was performed by aspiration of blood fed and gravid mosquitoes from 39 houses. Mosquitoes were placed in labelled paper cups with information identifying the collection date and collection site. A piece of cotton wool soaked in 10 % w/v sugar solution was placed on top of the netting material covering the paper cup to sustain the collected mosquitoes. The paper cups were then placed in a cool box and transported to the laboratory.Mosquito collections were conducted in April and May 2018 in Tulukuyi village located in Bungoma County 0.56°N 34.56°E 1427 m ASL  in order to standardize rearing conditions and physiological characteristics so as to eliminate any confounding that not standardizing would have introduced—the wild-caught mosquitoes were only used to generate sufficient samples for this standardized design and were not processed beyond species identification. Individual mosquitoes were placed in separate 50 ml falcon tubes containing damp cotton wool topped with filter paper for egg laying. Following egg laying, each adult female was transferred into individual 1.5 ml reaction tubes for molecular species identification (described below). F1 eggs from each isofemale were removed and placed into separate clean larval trays containing distilled water for hatching, while the parents underwent species identification as described below. Following species identification, all larvae from isofemales identified as An. gambiae s. s. were pooled, approximately 200 larvae per tray measuring 46 cm by 35 cm by 5 cm and reared together. Larvae were fed a combination of ground Brewer’s yeast , and Koi’s choice premium fish food  at a ratio of 1:2 for An. gambiae until pupation. Using a dissecting microscope , male and female pupae were separated within 24 hours of pupation in order to obtain virgin adult females. Female pupae were subsequently placed into cages for adult eclosion, while the males were euthanized and discarded. The resulting F1 adult females (~ 377) were sustained on cotton balls soaked in 10 % sugar solution for 2–3 days prior to insecticide susceptibility bioassays. In order to avoid potential confounding factors, all mosquitoes underwent identical standard handling and rearing in the insectary at the Kenya Medical Research Institute -Center for Global Health Research (KEMRI-CGHR), Kisian, Kisumu, under the following conditions: temperature of 27 ± 2 °C, relative humidity of 80 ± 10 %, and photoperiod of 12:12 light: dark cycle.Prior to species identification, forced oviposition was used to generate isofemale F1 progeny. 2 µl of DNA from each individual, along with known An. gambiae s.s. DNA as positive control, were used as templates for the PCR reaction [An. gambiae s.s.) were resolved by ethidium bromide-stained agarose gel 2 % electrophoresis.Using the ethanol precipitation method described by Collins, et al. , genomicreaction . The rea1 virgin, non-blood fed adult females aged 2–3 days were tested for permethrin resistance following the Centers for Disease Control and Prevention (CDC) guidelines for evaluating insecticide resistance [Anopheles). Anopheles gambiae Kisumu susceptible strain of the same age and physiological status were used to confirm the viability of the prepared bottles—all mosquitoes in the insecticide treated bottles died, while those in the acetone-treated bottles survived. Using the F1 progeny, the bioassays were conducted for 30 minutes at the end of which permethrin resistance was recorded. Mosquitoes that were alive after the bioassay were categorized as resistant and subsequently killed by freezing, while those that were dead or moribund were categorized as susceptible. Phenotyped mosquitoes were immediately placed in 1.5 ml Eppendorf tubes with unique identification codes and preserved at − 20 °C for subsequent molecular processing. Mosquitoes from the control bottles were not further processed.A total of 133 Fsistance . The con1 mosquitoes and vortexed at high speed for ~ 10 seconds to surface sterilize the mosquitoes. This was followed by a vigorous rinse using a vortex mixer at high speed for ~ 10 seconds, then a gentle rinse by pipetting for ~ 10 seconds; each with 250 µl of nuclease free water. Genomic DNA from the whole mosquito was isolated and purified using the MasterPure™ Gram Positive DNA Purification Kit following the manufacturer’s instructions . During DNA extraction, four blank controls  and two 1 g soil samples from Kisian (as a distinct source of microbes) were also processed to catch any potential sample processing and cross contamination respectively. Purified DNA samples were stored at − 20 °C for subsequent analysis.250 µl of 70 % ethanol was added to each tube of individual Fkdr-East and kdr -West alleles using DNA from F1 mosquitoes. Following the protocol by Bass, et al. [kdr-East: 95˚C for 10 min then 40 cycles of 95˚C for 10secs and 60˚C for 45 sec. For kdr- West, the cycling conditions were 95˚C for 10 min followed by 40 cycles of 92˚C for 15 sec and 60˚C for 60 sec.RT-PCR was used to detect the presence of both , et al. , samplesTCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG) and 805r (GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC) primers [1 mosquitoes. Four no-template controls (PCR grade water), along with the six controls from the DNA extraction step—two cross-contamination controls (soil samples), and four blanks—were also processed. The PCR reaction mixture  comprised of 10 µl of 2× KAPAHiFi HotStart Mix , 5 µM each of 341f and 805r primers and 5 µl of DNA template which was ≥ 20 ng/µl. Reactions were conducted using the BIO-RAD T100 thermal cycler with the following cycling conditions: 95 °C for 3 min for initial denaturation, followed by 25 cycles of 95 °C for 30 sec, 55 °C for 30 sec, 72 °C for 30 sec and extension at 72 °C for 5 min. The resulting amplicons of ~ 460 bps were purified using Agencourt AMPure XP beads  at 0.87 × sample volume and eluted in 45 µL TE buffer. The purified amplicons including those from blank and cross contamination controls were submitted to the Biotechnology Core Facility at the US Centers for Disease Control and Prevention, Atlanta for library preparation and sequencing.Using the 341f , index primers from Nextera XT Index kit v2 set A, B and D; , and 10–300 ng of each 16S rRNA gene amplicon, along with all controls, as template. PCR thermal cycler conditions were set to: 98 ºC for 30 sec, followed by 8 cycles of 98 ºC for 10 sec, 55 ºC and 65 ºC for 30 sec each, followed by a final extension at 65 ºC for 5 min. The resulting products were cleaned using Agencourt AMPure XP beads at 1.2 × volume of each library. These were subsequently analysed for size and concentration, normalized and pooled at a final concentration of 2 nM. The pool was denatured using Illumina guidelines for loading onto flow cell for cluster generation, and sequencing was performed on an Illumina Miseq using Miseq 2 × 250 cycle paired-end sequencing kits. The resulting sequence reads were filtered for read quality, basecalled and demultiplexed using bcl2fastq (v2.19.1).Resulting raw paired-end sequencing reads were demultiplexed and imported into the Quantitative Insights Into Microbial Ecology (QIIME) 2 pipeline v.2018.11  for analAlpha and beta diversity indices  were comBray-Curtis dissimilarity beta diversity index, a quantitative measure used to determine compositional dissimilarity of features between samples, was also computed using the q2-diversity plugin. The Bray-Curtis dissimilarity matrices were computed using both rarefied (to a sampling depth of 100 ASVs per sample as described above) and unrarefied ASVs. Both resulted in significant differences between the microbiota of resistant and susceptible mosquitoes . With default parameters, an alpha value of 0.05 was used for both the factorial Kruskal-Wallis and pairwise Wilcoxon tests within LEfSe, and a threshold value of > 2 was used on the resulting logarithmic LDA score to identify differentially abundant ASVs. The effect sizes of differentially abundant ASVs were visualized as bar plots.The linear discriminant analysis (LDA) effect size method (LEfSe)  was usedThe analysis of composition of microbiome method, ANCOM , was use1 female An. gambiae s.s. were tested for resistance to permethrin using 5 × (107.5 µg/ml) the discriminating dose (21.5 µg/ml) of the insecticide, and 52.6 % of the samples tested were found to be susceptible. One hundred of the screened samples (50 resistant and 50 susceptible) were subsequently processed for characterizing the microbiota and kdr allele frequencies. Of all 100 samples, 99 % had the kdr east (Vgsc_1014S) mutation and the remaining one had the kdr west (Vgsc_1014F) gene mutation. This high frequency of kdr east mutation indicated fixation in the mosquito population and thus precluded further correlation analysis between microbial composition and kdr allele frequencies. Microbial community characterization of all 100 samples yielded 4,319,065 raw sequencing reads, in addition to 5,226 raw reads from blank and cross-contamination controls . This heterogeneity in microbial community structure associated with insecticide resistance status was further illustrated by principal coordinates analysis (PCoA), in which the microbiota of susceptible samples clustered closely together and away from those of primarily dispersed resistant samples  , Enterobacter (7.25 %), Acinetobacter (3.88 %), Klebsiella (3.84 %), an uncharacterized Enterobacteriaceae (3.30 %), and Lysinibacillus (3.27 %), together accounting for more than 55 % of ASVs . The six most dominant genera among resistant mosquitoes were Lysinibacillus (13.97 %), Pseudomonas (11.95 %), Acinetobacter (8.54 %), Thorsellia (6.49 %), Asaia (4.23 %) and Bacillus (4.08 %). On the other hand, 21 genera were only found in the susceptible mosquito samples including Marmoricola, Roseomonas, Dyadobacter, Lactococcus, and Myxococcus, among others. Among susceptible mosquitoes, Asaia was the most dominant, with a relative abundance of 48.76 % followed by Enterobacter (9.23 %), Klebsiella (4.41 %), Enterococcus (3.63 %) and Acinetobacter (2.45 %).The most abundant bacterial taxa across all samples were those assigned to acter 7.2 %, AcineRubrobacter which was detected at low abundance in 20 of the 39 permethrin resistant samples and only in two susceptible mosquito samples, also at low levels of abundance. Similarly, ASVs assigned to unclassified Rhodospirillales (JG37-AG-20) and unclassified Obscuribacteriales were detected in 18 and 9 resistant mosquitoes, respectively, but only in 1 and 4 susceptible mosquitoes, respectively. ASVs assigned to the genera Streptococcus, Thermomonas, Sphingobacterium, Ornithinimicrobium and Lysinibacillus were detected in more permethrin resistant samples compared to the susceptible samples  also revealed significant differences in microbiota composition between susceptible and resistant mosquitoes. Focusing on the genus level, four bacterial genera, oes Fig. . The firoes Fig. . On the les Fig. ; this geles Fig. . Althougles Fig. , LEfSe hRubrobacter (W = 51) and unclassified Rhodospirillales (JG37-AG-20) (W = 63) as significantly more abundant in resistant compared to susceptible samples  W = 3 as signAn. stephensi, An. arabiensis and An. albimanus have shown links between mosquito-associated microbiota and resistance to pyrethroids and organophosphates [1 progeny of field-derived An. gambiae s.s. were comparatively characterized. Results showed significant differences in microbiota composition between resistant and susceptible mosquitoes with enrichment of different bacterial taxa between resistant and susceptible mosquitoes.Recently, studies of osphates , 18, 19.kdr east allele in the F1 progeny originating from Tulukuyi, Western Kenya. These findings corroborate earlier reports of high pyrethroid resistance in the same area [kdr east allele suggests that the mutation is fixed in this mosquito population. Other studies conducted in western Kenya have also reported the presence of high kdr east allele frequencies which is attributed to the continued use of insecticide–based vector control methods [kdr in conferring the intense permethrin resistance detected in the population. The fixation of the kdr east mutation in the population also precluded further analysis of any associations between kdr alleles and the mosquito microbiota. Indeed, a recent study identified no links between the two [Intense resistance (at 5× the diagnostic dose) to permethrin was detected, along with high frequency (99.14 %) of the ame area , 20. Mulame area . The hig methods –40. Howe methods ), are mo the two . The autAn. gambiae s.s. samples, a majority of which have previously been identified in Anopheles and other mosquito genera including Aedes aegypti [Results showed diverse bacterial taxa from individual  aegypti –46. HoweAn. gambiae s.s. were also shown. There is evidence that insecticide detoxifying microbes in agricultural insect pests contribute to insecticide resistance in their hosts [An. albimanus microbiota differed by resistance to fenitrothion and was altered by exposure to different pyrethroids, and Aedes aegypti microbiota differed by resistance to lambda-cyhalothrin [An. albimanus that were exposed or resistant to insecticides. Huang et al. [versus susceptible mosquitoes, particularly those of resistant mosquitoes, is suggestive of this type of adaptation.Significant differences in microbiota composition and structure between permethrin resistant and susceptible ir hosts , 48. Recalothrin , 10, 49.g et al.  and Tangg et al.  documentg et al. . The dif1 progeny of wild adult females collected from the same location and reared under identical conditions. Except for their permethrin resistance status, which was determined at 2–3 days post adult eclosion, the mosquitoes had identical physiological characteristics. These identical rearing conditions and subsequent uniform physiological characteristics may explain the homogeneity in alpha diversity across samples. On the other hand, the differences in microbial composition associated with their permethrin resistance status provide further evidence of insecticide selection pressure on the mosquito microbiota. Previous studies have shown that a majority of the mosquito microbiota is obtained from mosquito aquatic habitats at the larval stage, and also from food sources as adults [Despite significant differences in microbiota composition and structure (beta diversity), there was no significant difference in alpha (Shannon) diversity between the microbiota of resistant and susceptible mosquitoes. This is suggestive of a homeostatic-controlled number of microbial taxa across individual mosquitoes, with an insecticide resistance-associated perturbation of the type and relative abundance of specific microbial taxa. Mosquitoes used in this study were Fs adults . Newly es adults . Howevers adults , 52, 53 Sphingobacterium, Lysinibacillus, Streptococcus and Rubrobacter as significantly more abundant in resistant mosquitoes and Myxococcus as significantly more abundant in susceptible mosquitoes. The first three genera were only detected in resistant mosquitoes, while Rubrobacter was at least three-fold more abundant in resistant compared to susceptible mosquitoes. In a study conducted by Hu et al. [Lysinibacillus sphaericus was identified as a microbe with the ability to degrade up to 83 % of cyfluthrin (a pyrethroid) after 5 days of incubation by utilizing the insecticide as its source of carbon or nitrogen. In the current study, Lysinibacillus was only detected in resistant mosquitoes, likely as a result of its ability to utilize pyrethroids. Lozano and Dussán [Lysinibacillus sphaericus to be used in bioremediation of heavy metals. Sphingobacterium and Streptococcus, also only detected in resistant mosquitoes in this study, are bacterial genera known to degrade pyrethroid insecticides such as cypermethrin [Streptococcus and Rubrobacter have been categorized as core microbiota of the digestive system of Anopheles culicifacies [Rubrobacter are known to be thermophilic and extremely resistant to UV thermal and gamma radiations [Actinobacteria, the phylum to which Rubrobacter belongs, have been associated with degradation of insecticides including pyrethroids [Rubrobacter in insecticide resistant mosquitoes could suggest their contribution to resistance. On the other hand, the genus Myxococcus was only detected in susceptible mosquitoes. This bacterial genus is known to be predatory on other bacteria [Myxococcus and their secondary metabolites on mosquito physiology, including insecticide susceptibility.Differential abundance testing identified u et al. , Lysinibd Dussán  also desrmethrin –58. Bactcifacies . Althougdiations . Other bethroids , 62, andbacteria , chitinabacteria , capablebacteria , and inhbacteria . HoweverAe. aegypti it has been demonstrated that infections with certain microbes precludes colonization by others [In an aquatic microcosm, it has been demonstrated that insecticides, if used singly or in combination, can reduce microbial diversity and/or induce shifts in microbial community structure . Recent y others , and thay others , 70. Fury others , 67.1 progeny of field-collected An. gambiae s.s. from Tulukuyi, Bungoma, western Kenya was detected. This was accompanied by a high frequency of (> 99 %) of the kdr east allele, suggesting fixation in the population. These results also show, for the first time, significant differences in microbiota composition between permethrin resistant and susceptible An. gambiae s.s. These findings corroborate results of previous research on other Anopheles species from different geographic locations. The abundance of Rubrobacter, Lysinibacillus, Sphingobacterium and Streptococcus were associated with resistant mosquitoes, while the abundance of Myxococcus was associated with susceptible mosquitoes. The enrichment of these specific bacterial taxa highlights the potential for discovering novel microbial markers of insecticide resistance that could complement existing insecticide resistance surveillance tools. With this increasing evidence of associations between mosquito microbiota and insecticide resistance, future work will evaluate the underlying microbial mechanisms of insecticide resistance.In this study, intense permethrin resistance in FAdditional file 1. Comparison of Bray curtis dissimillarity indices between the microbiota of permethrin resistant and susceptible individuals using rarefied and unrarefeid data.Additional file 2. Shannon diversity indices.Additional file 3. Taxonomic annotation and frequency of ASVs from permethrin resistant and sucseptible samples.Additional file 4. ANCOM statistical results.Additional file 5. Summary statistics of raw sequencing outputs and resulting data following quality control and filtering.Additional file 6. Shannon alpha diversity index rarefaction curves.


Dopamine loss beyond the mesostriatal system might be relevant in pathogenic mechanisms and some clinical manifestations in PD. The primate thalamus is densely and heterogeneously innervated with dopaminergic axons, most of which express the dopamine transporter, as does the nigrostriatal system. We hypothesized that dopamine depletion may be present in the thalamus of the parkinsonian brain and set out to ascertain possible regional differences.The toxin 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine was administered to adult macaque monkeys using a slow intoxication protocol. The treated macaques were classified into 2 groups according to their motor status: nonsymptomatic and parkinsonian. Dopamine innervation was studied with immunohistochemistry for the dopamine transporter. Topographic maps of the dopamine transporter‐immunoreactive axon distribution were generated and the total length and length density of these axons stereologically estimated using a 3‐dimensional fractionator.Parkinsonian macaques exhibited lower dopamine transporter‐immunoreactive axon length density than controls in mediodorsal and centromedian‐parafascicular nuclei. Dopamine denervation in the mediodorsal nucleus was already noticeable in nonsymptomatic macaques and was even greater in parkinsonian macaques. Reticular nucleus dopamine transporter‐immunoreactive axon length density presented an inverse pattern, increasing progressively to the maximum density seen in parkinsonian macaques. No changes were observed in ventral thalamic nuclei. Dopamine transporter‐immunoreactive axon maps supported the quantitative findings.Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.Changes in the dopamine innervation of various thalamic nuclei are heterogeneous and start in the premotor parkinsonian stage. These changes may be involved in some poorly understood nonmotor manifestations of PD. © 2019 The Authors.  The primate thalamus is densely innervated by dopaminergic axons.Dopamine loss in PD has been reported in regions beyond the mesostriatal system, including the globus pallidus, subthalamic nucleus, and motor cortex.The thalamus is the only target of basal ganglia outflow to the cortex,Here, we explored the distribution and density of dopamine transporter‐immunoreactive (DAT‐ir) axons in the thalamus of parkinsonian macaques using a model of slow progressive dopamine depletion. DAT is the relevant dopamine marker to be analyzed in the thalamus of parkinsonian macaques: not only is it specific and expressed by the majority of dopaminergic axons in nonmidline nuclei, but the axons expressing DAT are most vulnerable in PD and MPTP‐induced parkinsonism.Macaca fascicularis previously studied to stage the degree and extent of the nigrostriatal lesion.The present study used brain tissue from our macaque monkey brain bank. We used tissue from 20 brains of young l‐dopa or dopamine agonists during the experiment. Animals were evaluated by the research team after each MPTP dose and while the parkinsonian syndrome was progressing until complete stabilization. Motor signs were assessed through the validated Kurlan motor score .Sixteen macaques aged 4–7 years were treated every 2 weeks with intravenous doses of MPTP (0.5 mg/kg).recovered.Macaques that exhibited evident parkinsonian signs after the last MPTP injection and that remained affected thereafter until sacrifice were classified as parkinsonian . Macaques that maintained normal motor features after the last MPTP dose were considered nonsymptomatic (n = 8); see Supporting Table See Supporting Appendix High‐resolution maps of DAT‐ir axons were generated through a mosaic of 20× magnification pictures taken on a Zeiss Axioskop microscope  equipped with a digital camera , using Neurolucida software . HighPass and Kodalith filters of this software were used to enhance axon‐background contrast  using the spaceball stereological approach.U test). The correlation calculation of DAT‐ir axon length density with earlier data from the same experimental subjectsP < 0.05. Data from 1 control macaque (M2) and data for the R nucleus from 1 parkinsonian macaque (M17) were excluded because of insufficient tissue sections for optimal stereological study. Outliers were included in the statistical analysis. Mean and standard error the mean are used throughout the text, and median and interquartile range are used in the box‐plot graphic representations.Statistics were performed with SPSS software  and R Studio. Because the data from our experimental groups (n = 4–8) were not normally distributed, all comparisons were made using nonparametric statistical tests  followed by the ventral nuclei (0.76 ± 0.31 m of DAT‐ir axons/mm3). CnMd‐Pf and R had low densities of DAT‐ir axons ; see Figure DAT‐ir axon length density varied in the different nuclei. The highest length density was present in MD  and by 48% in parkinsonian macaques . DAT‐ir axon length density in CnMd‐Pf was 43% lower in parkinsonian macaques compared with controls (P = 0.04) and 38% lower in parkinsonian macaques compared with nonsymptomatic macaques  and A10 ; see Figure R2 = 0.26; P = 0.01) and A10 ; see Figure Correlation analyses were performed between DAT‐ir axon length density in the thalamic nuclei, number of mesencephalic dopaminergic neurons, DAT innervation in the striatum, and motor status of the same macaques.This study provides the first demonstration of widespread changes in the thalamic dopaminergic system in slowly and progressively induced MPTP‐parkinsonism in macaques. We found a decrease in thalamic dopaminergic innervation in MD and CnMd‐Pf that was correlated with the loss of mesencephalic dopaminergic TH+ neurons. We also have shown an unexpected increase in dopaminergic axons in the R nucleus. Changes occurred in all MPTP‐treated macaques, whether nonsymptomatic or symptomatic, but were more overt and intense in the symptomatic parkinsonian macaques.The stereological method used here allows rigorous quantitative length and volume analyses that do not depend on presumptions about the shape, size, or randomness of the objects under study.DAT‐ir axon length density declines across MD in nonsymptomatic macaques, and the decline is more pronounced in parkinsonian macaques Fig. A. In addRegarding the thalamic nuclei integrated in the basal ganglia motor circuitry, only the parkinsonian macaques showed decreased DAT‐ir axon length density in CnMd‐Pf. This decline in DAT‐ir axon length density Fig. B correlaThe decrease of DAT‐ir axon length density in MD and CnMd‐Pf could be because of degeneration of DAT‐ir axons or of phenotype modifications in dysfunctional dopaminergic neurons, as previously suggested for the loss of TH and DAT axons in the striatum of PD patients.new branches on DAT‐ir axons of the R nucleus in our MPTP‐treated macaques. This is unlike the changes in dopamine axon morphology reported in the striatum of MPTP‐treated monkeys.The finding of increased DAT‐ir axon length density in R was unexpected. DAT‐ir axon length density in R does not correlate with the number of TH+ neurons,Although changes in the dopamine innervation of the thalamus in the parkinsonian brain have never been reported in as much detail as here, our findings concur with previous data in the literature on MPTP monkeys and humans with PD.Biochemical studies using chromatography in the thalamus of MPTP‐treated macaques have provided inconclusive data.The dopamine depletion in MD, although widespread, predominantly involves dorsal regions of this nucleus Figs. A,B,D–H. The CnMd‐Pf complex has been implicated in PD pathophysiology and suggested as a possible target for functional neurosurgery.Changes in dopamine innervation of R deserve comment. R is an inhibitory nucleus that receives nonreciprocal projections from the cortex and subcortical structures and is reciprocally connected with all thalamic nuclei; each region of R is connected with a set of thalamic nuclei.Full understanding of changes in thalamic dopaminergic transmission in PD and PD models requires additional studies on potential changes in dopamine receptors and dopamine synaptic function, as well as on their impact on the thalamocortical circuits involved.This study gives evidence of well‐defined and specific changes in thalamic dopamine innervation in nonsymptomatic and symptomatic MPTP‐treated macaques. Interestingly, MD and CnMd‐Pf nuclei sustain marked dopamine denervation, whereas R exhibits hyperinnervation. Thus, the present findings reveal yet another nonstriatal site, the thalamus, in which dopamine changes may affect brain function in the presymptomatic and symptomatic phases of parkinsonism. We speculate that changes in thalamic dopamine innervation may contribute to the pathophysiology of some ill‐understood manifestations of the parkinsonian state such as attention and executive deficits and sleep impairment.M.H.G.M.: 1A–C, 2A–C, 3A,B.J.B.: 1A–C, 2C, 3B.M.A.G.C.: 1A–C, 2C, 3B.J.A.O.: 1A,B, 2C, 3B.C.C.: 1A–C, 2C, 3B.1) Research project: A. conception, B. organization, C. execution; 2) statistical analysis: A. design, B. execution, C. review and critique; 3) manuscript: A. writing of the first draft, B. review and critique.M.H.G.M. is an employee of the Autonomous University of Madrid and HM‐Puerta del Sur University Hospital. J.B. is currently funded by grant S2017/BMD‐3700 (NEUROMETAB‐CM) from Comunidad de Madrid co‐financed with the Structural Funds of the European Union, Fundación BBVA and Fundación Tatiana Pérez de Guzmán el Bueno. M.Á.G.C. is an employee of the Neural Systems Laboratory, Department of Health Sciences, Boston University. J.A.O. is funded from the Ministry of Science and Education of Spain, Fundación La Caixa and CIBERNED; has received honorarium for lecturing in meetings organized by BIAL, Zambon, and Boston Scientific in Spain, as member of Insightec's advisory board, and as member of the Adverse Event Committee for the Biogen randomized immunotherapy trial. C.C. is an employee of the Autonomous University of Madrid and is funded by the Chair UAM‐Fundación Tatiana Pérez de Guzmán el Bueno.TABLE S1. Macaque monkey features, number of MPTP injections, parkinsonian scores, and survival after MPTP.TABLE S2. Stereological estimations. Total DAT+ axon length, nucleus volume, and DAT+ axon length density of each macaque and nucleus analyzed.FIG. S1. DAT‐ir axon map generation and stereological method. High‐resolution maps of DAT‐ir axons were generated through a mosaic of 20× magnification pictures (A). HighPass (B) and Kodalith (C) filters were used to enhance axon‐background contrast. Stereological images . The hemispherical probe used as a method of length estimation (D). The gray arrow represents the thickness of the section, the red arrow represents the radius of the hemisphere, and the green arrow, the upper guard area. Axons are depicted in brown (D). Microphotographs of a sampling point (E) from top to bottom. The distance between each image is 1 μm on the Z axis, from the top (1) to bottom (14) of the section. The white circles represent consecutive perimeters of the hemisphere. The red arrowhead  indicates the intersection of a DAT‐ir axon with the hemisphere. The calibration bar applies to all images.FIG. S2 Correlation matrix. Correlation matrix between motor scale, DAT‐ir axon length density in mediodorsal (MD DAT+), centromedian‐parafascicular (CnMd‐Pf DAT+), ventral ,and reticular (R DAT+) nuclei, as well as the dopaminergic innervation of the striatum analyzed by optical density (Str DAT OD) and the numbers of mesencephalic dopaminergic neurons . The color code is on the bar to the right, which gives the correlation scores from ‐1 to 1.Appendix 1. Material and Methods. Brain ProcessingAfter being stable for several weeks in the corresponding motor state, the macaques were deeply anesthetized with intraperitoneal sodium pentobarbital (10 mg/kg). Saline was perfused through the ascending aorta, followed by 4% paraformaldehyde in phosphate buffer (PB) and a series of PB sucrose solutions of increasing concentrations (5%‐10%‐20%). One hemisphere of each brain was stereotaxically blocked in the sagittal plane. Brain blocks were cryoprotected in 30% sucrose for about two weeks under gentle movement at 4° C until sunk. Then, 40 μm parasagittal sections were obtained using a freezing microtome.Appendix 2. Results. Correlation analysesP = 0.006), optical density in the striatum , and number of TH+ neurons in mesencephalic dopaminergic groups A8, A9, and A10 . DAT‐ir axon length density in the CnMd‐Pf complex correlated with motor scale , and DAT optical density in the striatum . In addition, significant correlations were found between DAT‐ir axon length density in CnMd‐Pf and the numbers of TH+ neurons in A9 and A10 , but not with the number of TH+ neurons in A8. In R nucleus, DAT‐ir axon length density did not correlate with motor scale score or DAT optical density in the striatum, but it was correlated with the number of TH+ neurons in group A8 .In MD, DAT‐ir axon length density significantly correlated with motor scale (rho = ‐0.62, Click here for additional data file.


Surgical procedure usually causes serious postoperative pain and poor postoperative pain management negatively affects quality of life, function and recovery time. We aimed to investigate the role of wound infiltration with ropivacaine as an adjuvant to patient controlled analgesia (PCA) in postoperative pain control for patients undergoing transforaminal lumbar interbody fusion.One hundred twelve patients undergoing lumbar fusion were retrospectively reviewed and divided into two groups (ropivacaine and control groups) according to whether received wound infiltration with ropivacaine or not. Visual Analogue Scale (VAS) score, analgesics consumption, number of patients requiring rescue analgesic, hospital duration and incidence of complications were recorded. Surgical trauma was assessed using operation time, intraoperative blood loss and incision length.P < 0.001) and similar results were observed at 8, 12, 24, 48 and 72 h postoperatively(P < 0.001). Fewer patients required rescue analgesia within 4 to 8 h postoperatively in ropivacaine group . Length of postoperative hospital durations were shorter in patients receiving ropivacaine infiltration compared to control cohorts . The incidence of PONV in ropivacaine group was lower than that in control group . However, VAS scores were similar in two groups at each follow-up points postoperatively, and no difference was observed(P > 0.05).The amount of sufentanil consumption in ropivacaine group at 4 h postoperatively was lower than that of control group (24.5 ± 6.0 μg vs 32.1 ± 7.0 μg, Wound infiltration with ropivacaine effectively reduces postoperative opioid consumption and PONV and may be a useful adjuvant to PCA to improve recovery for patients undergoing lumbar spine surgery. Transforaminal lumbar interbody fusion (TLIF) has been widely used in treatment of lumbar degenerative spine disorders, and achieved good clinical results and high patient satisfaction , 2. It cTraditionally, patient-controlled analgesia (PCA) has been identified as effective in postoperative pain management and is the most frequently used analgesic method for spine surgery , 5. HoweIn recent years, wound infiltration with local anesthetics has become an attractive method in postoperative analgesia because of its safety, simplicity and low-cost , 8. As aWith the ideal analgesic modality for lumbar fusion surgery still unknown and possibly simpler alternatives to local infiltration analgesia gaining popularity, it is imperative to clarify the role of wound infiltration with ropivacaine in managing postoperative pain after this procedure. We hypothesized that wound infiltration with ropivacaine as an adjuvant to PCA for patients undergoing TLIF is more effective than PCA alone, resulting in lower postoperative pain scores, less consumption of opioid medications and lower incidence of postoperative nausea and vomiting (PONV) compared with PCA alone.This retrospective cohort study was conducted in Liaocheng People’s Hospital. All patients were identified to undergo single-level TLIF procedure with a single surgeon between January 2016 and December 2018. The inclusion criteria were as follow: age 18–65 years, primary diagnosis of lumbar disc herniation, lumbar spinal stenosis and lumbar degenerative spondylolisthesis (grade 1), single level TLIF , American Society of Anesthesiologists (ASA) grade I to II. Patients were excluded according to the exclusion criteria: allergic to ropivacaine, preoperative opioid consumption in last 3 months, and history of spine surgery.Enrolled patients were divided into two groups, ropivacaine group and control group. Each patient provided written informed consent before enrollment. The study was approved by the Ethics Committee of Liaocheng People’s Hospital.The procedure was performed as described by Ge . All proJust before closure, 10 ml ropivacaine (concentration: 0.75%) was infiltrated in paravertebral muscles, subcutaneous, and cutaneous tissue along each side of the wound edges. At the end of surgery, patients were turned to supine position, and extubated successfully on the table. Once awake and responded to verbal commands, patients were transferred to the post-anesthesia care unit (PACU). After PACU, patients were transferred to spine ward for further monitoring and recovery care.All patients received intravenous PCA with 0.8 μg/ml of sufentanil for 72 h. The sufentanil was administrated via PCA pump at a bolus of 2 ml (1.6μg) with a 5 min lockout time and the maximum dosage was 12.8μg per hour. Flurbiprofen axetil was injected as a rescue analgesic when requested by patients with visual analogue scale (VAS) scores≥5.Patients were routinely administered prophylactic antibiotics for 24 h and encouraged to start out-of-bed activities with braces within 3 days after surgery. Mechanical thomboprophylaxis was given to prevent phlebothrombosis of both legs. Since discharge from the hospital, all patients were clinically and radiologically assessed in outpatient clinic every 3 months.Primary outcome was total sufentanil consumption over the first 72 h. The sufentanil consumption can be calculated by multiplying the volume by the concentration . The volume of saline was shown in the PCA pump. Secondary outcome measures were VAS scores, number of patients requiring flurbiprofen axetil as analgesic rescue and incidence of complications including PONV and wound infection. Operation time, intraoperative blood loss, incision length and length of postoperative hospital duration were also recorded in the data.p = 0.05). For the secondary outcome of VAS score, sample size estimates were also considered. On the basis of the data from clinical practice and the study by Elder et al. [n = 50, σ = 16, δ = 10, α = 0.05). The sample size and power analysis were performed using Power and Sample Size Calculation version 3.1.6.The sample size was determined for the primary outcome measure. According to previous study , a differ et al. , the star et al. , 15 and P value < 0.05 was considered statistically significant.The SPSS 22.0 statistical package  was used for statistical analyses. Continuous data were presented as the mean ± standard deviation and analyzed using two-sample t test and ANOVA analysis. Chi square test was performed to analyze count data. For all analyses, a This clinical trial enrolled 112 patients undergoing single-level TLIF procedure, 60 patients who received wound infiltration with ropivacaine in ropivacaine group and 52 without ropivacaine infiltration in control group. Patients’ demographics and basic characteristics, including age, gender, weight, height, body mass index (BMI), primary diagnosis and operation level were shown in the Table P = 0.26). There was also no difference in incision length and intraoperative blood loss between two groups (P = 0.299 and P = 0.314)  , and significant difference was detected between two groups P = 0.05 (Table P < 0.001). Significant difference was also found in the cumulative sufentanil consumption between two groups at 8, 12, 24, 48 and 72 h after surgery (P < 0.001).The amount of sufentanil consumption at 4 h postoperatively in ropivacaine group was lower than that in control group (P < 0.001). Similar results were observed within 8 to12 hours and 12 to 24 h postoperatively (P < 0.001 and P = 0.001). However, no difference was detected within 24 to 48 h and 48 to 72 h postoperatively (P = 0.276 and P = 0.547) . However, fewer patients in ropivacaine group needed analgesic rescue within 4 to 8 h postoperatively compared to control group (P = 0.017). Within 8 to 12 h postoperatively, no difference was found between two groups (P = 0.101) . Similar results were shown between the ropivacaine and control groups at 8 h , 12 h , 24 h , 48 h  and 72 h  postoperatively . Only one patient had wound infection in each group and no difference was detected (P = 0.919, Table The incidence of PONV in the ropivacaine group was lower than that in the control group (18.3% vs 40.4%, In this study, we adopted wound infiltration with ropivacaine as an adjuvant to PCA in TLIF procedure to assess its efficacy in postoperative pain management. Results showed better outcomes in patients who received the wound infiltration with ropivacaine. It reduced the consumption of opioid drugs via PCA after TLIF procedure and decreased the number of patients who required rescue analgesia, while achieving similar pain relief. The data further indicated a lower incidence of PONV and a shorter hospital duration in the ropivacaine group.Currently, PCA is the most widely used approach to manage postoperative pain after spine surgery. However, the use of opioids in PCA is often associated with adverse effects. So multimodal pain management is recommended in order to reduce opioid-related adverse effects. Since Mullen and Cook first demonstrated the use of wound infiltration with local anesthetics in spine surgery in 1979 , a few lThe main outcome measures in this study were visual analogue pain score and opioid usage. In the current study, results showed patients receiving ropivacaine infiltration reported similar VAS scores and less sufentanil consumption via PCA at each follow-up point within 72 h after surgery, which was not completely consistent with previous reports. Although similar VAS score was reported in two groups, less opioid use was another important indicator that reflected the decreased postoperative pain in ropivacaine group. We further found that periodic consumption of sufentanil in the ropivacaine patients was less than that of the control group only within 24 h postoperatively. We attributed this to that the single dose of ropivacaine was injected in our study and its duration acted within 24 h . This alThere are multiple choices for local anesthetic. Bupivacaine and ropivacaine are commonly used after surgery, but ropivacaine is reported to have a lower risk of cardiovascular or central nervous system toxicity . Elder  used an PONV is a common side effect of opioid-based intravenous PCA. Previous studies reported that a logarithmic dose response relationship between the use of postoperative opioids and PONV , 25. TheEffective pain management is now recognized as one of the three fundamental aspects of enhanced recovery after surgery . In thisThere are some limitations to this study, which may impair the ability to assess the effect of wound infiltration with ropivacaine on postoperative pain management. First, this was a retrospective cohort study in a single center, not randomized and blind, which may introduce the possibility of selection bias. Second, we did not analyze the difference of time to administrate rescue analgesic. Moreover, this study enrolled a small patient population. In the future, prospectively randomized controlled study, including more patients in multi-center will be performed to properly evaluate the role of wound infiltration with ropivacaine as an adjuvant to PCA in postoperative pain management.Results of this study indicate that wound infiltration with ropivacaine effectively reduces postoperative opioid consumption and PONV and may be a useful adjuvant to PCA to improve recovery for patients undergoing lumbar spine surgery.


Non‐pharmacological interventions are recommended for the treatment of challenging behaviours in individuals with intellectual disabilities by clinical guidelines. However, evidence for their effectiveness is ambiguous. The aim of the current meta‐analysis is to update the existing evidence, to investigate long‐term outcome, and to examine whether intervention type, delivery mode, and study design were associated with differences in effectiveness.An electronic search was conducted using the databases Medline, Eric, PsychINFO and Cinahl. Studies with experimental or quasi‐experimental designs were included. We performed an overall random‐effect meta‐analysis and subgroup analyses.d = 0.573, 95% CI [0.352–0.795]), and this effect appears to be longlasting. Interventions combining mindfulness and behavioural techniques showed to be more effective than other interventions. However, this result should be interpreted with care due to possible overestimation of the subgroup analysis. No differences in effectiveness were found across assessment times, delivery modes or study designs.We found a significant moderate overall effect of non‐pharmacological interventions on challenging behaviours (Non‐pharmacological interventions appear to be moderately effective on the short and long term in reducing challenging behaviours in adults with intellectual disabilities. Furthermore, we aimed to investigate whether study design (i.e. randomised versus non‐randomised) was related to differences in outcome.22.1https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=51263). We included studies that 1) reported on the evaluation of one or more non‐pharmacological intervention(s), primarily aimed at reducing or eliminating challenging behaviours of adults with intellectual disabilities (regardless of other diagnoses); 2) included a sample with at least 75% of participants of 18 years or older; 3) used an experimental design  or quasi‐experimental design (pretest‐posttest or controlled study) with at least 15 participants; 4) were English‐written; 5) were published in an academic, peer‐reviewed journal; 6) contained sufficient data to perform meta‐analyses .The current meta‐analysis was registered at PROSPERO . The following study characteristics were recorded from the included studies: 1) participant characteristics ; 2) intervention characteristics ; 3) number of participants, comparison groups, and design; and 4) outcome measures.The first author  screened all search results on their eligibility in a three‐step process: screening based on the title, based on the abstract, and based on the full text paper. The excluded articles were checked by the last author  and disagreement was resolved through consensus. If agreement could not be achieved, the second author  was consulted. Data extraction was done by the first author. In case data were insufficiently described in the paper, authors were contacted by e‐mail or through Researchgate (All included studies were assessed by the first author (EB) on potential sources of bias: random sequence, allocation concealment, blinding of outcome assessment, incomplete outcome data, selective reporting, group similarity at baseline, and personal or financial gain . A Cohen's d of 0.2 was considered small, 0.5 moderate, and 0.8 large  if a study contained multiple parameters measuring different challenging behaviours, we used a summarised measure for the calculation of an overall challenging behaviours measure ; 3) if a studied intervention resulted in significant improvement of behaviours, the direction of the effect was stated positive; 4) data were standardised by post score standard deviations (SD); and 5) in case of multiple follow‐up time points, these were computed together as a single measure. We conducted a sensitivity analysis using ‘one study removed analyses’  ABA or behavioural interventions, 2) cognitive behavioural therapy (CBT), 3) interventions combining mindfulness and behavioural techniques, 4) multisensory therapy, and 5) specialised teams using personalised treatment plans ). All categories (i.e. intervention type) were compared on effectiveness. In the third and fourth subgroup analyses we compared interventions directly aimed at the individual with environment mediated interventions, and RCTs with non‐RCTs, respectively.Finally, to examine possible publication bias we generated a funnel plot  and intervention characteristics  is presented in Table We solely used the keyworkers data of the Aberrant Behavior Checklist. Namely, the majority of included papers used keyworkers /staff members as informants. Additionally, some data of the home carers were missing.Figure 3.2d = .573, P < .001, CI ). The individual and combined effect sizes, lower limits, upper limits, z‐values and p‐values are presented in Figure I2 = 91.40%). The sensitivity analyses showed that the effect sizes varied between 0.491 and 0.666. These values fall within the range of the confidence interval of the overall effect size, indicating that our results were robust.The random‐effects model showed an overall treatment effect with a moderate effect size . There was however a significantly higher effect of interventions combining mindfulness and behavioural techniques than of all other intervention types . There were no significant differences between behavioural interventions versus all other intervention types , or CBT versus all other intervention typers . Furthermore, we found no significant differences between individual interventions ersus environment mediated interventions , and RCTs controlled designs versus non‐RCTs designs .We found no significant differences between post‐intervention assessments versus follow‐up assessments , suggesting that treatment effects of non‐pharmacological interventions sustain after the intervention has ended. However, we must be cautious with the interpretation and implications of this finding, as the measures of post intervention assessments and follow‐up assessments are not independent from eachother. To our knowledge, there have been no earlier studies that have compared post‐intervention effects with follow‐up effects. Currently, in clinical practice, pharmacological treatments, instead of non‐pharmacolocial interventions, are often the first treatment of choice  and non‐RCTs (n = 11) was more even than in earlier ones . The exclusion of approximately a third of the eligible papers increased the risk of bias and may have affected our results. Second, we did not include single‐case studies in our meta‐analysis. This resulted in a loss of papers, especially from earlier research on interventions for challenging behaviours within the population of individuals with intellectual disabilities. However, we chose to include only studies with experimental or quasi‐experimental designs, in order to update and build upon previous meta‐analyses of studies using these kind of designs .