The objective of the study was the analysis of adherence and self‐perceived treatment response to long‐term botulinum neurotoxin type A (BoNT‐A) treatment in different neurological indications.In this retrospective, monocentric, observational study, cross‐sectional and longitudinal data of 1351 patients documenting 20705 injection appointments at the BoNT outpatient clinic of Heinrich Heine University Duesseldorf between 1989 and 2014 were retrospectively analyzed. Patients had been treated with BoNT for neurological conditions, including cervical dystonia (CD), blepharospasm (BSP), other dystonia (ODT), hemifacial spasm (HFS), and spasticity (SPAS). The parameters longitudinally analyzed for the entire cohort were therapy duration as well as the mean and cumulative BoNT‐A dose. Cross‐sectionally, for subgroups of at least 721, patients’ global self‐perceived quality of health and life, global self‐perceived reduction of symptoms by BoNT‐A treatment as well as the clinical global impression were evaluated. Furthermore, mouse hemidiaphragm assay antibodies (MHDA‐ABs) were analyzed in a subgroup.The mean treatment duration was 4.58 years (95% CI 4.32–4.84), and 678 (50.2%) therapy dropouts of 1351 patients occurred within the first 8 years. Therapy adherence and self‐perceived symptom reduction in long‐term BoNT‐A treatment over the years were significantly longer in BSP, HFS, and CD patients than in ODT and SPAS patients.The treatment indication determines long‐term adherence and self‐perceived symptom reduction in BoNT‐A therapy, which are better in BSP, HFS, and CD patients than in ODT and SPAS patients. MHDA‐ABs had a significant impact on global self‐perceived symptom reduction, but with only a limited degree. In accordance with the Declaration of Helsinki, written informed consent was obtained from all patients on regular follow‐up at the outpatient clinic, and oral informed consent was obtained in a standardized manner prior to all telephone interviews that were performed with patients no longer on follow‐up.Data from 1351 patients documented and treated at the BoNT outpatient clinic of the Department of Neurology, University Hospital at Heinrich Heine University Duesseldorf, Germany between 1989 and 2014 were retrospectively and cross‐sectionally analyzed. Only patients with neurological indications and at least one BoNT‐A injection were included. The mean age of all patients at treatment beginning was 55.40 ± 14.54 SD years.n = 527 with a mean age at treatment beginning of 53.44 ± 13.41 SD years), BSP (n = 173 with a mean age at treatment beginning of 62.53 ± 12.42 SD years), ODT (n = 283 with a mean age at treatment beginning of 51.19 ± 15.46 SD years), HFS (n = 184 with a mean age at treatment beginning of 61.01 ± 13.48 SD years), and SPAS (n = 184 with a mean age at treatment beginning of 55.03 ± 15.16 SD years). The ODT subgroup included patients with Meige syndrome, oromandibular and oropharyngeal dystonia, focal or segmental dystonia of the extremities, and generalized dystonia.Patients were divided into five subgroups: CD (All assessments were conducted by the treating physician at the scheduled reinjection appointments in our BoNT outpatient clinic.The European Organisation for Research and Treatment of Cancer (EORTC) QLQ‐C30 (version 3.0) questionnaire was designed and validated to assess health‐related QoL in the previous week.Further items assessed were the self‐perceived reduction of symptoms from the patient’s point of view over the last BoNT injection interval and the clinical global impression regarding the patient’s symptoms from the treating physician’s point of view at the appointment for BoNT reinjection. These items were rated on a scale ranging from 0% (no symptom reduction) to 100% (complete symptom reduction) compared to the status prior to the first BoNT‐A therapy (from the patient’s point of view) and compared to the maximum possible manifestation of the treated disorder (from the physician’s point of view).We used our local database to analyze longitudinal data of 1351 patients regarding therapy duration, the number of injections, and injected mean unified dose units (uDUs). Furthermore, we cross‐sectionally investigated the global self‐perceived quality of health in 722 patients, global self‐perceived QoL in 721 patients, global self‐perceived reduction of symptoms by BoNT‐A treatment in 734 patients, and clinical global impression regarding symptoms evaluated by the treating physician in 733 patients.BoNT‐A antibody testing was performed by an independent blinded contractor  using two consecutive sandwich enzyme‐linked immunosorbent assays (ELISAs) for screening and confirmation of binding antibodies, as previously described.In a previous analysis, we reported the prevalence of MHDA‐ABs against BoNT‐A in 596 long‐term treated patients, but we did not analyze adherence to therapy or patient satisfaction.In line with previous studies,U test was used with Bonferroni correction for multiple group comparisons, as indicated in the Results section. Spearman correlation analysis was performed to analyze the association between the different parameters. A stepwise multilevel linear regression model was used to detect factors significantly influencing the BoNT dose. For all analyses, P‐values < 0.05 were considered significant. Power analyses to estimate the sample sizes necessary to obtain an actual power (1‐beta) of 0.95 (two‐tailed) were performed with G*Power (Version 3.1.9.2) to determine possible reasons for negative results in subgroup analyses when applicable.SPSS statistics package (IBM) 20 was used for statistical analysis. In addition to descriptive statistics, Kaplan–Meier analysis of the five disorder subgroups was performed using Cox proportional hazard models to compare the trajectories of the different groups. To compare group characteristics, analysis of covariance (ANCOVA) with Bonferroni confidence interval adjustment correcting for age and treatment duration was performed. For nonparametric testing, the Wilcoxon or Mann–Whitney We analyzed the data of 1351 patients with altogether 20705 injection appointments who received at least one BoNT injection at our center. These injection appointments were distributed as follows: 9092 CD, 3304 BSP, 2832 ODT, 3274 HFS, and 2203 SPAS treatments. The maximum duration of treatment was 23 years, with a mean of 4.58 (95% CI 4.32–4.84) treatment years.P < 0.05, Cox proportional hazard models correcting for age at first injection). Fifty‐nine percent of the 173 BSP, 52% of the 184 HFS, 46% of the 527 CD, 25% of the 283 ODT, and 28% of the 184 SPAS patients remained on treatment for over 16 years. The longest follow‐up data of 23 years were available for CD patients, with 45% treatment adherence , than BSP, HFS, and CD patients. SPAS patients showed a significantly earlier decline  as at least 50% self‐perceived symptom reduction was already reached by 7 years of treatment in 60% of the patients compared to 16 years for CD, BSP, and HFS patients  CD, 113/173 (65%) BSP, 122/283 (43%) ODT, 121/184 (66%) HFS, and 75/184 (41%) SPAS patients could be included. The Kaplan–Meier analysis revealed that 74% of the patients with CD, 71% of patients with BSP, and 77% of patients with HFS experienced a stable reduction of self‐perceived symptoms of at least 50% with BoNT‐A treatment over 16 years of treatment. SPAS and ODT patients had significantly higher rates of insufficient treatment response, as reflected by indicating <50% self‐perceived symptom reduction in 83% of patients at 16 years . Sixty‐eight percent of the patients with CD and 66% of the patients with HFS experienced at least medium global QoL (≥4) after 16 years of treatment, whereas 40% of patients already reached a scale of <4 at 10 years for BSP, ODT, and SPAS  global self‐perceived general QoL QLQ C30‐30). For this Kaplan–Meier analysis, 300/527 (57%) CD, 112/173 (65%) BSP, 123/283 (43%) ODT, 119/184 (65%) HFS, and 67/184 (36%) SPAS patients were available. The Kaplan–Meier curves indicated that SPAS and ODT patients experienced a significantly higher risk of dropping under a QoL (OLQ C30‐30) score of 4  than CD and HFS patients. BSP patients had a significantly higher risk of decline in global QoL than HFS patients but significantly less decline in global QoL than ODT and SPAS patients , BSP , ODT , HFS , and SPAS .The self‐perceived symptom reduction assessed by patients was negatively correlated with the clinical global impression of severity evaluated by the treating physician in all indications, suggesting that the low severity assessed by the treater was associated with good subjective response to therapy: CD , BSP , ODT , and SPAS  as well as with global self‐perceived QoL (QLQ C30‐30) in CD , BSP , ODT , and SPAS .Furthermore, patients’ self‐perceived symptom reduction was moderately and positively correlated with global self‐perceived quality of health (QLQ C30‐29) in CD  in the different groups of disorders are presented in Figure r2 = −0.233, P < 0.001), BSP , ODT , and HFS , all Spearman, Fig. r2 = 0.033, P = 0.777). To detect factors influencing the mean single uDUs, a stepwise multilevel linear regression model analyzing treatment group, treatment adherence, global self‐perceived symptom reduction, clinical global impression of symptom severity, global self‐perceived quality of health, global self‐perceived QoL, treatment years, and MHDA‐AB status was performed.Correlation analysis of the unified dose units of the mean dose per session revealed negative correlations with self‐perceived symptom reduction assessed by the patients, indicating that patients with weaker self‐perceived response to therapy were treated with higher doses for all treatment groups (CD (P < 0.001), MHDA‐AB status (P < 0.001), and global self‐perceived symptom reduction (P < 0.001) explaining 20% of the variance of the uDU values  = 34.212).Significant predictors for mean single uDUs were treatment indication (P ≥ 0.05).No additional significant influence was revealed for treatment adherence, clinical global impression of symptom severity, global self‐perceived quality of health, global self‐perceived QoL, and treatment years  at the time of cross‐sectional assessments of global self‐perceived general QoL and global self‐perceived symptom reduction. We attempted to contact all of these patients by telephone, and 143 21.3%) patients could be reached and gave consent to a telephone interview regarding their current treatment. These patients reported receiving no specific treatment (35%), BoNT therapy at another clinic (27.3%), alternative non‐neurological treatment  (16.8%), oral medication  (8.4%), or surgical treatment (4.9%), or they eventually returned to our clinic (7.7%) (Table 1.3% patiP < 0.05 Mann–Whitney U with Bonferroni post hoc test). We observed a higher clinical global impression of symptom severity and less self‐perceived symptom reduction . Global self‐perceived quality of health (QLQ C30‐29) and global self‐perceived QoL (QLQ C30‐30)  between MHDA‐AB‐positive and MHDA‐AB‐negative patients only for the global self‐perceived quality of health of ODT and for global self‐perceived symptom reduction in CD, whereas all other items showed no significant differences between MHDA‐AB‐positive and MHDA‐AB‐negative patients in all subgroups.Independent analysis of the different neurological disorders revealed a significant difference  in the analysis of all patients (78 MHDA‐AB‐positive patients with mean uDUs 1203.28 ± 1072.50 SD vs. 501 MHDA‐AB‐negative patients with mean uDUs 595.75 ± 415.15). Independent analysis of the patients by treatment indication revealed that significant differences between MHDA‐AB‐positive and MHDA‐AB‐negative patients were observed only for the CD subgroup (60 MHDA‐AB‐positive patients with mean uDUs 1348.93 ± 1161.93 SD vs. 339 MHDA‐AB‐negative patients with mean uDUs 744.18 ± 342.2 SD) and for the BSP subgroup (3 MHDA‐AB‐positive patients with mean uDUs 338.18 ± 411.13 SD vs. 48 MHDA‐AB‐negative patients with mean uDUs 92.58 ± 109.28 SD), whereas no significant differences were detected for the other treatment groups , the estimated sample size of MHDA‐AB‐positive and MHDA‐AB‐negative patients in the comparison of uDUs was 96 patients (48 for each group) for all patients, 108 patients (54 for each group) for CD patients, 80 (40 for each group) for BSP patients, 72 (36 for each group) for ODT patients, and 170 (85 for each group) for SPAS patients, suggesting that our analysis was underpowered for the analysis of the subgroups except for CD and ODT.In a power analysis for an actual power of 0.95 ; shorter therapy duration due to older age, earlier death or progression of disability ; or a combination of all of the above reasons.In addition, the self‐perceived symptom reduction by long‐term BoNT‐A treatment over the years appeared to last longer in BSP, HFS, and CD patients than in patients with SPAS and ODT, suggesting that self‐perceived efficacy of therapy may play a role in the adherence of our patients.As higher mean single doses per session of BoNT‐A were used in SPAS patients than in the patients with other indications, the risk of developing MHDA‐ABs against BoNT‐A was higher, as recently reported,Moreover, higher doses of BoNT‐A could have increased the risk of developing MHDA‐ABs in the first place. The differences in BoNT‐A dosing between MHDA‐AB‐positive and MHDA‐AB‐negative patients were not significant for the other treatment groups, again probably because of the low numbers of MHDA‐AB‐positive patients in these groups, which again is supported by the power analysis. We acknowledge that the results of the subgroup analysis of the effects of MHDA‐ABs in the treatment groups except for the CD group should be interpreted with great caution due to the low numbers of MHDA‐AB‐positive patients in these groups.We concluded that MHDA‐ABs had a significant impact on global self‐perceived symptom reduction, but with only a limited degree.Along with the course of therapy, an unsatisfactory treatment response, also in the absence of MHDA‐ABs, is often counteracted by increasing the doses to be injected. In line with this, our analysis revealed a weak but significant correlation between dose and self‐perceived symptom reduction, with higher mean single uDUs being associated with worse self‐perceived symptom reduction for all indications except for SPAS, for which no correlation was detected. The factors significantly influencing the uDUs injected were treatment indication, MHDA‐AB status, and global self‐perceived symptom reduction. Prospective studies on larger cohorts are warranted to address this issue.Another major factor influencing the response to therapy was the complexity of the disorder and of the required injection patterns. In our cohort, the ODT group received lower BoNT‐A doses per session than our CD patients but had comparatively lower adherence to therapy and less self‐perceived symptom reduction over time. The reason may be that the ODT subgroup was composed of a more heterogeneous group of dystonias. Possibly, the diversity of this ODT group and the complexity of the required injection patterns made it harder to maintain good and stable self‐perceived symptom reduction over time, which then resulted in lower adherence to therapy. These reasons may also apply to our SPAS patients, who also often present complex symptoms and injection patterns.Considering the treatment duration of some patients and a consistent mean QLQ C30‐30 score of ≥4 throughout all therapeutic groups and intervals, long‐term usage of BoNT‐A appeared to at least maintain QoL, which was consistent with previously published studies on the long‐term efficacy of BoNT‐A treatment.The EORTC global self‐perceived health status (QLQ C30‐29) and global self‐perceived QoL (QLQ C30‐30) were selected because they can be assessed very rapidly and are not disease‐specific, which, on the one hand, might be an advantage for the study of patients with heterogeneous disorders who receive BoNT‐A treatment for different indications. However, the meaningfulness was limited because we investigated only two questions of the EORTC QLQ C30. The limited specificity of these measures may also be associated with sensitivity reduction for the unique challenges of the different indications, particularly when these indications are grouped.To reduce selection bias when analyzing only patients on therapy, we chose to also include patients who had previously dropped out of follow‐up at our center. The majority of patients who dropped out received no specific further treatment, BoNT treatment outside of our outpatient clinic, or non‐neurological treatment options.However, we have to acknowledge that the percentage of patients available for telephone interviews  was rather low. This was most likely due to the often long time lapse between dropping out of therapy and the time of our assessments.Another limitation of our study was the retrospective design and the lack of a control group, which made it impossible to exclude confounding factors such as aging, coexisting comorbidities, additional medications, and/or procedures, which might have influenced global QoL. As an example, health utility naturally declines with age within the general population.Furthermore, we acknowledge that the conversion calculation of uDUs by multiplying the inco‐BoNT and ona‐BoNT units by 2.5 to reach comparability with abo‐BoNT is heterogeneously performed and controversially discussed in the literature. However, our conversion rate was in line with that of several previous studies.This study investigated a large variety of neurological disorders with different disease severity, progression, and variable treatment histories as well as dosing regimens. These and the abovementioned factors added confounding variability to the interpretation of our data. However, despite these limitations, they also contributed to the strengths of the study, as PROs of real‐world clinical practice with all its complexity were analyzed and reported.In summary, our study retrospectively examined the long‐term results of therapy adherence, global QoL, and self‐perceived symptom reduction after BoNT treatment involving a wide range of indications, allowing comparative analyses. SPAS and ODT patients presented fewer positive outcomes compared to HFS, BSP, and CD patients. MHDA‐ABs against BoNT had only limited effects on the outcomes assessed. Our data indicate that in a relevant proportion of patients with neurological disorders, BoNT therapy can help to improve and maintain self‐perceived symptom reduction and QoL over substantial periods of time.JL, AJ, HH, and PA designed the study, acquired and analyzed the data, created the figures, conducted literature research, and wrote the manuscript. JL, GS, and PA performed the statistical analysis. All authors  drafted a significant portion of the manuscript or figures, interpreted the data, critically revised the manuscript for important intellectual content, and approved the final version of the manuscript.John‐Ih Lee has received honoraria for speaking/consultation from Bayer Healthcare, Boehringer Ingelheim, Allergan, Novartis, Ipsen, Teva, and Daiichi‐Sankyo as well as travel grants from Bayer Healthcare, Merz, Allergan, and Ipsen outside the submitted work. Allergan, Ipsen, and Merz manufacture the drugs that were used in this study. Alexander Jansen declares no disclosures relevant to the manuscript. Sara Samadzadeh declares no disclosures relevant to the manuscript. Ulrike Kahlen has received travel grants from Merz, Allergan, and Ipsen outside the submitted work. These companies manufacture the drugs that were used in this study. Marek Moll has received travel grants from Merz outside the submitted work. This company manufactures one of the drugs that were used in this study. Marius Ringelstein received speaker honoraria from Novartis, Bayer Vital GmbH, Roche, Alexion, and Ipsen and travel reimbursement from Bayer Schering, Biogen Idec, Merz, Genzyme, Teva, Roche, and Merck outside the submitted work. Ipsen and Merz manufacture drugs that were used in this study. Giulia Soncin declares no disclosures relevant to the manuscript. Hans Bigalke works for Toxogen and declares grant, personal fee, and nonfinancial support from Allergan, Ipsen, and Merz Pharmaceuticals outside the submitted work. These companies manufacture the drugs that were used in this study. Orhan Aktas has received honoraria for speaking/consultation and travel grants from Bayer Healthcare, Biogen Idec, Chugai, Novartis, Medimmune, Merck Serono, and Teva and research grants from Bayer Healthcare, Biogen Idec, Novartis, and Teva outside the submitted work. Alexia‐Sabine Moldovan has received travel grants from Merz, Allergan, and Ipsen outside the submitted work. These companies manufacture the drugs that were used in this study. Julia Waskoenig has received travel grants from Allergan and Ipsen outside the submitted work. These companies manufacture the drugs that were used in this study. Sebastian Jander has received honoraria for speaking/consultation from Bayer Healthcare, Boehringer Ingelheim, Bristol‐Myers Squibb, Pfizer, Biogen, Alexion, and Daiichi‐Sankyo as well as travel grants from Bayer Healthcare and Daiichi‐Sankyo outside the submitted work. Michael Gliem has received honoraria for speaking/consultation from Bayer Healthcare and Boehringer Ingelheim and a research grant from B. Braun outside the submitted work. Alfons Schnitzler has received honoraria for speaking/consulting from Medtronic, Boston Scientific, Abbott/SJM, Grünenthal, AbbVie, UCB, MEDA Pharma, GlaxoSmithKline, and Teva. Hans‐Peter Hartung has, outside the work presented, received fees for serving on steering or data monitoring committees from Bayer Healthcare, Biogen, Celgene Receptos, GeNeuro, Sanofi Genzyme, Merck, Novartis, Octapharma, Teva Pharmaceuticals, MedImmune, and Roche; fees for serving on advisory boards from Biogen Idec, Sanofi Genzyme, Merck, Novartis Pharmaceuticals, Octapharma, Teva Pharmaceuticals, and Roche; and lecture fees from Biogen, Sanofi Genzyme, Merck, Novartis Pharmaceuticals, Octapharma, Teva Pharmaceuticals, MedImmune, and Roche. Harald Hefter has been supported by a restricted grant of the Inge‐Diesbach‐Stiftung. This grant did not influence the design and content of the present study. He declares no other disclosures relevant to the manuscript. Philipp Albrecht reports grants from Ipsen, grants from Merz Pharmaceuticals, for MHDA‐AB testing and analysis of the data of patients with spasticity, respectively, during the conduct of the study; grants and personal fees from Allergan, grants and personal fees from Biogen, grants and personal fees from Merck, grants and personal fees from Novartis, grants and personal fees from Roche, personal fees from Teva, grants, personal fees, and nonfinancial support from Celgene, personal fees from Bayer Healthcare, grants and personal fees from Sanofi Aventis Genzyme, outside the submitted work; Allergan, Ipsen, and Merz manufacture the drugs that were used in this study.Open access funding enabled and organized by Projekt DEAL.


In the naïve mouse brain, microglia and astrocytes are the most abundant immune cells; however, there is a complexity of other immune cells present including monocytes, neutrophils, and lymphocytic cells, such as natural killer (NK) cells, T cells, and B cells. In Alzheimer’s disease (AD), there is high inflammation, reactive microglia, and astrocytes, leaky blood–brain barrier, the buildup of amyloid-beta (Aβ) plaques, and neurofibrillary tangles which attract infiltrating peripheral immune cells that are interacting with the resident microglia. Limited studies have analyzed how these infiltrating immune cells contribute to the neuropathology of AD and even fewer have analyzed their interactions with the resident microglia. Understanding the complexity and dynamics of how these immune cells interact in AD will be important for identifying new and novel therapeutic targets. Thus, this review will focus on discussing our current understanding of how macrophages, neutrophils, NK cells, T cells, and B cells, alongside astrocytes, are altered in AD and what this means for the disorder, as well as how these cells are affected relative to the resident microglia. Alzheimer’s disease (AD) is the most prevalent neurodegenerative disease with core neuropathological features including the amassing of amyloid-beta (Aβ) plaques and neurofibrillary tangles (NFT) along with neuroinflammation and cognitive decline . Until mMicroglia are the main immune cells for the CNS. They are responsible for monitoring and maintaining the homeostatic environment through surveillance. Once microglia receive “alert” signals, they will react through the morphological altering of their cytoskeleton to respond to pathological events . Based o–/– mice, the Aβ plaques are much more defused throughout the brain, with reduced microglial engulfment of the Aβ plaques  or blocked by an antibody, neutrophils are unable to enter the brain  Rag2 plaques . Howeverecreased . There wAPP mice . TogetheT cells are a type of lymphocyte that responds to immune challenges as a part of the adaptive immune system . There aAlthough most studies are using both male and female mice grouped together, one found differences in the number of T cells between APP/PS1 males and females, with females having overall more T cells with specific increases in Th and Tc cells . They alswe/PSEN1Δ E9 mice were given combinatorial antibiotics (ABX) that alter the gut microbiome, this led to attenuated Aβ plaque formation as well as increased Treg cells in the brain and blood (SWE/PS1Δ E9 mice (There have also been multiple studies that have implicated the gut microbiota as a factor in affecting the infiltration of T cells into the brain , 2020. Wnd blood . This tr E9 mice . However E9 mice , indicat–/–/Il2rγ–/– mice (–/–/Il2rγ–/– mice resulted in an increase in brain IgG levels and a concurrent reduction in plaque volume (B cells are involved in the adaptive immune response by producing antibodies that coat target cells, allowing for easier engulfment by macrophages . B cells–/– mice . Exposur–/– mice . When pr–/– mice . Also, We volume . In APOEe volume . This ine volume . Howevere volume . These Be volume . This die volume . It shoue volume . Taken tIn AD, current studies focus on modulating Aβ plaque formation and altering the local neuroinflammation; however, other important contributors can consume Aβ plaques and induce neuroinflammation—the peripheral immune cells. Investigations on AD have analyzed microglia either directly or indirectly with macrophages , neutropSW-J performed the literature search and wrote the manuscript. RB critically revised the work. Both authors contributed to the idea for the article.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Results of ACTH stimulation test (ACTHst), pre‐ and post‐trilostane serum cortisol concentrations (SCCs), urine concentration (urine‐specific gravity [USG]), and urine cortisol : creatinine ratios (UCCRs) are common variables used to monitor trilostane treatment of dogs with pituitary‐dependent hyperadrenocorticism (PDH). However, none has consistently discriminated dogs receiving an adequate dose (A) from those overdosed (O) or underdosed (U).To assess and compare recommended monitoring variables, including serial SCCs in a cohort of dogs with PDH treated with trilostane.Privately owned dogs with PDH (n = 22) and 3 healthy dogs (controls).Prospective, multicenter, 2‐day study. On day “a” (randomized): ACTHst was completed. Day “b” (>2 to <7 days later): SCCs were assessed −0.5 hours, immediately before, and 1, 2, 2.5, 3, 3.5, 4, 6, 8, and 12 hours after trilostane administration. On the first study day, urine collected at home was assessed for USG, UCCR and owner opinions regarding PDH were categorized as: A , U (remains symptomatic), or ill (possible O).At 27 pairs of evaluations, 7 dogs were categorized as A, 19 U, and 1 possible O (excluded from the study). There was overlap in SCC results from the A and U dogs at every time point. Results of USG, UCCR, and ACTHst did not discriminate A from U dogs. Trilostane suppresses SCC within 1 hour of administration and its duration of action in most PDH dogs is <8 hours.No single variable or group of variables reliably discriminated A dogs from U dogs during trilostane treatment for PDH. Aadequate doseACTHstACTH stimulation testeACTHendogenous ACTHGgood doseHAChyperadrenocorticismLDDSTlow dose dexamethasone suppression testOoverdosedPDpolydipsiaPDHpituitary‐dependent hyperadrenocorticismPPpolyphagicPUpolyuriaSCCsserum cortisol concentrationsUunderdosedUCCRsurine cortisol : creatinine ratiosUSGurine‐specific gravity1Between 1970 and 2000, the most common medical treatment for dogs with pituitary‐dependent hyperadrenocorticism (PDH) was mitotane , a cytotoxic drug that targets adrenocortical cells.Several different mitotane protocols were suggested for dogs with PDH.With so many issues raised regarding the ACTHst, it is not surprising that alternative monitoring variables have been investigated, including endogenous ACTH (eACTH), cortisol : eACTH ratios, urine cortisol : creatinine ratios (UCCRs), and circulating baseline serum cortisol concentrations (SCCs) before or after trilostane administration or both.22.1Healthy control dogs and dogs with confirmed PDH were prospectively recruited from 3 veterinary hospitals in Spain  after obtaining informed consent from their owners. Health of the control dogs based on history, physical examination findings, and results of CBC, routine serum biochemistry and urinalysis that were within the reference range. In each PDH dog, hyperadrenocorticism (HAC) initially would be suspected from a review of historical information and physical examination findings. All PDH dogs must have had polyuria (PU) and polydipsia (PD) as owner concerns and either have been described as having excellent appetite or being polyphagic (PP). Each must have had at least 4 of the following 6 clinicopathologic findings: increased serum alkaline phosphatase activity, alanine aminotransferase activity, and serum cholesterol concentration; low BUN concentration or BUN concentration near the lower reference limit ; USG < 1.020; and no microbial growth on bacteriologic culture of urine. No dog had a BUN concentration above the reference interval. No dog had evidence of any serious illness other than PDH, including diabetes mellitus, chronic kidney disease, or neurologic signs consistent with a large pituitary mass. Results of a low dose dexamethasone suppression test (LDDST) or ACTHst must have been consistent with the diagnosis of HAC in each dog; not all dogs underwent both tests. Diagnosis of PDH was made if a dog had at least 2 of the following: a LDDST result indicative of PDH, ultrasonographic evidence of 2 relatively equal‐sized adrenal glands, or plasma concentrations of eACTH > 45 pg/mL .2.2The initial trilostane dosage for each PDH dog enrolled was 0.5 to 1.1 mg/kg PO q12h. Each dog must have been treated for a minimum of 30 days and their doses adjusted at previous visits, if such visits were made, in an attempt to achieve clinical control. Commercially available trilostane  was used and, if needed, capsules with the calculated dose were prepared by a compounding pharmacy using licensed trilostane. Each owner of a dog enrolled in the study agreed to bring the dog to the hospital for 2 study days, the second no sooner than 3, and no more than 7 days after the first visit. It also was agreed that no change in trilostane dose or frequency of administration would take place between the first and second study days. Diet and environment were kept as stable as possible by the owner of each dog during this intervening period. Any dog evaluated more than once had a minimum of 60 days between the 2 pairs of assessment days. Repeat assessments were evaluated independently.2.3Other than not receiving trilostane, the healthy dogs were evaluated in the same manner as the trilostane‐treated PDH dogs. Two different sets of evaluation were completed on all dogs. At each evaluation, a complete physical examination was performed after asking the owner about the dog's general well‐being. Owners of PDH dogs were specifically questioned on the first study morning regarding their dog's response to trilostane, understanding that their primary reason for pursuing treatment was resolution of clinical signs. From that owner‐veterinarian conversation, each veterinarian confirmed with the owner 1 of 3 subjective conclusions: that their dog's clinical signs had resolved , that their dog was symptomatic and likely would benefit from additional medication even if some improvement in PU, PD, PP or some combination of these had been noted , or that their dog was ill  and possibly overdosed (O). Any dog considered ill by the owner or considered ill after the physical examination was to be removed from the study and treated as necessary.Dogs were randomly assigned to be first evaluated with either the “a” or “b” protocol. Owners were asked to refrain from feeding their dogs on study days and to bring food and trilostane to the hospital with their dogs 60 minutes before trilostane was to be administered. This time might have allowed some dogs to become acclimated to the hospital while the owner history was obtained. Urine, collected and brought in by the owner on the first of 2 study mornings, was assessed for USG, analytes, and UCCR. On study day “a,” 2 hours after trilostane administration, blood was obtained for CBC, serum biochemistry profile, and baseline SCC. Adrenocorticotropic hormone  then was administered  and blood collected 1 hour later. On study day “b,” each dog had an IV catheter placed 15 minutes before approximately 1 mL of blood was obtained for SCC 30 minutes (−0.5 hour) before trilostane administration. Samples also were obtained via the catheter immediately before (0 hour) and 1, 2, 2.5, 3, 3.5, 4, 6, 8, and 12 hours after trilostane was given. The 12‐hour blood sample was obtained immediately before trilostane was again given and also could be considered a 0 hour SCC.2.4Owner opinion  was the standard against which the studied variables were assessed. Those variables included results of USG, UCCR, ACTHst, pretrilostane basal SCCs, and post‐trilostane serial SCCs. Often‐used criteria for 2 tests also were compared with owner opinion: USG ≤ 1.019 = U and USG ≥ 1.020 = G; post‐ACTHst SCC ≤ 1 μg/dL = too low; 1.0 to 5.5 μg/dL = A; and >5.5 μg/dL = U.2.5Serum and urine cortisol concentrations were measured using of a commercial cortisol assay  that has been validated for use in dogs. The sensitivity of this assay was 0.5 μg/dL (13.8 nM/L).2.6P < .05.Statistical analyses were performed using commercially available software . Normal distribution was assessed using the Shapiro‐Wilk test. Because most of the data were not normally distributed, nonparametric tests were performed. When mean values were compared, the Mann‐Wilcoxon test was performed (results expressed as mean ± SD [±SD]). Spearman's rank correlation test was used to determine correlation between continuous variables. Differences were considered significant at 33.1Three healthy and 22 PDH dogs met their respective inclusion criteria. The healthy dogs  included 2 females (1 intact in anestrus and 1 spayed) and 1 neutered male. Their body weights were 15 kg, 17 kg, and 19 kg, respectively. The PDH dogs were 8 to 15 years of age  and included 9 females (5 intact) and 13 males (7 neutered) with body weights of 2.5 to 24.5 kg . Twenty‐nine evaluations were completed: 3 on healthy dogs and 26 in 21 of the PDH dogs; 1 dog was ill and not evaluated; 3 dogs were evaluated more than once. Two dogs were evaluated 3 times  and 1 dog was evaluated twice (U first and A second).Except for the ill dog, the CBC, serum biochemistry, and urinalysis results from each dog were within reference limits or had alterations expected in dogs with HAC.3.2Based on owner observations, the 1 ill dog was removed from the study but classified as a possible overdose, 7 were placed in the A group, and 19 in the U group. The suspected overdosed dog had a brief history of poor appetite and vomiting. At that time, serum electrolyte concentrations were within reference limits, ACTHst results were not consistent with hypocortisolism , and an alternative diagnosis (gastritis) was made. Because it was the only ill dog and because it was not overdosed, those test results were excluded.P > .05). Trilostane dosage did not differ between A group  and U group . As seen in Figure The mean duration of trilostane treatment for 21 PDH dogs studied was 8.6 months  and dosages at the time of the studies ranged from 0.2 to 6.6 mg/kg PO q12h . Dogs in the A group had been given trilostane for 3 to 28 months  and dogs in the U group 1 to 28 months . Duration of treatment was not significantly different between A and U groups (3.3P > .05) were found in ACTHst SCC results comparing dogs in the A group with those in the U group .The mean (±SD) post‐ACTHst SCCs were 5.64 ± 2.21 μg/dL  in A dogs and 7.86 ± 6.78 μg/dL  in U dogs; 15 of the 19 U dogs had post‐ACTHst SCCs <9.3 μg/dL, the highest result in the A group  in USG was found comparing the A group results  with the U group results  was found in UCCR results comparing the A group  with the U group  had ACTHst results of 1.0 to 5.5 μg/dL and USG ≥ 1.020, meeting all 3 commonly used criteria for an adequate dose . Four of 19 dogs classified by their owners as U (21%) had ACTHst results ≥5.5 μg/dL and USG ≤ 1.020, meeting all 3 commonly used criteria for being underdosed.3.4P < .05) than at 3 hours. The SCCs at 2, 2.5, and 3 hours were significantly lower (P < .05) than SCCs at −30, 0, 1, 3.5, 4, 6, 8, and 12 hours  and no significant difference (P > .05) was found between their prepill SCC at 0 hour and their prepill SCC at 12 hours. The pretrilostane SCC means of A dogs and U dogs were not significantly different .The mean prepill SCC at −0.5 hour for all PDH dogs was significantly lower than at 0 hour  from underdosed dogs (<1.020). It was assumed that well‐controlled dogs would no longer be PU/PD, which would be reflected by concentrated urine whereas underdosed dogs would remain polyuric and have dilute urine. However, not only did all A dogs have USG >1.020 as anticipated, but 11 of 19 U dogs also had USG >1.020. Thus, USG > 1.020 was a sensitive but not specific indicator of dogs receiving an A dose, rejecting our hypothesis. Conceivably, any dog receiving trilostane could have a second condition causing PU/PD, but dogs with common comorbidities associated with PU/PD were not enrolled in our study. In agreement with other studies, UCCR results did not consistently discriminate A from U dogs.Results of ACTHsts in our study did not correlate with clinical signs and did not consistently identify dogs that might benefit from dose adjustment, in agreement with several previous studies.Some authors have evaluated pretrilostane‐administration SCCs to assess HAC control and need for dose adjustment.Our results do not concur with these observations and recommendations. Reviewing the 26 serial cortisol studies, there was no time point in which SCCs discriminated A from U dogs, including the −0.5, 0, and 12 hours SCCs. The SCCs measured before and after trilostane administration overlapped Figures , and 8. The serial SCCs obtained from the 26 visits profile trilostane's effect in blocking cortisol synthesis and secretion. The SCCs results of all 26 visits were significantly lower at 2, 2.5, and 3 hours after administration than at all other time points. Using a q12h schedule, trilostane's effect begins within an hour and peaks approximately 2 to 3 hours after administration. Trilostane's effect appears to have completely dissipated in most dogs within each 12 hour‐period. For most profiles, as seen in Figure Our results and those of many previous studies support the need for individualizing treatment, regardless of initial dose, to the needs of the dog as noted by the owner. It seems logical that trilostane dose requirements would vary somewhat from dog to dog. The trilostane used in our study was from a single source, eliminating 1 explanation for different responses to similar doses. Because drug source was not an issue, these results suggest that it may be of value to assess the diets or the gastrointestinal health of A and U dogs. A problem in 1 of these areas could enhance or interfere with drug absorption or action. In the dogs studied here, no other medications were being given (another possible reason for different drug activity profiles).Our assumption was that owners would best know their dogs and whether their dogs, clinical signs of PDH had resolved completely, partially, or not at all. Use of owner opinion as the variable against which objective testing was assessed was based on the realization that most dogs with HAC develop intolerable clinical signs. Those signs are the most common reason for bringing a dog with PDH to a veterinarian and the reason for treatment. This approach does not ignore the many physiological benefits of treatment, rather it is appreciated that resolution of clinical signs usually correlates with the physiological benefits. Thus, owner opinion, although not always perfect, remains a key variable to understand and utilize when deciding whether a dose change is indicated. Finally, USG may have value as a sensitive (but not specific), simple, quick, and inexpensive indicator of appropriate dose and frequency.Limitations of our study include the relatively small number of PDH dogs in each owner opinion category. Perhaps control of diet, feeding times, or other factors in the home environment would be beneficial. A satisfactory owner questionnaire might have provided important information, but we believe no questionnaire would change overall owner appraisal of the dog's response to trilostane. Retrospectively, an additional time point SCC assessment at 11.5 hours of the serial cortisol concentration study also would have provided additional data regarding sampling “30 minutes before” trilostane administration. As discussed, a study of overdosed dogs will be important as would a study of dogs with adrenal‐dependent hyperadrenocorticism.Many of the tests most commonly used in monitoring dogs being treated with trilostane for PDH were included in our study. Furthermore, serial SCCs also were obtained beginning before and extending 12 hours after trilostane administration. No variable consistently discriminated dogs receiving an adequate dose from dogs that continued to exhibit clinical signs. As discussed, these results support the importance of knowing the owner's and veterinarian's goals for treatment, and these should be aligned before beginning treatment. Based on results of our study and many others, veterinarians treating dogs with trilostane for PDH are encouraged to develop an effective team approach. Valuable members of the team include the owner in addition to the veterinarian. Adequate time must be available for both team members when reevaluating these dogs so as to fully understand owner observations.Authors declare no conflict of interest.Authors declare no off‐label use of antimicrobials.Approved by the hospital board of the Veterinary Teaching Hospital Complutense, Las Palmas de Gran Canaria and from the Hospital Auna Especialidades Veterinarias.Authors declare human ethics approval was not needed for this study.


In several species, paraoxonase‐1 (PON‐1) decreases during inflammation, because of the presence of oxidative stress; its measurement recently has been validated in horses, but its role as a clinical biomarker is unknown.To evaluate sensitivity, specificity and likelihood ratio of PON‐1 activity to identify systemic inflammatory response syndrome (SIRS)‐positive horses or horses with a poor prognosis.One hundred seventy‐two blood samples from 58 sick horses from 3 different veterinary hospitals.In a cross‐sectional study, PON‐1 activity was measured upon admission and at 24‐hour intervals until discharge or death, and results were analyzed based on SIRS status and outcome.P = .05). The sensitivity of PON‐1 activity in identifying horses with SIRS or negative outcome was low (0.0%‐46.2% depending on the examined group) but its specificity was high (87.0%‐100.0%). However, when PON‐1 is low, the likelihood of death is 2.40‐3.89 times higher than the likelihood of survival. Repeated measurement of PON‐1 after treatment does not predict outcome.No statistically significant difference was found in median PON‐1 activity between SIRS and non‐SIRS cases or between survivors and non‐survivors except for mares, in which PON‐1 activity was significantly lower in SIRS‐positive horses (Evaluation of PON‐1 activity in horses with inflammation might be advisable in the future, but only low activity at admission may be relevant in predicting SIRS or negative outcome. TheRecently, the term systemic inflammatory response syndrome (SIRS), rather than endotoxemia, has been suggested to describe the clinical status of endotoxemic horses. Diseases that have been associated with SIRS in adult horses include especially those involving the gastrointestinal tract, such as the inflammatory intestinal diseases and strangulating obstructions.An early diagnosis should be the goal in management of SIRS patients, allowing starting adequate treatment in an early stage.Our aim was to compare PON‐1 activity in sick horses classified as SIRS‐positive or SIRS‐negative, as proposed by others,22.1The study was performed on 172 blood samples from 58 horses . Sick animals were referred to 3 different hospitals providing secondary health care.Horses were classified as sick on the basis of clinical examination and ancillary tests .3/μL), left shift , hyperthermia or hypothermia , tachycardia , and tachypnea . Horses with 0 or 1 abnormal criterion were included in the SIRS‐negative group, whereas horses with ≥2 abnormal criteria were included in the SIRS‐positive group.The following data were recorded in order to classify and divide the sick horses in SIRS‐positive or SIRS‐negative groupsRetrospectively, sick horses also were divided into survivors and non‐survivors. Animals were considered survivors if they were discharged from the hospital, whereas they were considered non‐survivors if they died or were humanely euthanized because of severe medical prognosis rather than for economic reasons.Although all the sick horses included in the study were admitted to the hospitals within 30 hours after the onset of the disease, it was not possible to standardize the time elapsed from the onset of clinical signs and the first sampling or to collect a complete history regarding the pre‐admission period. After the first sampling (T0), all of the horses received appropriate treatment based on the actual diagnosis and clinical presentation.Blood samples were collected by the investigators within 1 hour after admission at the hospital, and additional samples then were collected at 24‐hour intervals until discharge or death or for a maximum of 96 hours. Lipemic samples were excluded from the study.2EDTA) and analyzed using a cell counter  within 5 minutes after collection. A second 2.5‐mL aliquot was collected in plain tubes and centrifuged at 2100 relative centrifugal force for 10 minutes within 4 hours of collection. The harvested serum was placed in sterile tubes, frozen at −20°C to be transported to the laboratory, where serum PON‐1 activity was measured in a single batch as described below.Blood samples were collected from the jugular vein for the determination of CBC and PON‐1 activity using a sterile syringe and 16G needle. Each blood sample was divided in 2 aliquots: a 1‐mL aliquot was collected in potassium ethylene diamine tetra‐acetic . The rate of hydrolysis of paraoxon to p‐nitrophenol was measured by monitoring the increase in absorbance at 504 nm using a molar extinction coefficient of 18.050 L/mol/cm−1 as previously suggested.Serum PON‐1 activity was measured spectrophotometrically using an automated analyzer , and an enzymatic method already validated in horses.2.3Statistical analysis was performed using an Excel spreadsheet and specific software .U test. The same test was used to compare the results obtained upon admission between survivors versus non‐survivors. A Fisher exact test was used to verify the association between categorized PON‐1 results (within versus below the RI) and SIRS‐positive or negative classification or outcome (survivors versus non‐survivors). Statistical differences were set for P < .05.Results for PON‐1 activity upon admission to the hospital obtained from SIRS‐positive horsesTrue‐positive (TP): Sick horses with PON‐1 activity lower than the RI and SIRS‐positive;False‐positive (FP): Sick horses with PON‐1 activity lower than the RI and SIRS‐negative;True‐negative (TN): Sick horses with PON‐1 activity within the RI and SIRS‐negative; andFalse‐negative (FN): Sick horses with PON‐1 activity within the RI and SIRS‐positive.To assess diagnostic performance of PON‐1 activity in detecting SIRS‐positive horses, the numbers of samples from SIRS‐positive and SIRS‐negative subjects that upon admission had PON‐1 activity within or below the RI established in the previous studyThe same classification scheme was used to assess the diagnostic performance of PON‐1 activity in detecting animals with a poor prognosis, considering as “positive” the non‐survivors and as “negative” the survivors.In both instances, TP, TN, FP, and FN results were used to calculate sensitivity, specificity and likelihood ratios using standard formulas.Results from sequential samplings collected after treatment were not statistically compared to each other because of the low number of samples that had comparable follow‐up. Hence, the analysis of results collected during the follow‐up was limited to a visual observation of the trend recorded in animals that survived or died despite treatment.33.1The 58 sick horses were grouped as follows on the basis of the final diagnosis: obstructive or strangulated colic (n = 34), other gastrointestinal diseases , bacterial pneumonia or pleuropneumonia (n = 4), trauma , neoplasia (n = 2), and paraphimosis, neurological signs, pyometra, sinusitis, pericarditis and Cesarean section (n = 1 each).The SIRS‐positive horses consisted of 35/58, whereas 23/58 were classified as SIRS‐negative. The SIRS‐negative horses had obstructive (7/23) or strangulated (4/23) colic, trauma , 2/23 neoplasia and granulomatous enteritis, respectively, and 1/23 paraphimosis, pyometra, sinusitis, and choke, respectively. The SIRS‐positive horses had obstructive (4/35) and strangulated (19/35) colic, 4/35 pneumonia or pleuropneumonia , 3/35 severe trauma, 1/35 pericarditis, Cesarean section, and granulomatous enteritis associated with dermatitis, respectively.The SIRS score was 4 in 3/35 horses, all affected by pneumonia or pleuropneumonia, 3 in 15/35 animals , and 2 in 17/35 .Eighteen of 58 horses died despite treatment. Nine of these 18 horses were euthanized because of worsening clinical condition and not for economic reasons and 9/18 died spontaneously. Non‐survivor horses were affected by obstructive (n = 3) or strangulated colic (n = 9), pneumonia or pleuropneumonia (n = 4), trauma and other gastrointestinal diseases (n = 1 each). Thirteen horses died or were euthanized after the first sampling, 1 after the third sample, and 4 after the fifth and last sample.3.2At admission, 11/58 horses had PON‐1 activity lower than the lower limit of the RI of adult horses (38.0 U/mL). However, when results recorded in males, females or geldings were compared with the lower limit of the specific RI , only 10 horses  had low PON‐1 activity.P = .21) and between survivors  versus non‐survivors . Contingency analysis showed a significant association between categorized PON‐1 activity and SIRS classification  and between categorized PON‐1 activity and outcome (P = .02).No differences were found in PON‐1 activity between SIRS‐negative  versus SIRS‐positive horses . Conversely, in mares, PON‐1 activity was significantly lower (P = .05) in SIRS‐positive horses  compared with SIRS‐negative horses .No significant differences were found when the analysis was restricted to geldings .Authors declare human ethics approval was not needed for this study.AppendixS1: Supporting InformationClick here for additional data file.


Teen driving educational events are an effective strategy to increase adolescent drivers’ awareness of safe driving practices. The objectives of this study were to evaluate changing rates of self-reported driving practices and knowledge of the state Graduated Driver Licensing laws (GDL) by teens over a nine-year period in a single state.This was a prospective observational study of high school students ages 14 to 19 years old. Paper surveys were sent to the high schools participating in teen driving educational events (9 schools in 2009 and 4 schools in 2018). Students in those schools completed surveys prior to the events. Students completing the anonymous survey were invited to the event. Questions evaluated awareness of state GDL and safe and risky driving behaviors. Statistical comparisons of survey answers from 2009 to 2018 were analyzed using the z test of proportions .n = 273) reported “always” wearing their seatbelt. When asked about high risk behaviors, 78% (n = 309) of adolescents reported they personally “never” text while driving; 97% (385); never drive after drinking, and 87% (n = 344) never ride with someone who has been drinking. Compared to 2009 participants , the students in 2018 (4 schools scattered across state) reported wearing seatbelts “always” ; “never texting while driving” ; and “never drinking and driving” . No significant difference in rates of students having taken a driving education class nor driving over speed limit were reported.A total of 397 students participated in 2018 with ages ranging from 14 to 19 years. Racial distribution was 81% white, 14% black, and there were 57% female participants. Only 69% (Results are encouraging that participants in 2018 report more use of seatbelts, less texting while driving, less drinking while driving and lower numbers of being in MVC than in 2009. However, rates of high-risk driving behaviors are still concerning. Motor vehicle crashes (MVCs) are the number one cause of death for teens in the U.S. . Consent for event was written consent by parents to the school to allow them to travel to the event. Respondent identities were concealed as all surveys were anonymous. There was no individual incentive to participate. In 2009 there was a $500 award to the school with the most surveys.In 2009 there were nine schools from the central portion of the state participating in one event. In 2018 there were four schools from across the state  participating in four separate events. We calculated descriptive statistics and compared survey answers from 2009 to 2018 using the z test of proportions using a 2 tailed alpha level of 0.05 as significant. All analyses were conducted in Epi Info 7.0.9.7 .n = 44);15 years (n = 171); 16 years (n = 101); 17 years (n = 67), and 18 or older (n = 13), with 57% female (n = 228). Racial distribution was white ; black ; and Hispanic . Only 69% (n = 273) reported “always” wearing their seatbelt, and when asked if any physician had ever talked to the adolescent about wearing seat belts only 168 (42%) said yes. Only 63% (n = 249) reported having taken a driving class in the past. A total of 55% (n = 218) reported routinely going more than 10 miles above speed limit.A total of 397 students from four schools across Alabama participated in 2018. Ages of students ranged from 14 years (n = 309) of adolescents reported they personally “never” text while driving, 97% (n = 385) participants stated they never drive after drinking, and 87% (n = 344) stated they never “ride with someone whose been drinking.” Students (n = 225), reported seeing their parents wear seatbelts “always” 64% of time. When asked if their parents text while driving, only 26% said “never” and 15% said “most or all the time.” When asked if their parents had ever discussed safe driving with them, 15% reported no time was spent; 41% < 1 h, 27% 1–3 h, 8% said 4–6 h, and 9% over 6 h. A total of 230 (58%) were aware of the GDL laws, with only 26% correctly answering the curfew question.When asked about high risk behaviors, 78% ; “never texting while driving” ; and “never drinking and driving”   who died in passenger vehicle crashes in 2013 approximately 56% were not wearing a seat belt at the time of the crash , the risk of involvement in a motor vehicle crash is greater for teens than for older drivers . While our participants were primarily 15 and 16 years old, we also surveyed 17 and 18-year olds. Although not a direct comparison due to the slight age differences, our numbers were comparable to the 2011 NYRBS. Nationwide, 7.7% of students rarely or never wear a seatbelt, 8.2% drove in the last 3 days after consuming alcohol, and 32.8% texted while driving in the last 30 days (McKnight and McKnight Despite the presence of a GDL law in our state since 2002 with revisions in 2010 and 2015, our survey indicates many teens do not follow the guidelines of this law. Besides the GDL, our state has had a primary seat belt law since 1997, yet only 69% of respondents said they always wear their seatbelt when driving. In addition, 55% of respondents reported they routinely drive 5–10 mph over the speed limit. It is apparent that legislation is important, but there are additional factors involved in teen driving safety.One limitation of any self-reported survey is the risk of responder bias. As a result, participants may not answer truthfully, but this survey was anonymous and voluntary, so participants had no reason to falsify answers. There may also be bias in the type of student who would complete this kind of survey. We also did not specifically ask if the student respondent was a driver, thus we were not able to further analyze the responses by driver status. There is also the potential for recall bias as this survey asks respondents to remember the frequency of certain behaviors and actions. However, the survey questions were either taken directly from the NYRBS or created in similar style, and the NYRBS tool has been validated for reliability (Brenner et al. Teen driving death and injury is a significant problem in our nation. Results are encouraging that participants in 2018 report more use of seatbelts, less texting while driving and less drinking while driving than in 2009. However, rates of seatbelt use are still only 69%, and low rates of physicians discussing seatbelts were still reported. Also, an alarming number of teens still report risky driving behaviors in this study. Some state-based interventions such as the graduated driver licensing law, safe driving media campaigns, and a Teen Driving Toolkit for state pediatricians have already been instituted in Alabama, and the teen driving educational events have expanded to cover the different areas of the state. Persistent efforts to increase public awareness of teen driving safety issues is indicated.


Non-nutritive sweeteners (NNS) are widely consumed by humans due to their apparent innocuity, especially sucralose. However, several studies link sucralose consumption to weight gain and metabolic derangements, although data are still contradictory.To determine the effect of acute and chronic consumption of sucralose on insulin and glucose profiles in young healthy adults.This was a randomized, parallel, double-blind, placebo-controlled trial conducted in healthy young adults from 18 to 35 years old, without insulin resistance. A hundred thirty seven participants were randomized into three groups: a) volunteers receiving 48 mg sucralose, b) volunteers receiving 96 mg sucralose, and c) controls receiving water as placebo. All participants underwent a 3-h oral glucose tolerance test (OGTT) preceded by consuming sucralose or placebo 15 min before glucose load, at two time points: week zero (Wk0) and week ten (Wk10). Serum insulin and glucose were measured every 15 min during both OGTTs.p = 0.01), 30 min , 105 min  and 120 min  in the 48 mg sucralose group; 2) increased blood glucose at − 15 min , 0 min  and 120 min  in the 48 mg sucralose group; 3) increased area under the curve (AUC) of insulin in both 48 and 96 mg sucralose groups ; and 4) reduced Matsuda index in the 48 mg sucralose group .Compared to Wk0, consumption of sucralose for 10 weeks provoked 1) increased insulin concentrations at 0 min , however, the effects are not consistent with dose; further research is required.These data show that chronic consumption of sucralose can affect insulin and glucose responses in non-insulin resistant healthy young adults with normal body mass index (between 18.5 and 24.9 kg/mNCT03703141. In the past 40 years, the prevalence of overweight and obesity has increased worldwide to the extent of becoming an epidemic . Sugar oDespite NNS consumption is considered safe for humans –8, recenThus, the aim of this study was to investigate whether acute or chronic sucralose ingestion produces insulin or glucose alterations in healthy young individuals that daily consume 48 mg or 96 mg sucralose for 10 weeks, a sucralose amount equivalent to one or two diet sodas, respectively.This was a randomized, parallel, double-blind, placebo-controlled trial in young healthy adults, conducted in Mexico City. It met the CONSORT criteria as recommended elsewhere .The study was approved by the Ethics and Clinical Research committees of the General Hospital of Mexico Dr. Eduardo Liceaga  and followed the principles of the Declaration of Helsinki.clinicaltrials.gov (identifier code: NCT03703141).The study was conducted at the Laboratory of Proteomics and Metabolomics, Research Division at the General Hospital of Mexico Dr. Eduardo Liceaga. This trial was registered at Healthy volunteers from both sexes, aging 18–35 years were invited to take part in the study by poster advertisements and survey invitations by e-mail and phone calls. All volunteers that agreed to take part in the clinical trial signed the informed consent and received full explanation of the purposes and procedures of the study. Eligibility of candidates to enter the study was performed according to a screening process that included medical history, physical examination, recording of anthropometric measurements and blood samples for evaluation of hematology tests, glycated hemoglobin (HbA1c), glucose, insulin, liver function tests, blood chemistry, insulin resistance by the homeostatic model assessment (HOMA) and Human Chorionic Gonadotropin Hormone (in women). HOMA was calculated as follows: (Fasting Plasma Insulin) x (Fasting Plasma Glucose/22.5). Subjects enrolled in the study met the cutoff point of 3.8, as described by Qu et al . EligibiParticipants with previous diagnosis of any acute or chronic disease, malabsorption syndrome or short bowel syndrome, use of corticosteroids, antibiotics or non-steroidal anti-inflammatory drugs (NSAID) during the last 3 months prior to enter the study were excluded. Once enrolled, participants that attended less than 80% of weekly appointments, fell pregnant, smoked cigarettes or consumed alcohol were excluded from the study.The sample size estimation was performed using the GPower v.3.1 9.2 program , expectihttp://www.randomization.com including 6 individuals per block.BHN randomized participants into three groups, as follows: a) subjects receiving 48 mg sucralose, b) subjects receiving 96 mg sucralose, and c) subjects receiving water as placebo. Each group ingested sucralose or water as placebo every day, for 10 weeks. The allocation groups were unrevealed to the participants as well as to researchers who delivered sucralose or placebo, or to who conducted the weekly follow-ups. Randomization was generated using the Web site Sucralose solution  was diluted with pure drinking water. Clean, sterile, dark plastic bottles were filled with 60 mL of diluted sucralose, so that each bottle contained 48 mg (2 mM) or 96 mg (4 mM) sucralose. Placebo was prepared by just filling the bottles with 60 mL of water. In all cases, the liquids were not visible, colorless and not flavored. Cardboard boxes were assembled, each one containing 9 bottles with the same amount of sucralose or water. RBA prepared and placed the beverages in the bottles. BHN labeled the cardboard boxes according to the randomization scheme. ASR disseminated the beverages to participants. Each volunteer received one box every week.In order to evaluate energy intake  and diet composition , food frequency questionnaires from the past 7 days were applied in each weekly visit and intolerance symptoms or adverse events, if any, were registered. To evaluate participant dietary intake, researchers  were trained and administered 24-h food recalls and the Food Frequency Questionnaire with Intense Sweeteners (FFQIS), previously validated by our group . To asseThe participants’ total cholesterol, high-density lipoproteins (HDL), low-density lipoproteins (LDL), triglycerides, waist-to-hip ratio (WHR) and NNS consumption (mg/d) were measured before starting the intervention.At week zero (Wk0) and at week 10 (Wk10), bioimpedance and anthropometry assessments were performed using RJL Quantum IV system , a scale and a metric tape. An Oral Glucose Tolerance Test (OGTT), HbAc1, fasting glucose and fasting insulin were assessed at Wk0 and Wk10.The Matsuda insulin sensitivity index was calculated for control and sucralose groups at Wk0 and Wk10, as described elsewhere .Researchers (RBA and LHM) obtained blood samples. The biochemical analysis of blood samples was performed by trained personnel of the Hospital’s Central Laboratory. Researchers  collected anthropometrical and bioimpedance measurements from the participants and calculated WHR and Matsuda index.OGTTs were performed in participants with 8–10 h fasting. Briefly, a cannula was introduced in the antecubital vein. Fifteen minutes before the glucose load (75 g in 240 mL of water), one dose (one bottle) of sucralose or placebo was drank by each participant. Blood samples were drawn at − 15 min , at 0 min (immediately before drinking the glucose load), and at 15, 30, 45, 60, 75, 90, 105, 120 and 180 min, consecutively. Blood samples were sent to the hospital’s central lab for immediate glucose and insulin measurements. At the end of the OGTT, all participants received a light lunch. Plasma glucose was measured using a glucose analyzer  and plasma insulin was measured through an enzyme-linked immunosorbent assay .Data entry was performed twice by two separate managers. Demographic data were reported as means and standard deviations or proportions. The Kolmogorov-Smirnov test was used to assess normality for each variable.Areas under the curve (AUC), maximal concentration and time to maximal concentration from Wk0 and Wk10 of the OGTT, were also calculated for each group by the trapezoid method, using the pk module of the Stata 15 software .Differences between Wk0 and Wk10 of each group were evaluated by two-tailed paired-t tests. Differences between all groups at the same time point (Wk0 or Wk10) were compared by One-Way ANOVA. Differences between two groups at the same time points were analyzed using two-tailed t-tests.Univariant Analysis of Variance was performed to determine the existence of interactions between interventions  and time (Wk0 and Wk10). A two-way ANOVA was performed to analyze differences between Wk0 and Wk10, using the Bonferroni test to adjust for multiple comparisons.p value < 0.05 was set as statistically significant and p between 0.05 and 0.1 was considered to show a tendency.The IBM-SPSS version 23 statistical package  was used for the analysis. A Two hundred forty nine young adults were invited to the study (from February 2016 to June 2019); 137 accepted to participate and met the inclusion and exclusion criteria to enter the study. After randomization, assignments were 45 subjects in the control group (placebo), 46 subjects in the 48 mg sucralose group, and 46 subjects in the 96 mg sucralose group. By the end of Wk10, only 95 participants completed the study; 34 in the control group, 30 in the 48 mg sucralose group and 31 in the 96 mg sucralose group, and these were considered for statistical analyses. The principal reasons for withdrawal were intolerance to the sweetness of sucralose and digestive functional disorders , total cholesterol, HDL, LDL and triglycerides. Women were more prevalent than men in the three study groups (Table p = 0.01), at 30 min , at 105 min , and at 120 min  , at 0 min , and at 120 min . Although glucose concentration at Wk10 was higher than that found at Wk0, differences were not significant  might provoke derangements in the carbohydrate metabolism, we compared glucose and insulin levels in OGTTs at Wk0 and at Wk10. In the control group, no differences were found in insulin and glucose concentrations between Wk0 and Wk10 Fig. d. In thep = 1.00). Consumption time had no effect on glucose AUC  = 0.00, p = 1.00); in contrast, type of intervention showed a significant effect  = 3.327, p = 0.038, η2 = 0.035, 1-β = 0.624). A similar trend was found in the AUC of insulin, where no interaction between type of intervention and consumption time was observed  = 0.45, p = 0.63). Consumption time did not have a significant effect on the insulin AUC, however, it showed a tendency to increase  = 2.77, p = 0.10). In contrast, type of intervention had a significant effect on the AUC of insulin  = 3.74, p = 0.03, η2 = 0.039, 1-β = 0.679). Two-way ANOVA analysis showed no interaction between type of intervention and consumption time in both glucose and insulin AUCs  = 0.255, p = 0.91). However, type of intervention showed a significant effect on (a) the insulin AUC when compared subjects of the Bonferroni’s correction showed that this effect was significant for insulin AUC between 48 mg sucralose group versus participants of the 96 mg sucralose group , and (b) glucose AUC when compared volunteers of the 48 mg sucralose group versus control subjects   and consumption time (Wk0 and Wk10) was found in glucose AUC  = 0.00, ,184 = 0.p = 0.12) . At Wk0, insulin AUC tended to decrease in the 96 mg sucralose group as compared to that found in the 48 mg sucralose group . At Wk10, insulin AUC tended to decrease in the 96 mg sucralose group as compared to that found in the 48 mg sucralose group   but not to 96 mg sucralose  Fig. d.p = 0.01; for insulin, Wk0 = 8093 ± 4687 vs Wk10 = 9871 ± 6253, p = 0.006). It is worth mentioning that both glucose and insulin AUCs were similar when compared Wk0 versus Wk10 in the control group  and those drinking placebo. After 10 weeks of exposure, we found that volunteers receiving any sucralose concentration had higher glucose and insulin levels than those found in controls receiving placebo  (Table p = 0.30) , but not in the 96 mg sucralose group , whereas in volunteers receiving sucralose increased . However, no significant differences were reached.Overall, food consumption showed no significant differences among the three intervention groups in carbohydrates, lipids, proteins, and energy intake Table . After 1Adherence to intervention was also similar in the three groups; however, the highest adherence rate was found in the 48 mg sucralose group (94%) while subjects in the 96 mg sucralose group showed the lowest adherence rate (86%).The effect of the acute consumption of sucralose was assessed by comparing insulin values at − 15 min and at 0 min of the OGTTs performed at Wk0. No differences were found between placebo and sucralose groups (48 mg or 96 mg), Figs.  and 3.Two volunteers developed symptoms of hypoglycemia during OGTTs, one of the control group and the other one of the 96 mg sucralose group. However, these symptoms were mild and volunteers recovered soon. Volunteers also reported several digestive functional disorders Fig. .The most notable findings observed in the study were changes in insulin concentrations, insulin AUCs, and glucose AUCs in the 48 mg sucralose intervention group at 10th week. The most significant changes in insulin were found at 0, 30, 105 and 120 min, possibly as a delayed metabolic response generated to compensate the insulin increment to keep glucose on target. Likewise, the effect on the AUC was greater in insulin than in glucose. This data suggest that chronic consumption of sucralose reduces insulin sensitivity in young adults; in consequence, insulin production tended to increase with the aim of keeping glucose levels in normal values. Insulin did not only change, also a reduction in the Matsuda Index was found in the same group, which in turn supports the idea that insulin exerted a compensatory response to chronic sucralose consumption.Unexpectedly, these effects were only significant in the 48 mg sucralose group but not in the 96 mg sucralose group; possible explanations are discussed later.One unexpected finding was the high variability in OGTT glucose and insulin time points among participants; we consider that this resulted from the high HOMA value that we decided to set as cut off point (< 3.8).Several studies have shown that sucralose is not physiologically innocuous. Pepino et al, reported that acute consumption of 48 mg sucralose increased glucose concentrations as well as insulin AUC in a 5 h OGTT in individuals with obesity . HoweverFurthermore, Lertrit et al reported in a randomized double-blind cross over study that daily oral ingestion of 200 mg encapsulated sucralose for 4 weeks decreased whole body and hepatic insulin sensitivities  in 15 healthy volunteers without obesity . Sucralose was administered in capsules, which avoided the oral response to the sweetness . NonetheOn the contrary, the 12-week study in 46 normoglycemic male volunteers who received ~ 333.3 mg encapsulated sucralose or placebo 3x/day test, showed no significant differences between Wk0 and Wk10 OGTTs in HBA1c, glucose, insulin, and C peptide . In lighWe also found a statistically significant increase in HbA1c after consumption for 10 weeks of 96 mg sucralose. Davis et al also reported an increase in HbA1c in Hispanic young individuals with overweight or obesity who were frequent consumers of beverages with NNS at least for 1 year . This efIt is pertinent to mention that the effects of sucralose consumption for 10 weeks on insulin and glucose were only observed in the 48 mg sucralose group and not in the 96 mg sucralose group. Several explanations are possible that can be partially involved in this phenomenon. For instance, lower adherence to intervention in the 96 mg sucralose group than in the 48 mg group; however, this difference was not so great to completely explain what was observed. Likewise, the excessive sweetness of this dose of sucralose may have provoked an under consumption of the NSS that was not reported by participants. Other possible explanations may involve different mechanisms related to glucose and insulin homeostasis, like gut microbiota dysbiosis, sweet taste receptors response, cephalic response to sucralose, among others, that are discussed below.Sucralose induces a cephalic phase in the insulin response without any other stimulus, which can influence digestion and metabolism leading to the release of several hormones such as GLP-1, ghrelin, and insulin after oral exposure . In our Likewise, gut microbiota could also play a role in explaining the differences between groups. In this sense, Suez et al reported impaired glucose tolerance in mice after exposure to saccharin, sucralose or aspartame in the drinking water for 10 weeks, an effect that was dependent on the alteration in gut microbiota caused by NNS . MoreoveOther mechanisms that may also explain the response observed in the 96 mg sucralose group can be related to sweet receptor signaling in cells. This receptor, a TAS1R2/TAS1R3 heterodimer, is expressed in several tissues, from the upper gastrointestinal tract to intestinal brush and enteroendocrine cells  and recoBesides, it should be mentioned that our study did not find a beneficial effect of sucralose consumption on BMI, HOMA, cholesterol or triglycerides, which agrees with other studies that reported limited or no effects of NNS consumption on reduction of caloric intake and consequently BMI or other clinical manifestations associated with obesity . Even moA major limitation in our study was the limited effects in the 96 mg sucralose group, since the exact mechanism of the observed effects is unknown. Differences in adherence to intervention between groups also limit data interpretation. Furthermore, the moment at which sucralose was ingested daily was not registered, therefore subjects may not have ingested the sucralose at the same hour daily, or may have combined it with different foods, which may have altered the response to intervention. Nonetheless, in a real scenario, people do not ingest sucralose alone diluted in simple water; sucralose is found in different foods and beverages which contain a complex mixture of ingredients and often, other NNS too. Also, diet was not controlled, however, there were no statistically significant differences in carbohydrate, lipids or proteins intake between groups after 10 weeks of sucralose or placebo ingestion, although micronutrients were not measure. Likewise, gut microbiota changes were not assessed.Finally, the use of water as a placebo in the control group may not be the best election in all studies, especially those who wish to assess the cephalic response to sweetness. In our case, we did not avoid this response, however, if we had used another substance as a control, for example, another NNS or sugar, we would not have discerned the effect of sucralose from that of the substance used as control. Further studies with sucralose encapsulated should be still conducted.This study adds new evidence regarding the effect of chronic sucralose consumption on serum insulin and insulin sensitivity.An effect of chronic consumption of sucralose on insulin response in healthy volunteers subjected to an OGTT was observed, however, the effect was not consistent with dose.Further research is required before mayor claims can be made regarding the effect of sucralose consumption on glucose and insulin responses.


We showed excellent adherence and satisfaction with our telehealth care (TC) approach for COPD. Here, the results of a consecutive randomized controlled trial are presented.Patients were randomly assigned to TC or standard care (SC). During TC, patients answered six daily questions online, and focused on the early recognition of exacerbations, in addition to SC.P = 0.0015). Satisfaction with care (VAS) at baseline was 8.2; at the end of SC, 8.5 (P = 0.062); and after TC, 8.8 (P < 0.001). We detected significantly more moderate exacerbations during TC.The mean increase in COPD assessment test (CAT) was 1.8 vs. 3.6 points/year in the TC and SC groups, respectively (Whilst receiving TC, the slope of the CAT increase – an indicator of the naturally progressive course of COPD – was reduced by 50%. Satisfaction with care increased with TC. The higher number of detected moderate exacerbations probably indicates a higher diagnostic sensitivity than without TC. Telehealth care (TC) could be a relevant component of integrated care for chronic obstructive pulmonary disease (COPD). In brief, TC was described by McLean  as electAECOPD is characterized by symptoms, which often occur already days before the event . For earThe primary aim of the current study was to investigate the impact of a TC procedure on the course of COPD and HRQOL as assessed by the slope of individual CAT changes over the study periods.This was a multicentre randomized controlled crossover trial, involving 6 centres in Switzerland and Germany. Inclusion period was from April 2016 to September 2018. Last patient last visit was September 2019.ClinicalTrials.gov is NCT04485832.The continuous screening of all COPD patients took place in daily clinical practice. Each patient participated in the study for 12 months with a crossover after 6 months Figure . InclusiAfter screening and inclusion, a first consultation was arranged to collect baseline characteristics, perform randomization and give instructions to the participants. A user account on a web‐based online healthcare platform was installed (‘Evita’ by Swisscom) on the patient’s own technical device. For the study, an adapted plug‐in was created. In the following 6 months, patients starting with the intervention phase daily answered six questions, which were focused on the detection of AECOPD, and completed the CAT weekly. Patients starting with the control phase only filled the CAT questionnaire weekly. After 6 months, patients presented for the second visit, where the crossover took place. The last visit took place after 12 months. During the whole year, all patients had consultations for their COPD treatment as usual. Same access for both groups to equal clinical care according to local practice was granted.The daily asked ‘yes’ or ‘no’ questions focused on the recognition of AECOPD Figure . Whilst The CAT was filled weekly by the patients in both phases. For the study, the German version of the questionnaire was used.The primary end‐point was the group‐specific slope difference in weekly CAT over time. Satisfaction with care was assessed by a visual analogue scale from 0 to 10. Additional end‐points were the number of exacerbations and hospitalizations  due to AECOPD and the treatment costs per patient and year. Data were collected through hospital records, contacting the patient’s general practitioner and the rehabilitation clinics and asking the patients themselves. Treatment costs included the exact expenses for hospital and rehabilitation stays as well as estimated costs for planned and unplanned outpatient visits, medication and telephone contacts.The evolution of the CAT over time was analysed using linear mixed‐effects models. The fixed‐effects terms included time, group (intervention vs. control) and the sequential period in the crossover design. The patient ID was defined as a random‐effects term. The secondary and exploratory end‐points were analysed using generalized linear mixed models (including logistic and Poisson regression) and Student's paired t‐tests. All parameter estimates were reported together with their 95% confidence intervals. All analyses were done using the R statistical software with the extension package lme4.The trial was designed to detect a clinically relevant within‐patient difference in 2 CAT score points in 1 year. In order to detect a statistically significant difference in the primary end‐point in a within‐patient crossover design with a power of 80% and a significance level of 5% (two‐sided), and considering an expected dropout rate of 5% and a learning effect explaining 25% of the effect size in the patients starting with the intervention phase, 175 patients should be included in the study.In total, 150 of 168 patients (89%) completed the trial. The baseline characteristics of all 168 included patients are summarized in Table P = 0.0015; Figure The overall mean CAT score was 15.6 points. The mean CAT increase was 1.8 (standard error 0.55) vs. 3.6 (standard error 0.56) points/year in the TC and SC groups, respectively (P = 0.062); and after TC, 8.8 .Satisfaction with care on a visual analogue scale (ranging from 0 to 10) at baseline was 8.2; at the end of SC, 8.5  in comparison with standard care. Satisfaction with care was already high before the intervention and increased further with TC compared to SC. With TC, we detected a higher number of moderate AECOPD. TC was associated with a trend towards fewer days in hospital and lower total COPD‐related costs compared with SC.Strength of this study is the multicentre, randomized controlled crossover design, so that every patient experiences both SC and TC, serving as his own control, minimizing selection bias and improving generalizability. The latter has also been supported by keeping inclusion criteria as open as possible and exclusion criteria at a minimum. By this, in fact, nearly all COPD patients were eligible for the study. To the best of the authors’ knowledge, the association between CAT values and telehealth interventions has not been investigated in such a manner until now.et al [The demonstrated bisection of the CAT increase over time reflects a highly relevant modification of the disease course of COPD. Looking at the above‐mentioned exploratory end‐points, one mechanism of how our TC procedure could have influenced disease course might be the better detection and consequently timely treatment of significantly more moderate exacerbations, which are underdiagnosed according to the literature . Recentlet al  could noet al , 13. In et al , 16, 17.et al  and in tSatisfaction with care significantly increased with TC, which we had already observed in a feasibility trial . Our expRegarding total days in hospital due to COPD and total COPD‐related costs , we could not find a statistically significant difference between TC and SC, but the actual numbers suggest that there might be a benefit by using TC. However, the current study was not powered to evaluate this hypothesis appropriately.Regarding important exploratory end‐points like discussed above, we had insufficient statistical power to show significant differences. Achieving this would have required considerably more included patients.Whilst receiving TC, the slope of the CAT increase – an indicator of the naturally progressive course of COPD – was significantly reduced by 50% (−1.8 points/year). Satisfaction with care – already high before the intervention – increased further with TC. With TC, we detected a higher number of moderate AECOPD, probably indicating a higher diagnostic sensitivity than without TC. This could be achieved with manageable effort and by trend lower total COPD‐related costs.The study was funded by Swisscom Health AG, SWICA Krankenversicherung AG, PneumRx GmbH, AstraZeneca AG and Boehringer Ingelheim Schweiz GmbH. None of these had any influence on design, conduct, interpretation or writing of the manuscript. Prof. Kohler reports personal fees from Bayer, Boehringer, Novartis, Astra and Mundipharma, all outside the submitted work, and grants and personal fees from Roche and GSK. Prof. Tamm reports grants from Vifor AG and Schwabe Pharma AG, all outside the submitted work. Prof. Stolz reports grants from AstraZeneca AG, Curetis AG and Boston Scientific and personal fees from AstraZeneca AG, Novartis AG, GSK AG, Roche AG, Zambon, Pfizer, Schwabe Pharma AG and Vifor AG, all outside the submitted work.F. Rassouli: Conceptualization (lead); data curation (lead); formal analysis (lead); funding acquisition (lead); investigation (lead); methodology (lead); project administration (lead); supervision (lead); visualization (lead); writing – original draft (lead); writing – review and editing (lead). A. Germann: Conceptualization (supporting); data curation (supporting); formal analysis (supporting); investigation (supporting); methodology (supporting); project administration (supporting); writing – original draft (supporting); writing – review and editing (supporting). F. Baty: Data curation (supporting); formal analysis (supporting); investigation (supporting); methodology (supporting); validation (supporting); visualization (supporting); writing – original draft (supporting); writing – review and editing (supporting). M. Kohler: Conceptualization (supporting); data curation (supporting); investigation (supporting); methodology (supporting); writing – original draft (supporting); writing – review and editing (supporting). D. Stolz: Conceptualization (supporting); data curation (supporting); investigation (supporting); methodology (supporting); writing – original draft (supporting); writing – review and editing (supporting). R. Thurnheer: Conceptualization (supporting); data curation (supporting); investigation (supporting); methodology (supporting); writing – original draft (supporting); writing – review and editing (supporting). T. Brack: Conceptualization (supporting); data curation (supporting); investigation (supporting); methodology (supporting); writing – original draft (supporting); writing – review and editing (supporting). C. Kähler: Conceptualization (supporting); data curation (supporting); investigation (supporting); methodology (supporting); writing – original draft (supporting); writing – review and editing (supporting). S. Widmer: Conceptualization (supporting); data curation (supporting); investigation (supporting); methodology (supporting); project administration (supporting). U. Tschirren: Data curation (supporting); investigation (supporting); project administration (supporting). N. A. Sievi: Data curation (supporting); investigation (supporting); project administration (supporting). M. Tamm: Conceptualization (supporting); data curation (supporting); investigation (supporting); methodology (supporting); writing – original draft (supporting); writing – review and editing (supporting). M. H. Brutsche: Conceptualization (supporting); data curation (supporting); formal analysis (supporting); funding acquisition (supporting); investigation (supporting); methodology (supporting); project administration (supporting); writing – original draft (supporting); writing – review and editing (supporting).Figure S1. Randomized crossover design .Figure S2. Left upper part: patient view of the e‐health platform. By pressing “COPD study”, patients were transferred to the questionnaire. Lower part: screenshot of daily online questions to be answered by the patients (“yes” or “no”). Right upper part: “cockpit” of the study team with color‐coded alerts in the right column under “Status today” . Under “Weekly status”, the alerts of the last 7 days are displayed. Patients could make comments and ask questions. Adapted and translated from our pilot study [ot study  with perClick here for additional data file.


The goal of this work was to evaluate if men who underwent microsurgical varicocelectomy would have improvement in serum testosterone (T) as well as serum 17‐hydroxyprogesterone (17‐OHP—An intratesticular T biomarker) in addition to semen parameters after operation.t test and Wilcoxon rank test. Correlation analysis was performed with the Spearman test.We conducted a prospective analysis of 30 men who underwent microsurgical varicocelectomy from December 2018 to September 2019. We assessed varicocele grade and laterality, serum T, serum 17‐OHP, serum follicle‐stimulating hormone (FSH), serum LH, and semen parameters in baseline and follow‐up. According to the data distribution, we reported the median and interquartile ranges and utilized the Mann‐Whitney U, Student's P = .018), concentration  and TMSC  after surgery. We neither found a change in serum T nor a change in intratesticular T (serum 17‐OHP) after varicocelectomy (P > .05). FSH, LH and T were similar both before and after varicocelectomy (P > .05).In the baseline, 9 (30%) men had 17‐OHP < 55 ng/dL and 21 (70%) men presented with 17‐OHP ≥ 55 ng/dL. Also, 19 men had TMSC < 9 million, including 6 men with azoospermia, 1 man with cryptozoospermia, and 11 men with TMSC ≥ 9 million. We found an improvement in most SA parameters of most men, which include concentration , motility , and TMSC . About seven (36.8%) men had TMSC upgraded to > 9. There was a significant change in volume (2.1 [1.5‐2.8] to 2.4 [1.7‐3.6] cc, Despite improvement in semen parameters following varicocelectomy, we did not see changes in either serum or intratesticular T. This suggests that improvement of semen parameters following varicocele repair could be from factors other than changes in androgen levels within the testis. It is found in 15% of the general population, but is present in up to 35% of men presenting with primary infertility and up to 80% of men presenting with secondary infertility.Leydig cells drive spermatogenesis via the secretion of testosterone (T), which acts on Sertoli and/or peritubular cells to create an environment which enables normal progression of germ cells through the spermatogenic cycle.r = .78, P < .0001). We published a recent study in J UrolWe based the correlation of 17‐OHP with ITT in Amory et al2After institutional review board approval, we prospectively followed men who underwent microsurgical varicocelectomy from December 2018 to September 2019. Indications for varicocelectomy were according to the AUA guidelines.www.labcorp.com) and from 33‐195 ng/dL (QUEST—www.questdiagnotics.com). We preferred to use the cut point of 55 ng/dL, because we wanted to use a representative sample of fertile controls and was similar to the cutoffs used by the large commercial laboratories. Therefore, we evaluated men based on serum 17‐OHP ≤ 55 ng/dL (low 17‐OHP) or 17‐OHP > 55 ng/dL . Also, patients were divided according to baseline total motile sperm count (TMSC) in two groups: TMSC < 9 and TMSC > 9. We excluded men without baseline and post‐varicocelectomy measurements, those receiving exogenous T.In order to develop a “standard” level for serum 17‐OHP, we performed a cross‐sectional analysis of a representative sample of 181 fertile controls  aged 39 + 11.2 years. The 25th, 50th, and 75th percentile for serum 17‐OHP was 55, 72, and 102 ng/dL. We used 55 ng/dL as the threshold to determine the lower limit of normal. The lower limit of normal established by commercial laboratories ranges from 27‐199 ng/dL  or medians and interquartile ranges [25‐75] were calculated according to the data distribution. Comparison of numerical variables between groups was performed using the U Mann‐Whitney, Student's 3Between December 2018 and September 2020, a total of 30 men fit the inclusion criteria and underwent varicocelectomy. Clinical and demographic characteristics of the analyzed men are evident in Table P > .05). In contrast, most SA parameters had significant improvement after surgery, including volume , concentration  and TMSC  (Table P > .05) (Table P = .019), while those with T ≥ 300 had change on T of 518.5 [458‐627.5] ng/dL to 505 [406.3‐624.5] ng/dL (P = .046).When analyzing serum hormones changes after surgery, there was no significant difference of 17‐OHP, FSH, LH, and T levels when compared to baseline , follow‐up T and follow‐up 17‐OHP  and follow‐up 17‐OHP and postoperative semen volume . But, we did not find significant correlation between preoperative 17‐OHP and SA concentration, TMSC, varicocele grade, and laterality (P > .05)   Table .4Varicocele has been proposed to be the cause of infertility in a considerable amount of men seeking to conceive. Varicocelectomy is a cost‐effective treatment for infertility, with microsurgical subinguinal or inguinal as the best techniques.In our study on 30 patients, sperm concentration, motility, and TMSC improved in 60%, 46.6%, and 60% of patients. Using the Samplaski et alPrevious studies showed that men with normal T are less likely to improve total T postoperatively.Our study not only has strengths, but it also has its limitations. The strengths include the novelty of the study, associating varicocelectomy with ITT and semen parameters. All procedures were performed using microsurgical technique by a single high‐volume surgeon and all semen analyses were performed by a single specialist, reducing bias in surgical technique as well as sperm analyses. We also tried to control variability in this study by performing all serum measurements between 6:00 and 10:00 am, in a single laboratory. Although we could not define a precise association between ITT and SA parameters improvement after varicocelectomy, our findings of concentration and TMSC improvement after surgery comes in agreement with other studies,Medical therapy for infertile men with low T is well described in the literature. However, noninvasive assessment of ITT and its use in practice remains poorly described. Serum 17‐OHP could be used to titrate medical therapy of men,In conclusion, microsurgical varicocele repair resulted in improvements in all evaluated semen parameters, but not in ITT/17‐OHP or serum T levels. The mechanism by which varicocele repair improves semen parameters appears to be driven by factors other than changes in androgen synthesis within the testicular microenvironment.Dr. Ramasamy reports other from Acerus Pharmaceuticals, grants and other from Aytu BioSciences, grants and other from Boston Scientific, grants and other from Coloplast, other from Direx, grants and other from Endo Pharmaceuticals, other from Nestle Health, outside the submitted work; Dr. Patel reports other from AMS, other from Nestle Health, other from Aytu, outside the submitted work; all other authors have nothing to disclose.