M = 12; telehealth M = 11) and maintained or improved correct independent responding across all targets from in‐person treatment (M = 75%) to telehealth treatment (M = 80%). These findings provide initial evidence that some clients with autism benefit from technician‐delivered telehealth services.Telehealth delivery of applied behavior analysis treatment has focused on supervision or staff and parent training, rather than the direct delivery of treatment to clients. The novel coronavirus (COVID‐19) crisis had the potential to significantly disrupt access to direct treatment for individuals with autism. We report a sample of 17 cases that transitioned from in‐person to telehealth delivery of treatment when shelter‐in‐place orders were issued. Of these cases, 76% of participants transitioned to technician‐delivered telehealth services whereas the rest transitioned to a caregiver‐implemented telehealth model. Participants continued to access a similar dosage of treatment hours per week in spite of the treatment model transition (in‐person  Telehealth is defined by the Health Resources and Services Administration as the “use of electronic information and telecommunication technologies to support and promote long‐distance clinical health care, patient and professional health‐related education, public health and health administration”  assessment and treatment services  at a distant site to deliver services in‐person to the client  pandemic and the subsequent containment measures led to unprecedented challenges to continued access to ABA treatment services for individuals with ASD and IDD CASP, . FederalTo that end, the purpose of this study was to conduct an archival analysis of data collected during the transition from in‐person direct services with telehealth clinical direction to a direct intervention telehealth model by an ABA provider agency during the COVID‐19 pandemic. Use of existing data affords researchers the opportunity to study natural events, has the advantage of reducing threats to internal validity such as experimenter bias, and can indicate the generalizability of results. Therefore, we used this archival data to a) examine client progress in skill acquisition programs before and after the transition, b) examine whether various skills were associated with differential success in this direct telehealth model, and 3) stimulate future research on technician‐delivered telehealth service delivery in ABA treatment.Ten Board Certified Behavior Analysts® (BCBAs®) providers from the same ABA organization contributed data to the sample of 17 client participants. That ABA organization had specialized in providing services under a partial in‐person telehealth model for the past 6 years. All BCBA clinicians were trained to provide clinical direction via a synchronous telehealth modality to Registered Behavior Technicians™ (RBTs™) who were delivering in‐person ABA services prior to COVID‐19. The clinicians and the RBTs had been employed for varying lengths of time at the organization  use the technology platforms for videoconferencing and client's electronic health records for data collection, (b) ensure client privacy and adhere to Health Insurance Portability and Accountability Act regulations when providing services via telehealth, (c) build rapport with families and technicians via telehealth, and (d) effectively provide coaching and feedback to the RBT working in‐person via synchronous videoconferencing. The RBTs had received prior training on how to join the videoconference for weekly clinical direction and electronic data collection when rendering in‐person direct services.Archival data were obtained from a sample of 17 children and adults with ASD  who were receiving technician‐delivered in‐person services and telehealth supervision  prior to COVID‐19 pandemic and transitioned to a full telehealth service model. Participants were included in the analysis if they transitioned from in‐person treatment delivered by an RBT with telehealth supervision to any model of full telehealth treatment (see data extraction procedures section below). Clinicians collaborated with the family and used their clinical judgement based on their knowledge of the client and prior performance on goals to select the specific telehealth service delivery model. Thus, many individuals served by the organization did not transition to a direct telehealth treatment model  and were not included in the analysis.All participants were receiving in‐person treatment delivered by an RBT with real‐time clinical direction via synchronous videoconferencing modalities prior to COVID‐19. Data from this type of service were needed to conduct the comparison analysis. Participants were not included in this analysis if they were new to services during COVID‐19 or immediately prior to COVID‐19 and had no in‐person comparison data available. Initially, 24 participants were identified for the archival analysis. Seven participants were excluded from the analysis because in‐person session data were not available for comparison. The in‐person data were unavailable because (a) the participant was new to treatment (n = 3), (b) the participant received new and modified goals for telehealth services (n = 1), (c) the clinician initiated a previously planned fading of treatment intensity (n = 1), (d) the participant had less than three sessions of telehealth data due to use of a combined treatment model  (n = 1), and (e) the parent re‐initiated in‐person services (n = 1).Each participant's electronic record was reviewed by the supervising BCBA. Electronic records were stored in a Health Insurance Portability and Accountability Act‐compliant, cloud‐based practice management software system  that included all data, graphs, and progress notes. Records included the client's treatment history, initial assessment, treatment goals, individual targets, daily session data for skills in acquisition and behavior reduction goals, and updated progress reports. Ethnicity, diagnosis, and severity level of ASD, family household, and healthcare plan information were obtained through a review of each participant's records.Participants included in the analysis were 17 clients aged 3‐17 years . Table Practice Parameters for Telehealth‐implementation of Applied Behavior Analysis: Continuity of Care During the COVID‐19 Pandemic . The prerequisite skills included: (a) basic joint attention skills, (b) basic discrimination skills, (c) basic echoic skills, (d) basic motor imitation skill, (e) ability to follow common one‐step directions, (f) ability to participate in session with limited caregiver assistance, (g) ability to sit independently at a computer or tablet for 8‐10 min, (h) safety concerns and challenging behavior are low and/or caregivers are safely and effectively able to manage any challenging behavior, and (i) client is compliant with instructions and prompts delivered by the technician via synchronous videoconferencing and by the caregiver, if needed. Participants were scored as having evidence of the skill if they demonstrated the skill during prior clinical observations and/or via formal testing, as reflected in the archival record.Existing data in the client's records were reviewed for evidence of nine recommended prerequisite skills for direct telehealth treatment outlined in the CASP CASP Practice Parameters recommended prerequisite skills demonstrated by participants who transitioned to a telehealth direct service delivery model. . Seventy six percent (n = 13) of participants demonstrated all of the recommended prerequisite skills. The majority of participants demonstrated seven of the nine prerequisite skills and indicators. Basic discrimination skills and basic motor imitation skills were evident for 100% of participants. Basic joint attention skills, basic echoic skills, ability to follow common one‐step instructions, and compliance with technician and/or caregiver prompts were each evident for 94% of participants. Additionally, 100% of participants either had low levels of challenging behavior or the caregiver was able to safely manage their child's challenging behavior.Table The clinician completed a review of medical records and treatment data pre‐ and posttelehealth direct sessions using a written task analysis with a visual job aid for extracting the data. Clinicians were instructed to enter the data into a spreadsheet using a template and a sample file for guidance.Skill acquisition data were included for a given target if there was at least one pretransition session for the target in acquisition during in‐person services and at least three sessions for telehealth direct sessions . We also included program data if the individual met the mastery criterion in fewer than three sessions posttransition across both in‐person and telehealth sessions . We analyzed data for up to five sessions pre‐and posttransition, if five sessions of data were available. We only included targets in acquisition that were measured using a percentage correct measurement system, which was 96% of skills targeted.M = 55%; range, 16% ‐ 86%). This high proportion of generalization and maintenance targets was programmed specifically as an antecedent procedure to minimize challenging behavior and increase contact with reinforcement during sessions. New targets were introduced during direct telehealth services for many participants; however, these data were not included in the current analysis because in‐person sessions with those targets were not available for comparison.Information about general skill domains initially taught during direct telehealth services for each participant is provided as technician‐delivered telehealth service model if the client participated independently via synchronous videoconferencing without caregiver support, (b) caregiver‐assisted telehealth model, if the RBT delivered the treatment via videoconference and the caregiver assisted with prompting as needed, but the caregiver was not the primary intervention agent responsible for delivering treatment, and (c) a caregiver‐implemented telehealth model if the RBT guided the caregiver to implement all components of the intervention. Most clients received a combination of telehealth service delivery models throughout treatment. For example, some clients participated in technician‐delivered telehealth treatment for most targets but moved to a caregiver‐implemented telehealth model for adaptive living skills.Each target taught during a telehealth session was coded to determine what type of telehealth model was used to teach the skill. All telehealth service models involved an RBT providing instruction via videoconferencing to either the child or caregiver. The main difference between models was the amount of caregiver support required. Targets were coded as (a) in acquisition if the client had not yet demonstrated mastery of the skills as defined by their individual treatment plan ; (b) generalization if the client had met the initial mastery criteria for the target, but had not yet demonstrated the ability to perform the skill under different conditions; or (c) maintenance if the client had demonstrated stimulus and response generalization and the behavior was being monitored for continued demonstration of the skill.Skill acquisition targets were coded and assigned to one of three categories to gain a better understanding of the treatment phase since the expected behavior change varied based on the different types of treatment trials. Targets were coded as (a) same if their average correct independent responding during telehealth sessions was within half of one standard deviation of their in‐person sessions. Average responding that fell above this range was coded as improved and responding that fell below this range was coded as worsened. As a result, clinically nonrelevant changes in performance  were coded as ‘same’ since this difference was likely not outside of their expected session variation. Furthermore, the use of half of one standard deviation resulted in a highly conservative labeling criteria, which ensured that performance was not overestimated. Last, we calculated the percentage of targets that were the coded as the same or improved by dividing the number of targets labeled as same/improved outcomes by the total number of targets and multiplying by 100.The average percentage of correct independent responding for all skill acquisition targets was calculated separately for in‐person and each telehealth direct service model. We then categorized the participant's overall outcome as ‘same,’ ‘improved,’ or ‘worsened’ for each target. In order to establish an objective labeling criterion that accounts for typical performance variations across sessions, we operationally defined participant responses as Intercoder agreement was completed for 33%  of skill acquisition targets across all participants. A second independent coder was trained to review the data using the same procedures described above. In addition, the independent coder and first author reviewed data jointly and reached consensus  on the data analysis during one training session. We used a point‐by‐point comparison method and scored an agreement if the session data matched exactly and a disagreement if session data did not match for each target. Next, we calculated the percentage by dividing the agreements by the agreements plus disagreements and multiplying by 100. Agreement averaged 99% .Table F = 1.02, MSE = 205.7, p = .39).Figure F = 1.83, MSE = 735.0, p = .16).For targets in the acquisition phase of teaching , average correct independent responding was 55% (SD = 19%) for in‐person direct services, 60% (SD = 23%) for telehealth direct, 74% (SD = 18%) for caregiver‐assisted telehealth, and 66% (SD = 14%) for caregiver‐implemented services. Overall average across all telehealth models was 65%. Similar to the analysis reported above, results of an ANOVA indicated that session performance was similar across service delivery models  across all targets in in all phases of teaching. The remaining five participants had a decrease in performance . Similarly, 12 participants maintained or improved performance for targets in the acquisition phase of teaching across all telehealth models  and only five participants demonstrated a decrease in performance .Providers have been faced with a rapid transition from in‐person service delivery models of care to telehealth service delivery models to support families while maintaining social distancing during the COVID‐19 pandemic. To date, only two studies have been published on the direct service delivery of ABA treatment video synchronous videoconference, with participants indicating high levels of satisfaction with the treatment and positive outcomes  for individuals diagnosed with ASD. Notably, we were able to reestablish care for one participant (P8) who was experiencing a significant disruption in care prior to COVID‐19 due to living in a rural community with a severe provider shortage. Importantly, the results from just the initial sessions of direct telehealth treatment demonstrate maintained or improved responding for targets that were still in acquisition across all telehealth models for all participants . Moreover, participants retained a similar dosage of treatment services via telehealth (M = 11 hr/week) when compared to their prior in‐person service dosage (M = 12 hr/week).Ongoing in‐person ABA services were successfully transitioned to telehealth services, with minimal gaps in care  compared to those participants who demonstrated all the CASP‐recommended prerequisite skills . Caregiver responsibilities also prevented parents from providing the full dosage of treatment . Clinicians did not have access to the CASP‐recommended prerequisite skills during this transition and utilized their clinical judgment and family preferences to select an appropriate telehealth model. Despite the natural variability in treatment  that occurred as a result of the unplanned transition to a direct telehealth service delivery model, these results suggest that clinicians were able to provide continuity of care to families and participants who were successful in continuing to maintain and/or learn skills across all models.Those with the fewest recommended skills and characteristics  were assigned to the caregiver‐implemented model and experienced an average of 8 hr per week reduction in service delivery hours . The remaining participants averaged the same dosage of treatment posttransition . The reduced hours associated with the caregiver‐implemented model may have been due in part to these participants receiving a higher dosage of services pretransition  can benefit from some type of technician‐delivered telehealth service delivery model. Gaining an understanding of heterogeneity of treatment effect is critical for clinicians to evaluate how well a treatment can be expected to work for a subset of the population (Hagopian, Several limitations should be noted. This analysis captured the available skill acquisition data for clients who transitioned from one model to the other. However, clients were not randomly assigned to this condition and there was no explicit control condition. Thus, we cannot be certain what level of outcome would have been achieved if in‐person services had continued. Due to the extraordinary circumstances brought by the COVID‐19 crisis, the analysis was restricted to outcomes achieved under the direct telehealth treatment model compared to those achieved under the prior in‐person direct model. Follow‐up data also were not collected due to time needed for long‐term evaluation of the direct telehealth service delivery model. Conclusions regarding the relevance of the recently published practice parameters CASP,  also areAdditional research is needed to investigate the direct implementation of ABA treatment via both synchronous and asynchronous telehealth modalities, including optimal session timing, dosage, and structure. Comparison of in‐person services, partial in‐person telehealth services, and each direct telehealth service delivery is also needed in our field. Research should evaluate the optimal dosage of direct treatment and clinical oversight to guide health insurance funders on best practices and ensure optimal client outcomes (Lindgren et al., Additional research also is needed to identify strategies for assessing and preteaching identified prerequisite skills before an individual completely benefits from a full telehealth service delivery model. For example, some clients at this agency initially were not considered candidates for telehealth services based on prior observations of their skills. However, direct testing of the CASP prerequisite skills revealed that those individuals demonstrated these skills, and they subsequently successfully participated in limited telehealth direct service delivery sessions. Therefore, it will be critical to formally assess a client's skills to determine baseline levels and preteach necessary prerequisite skills. As the field continues to implement treatment directly via telehealth, clinical research will be needed to further identify optimal programs and skills to teach through this modality.Prior to the COVID‐19 pandemic, the healthcare industry was leveraging technology to address health access disparities (Rutledge et al., The COVID‐19 pandemic drastically changed the way healthcare is delivered and may have enduring impacts on healthcare service delivery. Although additional research is needed, behavior analysts leveraged technology and their knowledge of the basic principles and methodologies of ABA to continue to deliver medically necessary care to clients during this crisis. This study offers initial evidence of the promising effects of direct treatment via telehealth practice in ABA treatment.Appendix S1: Supporting informationClick here for additional data file.


Understanding spatiotemporal population trends and their drivers is a key aim in population ecology. We further need to be able to predict how the dynamics and sizes of populations are affected in the long term by changing landscapes and climate. However, predictions of future population trends are sensitive to a range of modeling assumptions. Deadwood‐dependent fungi are an excellent system for testing the performance of different predictive models of sessile species as these species have different rarity and spatial population dynamics, the populations are structured at different spatial scales, and they utilize distinct substrates. We tested how the projected large‐scale occupancies of species with differing landscape‐scale occupancies are affected over the coming century by different modeling assumptions. We compared projections based on occupancy models against colonization–extinction models, conducting the modeling at alternative spatial scales and using fine‐ or coarse‐resolution deadwood data. We also tested effects of key explanatory variables on species occurrence and colonization–extinction dynamics. The hierarchical Bayesian models applied were fitted to an extensive repeated survey of deadwood and fungi at 174 patches. We projected higher occurrence probabilities and more positive trends using the occupancy models compared to the colonization–extinction models, with greater difference for the species with lower occupancy, colonization rate, and colonization:extinction ratio than for the species with higher estimates of these statistics. The magnitude of future increase in occupancy depended strongly on the spatial modeling scale and resource resolution. We encourage using colonization–extinction models over occupancy models, modeling the process at the finest resource‐unit resolution that is utilizable by the species, and conducting projections for the same spatial scale and resource resolution at which the model fitting is conducted. Further, the models applied should include key variables driving the metapopulation dynamics, such as the availability of suitable resource units, habitat quality, and spatial connectivity. We show that the projected future trends of fungal populations are sensitive to type of modeling performed (occupancy patterns vs. colonization–extinction dynamics), the rarity of the species, the spatial scale of model fitting, and the resource‐unit data resolution. Our conclusions are based on Bayesian modeling of an extensive resurvey dataset. Such knHabitat patches naturally appear and disappear through succession and disturbance, but in production landscapes, these processes are largely replaced by management and conservation actions  fit to a single (static) snapshot of presence/absence data across the landscape , and the survey area covered  species with different landscape‐scale occupancy when using occupancy versus colonization–extinction models. The occupancy models are based on data from one point in time, while the colonization–extinction models are based on data from two points in time. As data suitable for occupancy models are available and frequently used for many species and many geographical areas, it is important to find out how the trends and magnitudes of change that occupancy models reveal differ from the ones revealed by colonization–extinction models for which data are currently scarce. Colonization–extinction models are expected to be more realistic for predicting changes as they focus on rate of changes (of occupancy). We hypothesize that the difference in the projected future occupancy between occupancy and colonization–extinction models is greater for a species with lower landscape‐scale occupancy because rare species can be expected to have slower colonization–extinction rates and therefore track changes in forest landscapes with a greater delay than common species. We further test for differences in projected future occupancies between modeling the data at (b) three different spatial modeling scales  and (c) two resource‐unit resolutions (two different minimum diameters for deadwood to be included) to find out how scale and resolution influence predictions of future population trends. Inferences were made based on projections of occupancy of two model species in forest production land and in land set aside from production across the whole boreal zone of Sweden. The projections were obtained through stochastic simulations using the occupancy and colonization–extinction models fitted at different spatial scales and resource‐unit resolutions. Building the models was part of our fourth aim, specifically (d) to test which local and regional environmental variables explain the occupancy and colonization–extinction dynamics at different spatial scales and resource‐unit resolutions.22.1We obtained the large‐scale extensive data on colonization–extinction dynamics by surveying spruce deadwood and fruit bodies of the focal polypore fungi in 174 forest patches across southern and central Finland once in 2003–2005  and covered a range of forest types: clear‐cuts with retention trees , woodland key habitats , and managed forests . In each forest patch, in both surveys (2003–2005 and 2014), we surveyed the two fungal species (Phellinus ferrugineofuscus and P. viticola) and deadwood both in each cell and in the remaining patch area. See Appendix A forest patch is a contiguous and homogeneous forest area that is surrounded by other land types or forests of different age or tree species Figure . The sur2.2For each species, we fitted hierarchical Bayesian state‐space models to the presence–absence data of the species at three spatial modeling scales  and two deadwood resource resolutions (diameter ≥ 5 cm or ≥ 15 cm). We included covariates collected for different spatial modeling scales that we hypothesized would explain the occupancies and colonization–extinction dynamics of the focal species Appendix . For theA detailed description of the occupancy and colonization–extinction models at the cell level is provided in Appendix https://snd.gu.se/en.The covariates to retain in the final fitted models were determined with forward stepwise model selection. This model selection was based on overlap of 95% credible intervals with 0, reduction in deviance, and biological knowledge on the species, as suggested by Gelman and Hill . The mod2.3To answer our study questions, we utilized available projections of forest conditions on National Forest Inventory (NFI) plots in adjacent boreal Sweden between 2010 and 2,110, the nationwide Forestry Scenario Analysis by the Swedish Forest Agency  and the smallest spatial modeling scale (20 × 20 m). For P. ferrugineofuscus, the colonization and extinction rates were comparable between the fine resource resolution at the smallest spatial modeling scale and the coarse resource resolution at the largest spatial modeling scale. At the fine resource resolution, the colonization rate increased and extinction rate decreased with increasing spatial modeling scale. Similarly, at the coarse resource resolution, the largest spatial modeling scale had the highest colonization rates and the lowest extinction rates. Extinctions resulted both from host logs disappearing due to decomposition and stochastically where suitable logs were recorded in both surveys.The species with the highest occupancy in the landscape, ns Table . We obse3.2P. ferrugineofuscus, the responses—probabilities of occurrence and colonization—were explained by the volume of spruce logs at the cell scale (here reflecting the presence of large logs), whereas the plot‐scale responses were explained by stand age and the patch‐scale responses by stand age or connectivity  and connectivity at the cell and plot scales, and the density of spruce logs at the patch scale. The best‐fitting measure of connectivity for P. ferrugineofuscus was the presence/absence of old (≥120 years) spruce forests within a distance that corresponds to a mean dispersal distance of 1 km. For P. viticola, two measures of connectivity were important: the volume of spruce or presence/absence of spruce in old forests within a distance that corresponds to a mean dispersal distance of 10 km. Deadwood resource resolution had an influence on whether the density of logs was selected or not in the models for P. viticola.For ty Table . The amoty Table , and hen3.3P. ferrugineofuscus and from 0.88 to 1 for P. viticola based on the colonization–extinction models. Occupancy models were more sensitive to the chosen resource resolution and spatial modeling scale than colonization–extinction models. Specifically, there was larger variation among the projection trajectories when using the occupancy models . However, here the .08 probability of decline also means a 1–.08 = .92 probability of increase, which is thus detected by the fine resource resolution.The magnitude of future increase in occupancy depended strongly on the spatial modeling scale  Figures  and 3. FP. viticola, we predicted clearly a more positive future population development with the fine resource resolution (≥5 cm) than with the coarse resolution (≥15 cm), and the precision of the prediction was higher for the coarse resolution  but less probable (.47 and .38) based on occupancy models that used the fine resolution. Projections based on the occupancy models for P. ferrugineofuscus showed a decline in the production land only for the models based on the coarse resource resolution; for the fine resolution, the trends were more stable  decline in the production land only when we modeled at the coarse resource resolution; at the fine resolution, the probability of decline was zero  had a great impact on the future predictions. For on Table . For P. e Figure . Project.47 and .8 based oo Figure . We pred4When making predictions for ecological systems, it is seldom clear from the outset which models to use and at what scale and resolution the modeling should be performed , simulating detailed small‐scale deadwood dynamics may be inefficient. For such species, model fitting and projection simulation at a larger scale (here plot or patch) may be more appropriate, especially if the general question of the study concerns a landscape or region. Thus, conducting modeling and projection simulations at a more aggregated spatial resolution is acceptable. On the other hand, when modeling at a larger spatial scale, more distal predictors  are selected—these affect the species more indirectly than the proximal predictors they replace  as the significant covariate of resource availability. With different minimum sizes of deadwood inventoried, the deadwood quantities such as density and volume of deadwood—the measures of resource availability used as covariates in the models and projections—may also change (Hottola, Ovaskainen, & Hanski, P. ferrugineofuscus whose colonization probability increases with diameter (Jönsson, Edman & Jonsson, Resource‐unit resolution can have a considerable influence on the predictions of future population development. For 4.4Despite the differing occurrence probabilities and rate of change in future occupancies produced by the occupancy and colonization–extinction models, the direction of the change was usually the same. This is partly explained by the fact that the covariates selected for the colonization probabilities were, in most cases, the same as those selected for the occupancy probabilities. Arguably, precise predictions of biological responses to environmental change, especially if extrapolating beyond current conditions and into the future, require elaborate mechanistic process‐based models, driven by the detailed life history of the species (Evans et al., There are no competing interests to report.JN, PJH, JS, and TS conceived the ideas and designed methodology; JN, JS, and TS designed the data collection; PJH, LM, and JN analyzed the data; OK wrote the software to simulate deadwood decomposition; AL conducted the simulations of forest dynamics and management; and JN, PJH, and TS led the writing of the manuscript. All authors contributed critically to the drafts and gave final approval for publication. Click here for additional data file.


Early warning systems involve the routine monitoring and recording of vital signs or clinical observations on specifically designed charts with linked escalation protocols. Meeting criteria for abnormal physiological parameters triggers a color‐coded or weighted scoring system aimed to guide the frequency of monitoring, need for, and urgency of clinical review. Color‐coded systems trigger a clinical response when one or more abnormal observation is recorded in the red zone or two or more mildly abnormal parameters in the amber zone. The principle of maternity‐specific early warning systems to structure surveillance for hospitalized women is intuitive. The widespread use and policy support, including recommendations following confidential enquiries and from the National Health Service Litigation Authority, is not, however, currently backed up by a strong evidence base. Research is required to develop predictive models and validate evidence‐based maternity‐specific early warning systems in the general maternity population. CIconfidence intervalEWSearly warning systemICUintensive care unitMEOWSmodified early obstetric warning scoreCurrent MEOWS trigger thresholds vary, based arbitrarily on clinical consensus or expert opinion. Limited evidence links implementation of MEOWS with improved outcomes in the general pregnant population and further research is required to develop predictive models and validate evidence‐based MEOWS.1Maternal deaths in the UK are rare (4.65 per 100 000 live births in 2012‐2014) compared with the global burden (216 per 1 00 000 live births in 2015).Delay is a major contributor to maternal mortality. The effective management of an acutely unwell pregnant woman can be challenging and requires an appropriate and timely response. An approach to tackling this clinical challenge is the use of early warning systems (EWS). EWS involve the routine monitoring and recording of vital signs or clinical observations on specifically designed charts with linked escalation protocols. They list criteria for abnormal physiological parameters that trigger a color‐coded or weighted scoring system aimed to guide the frequency of monitoring, need for, and urgency of clinical review. Color‐coded systems trigger a clinical response when one or more abnormal observation is recorded in the red zone or two or more mildly abnormal parameters in the amber zone. In this commentary we will examine the evidence base behind modified early obstetric warning scores (MEOWS) and discuss the issues surrounding current practice.The UK Confidential Enquiry into Maternal Deaths published in 2007 recommended the introduction of MEOWS for all acute obstetric admissions, including women in early pregnancy.Subsequent reports have recommended their use but have also acknowledged their shortcomings and the lack of an evidence‐based standardized approach in maternity populations. The latest report published in 2016 raises the issue of ensuring that MEOWS remain fit for purpose in view of developments in modern information technology, near patients’ testing, and sepsis red flags.A principal component of an EWS relies on a phase of decompensation in the physiological parameters measured; signaling an opportunity to intervene and prevent further deterioration. Concerns have been raised in translating this principle directly to the pregnant population with its unique physiological adaptations, which may allow for a longer period of apparent compensation but one that can be followed by an abrupt deterioration. For this reason the level of consciousness as a parameter in an early warning score has been criticized. A reduced or altered level of consciousness is not an early warning sign but a red flag indicating established illness.2A recent analysis of charts of vital signs from consultant‐led maternity units across the UK demonstrated considerable variation in EWS and escalation protocols.Bick et al performed a cross‐sectional survey across the maternity services of the UK National Health Service.A systematic review conducted to aid in the development of an Irish national guideline looked at 33 studies separated into four categories—descriptive studies, clinical practice guidelines, effectiveness studies, and development and validation studies.An ethnographic study conducted in two UK hospitals over a 7‐month period also found that charts were used at the health provider’s discretion.th CEMACE report. Outcomes at 30 days were retrieved from hospital records and patients’ notes including morbidity, death, admission to ICU, and discharge. The data analyzed were tested for associations between abnormal triggers and the presence of morbidity by calculating the relative risk for individual parameters. They report 89% sensitivity (95% CI 81%‐95%) and 79% specificity (95% CI 76%‐82%) and concluded that MEOWS charts are a useful bedside test for predicting morbidity. A low positive predictive value of 39% indicated a low prevalence of maternal morbidity. The authors of this study conclude that this supports the widespread use of MEOWS for all obstetric patients. Although MEOW’s ability to identify morbidity is promising, further evidence is needed to demonstrate the benefit of introducing this to the pregnant population as a whole. This would include its benefit over established clinical practice and health economic benefits.A validation study looking prospectively at 676 consecutive maternity inpatient admissions reviewed MEOWS triggers and morbidity.A retrospective case‐controlled study carried out across 2 tertiary obstetric units in Canada extracted MEOWS variables in the 24 h prior to women’s admission to the ICU.P = 0.01) and composite maternal morbidity (P = 0.01) comparing baseline and after the implementation of the maternity early warning trigger tool. The authors suggest that areas to focus on in the development of an EWS are ease of use and an alert frequency low enough to prevent alarm fatigue but high enough for clinicians to associate value with the trigger.Shields et al conducted a pilot study over 6 sites in the USA following the implementation of a maternity early warning trigger tool.P < 0.05) were weighted following multiple logistic regressions and used to create a statistical obstetric trigger system. The primary outcome was survival. They reported an area under the receiver operator curve of 0.995 (95% CI 0.992‐0.998) for the resulting statistical score. Additional variables were then added to create a clinical score. This included high systolic and diastolic blood pressure and temperature >38°C, although these variable were not demonstrated to be statistically significant. Their addition to this score was felt necessary to make the system clinically relevant and acceptable and did not result in a significant decrease in the score’s discriminatory ability. A sensitivity of 97% and a specificity of 87% were quoted with a score of 12. This may indicate it is able to discriminate between survivors and non‐survivors but it does not validate a system for the early detection of deterioration. Although this article reports on a large data set, it cannot be directly translated to the ward setting and further external validation is required. Furthermore, a retrospective secondary analysis of data has potentially missed clinically relevant data. The non‐ventilated respiratory rate was absent from 96% of the cases that resulted in death in the validation set of data.Carle et al performed a retrospective secondary analysis on physiological data collected for a routine audit from a critical care obstetric population.3The principle of a maternity‐specific EWS to structure surveillance for hospitalized women is intuitively sound. Their current widespread use and policy support, including recommendations following confidential enquiries and from the National Health Service Litigation Authority, are not, however, currently backed by a strong evidence base. There is limited evidence linking the implementation of MEOWS charts to improved outcomes in the general pregnant population. Deaths in the UK obstetric population are rare and the challenge is to equate the impact of MEOWS with meaningful outcomes. There appears to be room for improvement as substandard care continues to be highlighted in recurrent confidential enquiries.The wide variation that exists in chart layout and implementation undermines confidence in the validity of MEOWS.AS has developed an automated vital signs monitoring device  with Microlife, incorporating a traffic light triage system. AS is principle investigator on the ongoing CRADLE Projects. JS is co‐investigator on the CRADLE 3 trial.


Congenital protein C deficiency is an important cause of thrombosis in humans but is not described in dogs. A 4‐year‐old Hungarian Vizsla was presented for investigation of acute onset of ascites. Computed tomography of the chest and abdomen and echocardiography confirmed a large thrombus within the right ventricle. A cause for thrombosis was not initially identified. The clinical signs resolved rapidly and the dog was administered clopidogrel and discharged. Plasma protein C activity measured 2 and 6 weeks later was markedly lower than expected on both occasions. All known causes of acquired protein C deficiency were excluded, and the dog was diagnosed with a congenital protein C deficiency. After diagnosis, the administration of clopidogrel was stopped and administration of rivaroxaban was started. The dog remains well with no evidence of recurrent thrombosis with 6 months of follow‐up. CTcomputed tomographyDOACdirect oral anticoagulant1Protein C is a circulating, vitamin K‐dependent protease produced by the liver with importance in the regulation of coagulation. The activated form of protein C acts as an anticoagulant by inactivating factors Va and VIIIa and thereby regulating the subsequent thrombin generation. Consequently, deficiencies of this protein predispose to venous thrombotic events. Deficiencies in protein C can be hereditary or acquired. While severe congenital deficiencies in people are associated with clinical signs during the neonatal period, mild deficiencies can be asymptomatic or result in recurrent episodes of venous thrombosis later in life.2A 4‐year, 9‐month‐old male neutered Hungarian Vizsla was referred for investigation of a 2‐3 day history of acute onset abdominal enlargement and SC edema. The owner reported acute onset of clinical signs, which had initially progressed over the first 48 hours. Abdominal effusion was documented during ultrasound examination at the referring practice. The dog was reported to be otherwise well with no previous medical problems.At the time of presentation, the dog was bright and alert. On physical examination, the abdomen was distended and there was localized SC edema affecting the caudoventral abdominal wall and inguinal region. No other abnormalities were detected on physical examination.d‐dimer concentrations were elevated on the day of presentation  and the day after presentation (>500 to <1000 ng/mL)No abnormalities were detected on initial hematology. Biochemistry showed only mild‐moderate elevation in serum alanine aminotransferase  activity. Postprandial bile acids were within reference range . No abnormalities were detected on full urine analysis. Urine protein : creatinine ratio was 0.15 (reference range 0.0‐1.0), and urine specific gravity was 1.040. Prothrombin and activated‐partial thromboplastin times were within reference ranges. Plasma fibrinogen concentration was slightly below reference range on the day of presentation  but was found to be normal on the day after presentation (3.33 g/L). An echocardiogram was performed by a board‐certified specialist in veterinary cardiology and confirmed the presence of a space‐occupying lesion within the right ventricle, with part of the lesion extending into the right atrium during systole. Left ventricular end‐diastolic and systolic diameters were normal with normal systolic function and normal left atrial size. Right and left ventricular outflow velocities were normal, and there was no evidence of pulmonary hypertension or elevated right ventricular pressure.Computed tomographic (CT) imaging of the thoracic, abdominal, and pelvic cavities was performed under general anesthesia, precontrast and postcontrast  along with an ECG‐gated cardiac CT. The images were reviewed by a board‐certified specialist in veterinary diagnostic imaging. A lobulated, approximately 2‐cm diameter mass‐lesion causing a filling defect within the contrast pool of the right ventricle was seen. The heart appeared otherwise unremarkable. A moderate‐large volume of abdominal free‐fluid was seen along with SC fluid accumulation affecting the ventral abdominal and inguinal regions. No other relevant changes were seen and all visualized vascular structures appeared normal.Analysis of the abdominal fluid (collected by abdominocentesis and performed before imaging) confirmed a protein‐rich transudate . Nucleated cell count was low (2.78/μL) and consisted of mixed neutrophils, lymphocytes, macrophages, and mesothelial cells. No atypical cells were seen.The dog was hospitalized for 2 days for observation and was treated with clopidogrel  4 mg/kg PO q24h to be continued long term. At the time of discharge from hospital, both the gross abdominal distension and severity of SC edema appeared significantly improved. The dog was reexamined 1 week after discharge and both the abdominal distension and SC edema had resolved and the dog was reported to be well at home. Repeat echocardiography at this point showed a subjective reduction in the size of the ventricular thrombus. Repeat physical examination after 3 weeks detected no abnormalities and the thrombus could no longer be visualized on echocardiogram. There were no echocardiographic changes suggestive of pulmonary hypertension.g for 15 minutes. The citrated plasma was then pipetted from the citrated tubes into plain conical tubes, taking care to avoid the plasma‐cell interface. The citrated plasma was respun for a further 15 minutes, and the plasma was then transferred into a plain tube, taking care to avoid aspiration of any residual cells in the conical part of the tube. Serum was prepared by centrifuging whole blood at 3000g for 10 minutes. Samples were frozen at −20°C within 30 minutes of sampling. Samples were transported to the laboratory, frozen overnight, and all samples were analyzed within 1 week. Measurement of protein C activity by Chromogenix Coamatic chromogenic assay  on a Sysmex CS2000i automated analyzer  was markedly reduced at both 2 and 6 weeks after presentation being 47.5 and 8.7 iu/dL, respectively (canine reference range 75%‐135%). Phenotypic assays for antithrombin activity and activated protein C resistance were normal with reference to canine normal ranges in the literature for same‐type assays. An immunoturbidimetric antigenic assay for free protein S and ELISA for protein C failed to provide readings as the captured antibodies did not cross‐react with canine proteins. Antiphospholipid antibodies have been reported in dogs,Blood drawn by jugular venipuncture at 2 and 6 weeks after initial presentation was submitted to a commercial human laboratory to investigate the possibility of a congenital thombophilic disease. Measurement of prothrombin and activated‐partial thromboplastin times were repeated at both time points and results were within normal limits on both occasions. The dog was clinically well at the timing of both samples. Both platelet‐poor plasma and serum were submitted. For preparation of platelet‐poor plasma, blood was initially collected into 3.2% sodium citrate tubes, which were centrifuged at 2000The dog was diagnosed with a congenital protein C deficiency leading to thrombus formation. Administration of the previously prescribed clopidogrel was stopped and administration of the selective direct factor Xa inhibitor, rivaroxaban  1 mg/kg PO q24h, was started. The dog remains clinically well at home with approximately 6 months follow‐up.3This is a report describing a congenital protein C deficiency in a dog leading to clinical signs associated with thrombosis. Based on the history and physical examination findings in this case, a disease‐causing venous congestion from the abdomen and abdominal wall was initially suspected as the cause for the clinical signs. Unexpectedly, the thrombus was detected within the right ventricle and the authors suspect that this had recently embolized from the caudal vena cava and previous vascular obstruction due to this thrombus was the cause for the reported clinical signs. The rapid resolution of clinical signs without specific intervention would support this hypothesis. On consideration of diseases known or suspected to result in a hypercoagulable state in dogs, a predisposing cause for thrombus formation had not been identified during initial investigations. Bile‐acid simulation testing returned normal results and the presence of a portosystemic shunt vessel was excluded based on the results of the CT. There was no evidence of a concurrent inflammatory state and the dog did not fulfill the requirements for making a diagnosis of disseminated intravascular coagulopathy. This was the reason for pursuing investigation of conditions known to predispose to thrombosis in human patients.A diagnosis of congenital protein C deficiency is made in human patients upon documenting a persistent decrease in plasma protein C concentrations in the absence of any of the previously mentioned acquired causes of deficiency.Chromogenic assays are recommended for initial evaluation of protein C deficiency in humans because interferences that falsely prolong or shorten clotting times in clot‐based assays cannot operate in chromogenic assays whose analytical principles are independent of coagulation pathways.Current recommendations from the American College of Chest Physicians endorse the use of anticoagulant medication for an indefinite period in patients suffering an unprovoked venous thromboembolic event.The clinical signs associated with thrombosis resolved relatively quickly in this case and the dog remains well at home 6 months after initial presentation with no clinical signs suggestive of recurrent thrombosis. The dog is to remain on daily rivaroxaban indefinitely. Congenital thrombophilic disease should be considered in dogs with thrombosis for which an underlying disease classically thought to predispose to a hypercoagulable state cannot be found. Long‐term treatment with DOACs is likely appropriate.Gary Moore was employed by the commercial laboratory at which the testing for potential thrombophilic diseases was performed.Authors declare no off‐label use of antimicrobials.Authors declare no IACUC or other approval was needed.Authors declare human ethics approval was not needed for this study.


Clusterin is a topologically dynamic chaperone protein with the ability to participate in both intra‐ and extacellular proteostasis. Clusterin has been shown to be upregulated in the spinal cord of patients with amyotrophic lateral sclerosis (ALS) and has been shown to protect against TDP‐43 protein misfolding in animal and cell models. Previous studies have demonstrated an association between the pathological burden of TDP‐43 misfolding and cognitive deficits in ALS, demonstrating high specificity, but correspondingly low sensitivity owing to a subset of individuals with no evidence of cognitive deficits despite a high burden of TDP‐43 pathology, called mismatch cases.post mortem brain tissue of mismatch cases. We employed a modified in situ hybridization technique called BaseScope, with single cell, single transcript resolution.Hypothesizing that differences in the ability to cope with protein misfolding in these cases may be due to differences in expression of protective mechanisms such as clusterin expression, we assessed the spatial expression of clusterin and another chaperone protein, HspB8, in Mismatch cases demonstrated differential spatial expression of clusterin, with a predominantly neuronal pattern, compared to cases with cognitive manifestations of their TDP‐43 pathology who demonstrated a predominantly glial distribution of expression.Our data suggest that, in individuals with TDP‐43 pathology, predominantly neuronal expression of clusterin in extra‐motor brain regions may indicate a cell protective mechanism delaying clinical manifestations such as cognitive dysfunction. SOD1 mutation post mortem brain and spinal cord tissue, TDP‐43 is found to be pathologically phosphorylated and C‐terminally truncated in cytoplasmic aggregates Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease characterized by muscle denervation and atrophy leading to paralysis and death. These motor features are often accompanied by cognitive dysfunction in as many as 50% of ALS patients with up to 15% of patients exhibiting features of frontotemporal dementia (FTD) Protein misfolding, aggregation and subsequent cell death are common pathways in all neurodegenerative diseases exhibiting cognitive phenotypes. However, cognitive defects in ALS, while common, typically affect multiple domains and there is a distinctive cognitive profile in ALS compared to other neurodegenerative diseases, and cognition is therefore best assessed by an ALS specific cognitive test such as the Edinburgh Cognitive ALS Screen (ECAS). The ECAS is a neuropsychological assessment specifically designed to assess the cognitive deficits associated with ALS, notably (i) verbal fluency, (ii) executive function and (iii) language While several studies have shown an association between TDP‐43 pathology and cognitive deficits, these studies have consistently identified a subgroup of patients who have abundant TDP‐43 pathology and no corresponding cognitive defects in situ hybridization technique called BaseScope. In doing this, we demonstrate spatial expression differences in clusterin between cases with cognitive deficits and mismatch cases without cognitive manifestations, highlighting an important protective mechanism.Within our cohort of ALS brain bank patients, 27 patients had undergone standardized cognitive testing using ECAS during life. Of these 27 patients, following in depth neuropathological assessment of TDP‐43 pathology, we were able to identify six patients who fit the classification of a mismatch case, with abundant TDP‐43 pathology and a normal ECAS score. For comparison, we identified 11 cases who had TDP‐43 pathology with evidence of mild cognitive deficits. Within this cohort we analysed the spatial expression of clusterin and HspB8, with single cell, single transcript resolution, employing a novel modified post mortem. In our analysis, we sought to assess protective mechanisms (cell‐type specific clusterin and HspB8 expression). All clinical data including the ECAS were collected as part of Scottish Motor Neurone Disease Register (SMNDR) and Care Audit Research and Evaluation for Motor Neurone Disease (CARE‐MND) platform  and all patients consented to the use of their data during life. Control brains were selected from the sudden death brain bank and therefore have not died of a chronic illness or neurological condition. All control cases are rigorously assessed by experts, both clinically and neuropathologically, to rule out any evidence of disease, including the use of an extensive standardized panel of immunohistochemistry, with pathology being assessed using well‐defined and published grading systems. All post mortem tissue was collected via the Edinburgh Brain Bank  in line with the Human Tissue (Scotland) Act. Use of human tissue for post mortem studies has been reviewed and approved by the Edinburgh Brain Bank ethics committee and the Academic and Clinical Central Office for Research and Development (ACCORD) medical research ethics committee (AMREC).We identified, from the Medical Research Council (MRC) Edinburgh Brain Bank, a cohort of 17 ALS patients for neuropathological assessment, all of whom had undergone standardized cognitive testing using the ECAS and demonstrated TDP‐43 in nonmotor brain regions at post mortem from standardized Brodmann areas (BA) relating to cognitive dysfunction in ALS (BA44/45 was selected for its role in language and fluency function and BA46 for its role in executive and fluency) and fixed in 10% formalin for a minimum of 24 h. Tissue was dehydrated in an ascending alcohol series (70–100%) followed by three successive 4‐h washes in xylene. Three successive five‐hour paraffin wax embedding stages were performed followed by cooling and sectioning of the formalin‐fixed paraffin embedded (FFPE) tissue on a Leica microtome in 4‐μm sections on to a superfrost microscope slide. Sections were dried overnight at 40°C and immunostaining was performed using the Novolink Polymer detection system with the proteintech anti‐phospho(409‐410)‐TDP‐43 antibody at a 1 in 1000 dilution and DAB chromogen and counterstained with haematoxylin, according to standard operating procedures. As previous studies have demonstrated no difference in or effect of relative abundance of TDP‐43 pathology with cognitive manifestations Brain tissue was taken at Advanced Cell Diagnostics) were used as per the manufacturer's guidelines according to the original protocol FFPE tissue was sectioned at 4 μm thickness on to superfrost slides. BaseScope reagents , suggesting that disease duration was not likely to be playing a significant role in the clinical manifestations of TDP‐43 pathology in these cases. Furthermore, the time between ECAS testing and death was not significantly different between the two groups. The group with no cognitive impairment was comprised of four individuals assessed within one year of death and two individuals with more than a one‐year gap between ECAS testing and death. The group with cognitive impairment was comprised of six individuals assessed within one year of death and five individuals with more than a one‐year gap between ECAS testing and death. Fisher's exact test revealed no significant difference between these two groups as the two‐tailed p value equates to 0.6004. Two mismatch cases had an underlying genetic mutation, both of which were a C9orf72 hexanucleotide repeat expansion (30%), compared to five genetic mutations (four C9orf72 and one NEK1 mutation) in the 11 comparison cases with cognitive deficits (45%). Fisher's exact test revealed no significant difference between these two groups as the two‐tailed p value equates to 1.0000.Within our cohort of 27 patients who had undergone ECAS testing during life, we identified a subgroup of six patients that demonstrated no cognitive impairment when assessed by the ECAS, but did exhibit extra‐motor TDP‐43 pathology when assessed at Given that these mismatch cases had pathologically misfolded TDP‐43 in extra‐motor brain regions without suffering clinical manifestations at the time of ECAS assessment during life, we wanted to investigate if they had upregulation of compensatory, protective mechanisms that could account for this altered protein misfolding capacity and which would allow for this high burden of protein misfolding to be tolerated. We assessed the expression of two chaperone proteins: clusterin and HspB8, both known to protect neurones from intracellular protein misfolding stresses, and more specifically known to protect against TDP‐43 proteotoxicity A,B) C,D). Cell‐type specific expression of clusterin was quantified in representative brain regions using BaseScope analysis, allowing for the direct visualization of single mRNA transcripts at a single cell level. This revealed a statistically significant increase in expression of neuronal clusterin in mismatch cases  and a statistically significant increase in expression of glial clusterin in cases with TDP‐43 pathology with a cognitive deficit . HspB8 is another chaperone protein, which was used as a comparator whose intracellular role in proteostasis is well‐established in reducing TDP‐43‐associated proteotoxicity A,B), unlike clusterin, was not differentially regulated between individuals with or without cognitive deficits. Furthermore, given the differential expression pattern of HspB8 was noted to be in the white matter glia, this pattern more likely reflects reactive gliosis and unlike clusterin is not spatially dysregulated between cognitively impaired and cognitively intact individuals .As previously demonstrated, clusterin expression was increased in all ALS cases assessed compared to age‐ and sex‐matched controls with no clinical or pathological evidence of neurological disease Figure A,B 16. s Figure C.post mortem tissue, it is uncertain whether the differential expression of clusterin is (i) the cause of, or (ii) a consequence of the different cognitive‐pathological phenotypes, although, it is clear, that there are striking differences in putative protective cellular mechanisms in these patients.While there is evidence to suggest a statistically significant association of cognitive deficits in ALS with TDP‐43 pathology Stratifying patients for clinical trials based on cognition, would be beneficial as the high specificity would result in only patients with definite TDP‐43 pathology being recruited. However, this approach, owing to reduced sensitivity, would fail to identify mismatch cases, that could also benefit from therapies targeting TDP‐43 misfolding. Our findings here, suggest that these mismatch cases could instead be identified by clusterin phenotyping, in addition to cognitive testing, as, the striking differential expression of clusterin could be a target for biomarker development. Clusterin is a normally secreted chaperone protein, with the ability to retrotranslocate to the cytosol under conditions of intracellular stress, such as TDP‐43 misfolding and accumulation LE, JG, CS and SA contributed to (i) conception and design of the study, (ii) acquisition and analysis of data and (iii) drafting a significant portion of the manuscript or figures. KM contributed to (i) conception and design of the study, (ii) acquisition and analysis of data. TB, SC and SP contributed to (i) conception and design of the study and (ii) drafting a significant portion of the manuscript and figures.The authors declare no conflicts of interest.


To estimate the risk of miscarriage associated with chorionic villus sampling (CVS).This was a retrospective cohort study of women attending for routine ultrasound examination at 11 + 0 to 13 + 6 weeks' gestation at one of eight fetal‐medicine units in Spain, Belgium and Bulgaria, between July 2007 and June 2018. Two populations were included: (1) all singleton pregnancies undergoing first‐trimester assessment at Hospital Clínico Universitario Virgen de la Arrixaca in Murcia, Spain, that did not have CVS (non‐CVS group); and (2) all singleton pregnancies that underwent CVS following first‐trimester assessment at one of the eight participating centers (CVS group). We excluded pregnancies diagnosed with genetic anomalies or major fetal defects before or after birth, those that resulted in termination and those that underwent amniocentesis later in pregnancy. We used propensity score (PS) matching analysis to estimate the association between CVS and miscarriage. We compared the risk of miscarriage of the CVS and non‐CVS groups after PS matching (1:1 ratio). This procedure creates two comparable groups balancing the maternal and pregnancy characteristics that are associated with CVS, in a similar way to that in which randomization operates in a randomized clinical trial.P < 0.0001). The PS algorithm matched 2122 CVS with 2122 non‐CVS cases, of which 40 (1.9%) and 55 (2.6%) pregnancies in the CVS and non‐CVS groups, respectively, resulted in a miscarriage (odds ratio (OR), 0.72 ; P = 0.146). We found a significant interaction between the risk of miscarriage following CVS and the risk of aneuploidy, suggesting that the effect of CVS on the risk of miscarriage differs depending on background characteristics. Specifically, when the risk of aneuploidy is low, the risk of miscarriage after CVS increases ) and when the aneuploidy risk is high, the risk of miscarriage after CVS is paradoxically reduced ), presumably owing to prenatal diagnosis and termination of pregnancies with major aneuploidies that would otherwise have resulted in spontaneous miscarriage. For example, in a patient in whom the risk of aneuploidy is 1 in 1000 (0.1%), the risk of miscarriage after CVS will increase to 0.3% (0.2 percentage points higher).The study population consisted of 22 250 pregnancies in the non‐CVS group and 3613 in the CVS group. The incidence of miscarriage in the CVS group  was significantly higher than that in the non‐CVS group (0.9% (207/22 250); The risk of miscarriage in women undergoing CVS is about 1% higher than that in women who do not have CVS, although this excess risk is not solely attributed to the invasive procedure but, to some extent, to the demographic and pregnancy characteristics of the patients. After accounting for these risk factors and confining the analysis to low‐risk pregnancies, CVS seems to increase the risk of miscarriage by about three times above the patient's background risk. Although this is a substantial increase in relative terms, in pregnancies without risk factors for miscarriage, the risk of miscarriage after CVS remains low and similar to, or slightly higher than, that in the general population. Copyright © 2020 ISUOG. Published by John Wiley & Sons Ltd. abstract to view the translations.This article's abstract has been translated into Spanish and Chinese. Follow the links from the  What are the novel findings of this work?The risk of miscarriage following chorionic villus sampling (CVS) is highly dependent on the patient‐specific background risk of miscarriage. Because risk factors associated with CVS (risk factors for aneuploidy) are also associated with spontaneous miscarriage, in women at low risk for aneuploidy, CVS is associated with a significant increase in the miscarriage rate while, paradoxically, in women with high risk of aneuploidy, the risk of miscarriage after CVS is reduced, presumably owing to prenatal diagnosis and termination of pregnancies with major aneuploidies that would otherwise have resulted in spontaneous miscarriage.What are the clinical implications of this work?The true procedure‐related risk of miscarriage after CVS can only be estimated by examining women at low risk for aneuploidy. In such women, the risk of miscarriage after CVS increases by about three times. Although this is a substantial increase in relative terms, in pregnancies without prior risk factors the risk of miscarriage after CVS remains low and similar to, or slightly higher than, that in the general population.vs non‐invasive testing, but it was derived indirectly through, first, randomized controlled trials (RCTs) comparing CVS with first‐ or second‐trimester amniocentesis, and second, comparison of the rate of miscarriage in groups with similar risk factors that had CVS vs those that did not have invasive testing. The results of such trials established that, first, the risk of miscarriage following CVS is lower than that following early amniocentesis but similar to that following mid‐trimester amniocentesis, and second, the risk of miscarriage is similar following transabdominal and transcervical CVSChorionic villus sampling (CVS), which was first described in 1975 and introduced into widespread clinical practice in the 1980sAnother approach for estimating the procedure‐related risk of miscarriage from CVS is to compare the rate of miscarriage between women who had CVS and those who did not have invasive testing. However, such an approach is likely to entail bias against CVS because several of the factors that lead to the need for CVS are also risk factors for miscarriage, such as increased maternal age, increased fetal nuchal translucency (NT) thickness, low serum pregnancy‐associated plasma protein‐A (PAPP‐A) and abnormal flow in the fetal ductus venosusThe main objective of this multicenter study was to estimate the CVS‐related risk of miscarriage after accounting for the effects of maternal and pregnancy characteristics that could have driven the decision to undergo CVS.n = 651 (2.5%)) or 1–2 weeks earlier (n = 25 212 (97.5%)) for measurement of serum free β‐human chorionic gonadotropin (β‐hCG) and PAPP‐A. Screening for trisomies 21, 18 and 13 was carried out using The Fetal Medicine Foundation algorithm, which combines maternal age, fetal NT, ductus venosus flow and multiples of the median (MoM) values of free β‐hCG and PAPP‐Ain‐vitro fertilization.This was a retrospective cohort study of women attending for routine ultrasound examination at 11 + 0 to 13 + 6 weeks' gestation at one of eight participating fetal medicine units in Spain , Belgium  and Bulgaria , between July 2007 and June 2018. During this visit, patient characteristics and medical history were recorded and an ultrasound examination was carried out to assess viability, diagnose major defects, measure fetal crown–rump length (CRL) and fetal NT thickness, and assess ductus venosus flow (positive or negative/reversed a‐wave). A blood sample was collected in the same visit (in‐vitro fertilization), cigarette smoking during pregnancy (yes or no), parity (parous or nulliparous if no previous pregnancy reached at least 24 weeks' gestation), and medical history of diabetes mellitus and chronic hypertension (yes or no).The following patient characteristics were recorded: maternal age, weight, height, ethnicity , method of conception  all singleton pregnancies undergoing first‐trimester assessment at Hospital Clínico Universitario Virgen de la Arrixaca in Murcia (Spain) that did not undergo CVS (control group); and (2) all singleton pregnancies that underwent CVS following first‐trimester assessment at any of the participating centers. The main indication for CVS was increased risk for aneuploidy, but other reasons were increased NT thickness, history of genetic disease in the family, previous aneuploidy or maternal request. The eligibility criteria were singleton pregnancy with a live fetus at 11 + 0 to 13 + 6 weeks without genetic anomalies or major fetal defects  diagnosed before or after birth. We excluded pregnancies resulting in termination for any reason, pregnancies lost to follow‐up and those that underwent amniocentesis later in pregnancy.The primary outcome measure was the incidence of miscarriage, defined as pregnancy loss occurring before 24 weeks' gestation regardless of the interval between CVS and fetal demise. The findings of the investigations and pregnancy outcome were recorded in computer databases. Approval for the study and waiver of consent was obtained from the relevant research ethics committee of each participating center.U‐test or two‐tailed χDescriptive data are expressed as median and interquartile range (IQR) and as proportions (absolute and relative frequencies). Comparisons between the treatment groups were performed using the Mann–Whitney Because we noted important differences in baseline clinical characteristics between the CVS and the non‐CVS groups, we performed a PS matching analysis to assess the effect of CVS on the risk of miscarriage, adjusting for the confounding bias caused by this imbalance. Compared with classic multivariate adjustments, the PS permits finer adjustments for wider sets of covariates. PS was defined as the conditional probability of having CVS given the measured covariates in order to balance covariates in the two groups. To obtain the PS, we fitted a logistic regression model with CVS as the dependent variable and then we modeled the conditional probability of undergoing CVS as a function of baseline and those clinical characteristics associated with having CVS. We used the PS to match, without replacement, each complete CVS case with the non‐CVS case that had the closest PS in a 1:1 ratio, in order to optimize the precision of the estimate of association and limit bias. We also accepted cases only if the difference in PS between matched cases was small , resulting in excellent balance between the CVS and non‐CVS cases as matched samplesThe statistical software package R was used for data analysis The study population consisted of 22 250 singleton pregnancies in the non‐CVS group and 3613 in the CVS group .The incidence of miscarriage in the CVS group was 2.1% (77/3613), significantly higher than that in the non‐CVS group (0.9% (207/22 250)) . We hypothesized that the most likely explanation for this paradoxical effect of CVS ‘reducing’ the risk of miscarriage was that many of the cases that would have resulted in spontaneous miscarriage if the pregnancy had continued underwent elective termination following an abnormal genetic diagnosis. If this is true, this ‘protective’ effect of CVS should be higher in cases at high risk of having a genetic anomaly and lower in low‐risk cases.The PS algorithm matched 2122 of the CVS cases with 2122 non‐CVS pregnancies, largely reducing the initial imbalance between the two groups, with the between‐group standardized differences for all variables being lower than the recommended 10% limit  and 0.131  in the low‐risk subgroup (n = 2122). In the high‐risk subgroup, 1062 cases underwent CVS, of which 23 (2.2%) had a miscarriage, and of the 1060 cases that did not undergo CVS, 49 (4.6%) had a miscarriage ). In contrast, in the low‐risk subgroup, 17 (1.6%) miscarriages occurred in the CVS group (n = 1060) compared with six (0.6%) miscarriages in the non‐CVS group (n = 1062) ). Both effects were statistically significantly different (P for the interaction = 0.0003)  in the high‐risk subgroup  of cases because of termination of pregnancy or fetal defects, compared with only 4.2% (1070/25 519) in the non‐CVS group n = 1015) or invasive testing (amniocentesis or CVS (n = 982)), and found no significant differences in the risk of miscarriage between the two groups ; P = 0.47)A recent RCT randomized women at high risk of aneuploidy into cell‐free DNA testing (In cases in which there is a clear indication for performing prenatal genetic testing, clinicians can reassure women that their risk of miscarriage mainly depends on the results of the genetic diagnosis and the conditions that led to it more than the procedure itself. However, in the absence of any major fetal defect or other additional risk factors for chromosomal abnormality, clinicians should report an individualized procedure‐related risk based on the clinical characteristics of the patient.,The main limitations of this study are related to its observational and retrospective nature, and the consequent heterogeneity between the two study groups Figure . AlthougThe main strength of our study relates to the large sample of both CVS and non‐CVS cases, which were selected after matching women of both groups but with identical PS for having a CVS. Since the matching was indirectly based on known risk factors for aneuploidy, we were able to perform subgroup analysis to demonstrate the interaction between the risk of aneuploidy and CVS by comparing patients with a very similar risk profile.All invasive procedures were performed using the same technique and by fetal medicine experts or their trainees at the end of such training. This represents both an advantage, because it reduces variability between operators, and a disadvantage, since the results might not be valid for different approaches and levels of expertise.The risk of miscarriage in pregnancies that undergo CVS is about 1% higher than that in pregnancies that do not have CVS, although this excess risk is not attributed entirely to the invasive procedure but to some extent to the demographic and pregnancy characteristics of the patient. After adjusting for these risk factors and confining the analysis to low‐risk pregnancies, CVS seems to increase the risk of miscarriage by about three times above the patient's background risk. Although this is a substantial increase in relative terms, in pregnancies without risk factors, the risk of miscarriage after CVS will remain low and similar to, or slightly higher than, that in the general population.Table S1 Additional statisticsClick here for additional data file.Appendix S1 Propensity score analysis according to background risk for miscarriageClick here for additional data file.


Targeted protein degradation (TPD), the ability to control a proteins fate by triggering its degradation in a highly selective and effective manner, has created tremendous excitement in chemical biology and drug discovery within the past decades. The TPD field is spearheaded by small molecule induced protein degradation with molecular glues and proteolysis targeting chimeras (PROTACs) paving the way to expand the druggable space and to create a new paradigm in drug discovery. However, besides the therapeutic angle of TPD a plethora of novel techniques to modulate and control protein levels have been developed. This enables chemical biologists to better understand protein function and to discover and verify new therapeutic targets. This Review gives a comprehensive overview of chemical biology techniques inducing TPD. It explains the strengths and weaknesses of these methods in the context of drug discovery and discusses their future potential from a medicinal chemist's perspective. Targeted protein degradation has created tremendous excitement in chemical biology and drug discovery. This Review gives a comprehensive overview of chemical biology tools as well as therapeutic approaches inducing targeted protein degradation and discusses them from a medicinal chemist's perspective. This happens in an occupancy‐driven manner with the inhibitor binding to its target and occupying the binding site, thereby inhibiting target function.Native protein degradation occurs via one of two main mechanisms in the cell: the ubiquitin–proteasome system (UPS) and the autophagy‐lysosome pathway Figure . ProteinWhile the 26S proteasome efficiently degrades short‐lived, soluble unfolded or misfolded proteins and polypeptides,Ubiquitination is at the heart of the degradation machinery for proteasomal‐ as well as autophagy‐mediated degradation, with E3 ligases as the critical components of the ubiquitination cascade. E3 ligases provide strict spatial and temporal substrate specificity and over 600 genes encoding for ubiquitin E3 ligases in the human genome, contributing to the cellular specificity and complexity of the ubiquitination system.This review provides a comprehensive overview of various TPD techniques for chemical biology and drug discovery, highlighting their strengths and limitations from a medicinal chemist's perspective. To discriminate between the different methods, we divided them into two main categories: 1. Degradation of tagged target proteins; 2. Degradation of untagged target proteins. A protein tag comprises a peptide sequence or protein genetically fused to the protein of interest (POI) to allow its selective detection and/or purification.2To generate a better target understanding and validate a target in a disease context controlling protein activity and abundance is a very powerful tool. Although, methods like CRISPR/Cas2.1Maintaining protein homeostasis is pivotal for cell survival and proliferation. Therefore, the equilibrium between protein synthesis and degradation must be carefully regulated to keep the system in balance. Proteins, which are naturally degraded by the UPS, are displaying specific degradation signals, termed degrons, which represent E3 ligase binding motifs.2.1.1One of the first conditional degrons was identified in budding yeast and allows to induce temperature dependent protein degradation Figure  a. This 2.1.22.1.2.1A widely used and robust method to degrade a broad range of target proteins is the auxin‐inducible degron (AID). In plants, the hormone auxin triggers the degradation of the AID by means of the plant F‐box protein TIR1 and the CUL1‐RING ligase.2.1.2.2As mentioned above the AID demands, in addition to the AID itself, the exogenous introduction of the F‐box protein TIR1 to achieve degradation. An alternative presents the use of destabilizing domains (DDs) which constitutively induce the degradation of the target protein themselves. Upon ligand binding the DD is stabilized in a dose dependent manner thus preventing the degradation of the DD‐POI fusion construct Figure  c. Thus 2.1.2.3A highly interesting degron concept is described by small molecule‐assisted shutoff (SMASh) which belongs to the family of destabilizing tags. SMASh combines a constitutive degron with a protease and its corresponding cleavage site all derived from the hepatitis C virus Figure  e.32 Aft2.1.3t1/2=30 min) degrade a target protein fusion construct in mammalian cells and zebrafish upon blue‐light irradiation.Activating a degron via temperature or a small molecule is a very convenient strategy to modulate protein abundance but does not provide a spatial component to control the target protein levels. To allow spatiotemporal control over the target light‐activated degrons (LADs) were designed Figure  f. In a 2.2F36V‐fusion (dTag system) proteins are working is well characterized and understood (for more detailed information please see section 3.3 PROTACs). In short, the bifunctional degrader brings the tagged protein as well as an E3 ubiquitin ligase in close spatial proximity inducing ubiquitination and subsequent proteasomal degradation of the tagged protein.A very powerful tool to quickly achieve TPD for a wide range of target proteins and without the need to identify a specific binder represents the use of tag specific degraders. In this case, the degrader molecules are optimized to engage the protein tag resulting in effective removal of the tag‐POI fusion construct. The two main tags which are widely used as chemical biology tools for this technology are the HaloTagThe HaloTag 33 kDa) is a widely used self‐labeling tag introduced by Promega® which covalently binds to chloroalkanes.3 kDa is F36V protein tag (12 kDa) fused to the target protein as well as a bivalent degrader molecule (dTag). The dTag selectively binds to FKBP on one site and the E3 ligase Cereblon (CRBN) on the other site and thereby induces degradation of the fusion protein construct .g Figure  a.3 AlthBI‐3802 induces the degradation of BCL6 in a proteasome dependent manner and significantly outperforms the corresponding inhibitor BI‐3812, a close analog  and the degradation of neo‐substrates—non‐native substrates recruited by exogenous ligands—is a method already used and optimized by many different viruses to defend themselves against the host's response.3.3The technique currently creating by far the most excitement in the field of TPD are PROTACs. Compared to other approaches like TRIM‐away section 3.4) or hydrophobic tagging (section 3.1) PROTACs are highly modular. As large small‐molecules they show borderline drug‐like properties but have surprisingly proven suitable for oral application..4 or hyd90 or IC95) for small molecules, the residual binding affinity in combination with the subsequent target degradation renders PROTACs still efficacious making them less liable to many frequently observed resistance mutations.PROTACs are bifunctional molecules comprising a target binding moiety, an E3 ligase recruiter and a linker Figure  c. The p50s) in the low‐ and sub nanomolar range are commonly observed even when binding to the E3 ligase or the target protein are only in the micromolar range.G12C and BTK PROTACs have been identified, recently.While empiric guidelines like the rule‐of‐five−1 for clinical applications is an enormous challenge as many principles established for small molecule inhibitors do not translate to larger molecules. Despite these challenges, Arvinas® has managed to identify orally available PROTACs for their first two clinical programs and other companies claim to have achieved oral bioavailability for their PROTACs, as well. With only very few design guidelines available PROTAC optimization is still no straight forward process.Optimizing a beyond rule‐of‐five compound with a molecular weight most likely between 700 and 1200 g molIn case no active PROTACs can be identified using this setup or as additional support for rational PROTAC optimization further assays are useful. Especially monitoring the formation of the ternary complex comprising the target protein, the PROTAC and the E3 ligase is important at this point. Measuring ternary complex formation has been mainly done by using biophysical assays such as isothermal titration calorimetry (ITC) or surface plasmon resonance (SPR) which are both limited by low or medium throughput, respectively.To aid PROTAC optimization, attempts to crystallize the ternary complex in order to understand the orientation of the two ligands as well as the linker is highly recommended. Structural insight can be tremendously helpful to guide PROTAC design and can lead to surprising but useful tweaks not obvious at first glance.While several assays have been described for the in vitro optimization of PROTACs very little is known about how to design PROTACs for in vivo applications. Despite various xenograft studies using PROTACs are reported, optimization strategies for in vivo experiments are only beginning to emerge.3.3.1Despite the excitement about PROTACs as a novel therapeutic modality, PROTACs bear also a huge potential as a chemical biology tool (e.g. section 2.2). The design of photo‐switchable PROTACs allows for temporal control of TPD Figure  a.82 The3.3.2Complementary to PROTACs, lysosome targeting chimeras (LYTACs) allow the degradation of extracellular and membrane target proteins.3.3.3The second major pathway of protein degradation—autophagy—is pivotal for the degradation of misfolded proteins, aggregates and especially whole cell organelles. In a recent study the autophagy pathway has been hijacked for the first time to rationally degrade a desired protein as well as fragmented mitochondria Figure  d.85 Bas3.4In contrast to PROTACs which are currently investigated as potential remedies for diseases the TRIM‐away technology has a great potential to be a valuable tool in chemical biology and target validation.3.5As already mentioned above, the rational design of a targeted protein degrader relies on the availability of a suitable target binder. However, most proteins of the undruggable proteome are termed undruggable due to the lack of chemical matter. Biologics on the other hand can be raised against most protein targets but are limited to extracellular or surface proteins. Nevertheless, by fusing a peptide or antibody‐mimetic directly to a human or bacterial E3 ligase so called bioPROTACs were designed to specifically degrade challenging intracellular proteins Figure  b.87 As 4As highlighted by the various achievements within recent years, TPD has matured from a chemical biology niche to a fully established application for target validation and discovery. Furthermore, TPD in form of molecular glues is established on the market with billions of revenues created by the IMiDs alone and has even advanced to the clinic in the very young field of PROTAC‐mediated degradation in 2019.F36V‐POI fusion proteins from the system.F36V‐tag (12 kDa) might influence the target protein in an unfavorable way and needs to be checked beforehand. Future advances in gene editing technologies will improve the ability to insert these tags on an endogenous level making them hopefully available to almost any desired cell line in the future.With the myriad of methods to choose from one can easily be overwhelmed and struggle to find the best system for the problem at hand. For a condensed overview of the discussed techniques we summarized their key features in Table 50s would predict. With respect to TPD, this process most likely has removed several potent protein degraders without ever realizing their existence. Consequently, sooner or later the hit‐to‐lead process in industry will have to be adapted accordingly. In the future, aiming for the identification of small‐molecule target protein degraders instead of inhibitors will emerge as a common strategy in early research.While the outlook for the chemical biology side of TPD is highly encouraging it is equally bright for the therapeutic angle targeting untagged proteins. Already in the short period of rationally designing protein degraders, post elucidation of the IMiD mode of action (2010), several CRBN modulators with different selectivity profiles haven been identified and three are currently evaluated in clinical trials.Considering the recent successes of TPD and especially PROTACs experts in the field are excited to see whether PROTACs can live up to their high expectations. Although the first human PK data look promising PROTACs still have a long way to go until they will achieve approval and an even longer way to see how they will perform on the market. Crucial questions like: “How quickly will we see resistance emerge?” or: “What will the main resistance mechanism be?” are waiting to be answered. Efforts to pinpoint common PROTAC resistance mechanisms consistently found mutations hampering the UPS while leaving the target protein unscathed.Despite these open questions the hunt to identify the next clinical candidates is in full swing. Almost every pharmaceutical company is pursuing TPD programs either alone or in collaboration with one of the young biotech companies in the field. Upcoming decisions on several patent applications are monitored closely by everyone working on TPD. While some companies are aiming to discover new chemical matter for the established E3 ligases others are focusing on unraveling the technology itself. However, a set of rules on how to design the perfect PROTAC for a given target remains to be crafted. Thus far, the correlation between in vitro and in vivo data still poses a massive challenge when it comes to PROTAC design. Additionally, immense efforts are underway to identify and hijack tissue or disease specific E3 ligases in order to address certain diseases more selectively or increase the therapeutic window. Without any doubt many things are happening around TPD and new ideas and directions are appearing on a constant basis. Inspired by the non‐native PPIs commonly observed in TPD, ideas are emerging to induce other post translational modifications besides ubiquitination. Early examples recruiting phosphatases or RNAses to eliminate proteins before they are produced will only be the tip of the iceberg.In light of the success of biologics and the emerging progress of nucleotide‐based therapeutics as well as the upcoming gene therapies, small molecule drug discovery has been looking for its own shot to address the undruggable proteome. TPD is among the technologies which helps to fill this void offering a path towards a medicinal chemistry based approach able to compete with many of the new modalities emerging within the last decades.All authors are or were employees of Bayer AG.Laura Luh obtained her PhD working on transcription factors with implications in cancer at the Goethe University Frankfurt. After joining Evotec in Hamburg to establish new techniques to assess small molecule target interactions, she moved to Cambridge to join Anne Bertolotti's lab at the MRC Laboratory of Molecular Biology conducting her postdoctoral studies on specific phosphatase inhibitors in order to correct protein misfolding defects. In 2018, she joined Bayer to work on targeted protein degradation in different therapeutic areas.Ulrike Scheib studied biochemistry in Tübingen and completed her master's thesis at the UC in San Diego. For her PhD in biophysics she joined the optogenetic research group of Peter Hegemann at the Humboldt‐University of Berlin in 2013 and studied rhodopsin‐guanylyl cyclase. In 2018 she started as a PostDoc at Bayer in Berlin and is particularly interested in structure–function relationships and protein degradation.Katrin Juenemann studied biology at the Friedrich‐Schiller‐University in Jena. She completed her PhD in Molecular biology at the Leibniz Institute on Aging in Jena and continued her scientific work on neurodegenerative diseases as a postdoctoral fellow at the Academic Medical Center in Amsterdam. In 2016 she joined the Leibniz Institute for Molecular Pharmacology as an AXA Research fellow to study intracellular ubiquitination and protein degradation associated with neurodegeneration. As a scientist in preclinical research at Bayer she works on targeted protein degradation.Lars Wortmann studied chemistry at the University of Frankfurt. He received his Ph.D. from the RWTH Aachen and performed postdoctoral studies at Stanford University with a particular focus on stereoselective synthesis. In 2001 he joined the Medicinal Chemistry department of Schering AG (now Bayer AG). He has worked on several oncological projects and he is one of the main inventors of Bayer's clinical ATR inhibitor BAY 1895344. Additional interests: chemical probes for open science, PROTACs, chemical biology.Michael Brands studied chemistry in Münster and completed his doctoral thesis at the Max‐Planck‐Institut für Kohlenforschung in Mülheim in 1993. After a postdoctoral stay with Wolfgang Oppolzer at the University of Geneva, he started his industry career in Drug Discovery. Today he is head of the Small Molecule Innovation Department at Bayer Pharmaceuticals R&D responsible for Lead Discovery, Medicinal Chemistry and Thorium Conjugate Research. Since 2006, he teaches Medicinal Chemistry at the University of Paderborn.Philipp M. Cromm studied chemistry at the Technical University Munich where he worked in the group of Horst Kessler. For his master's thesis he spent time with David J. Craik at the Institute for Molecular Bioscience and received his PhD under guidance of Herbert Waldmann at the Max‐Planck‐Institute for Molecular Physiology. Thereafter, he carried out postdoctoral studies in the group of Craig Crews at Yale University working on targeted protein degradation. In 2018 he joined Bayer AG as a Medicinal Chemist.