Morphogenesis is a continuous process of pattern formation so complex that it requires in vivo monitoring for better understanding. Changes in tissue shape are initiated at the cellular level, where dynamic intracellular F-actin networks determine the shape and motility of cells, influence differentiation and cytokinesis and mediate mechanical signaling. Here, we stain F-actin with the fluorogenic probe SiR-actin for live fluorescence imaging of whole chick embryos. We found that 50 nM SiR-actin in the culture medium is a safe and effective concentration for this purpose, as it provides high labeling density without inducing morphological malformations. Embryogenesis is a complex process of tissue formation driven by the tightly coordinated behavior of numerous cells. Next to proliferation and programmed cell death, this involves shape changes and relative cell movements . Cell shRecently, a powerful probe was introduced to overcome the hurdles in live fluorescent imaging of actin dynamics. Silicon-rhodamine actin (SiR-actin)  combinesWe could successfully fill this gap by adding SiR-actin to the culture medium of early chick embryos grown in the “submerged filter paper sandwich” , a variaWe used SiR-actin to image the supra-cellular organization of F-actin during somite formation in the chick embryo. Somites are the predecessors of vertebrae, intervertebral discs, ribs and muscles and impose a segmented organization on the peripheral nervous system . The chaWe prepared the culture medium as a mixture of Pannett-Compton (PC) -saline ,29 and fGallus gallus, Drost BV, Loosdrecht, North Holland, The Netherlands) were incubated at 37.5 °C in a humidified atmosphere for 32–36 h and subsequently transferred into submerged filter paper sandwiches [Fertilized chicken eggs , equipped with a PlanNeoFluar Z 1.0× objective, a Cy-5 filter cube  and a Hamamatsu ORCA Flash 4.0 camera . Time lapse images were acquired at 5 min intervals. Sixteen-bit grayscale images of 2048 × 2048 pixels were acquired at different magnifications of the zoom objective. The tiles module of the Zeiss Zen software was used to acquire panoramic images with a 10% overlap of single tiles ). Single tiles were stitched afterwards using the Zen software.Embryos were transferred into filter paper sandwiches  and carePreliminary experiments with SiR-actin concentrations ranging from 3 nM to 450 nM in the presence of 2% thin albumen revealed that a satisfying fluorescence signal did not develop for a SiR-actin concentration below 30 nM. On the other hand, SiR-actin concentrations higher than 200 nM led to morphological anomalies during later embryonic development. n = 3; thin albumen percentage: 2%), nor in embryos cultured with the submerged filter paper sandwich technique [n = 3 for each, average ± SD, While the initial live recordings of F-actin in the young chick embryo were successful, we found that culturing in the presence of 240 nM SiR-actin for more than 12 h induced morphological abnormalities. Incompletely separated somites . Here we received a Pearson’s coefficient R = 0.93, indicating a very high degree of correlation between the two signals. This confirms the usefulness of SiR-actin to visualize actin dynamics in vivo. To explore the potential of our culture technique, we incubated live embryos with 50 nM SiR-actin overnight and imaged them, subsequently, on an upright confocal microscope. To compare the staining characteristics of SiR-actin and fluorescently labeled phalloidin, we performed a co-staining of fixated chicken embryos with the same concentration of both probes (250 nM). We observed an almost perfect overlap between the two staining patterns A, which We established a simple protocol for the live staining of F-actin in whole embryo cultures of early chick embryos using SiR-actin in combination with the ‘submerged filter paper sandwich’ . In thisWhile it is satisfying to see that the adapted SiR-actin staining protocol allows for live imaging of whole chick embryos, the study has some limitations. First, it only presents a proof-of-principle and an indication that an optimal range of concentrations may exist between thresholds of detectability (30 nM) and safety (200 nM). Replication studies with higher sample numbers are needed for further optimization of the protocol. In the direct comparison between 50 and 250 nM SiR-actin concentrations, embryos of different ages were used . The younger age used in the higher concentration, with possibly higher permeability for SiR-actin, could be responsible for the malformations observed at this concentration. On the other hand, the lower concentration (50 nM) appeared to be sufficient for the older and presumably less permeable embryos. That we never observed morphological malformations in the control embryos or our earlier studies  shows thDue to technical limitations, we could not acquire time lapse images at confocal resolution. We are confident that water immersion objectives , in combination with light-sheet microscopy, will allow the acquisition of high-resolution time-lapse series. Immersion of the objective into the culture medium, followed by the application of the mineral oil layer, will create a stable setup without evaporation, which should allow the observation of embryonic development over many hours.We exemplarily showed that SiR-actin penetrates deep enough into the embryonic tissue to stain even the apical actin cortices of the somites. Other embryonic structures, like the early embryonic heart or the epithelial cells of the endoderm C, are evSiR-actin uptake into the tissue may additionally be improved by using the broad-spectrum efflux pump inhibitor Verapamil, supplied with the SiR-actin kit. We avoided the use of Verapamil, as it is known for its teratologic effects on morphogenesis in early chicken embryos ; yet fur


Pneumonia is a common and severe complication of abdominal surgery, it is associated with increased length of hospital stay, healthcare costs, and mortality. Further, pulmonary complication rates have risen during the SARS-CoV-2 pandemic. This study explored the potential cost-effectiveness of administering preoperative chlorhexidine mouthwash versus no-mouthwash at reducing postoperative pneumonia among abdominal surgery patients.A decision analytic model taking the South African healthcare provider perspective was constructed to compare costs and benefits of mouthwash versus no-mouthwash-surgery at 30 days after abdominal surgery. We assumed two scenarios: (i) the absence of COVID-19; (ii) the presence of COVID-19. Input parameters were collected from published literature including prospective cohort studies and expert opinion. Effectiveness was measured as proportion of pneumonia patients. Deterministic and probabilistic sensitivity analyses were performed to assess the impact of parameter uncertainties. The results of the probabilistic sensitivity analysis were presented using cost-effectiveness planes and cost-effectiveness acceptability curves.In the absence of COVID-19, mouthwash had lower average costs compared to no-mouthwash-surgery, $3,675  versus $3,958 , and lower proportion of pneumonia patients, 0.029 versus 0.042 (dominance of mouthwash intervention). In the presence of COVID-19, the increase in pneumonia rate due to COVID-19, made mouthwash more dominant as it was more beneficial to reduce pneumonia patients through administering mouthwash. The cost-effectiveness acceptability curves shown that mouthwash surgery is likely to be cost-effective between $0 (R0) and $15,000  willingness to pay thresholds.Both the absence and presence of SARS-CoV-2, mouthwash is likely to be cost saving intervention for reducing pneumonia after abdominal surgery. However, the available evidence for the effectiveness of mouthwash was extrapolated from cardiac surgery; there is now an urgent need for a robust clinical trial on the intervention on non-cardiac surgery. Pneumonia is a common and severe complication that occurs after abdominal surgery with incidence rates reported between 4% and 17.5% . PostopeIn March 2020, the WHO declared the spread of corona-virus disease COVID-19) a global pandemic , 6. Rese a globalWe aimed to assess the potential cost-effectiveness of preoperative chlorhexidine mouthwash when compared to no-mouthwash at reducing postoperative pneumonia among abdominal surgery patients and explore the impact of COVID-19 on the cost-effectiveness results in a LMIC setting (South Africa).We developed a decision analytic model in Microsoft Excel 2016 . The choice of the model was appropriate due to the short timeframe of the condition . We asseThe model structure was developed in consultation with clinical experts from the NIHR Global Health Research Unit on Global Surgery . The agrThe following assumptions were necessary in order to carry out the analysis. Patients in the mouthwash arm were administered chlorhexidine two times immediately before anaesthesia. Mouthwash was more effective than no-mouthwash-surgery at reducing postoperative pneumonia based on data extrapolated from cardiac surgery and mechanical ventilated patients , 13. TheThere were no randomised control trials on the effectiveness of mouthwash at reducing pneumonia after abdominal surgery. We therefore derived probability estimates directly from two international prospective cohort studies. Firstly, data for South African patients recruited in the “African Surgical Outcomes Study” (ASOS) were used to estimate most probabilities in the control arm . SecondlDue of lack of evidence on the intervention among non-cardiac surgery patients, to estimate the probabilities in the intervention arm we relied on evidence that mouthwash reduces pneumonia incidence rate by 0.52 (CI 0.39–0.71) relative risk reduction (RRR) among cardiac surgery patients . We madeCosts associated with postoperative pneumonia were sourced from studies done in USA through on a systematic review of the literature conducted as part of the current study see . The estTo convert the UK and USA costs to South African values we adopted the market-basket estimation approach . We collCosts in British Pounds were converted to International Dollars using purchasing power parity (PPP) conversion factors . One stuThe LoS data were collected from the RECON dataset  see Tab. The LoSThe effectiveness measure was the proportion of patients with pneumonia. Thus, the proportion of patients that had postoperative pneumonia in either the mouthwash or the no-mouthwash-surgery arm. In the analysis, an effectiveness value of “0” was assigned to pathways of patients who had postoperative pneumonia and a value of “1” to pathways of patients did not have postoperative pneumonia.In Scenario 1, we assumed the absence of COVID-19. We assessed the costs and benefits of two times administration of preoperative 0.2% chlorhexidine mouthwash compared to no-mouthwash.In Scenario 2, the analysis was similar to scenario 1 but included the following assumptions on COVID-19: (i) COVID-19 will increase postoperative pneumonia probability by 1.8% as shown by the COVIDSurg dataset .The analysis took the South African healthcare provider perspective with costs presented in International Dollars ($) and South African Rands (R). We used a 30-day timeframe because evidence shows that readmission rates are negligible and rarely change within 30 days of surgery . We assuDeterministic sensitivity analysis (DSA) was conducted to assess the sensitivity of the base case results to changes in a given input parameter while holding constant the other parameters. In both scenarios 1 and 2, the conservative estimate on the RRR was reduced in various stages up to 0.01. At each RRR value we explored the cost of mouthwash gel that would change the base case results. The rest of the sensitivity analyses were conducted at a more conservative RRR value (0.01) as parameters would be more sensitive at a low RRR value. For the parameters estimated based on expert opinion and model assumptions, we varied the values further upwards and downwards up to 90% to explore the point where the base case results would change.We additionally explored more scenarios assuming no patient needed mechanical ventilation and explored best case and worse case scenarios. For both scenarios 1 and 2, we simultaneously reduced probabilities of all mechanical ventilation pathways to zero to explore the possibility of abdominal surgery patient not requiring postoperative mechanical ventilation. Best and worst case scenario analyses were conducted by simultaneously changing a number of parameters using either the lower or upper bound values depending on what was likely to make things better or worse-off in terms of cost-effectiveness of mouthwash. The best case for mouthwash was when pneumonia, critical care unit, mechanical ventilation probabilities, general ward LoS, and critical care unit LoS were at the lower bounds and the bed day and pneumonia cost were at the upper bounds. Conversely, the lower bounds for bed day and pneumonia cost and the upper bounds for the former parameters were used as worst case scenario for mouthwash see .Probabilistic sensitivity analysis (PSA) was conducted to assess uncertainty of the base case estimates (in reference to 0.3 RRR). Ten thousand Monte Carlo simulations were run by simultaneously drawing random values of the parameters based on the assigned distribution. The results for each iteration were used to calculate the difference in costs and difference in proportion of pneumonia patients and presented on the cost-effectiveness plane . We calcResults presented in In the absence of COVID-19, only the analyses where either pneumonia, critical care unit, mechanical ventilation probabilities or critical care unit LoS in one arm was changed, holding constant the rest of the parameters, were any significant changes to base case results observed. A 20% increase in the probability of pneumonia patients admitted to critical care unit in the intervention arm made no-mouthwash-surgery dominant over mouthwash  difference in costs and -0.0081 difference in proportion of pneumonia patients). When critical care unit LoS in the control arm was reduced from 18.99 to 15.19 days, mouthwash was more expensive but was slightly more effective which generated an ICER of $49,378 . The rest of the Scenario 1 DSA results are displayed in see Mouthwash dominated until general ward LoS was increased from 11.36 to 15.38 days or critical care unit LoS was increased from 18.99 to 19.81 days in the mouthwash arm or general ward LoS was decreased below 7.34 days or critical care unit LoS was decreased below 18.19 days in the no-mouthwash-surgery arm.The extreme case analysis suggested that the cost of mouthwash gel had to increase at least to $11 (193) for mouthwash not to dominate. For example, at 0.03 and 0.01 RRR, mouthwash dominated no-mouthwash-surgery until the cost of mouthwash gel per patient rose above $289  and $11 (R 193) respectively.When no patient needed mechanical ventilation, mouthwash dominated as it reduced costs by $ -5 (R -88) and there was 0.0004 difference in proportion of pneumonia patients. In the best case scenario, mouthwash dominated as it reduced costs by $-277  and the difference in proportion of pneumonia patients was 0.0119. In the worst case scenario, mouthwash was dominated with $280  difference in costs and the difference in proportion of pneumonia patients was -0.0081.In the presence of COVID-19, DSA the results were similar to Scenario 1 results. Base case results changed only when either pneumonia, critical care unit, mechanical ventilation probabilities, general ward LoS or critical care unit LoS were varied in one arm (ceteris paribus). At 0.01 RRR, mouthwash dominated no-mouthwash-surgery as it reduced costs by $-6 (R –100) and the difference in proportion of pneumonia patients was 0.0004. The rest of the scenario 2 DSA results are displayed in The PSA results for scenario 1 are illustrated on the cost-effectiveness plane see . The aveFor scenario 2, the average difference in costs and proportion of pneumonia patients have been presented in Figs The results of the model-based analysis suggest that mouthwash is likely to dominate no-mouthwash-surgery in both the absence and presence of COVID-19. The average hospital costs for mouthwash were lower compared to no-mouthwash-surgery, at the same time, mouthwash was shown to have lower proportion of pneumonia cases than no-mouthwash-surgery. The results also show that there had to be a substantial reduction in general ward, critical care unit or mechanical ventilation LoS in the intervention arm or a substantial increase in at least one of the three parameters in the control arm for the intervention not to dominate (ceteris paribus). This implies that the small increase in costs associated with administering chlorhexidine mouthwash gel, $2.82 (R 18.85), is likely to be outweighed by the huge reduction in hospital costs arising from the reduction general ward, critical care unit and mechanical ventilation LoS.The results also suggest that COVID-19 increases hospital costs as the difference in costs between mouthwash and no-mouthwash-arms became higher due to the presence of COVID-19. This suggests that as the number of postoperative pneumonia cases increase because of the COVID-19 pandemic it will be even more cost-saving for hospitals to use preoperative mouthwash since the intervention is likely to be associated with lower proportion of pneumonia cases than no-mouthwash-surgery thereby reducing hospital costs.We made assumptions many of which deliberately undermined the possible effectiveness of mouthwash at reducing postoperative pneumonia. Despite the assumptions, our results have shown that the intervention is likely to be cost-effective. The extensive sensitivity analyses results suggested that even at low levels of effectiveness, mouthwash is likely to dominate no-mouthwash-surgery. The sensitivity analysis was conducted at a lower relative risk reduction rate suggesting that even the best case scenarios might have shown lower dominance than what could have been estimated if we had access to clinical data. This supports the urgent need to conduct clinical trials to access the effectiveness and cost-effectiveness of mouthwash surgery at reducing pneumonia among non-cardiac surgery patients to save resources especially LMICs.To our knowledge, this study is the first economic evaluation to explore the potential impact of preoperative mouthwash at reducing postoperative pneumonia at 30 days after abdominal surgery. Conducting research and randomised controlled trials in resource-limited settings is challenging because of the additional resources required to conduct such studies and collect robust data. The preliminary modelling approach carried out in this study has the benefit of highlighting the data which are likely to be most critical in the analysis and establish potential cost-effectiveness of preoperative mouthwash.This study had several limitations specifically with respect to the dearth of available data.First, three parameters in the control arm were estimated exclusively based on expert opinion. In the experimental arm, the critical care unit, mechanical ventilation and mortality probabilities of patients who developed pneumonia were estimated by reducing corresponding probabilities in the control arm assuming using 0.3 RRR. Further, in the experimental arm, critical care unit, mechanical ventilation and mortality probabilities of patients that did not develop pneumonia and the probability of dying in general ward for pneumonia patients were assumed to be same as probabilities of corresponding pathways in the control arm. On the positive side, the impact of the parameters on the model results were rigorously checked in the sensitivity analysis by reducing the RRR value to 0.01 and increasing or decreasing the probability of the parameter up to 90% and the results shown mouthwash to be a cost-effective intervention.Second, using costs data from other countries was an inevitable limitation of the study. Finally, the objective of the analysis was to assess the impact of COVID-19 on increasing pneumonia incidence rates after surgery as such a transmission dynamic model may be considered more appropriate . HoweverThe model based analysis here was based on very limited primary data and heavily reliant on assumptions but ones which have deliberately attempted to undermine the benefit of mouthwash. Even in these scenarios the results suggest that mouthwash is likely to be cost saving. Thus, there is an urgent need to conduct appropriately focused clinical trials to assess the effectiveness and safety of the mouthwash intervention at reducing pneumonia among non-cardiac surgery patients in order to present robust evidence to support these results and to save crucial and scarce resources.The cost-effectiveness analysis was conducted to evaluate the potential cost-effectiveness of mouthwash at reducing pneumonia among abdominal surgery patients in South Africa. The results suggest that preoperative mouthwash surgery is likely to save money because it reduces LoS. Even a small improvement in effectiveness of mouthwash is likely to reflect good value for money. However, this analysis was based on numerous assumptions due to the paucity of evidence of the proposed intervention among non-cardiac surgery patients. Further research, in the form of a clinical trial is required to assess the effectiveness and safety of the intervention among non-cardiac surgery patients.S1 Appendix(DOCX)Click here for additional data file.S2 Appendix(DOCX)Click here for additional data file.S1 Paper(DOCX)Click here for additional data file.S1 Fig(TIF)Click here for additional data file. 2 Jul 2021Preliminary model assessing the cost-effectiveness of preoperative chlorhexidine mouthwash in reducing postoperative pneumonia among abdominal surgery patients in South AfricaPONE-D-21-06295Dear Dr. Kachapila,We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at onepress@plos.org.If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact Kind regards,Emre BozkurtAcademic EditorPLOS ONE 4 Aug 2021PONE-D-21-06295 Preliminary model assessing the cost-effectiveness of preoperative chlorhexidine mouthwash at reducing postoperative pneumonia among abdominal surgery patients in South Africa Dear Dr. Kachapila:I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. onepress@plos.org.If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact plosone@plos.org. 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Mild Personality Disorder, Moderate Personality Disorder, Severe Personality Disorder). Otherwise, the clinician can assign a sub-diagnostic Personality Difficulty code . The clinician is also allowed to assign one or more trait domain specifiers that contribute to the individual expression of personality disturbances . Finally, with the aim of facilitating the identification of individuals who may respond to established treatments, a Borderline Pattern specifier has been included, which is essentially based on the DSM-5 Borderline PD diagnostic criteria. For a more detailed historical account and rationale behind the ICD-11 PD model, we refer to the overview article by Mulder in this special topic collection.WHO member states are soon expected to migrate from the ICD-10 to the ICD-11 Classification of Mental Disorders . While mGiven this radical shift in diagnostic practice, we now take the opportunity to focus on initial and preliminary findings and considerations related to the utility of the ICD-11 classification of PDs. The 17 articles included in this special topic collection are written by authors from 16 different nations. They address various aspects of this new diagnostic approach including assessment of personality functioning, utility of trait domain specifiers, the inclusion of a separate Anankastia domain, and conceptual considerations with reference to narrative identity, mentalization, and psychodynamic theory. Apart from pointing out key findings of the articles, we will also highlight challenges and opportunities that arise with respect to operationalization, clinical implementation, and future directions.Hutsebaut et al. show that the Semi-Structured Interview for DSM-5 Personality Functioning (STiP-5.1) may be employed to assess level of PD severity in incarcerated patients with good inter-rater reliability. Gamache et al. demonstrate that the 24-item Self- and Interpersonal Functioning Scale (SIFS) is a useful measure for determining severity of personality pathology based on the ICD-11 model, and showed promising alignment with external criteria. Finally, Clark et al. introduce a set of preliminary self-report scales for ICD-11 personality disorder, covering both personality functioning and trait domains, which generally showed excellent psychometric qualities.Blüml and Doering discuss how the ICD-11 classification of PD severity converges with long-standing psychodynamic conceptualizations of personality pathology, and provide a meaningful common ground for assessment and treatment of PDs. Using an empirical approach, Nazari et al. show that a pan-theoretical approach to personality functioning, such as the ICD-11 classification of PD severity, is well-aligned with the object-relations model of personality functioning. Lind illustrates how narrative identity contributes an indispensable aspect to ICD-11's definition of functioning in aspects of the self that revolves around “stability and coherence of one's sense of identity.” Finally, with their empirical findings, Rishede et al. make a compelling proposal about how the capacity for mentalizing is involved in the ICD-11 model of personality functioning, which is deemed particularly relevant for its clinical utility.Riegel et al. overall supported the ability of the 36-item Personality Inventory for DSM-5 and ICD-11 Brief Form Plus (PID5BF+M) to capture the five ICD-11 trait domains in a Czech-Speaking community sample, with the exception of the Disinhibition domain. Pires et al. demonstrate the ability of ICD-11 trait domain specifiers to differentiate patients with PDs from other clinical groups using the PID5BF+M measure. Fang et al. affirm that the ICD-11 trait domains have acceptable psychometric features in a large Chinese sample, including structural validity and continuity with familiar PD types. Gutiérrez et al. show that four trait domains  are roughly interchangeable across ICD-11 and DSM-5 trait systems, and propose how the trait domains' discriminant validity can be improved. Using a mixed sample from the Kurdistan region, Hemmati et al. demonstrate that the ICD-11 trait model outperforms the DSM-5 trait model in terms of factorial model fit within this particular region. Finally, Kerber et al. examine the utility of ICD-11 traits  for predicting treatment outcome and serving as a measure of change.Gecaite-Stonciene et al. review the empirical literature on personality features corresponding to the ICD-11 domain of Anankastia, and find this domain to have structural validity and substantial overlap with established traits of obsessive-compulsive PD. Using empirical data, Strus et al. show that the ICD-11 Anankastia domain reveals more distinct features of personality pathology than the DSM-5 domain of Psychoticism. Along the same lines, Clark et al. show that Anankastia is not merely the opposite end of a Disinhibition dimension. Finally, Bastiaens et al. use clinical cases to illustrate how the separate ICD-11 domain of Anankastia contribute with distinct and relevant patient information that is not merely explained by reversed Disinhibition.The ICD-11 PD workgroup decided to include a separate domain of Anankastia rather than focusing on low levels of Disinhibition as in the DSM-5 model. Strengths and weaknesses of this decision have already been discussed in the literature –7. Gecaiper se without having to use additional instruments or measures. Thus, it should be doable for practitioners to determine PD severity based on clinical observations or other available material. Nevertheless, standardized instruments or measures are often indispensable for ensuring sufficient reliability.Clinicians across all WHO member countries should be able to diagnose a PD using the freely accessible ICD-11 Clinical Descriptions and Diagnostic Guidelines  scale , which iClark et al. to capture the specified features of ICD-11 trait domains. Practitioners may also employ the 60-item Personality Inventory for ICD-11 (PiCD)  –13 as doort form , 14 aimeort form  is availort form  may be pFang et al. and Hemmati et al. Finally, as shown in the studies by Bastiaens et al., Kerber et al., Pires et al., and Riegel et al., the 36-item PID5BF+M can be used measure essential features of both ICD-11 and DSM-5 trait domains including 18 subfacets  may also be used to capture the ICD-11 traits , 18, as ubfacets .Extensive knowledge is already available about the clinical utility of PD severity and dimensional assessment in general –22, but It also seems highly relevant to provide clinical guidelines for trait domain specifiers (in combination with the severity classification) in order to assist individualized case formulation, treatment planning, and intervention. Initial research suggests that such aspects of the ICD-11 classification's clinical utility are satisfactorily supported , 25–28.Finally, we acknowledge the inclusion of a borderline pattern specifier as a preliminary pragmatic solution to divergent positions, which also may ease the transition for patients who have already been granted support or treatment based on a borderline diagnosis. Yet, preliminary research suggests that global severity of personality dysfunction substantially accounts for the variance described by Borderline PD –32. The BB wrote the first draft of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.JK and BB are involved in work related to ICD-11 field trials. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Patient report of functioning is one component of the neurocognitive exam following traumatic brain injury, and standardized patient-reported outcomes measures are useful to track outcomes during rehabilitation. The Traumatic Brain Injury Quality of Life measurement system (TBI-QOL) is a TBI-specific extension of the PROMIS and Neuro-QoL measurement systems that includes 20 item banks across physical, emotional, social, and cognitive domains. Previous research has evaluated the responsiveness of the TBI-QOL measures in community-dwelling individuals and found clinically important change over a 6-month assessment interval in a sample of individuals who were on average 5 years post-injury. In the present study, we report on the responsiveness of the TBI-QOL Cognition–General Concerns and Executive Function item bank scores and the Cognitive Health Composite scores in a recently injured sample over a 1-year study period. Data from 128 participants with complicated mild, moderate, or severe TBI within the previous 6 months were evaluated. The majority of the sample was male, white, and non-Hispanic. The participants were 18–92 years of age and were first evaluated from 0 to 5 months post-injury. Eighty participants completed the 1-year follow-up assessment. Results show acceptable standard response mean values (0.47–0.51) for all measures and minimal detectable change values ranging from 8.2 to 8.8 T-score points for Cognition–General Concerns and Executive Functioning measures. Anchor rating analysis revealed that changes in scores on the Executive Function item bank and the Cognitive Health Composite were meaningfully associated with participant-reported changes in the areas of attention, multitasking, and memory. Evaluation of change score differences by a variety of clinical indicators demonstrated a small but significant difference in the three TBI-QOL change scores by TBI injury severity grouping. These results support the responsiveness of the TBI-QOL cognition measures in newly injured individuals and provides information on the minimal important differences for the TBI-QOL cognition measures, which can be used for score interpretation by clinicians and researchers seeking patient-reported outcome measures of self-reported cognitive QOL after TBI. Cognitive concerns are common after traumatic brain injury (TBI), although the presentation of subjective complaints and objective impairments are heterogeneous across individuals . Post-inPatterns of post-injury recovery of cognitive symptoms have been shown to differ with injury severity, mechanism, and location, with the fastest rate of recovery for both objective cognitive impairments and subjective report of symptoms generally observed in the first 6 months post-injury . Cognitivia interview, although formal assessments of patient-reported outcomes (PROs) are useful for settings where standardization is needed  initiative funded by the National Institutes of Health Common Fund and the Quality of Life in Neurological Disorders (Neuro-QoL™) measurement system funded by the National Institute of Neurologic Disorders and Stroke   is a TBIa REDCap , 2019, oa REDCap . Furtherr = 0.86 (95% CI = 0.79–0.91); Cognition–General Concerns: r = 0.88 (95% CI = 0.81–0.92)] ] .The responsiveness of a PRO measure is an aspect of construct validity that estimates the ability of a measure to capture meaningful change over time . MinimalAs part of the process of marshaling evidence for the construct validity and utility of the TBI-QOL, the present study was designed to evaluate the responsiveness of the TBI-QOL cognition measures in a sample of individuals with recent TBI . Patient report of cognitive functioning and symptoms from this sample provides a unique opportunity for evaluating measure responsiveness, as improvement in self-reported cognition functioning would be expected for many individuals due to the typical course of recovery after TBI. Additionally, this will be the first study to evaluate the responsiveness of the TBI-QOL Cognitive Health Composite score, which is one of five recently developed summary metrics for the TBI-QOL measures . AlthougParticipants were 134 adults with a history of recent TBI recruited from three clinical sites in the United States as part of a larger multi-year study to evaluate longitudinal trajectories of recovery after TBI. All three sites were part of the TBI Model Systems program, which is a network of institutions that are funded by the United States National Institute on Disability, Independent Living, and Rehabilitation Research as leading centers for clinical care and research on TBI . CriteriData collection was conducted either as part of an in-person or telephone interview where participants received select measures from the TBI-QOL  as CATs with an eight-item minimum and 12-item maximum. These measures yield T-scores with a mean of 50 and standard deviation (SD) of 10. Since the TBI-QOL Cognition–General Concerns and Executive Function banks have been linked to the Neuro-QoL v1.0 metric, the reference sample for these item banks is a combined general population and clinical neurological sample . AdditioThere are 37 Executive Function and 39 Cognition–General Concerns items calibrated in these banks; the item stems , item contexts , and response sets  for these two banks have been published previously and will not be repeated here . The TBIParticipants completed the TBI-QOL measures in interview format at the initial assessment  and then a second time 1 year later. At the 1-year follow-up assessment, participants also completed a series of anchor items designed to capture participant perception of any change in symptoms or functioning since the initial assessment . This apSM online platform  to ensure consistency and standardization across data collectors and sites. Each data collector attended an interactive, web-based training session, passed a certification quiz, and completed multiple practice assessments prior to beginning live data collection. Data collectors met biweekly to review recruitment and accrual progress and discuss any actual or anticipated changes or challenges. Data collectors were trained to not provide assistance to participants in selecting their responses. Instead, interviewers simply read the questions aloud and directed the participant to the appropriate response card to select the response that they felt most closely fit their experience. All data were entered directly by the interviewer into the Assessment Centerplatform . The user)]  (Mdifference/SDdifference). SRM values ≥0.3 were considered indicative of a moderate effect size corresponding to meaningful change ]  and mini2 × SEM)  were com2 × SEM)  was compl change . Paired Responsiveness was further evaluated by examining associations between each of the 12 anchor item ratings and TBI-QOL change scores  using Pearson correlations. Correlation coefficient values ≥0.30 indicated a meaningful, moderate relationship . The Bent-tests, and exploratory stepwise multiple regression analyses. Exploratory analysis of patterns of variation in TBI-QOL change scores with demographic variables were also evaluated using Pearson correlations (age) and one-way ANOVAs  to understand any potential covariates. All analyses were conducted using SPSS Version 26  were compared using one-way ANOVA. Associations of TBI-QOL change scores with other markers of injury severity and recovery pace ; inpatient rehabilitation LOS; and living situation at time of initial evaluation) were examined using Pearson correlations, independent samples rsion 26 .Data from 128 participants with a medical record confirmed diagnosis of complicated mild (40%), moderate (21%), or severe (31%) TBI with a baseline assessment within 6 months of injury were analyzed. Injury severity was unknown or missing in 8% of cases. The majority of participants in the sample were male (60%), white (69%), and non-Hispanic (73%). The participants ranged in age from 18 to 92 years of age (mean 51.4) and were first evaluated from 0 to 5 months post-injury (mean 2.0 months). Additional demographic and injury severity indicators are shown in 95% values were 8.8 and 8.2 T-score points on the Cognition–General Concerns and Executive Function measures. SRM values ranged from 0.47 to 0.51. Paired samples t-tests indicated significant improvement in self-reported cognition after 1 year on both of the TBI-QOL cognition item banks and the Cognitive Health Composite (p ≤ 0.001).Mean TBI-QOL cognition measure scores and SEM values for each time point are presented in r ≥ 0.3 to indicate a meaningful, moderate correlation, three anchor items were found to be associated with meaningful self-reported improvement in cognition after 1 year: ability to pay attention; ability to multitask; and ability to remember. Considering mean change scores for these three anchor items, the observed mean Cognitive Health Composite score changes (as shown in The majority of participants reported improvement over the preceding year on the 12 anchor items examined. p ≤ 0.05) differences in mean change scores by TBI severity group for the Cognition–General Concerns and Cognitive Health Composite  and the Cognitive Health Composite (p = 0.034). To more fully parse the variation in change score by injury severity, the mean score change on the Cognitive Health Composite was compared for individuals of different injury severities by response to the three salient anchor items: attention, multitasking, and memory. One-way ANOVAs of TBI-QOL change scores by injury severity classification revealed significant .Evaluation of other markers of injury severity and recovery revealed weak to negligible associations of these clinical variables with TBI-QOL change scores see . There wThis study provides evidence to support the responsiveness of the TBI-QOL cognition item banks and Cognitive Health Composite score for use in individuals within the first 18 months of recovery post-TBI. Improvements in self-reported cognition were endorsed for the majority of participants in this sample, on both the TBI-QOL cognition measures and using a set of anchor items. Meaningful associations with TBI-QOL Executive Functioning and Cognitive Health Composite score change were observed with anchor ratings of attention, multitasking, and memory. Individuals who endorsed improvements in these domains on anchor ratings improved by about two-thirds of a SD on the TBI-QOL Cognitive Health Composite score. These findings are generally consistent with previous research showing marked improvements in the domains of executive functioning and memory, particularly in the early recovery period, following TBI . There w95% values reported .The datasets presented in this article are not readily available because a data use agreement must be signed prior to release. Requests to access the datasets should be directed to DT, . The contents represent original work and have not been published elsewhere.All TBI-QOL items, parameters, and data are ©2016 David Tulsky. All rights reserved. All TBI-QOL items originally from Neuro-QoL are ©2008–2013 David Cella on behalf of the National Institute for Neurological Disorders and Stroke. All items are freely available to the public upon request (contact All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


A growing body of evidence suggests that SARS-COV-2 infection during pregnancy may affect maternal-fetal outcomes and possibly result in implications for the long-term development of SARS-CoV-2–exposed children.The PROUDEST (Pregnancy Outcomes and Child Development Effects of SARS-CoV-2 Infection Study) is a multicenter, prospective cohort study designed to elucidate the repercussions of COVID-19 for the global health of mothers and their children.PREGNANT substudy will clinically assess the effects of SARS-CoV-2 infection on pregnancy, childbirth, and puerperium from a mechanistic standpoint to elucidate the pregnancy-related inflammatory and immunological phenomena underlying COVID-19. Pregnant women aged 18-40 years who have been exposed (proven with laboratory tests) to SARS-CoV-2  will be compared to control subjects with no laboratory evidence of in-pregnancy exposure to the virus . Subjects exposed to other infections during pregnancy will be excluded. The BORN substudy is a long-term follow-up study that will assess the offspring of women who enrolled in the prior substudy. It will describe the effects of SARS-CoV-2 exposure during pregnancy on children’s growth, neurodevelopment, and metabolism from birth up to 5 years of age. It includes two comparison groups; group A  comprises children born from SARS-CoV-2–exposed pregnancies, and group B  comprises children born from nonexposed mothers.The PROUDEST trial comprises 2 prospective, sequential substudies. The Recruitment began in July 2020, and as of January 2021, 260 pregnant women who were infected with SARS-CoV-2 during pregnancy and 160 newborns have been included in the study. Data analysis is scheduled to start after all data are collected.Upon completion of the study, we expect to have comprehensive data that will provide a better understanding of the effects of SARS-CoV-2 infection and related inflammatory and immunological processes on pregnancy, puerperium, and infancy. Our findings will inform clinical decisions regarding the care of SARS-CoV-2–exposed mothers and children and support the development of evidence-based public health policies.Brazilian Register of Clinical Trials RBR65QXS2; https://ensaiosclinicos.gov.br/rg/RBR-65qxs2DERR1-10.2196/26477 The natural history of COVID-19, a disease caused by SARS-CoV-2, is still being written. Individuals infected with SARS-CoV-2 may present with a broad spectrum of clinical manifestations, from no symptoms to dramatically progressive disease symptoms that eventually result in death  and immunoglobulin M [IgM] tests), which will be conducted at 14-21 days postpartum.Pregnant women with preexisting chronic diseases (except diabetes and hypertension); those taking continuous medications; those who consume tobacco, alcohol, or other drugs; and those with other suspected or confirmed congenital infections will be excluded.Neonates whose mothers qualified for inclusion in the PREGNANT substudy (had these women been screened) may also be admitted to the BORN substudy, even if their mothers did not participate in the preceding branch.Children initially assigned to the control (nonexposed) group who later become infected with SARS-CoV-2 (as confirmed via laboratory tests) during follow-up will be excluded from all analyses (from the time of SARS-CoV-2 infection diagnosis onward). However, they will continue to receive assistance under the same standards until the end of the study.No precise data are available on the prevalence of SARS-CoV-2 infection among pregnant women in Brazil, but international reports have estimated that up to 15.3% of all pregnancies have been exposed to the virus . Recent Our sampling approach however is not truly random; it is based on convenience, as eligible subjects will present to the recruitment centers. The aforementioned calculations only serve as a reference for avoiding the overestimation of the inclusion of participants. Given the limited amount of available knowledge regarding the effects of SARS-CoV-2 infection on pregnancy and child development, which resulted in the eminently exploratory character of our study, we adopted an “as much as feasible, but no more than reasonable” approach for defining the sample size.We set an a priori number of 300 SARS-CoV-2–exposed women for the PREGNANT phase. This will result in the inclusion of the expected 300 SARS-CoV-2–exposed children in the BORN phase. The subject allocation rate between the exposed and control groups was 1:1. This indicated the need for an additional 300 mothers and 300 children to constitute the nonexposed control groups. Hence, the overall sample size of the PROUDEST was set to 1200 participants (600 mother-child dyads consisting of 300 SARS-CoV-2–exposed mother-child dyads and 300 control dyads).To promote participant retention and completed follow-ups at pregnancy and pediatric outpatient clinics, we will actively search for patients via phone and email.A host of clinical, psychological, neurodevelopmental, biochemical, histological, and imaging assessments will be conducted in accordance with the PROUDEST protocol .Prenatal data from both the pregnant women and their fetuses will be gathered during the follow-up at the Pregnancy Outpatient Clinic of the University Hospital of Brasilia. These data will consist of the medical and sociodemographic data of the mothers; gestational age; symptoms, interventions, and outcomes related to COVID-19 (for SARS-CoV-2–exposed participants); congenital infection screening results; hypertensive disorders and other pregnancy-specific morbidities; general health assessments; general physical examinations; routine clinical biochemistry tests; and ultrasound scans. These scans will be performed between gestational weeks 11-13 and gestational day 6, from gestational week 22 to gestational week 24, and on a monthly basis in the third trimester of pregnancy to assess fetal growth and morphology, placental morphology, amniotic fluid volume, and dopplerfluxometry results. Maternal blood will be collected at the first prenatal consultation, regardless of gestational age. Antenatal consultations will occur monthly up to week 34, every 2 weeks between weeks 34 and 36, and then weekly up to delivery. During pregnancy, psychological risk assessments and mental health screens will be performed with the Beck Depression Inventory during the first prenatal consultation. . IndividAt childbirth, assessments will be conducted to identify the occurrence of dysfunctional labor and the premature rupture of membranes, the type of birth, and delivery outcomes. We will also conduct physical examinations and classifications of the newborns and anthropometry. The early initiation of breastfeeding, the need for neonatal intensive care, and the type of interventions will also be identified. Maternal blood, CSF from women undergoing spinal anesthesia for a cesarean section, and umbilical cord blood samples will be collected.CSF will be collected immediately before the infusion of the medicine for spinal anesthesia, which will be injected via a sterile syringe at an average dosage of 0.5 ml. CSF will be collected in a 4-mL cryotube. Blood samples from mothers and the umbilical cord will be collected in a heparinized tube and centrifuged immediately, and the plasma will be stored in 4-mL sealed cryotubes. CSF and blood samples will be subsequently stored at −80 °C for later analysis. The assessment of blood cell counts, inflammation markers , biochemistry  and SARS-CoV-2 tests (RT-PCR and IgM and IgG antibody tests) will be carried out.Circulating cytokine levels will be evaluated with the Luminex Bio-Plex Pro Human Cytokine 27 platform (Bio-Rad Laboratories). The cytokine profile assessment will analyze chemokines , proinflammatory cytokines , regulatory cytokines , and cell growth factors . All procedures will be performed according to the manufacturer's recommendations.Analyses will be performed at the clinical biochemistry laboratories of the hospitals where delivery occurred , the Central Laboratory of the Federal District Department of Health , and the University of Brasilia laboratory (cytokine profile assessments).The placenta will be subjected to fresh histopathological analyses for assessing possible morphological and histological changes that may be associated with SARS-CoV2 infection. Histopathological analysis will be conducted according to the Amsterdam protocol .Peripheral blood and CSF samples from the newborns will only be collected if there is clinical need; this will not be done per the routine research protocol. If such specimens are made available, they will also be subjected to the aforementioned analyses.All newborns will undergo neonatal screening tests in accordance with the recommendations of the Ministry of Health of Brazil. Five drops of blood will be collected on filter paper for the national neonatal screening program. This blood sample will be collected after 48 hours of life and will be used to screen for the following diseases: phenylketonuria, congenital hypothyroidism, biotinidase deficiency, cystic fibrosis, and congenital adrenal hyperplasia. After 24 hours of life and before discharge, a pulse oximetry test will be performed. Oxygen saturation in the right upper limb and one of the lower limbs will be measured. The pulse oximetry test will be considered normal if oxygen saturation is ≥95% and the difference between the limbs is not ≥3%. Hearing screening will be performed between 36 and 48 hours of life by analyzing otoacoustic emissions.After hospital discharge, all neonates will be followed up at the Pediatric Outpatient Clinic of the University Hospital of Brasilia. Child growth and neurodevelopment will be assessed at all visits. The first visit will be scheduled to occur on day 15 postpartum. Afterward, visits will be conducted monthly during the first 6 months of life. Thereafter, visits will be scheduled every 3 months until the children reach 12 months of age and every 6 months until the children reach 5 years of age. Nonscheduled visits may occur due to urgent clinical needs. The outpatient clinic staff (a multidisciplinary team) will be composed of pediatricians, psychologists, occupational therapists, speech therapists, physiotherapists, and nurses. The psychological effects of SARS-CoV-2 infection on mothers will be assessed with the Edinburgh Postnatal Depression Scale . This asThe assessment of children’s neurodevelopment will be carried out until they reach the 60th month of life. This assessment will analyze cognitive, motor, socioemotional, and language-related aspects and adaptive behavior. The evaluation will be conducted by using the Bayley III Child Development Scale  . From thCentral nervous system imaging assessments will be carried out via transcranial ultrasound doppler scans, which will be performed between the 15th and 90th day of the child's life. A brain magnetic resonance imaging scan will be performed if altered cephalic perimeter measures, neurological development delays, or abnormal ultrasound doppler scan findings are identified.Blood will be collected from SARS-CoV-2–exposed children aged 12 and 24 months to assess their metabolic profiles, which will be used to identify the long-term effects of SARS-CoV-2 infection on systemic metabolism that are potentially driven by past viral exposure and associated inflammatory responses. The examination will consist of assessments for energy metabolism markers , thyroid function markers (thyroid-stimulating hormone and free thyroxine), bone metabolism markers , adrenal tonus indicators , and renal function markers .All newborns will undergo extended hearing screening. Evoked otoacoustic emission and brainstem auditory-evoked potential tests will be performed during the child’s first year of life.t test or the Mann-Whitney U test.All data will be stored in REDCap , which is a tool for building and managing web-based surveys and databases. All variables will be summarized via standard descriptive techniques according to their type and distribution. For the bivariate analysis, differences in categorical variables between the exposed and unexposed groups will be verified with the Chi-square test or Fisher exact test, whereas differences in continuous variables between the groups will be assessed with the Student P value of <.05 will be considered significant. The control group will be composed of nonexposed mother-child dyads that meet the inclusion criteria. However, those with positive serology tests (IgG and IgM tests conducted at 14-21 days postpartum) will not be included in the control group. The groups will not be matched or paired based on age or other variables. However, any differences between the groups will be adjusted later via statistical means.For dichotomous outcomes, binomial regression models, which will be adjusted based on the unbalanced and relevant background features of the comparison groups, will be used to estimate the relative risks between the exposed and nonexposed groups. Partial correlation and general linear models will be used to assess the associations between continuous outcome variables and covariates; adjustments for imbalances will be made as appropriate. A The PROUDEST was approved by the Research Ethics Committee of the University of Brasilia School of Medicine (Certificado de Apresentação de Apreciação Ética 32359620.0.0000.5558) . It was At the time of the publication of this protocol, study enrollment and data collection have already started, but we have not completed the participant recruitment and data analysis phases. Therefore, data sharing is not yet feasible, as no data sets have been generated or analyzed at this stage of the study. As partial data become available, they will be displayed in the Brazilian Register of Clinical Trials .The PROUDEST is in the data collection phase. Study recruitment started in July 2020. As of January 2021, a total of 260 pregnant women who were infected with SARS-CoV-2 during pregnancy and 180 newborns from hospitals in the Federal District in Brazil have been included in the study. Data analysis is scheduled to start after all data are collected.The PROUDEST offers comprehensive insight (from both the obstetric and pediatric perspectives) into the effects of SARS-CoV-2 infection on the global health of pregnant women and their offspring. Specifically, the study will fill the deep gap in knowledge about the consequences of SARS-CoV-2 infection during early gestation , as women in all stages of pregnancy will be followed. The virus-induced inflammatory and immunological phenomena that occur in SARS-CoV-2–exposed mothers during this early period of life may have a particular impact on placental and fetal physiology or may even be associated with epigenetic signals. Therefore, these phenomena could conceivably affect the long-term outcomes of a child’s growth, development, and metabolism.A better understanding of these potential long-term consequences requires lengthy, prospective observational studies, such as the PROUDEST. This study will not only address the clinical outcomes associated with in-pregnancy exposure to COVID-19 but also evaluate a host of soluble tissue biomarkers (as described in this protocol) with the aim of comprehensively understanding the mechanisms underlying related clinical phenomena.Our data will add to the overall clinical and basic knowledge base for COVID-19, and our ultimate goal is to provide grounds for better managing SARS-CoV-2–exposed pregnant women and their children through direct means or by setting the stage for additional studies. In fact, the PROUDEST opens up a broad spectrum of possibilities for further, multidisciplinary research on the effects of SARS-CoV-2 infection on maternal, fetal, and pediatric health. Furthermore, our results might prove to be relevant from a social perspective, as they may provide data that support the tailored development and implementation of health policies that are specifically oriented to this particular demographic group.The study does have several limitations. Its observational nature limits inferences for causal associations to some extent. However, the cohort study design is the closest observational equivalent to a clinical trial in terms of analytical power, and the objective of the PROUDEST does not ethically allow for interventional experiments because such experiments would imply that pregnant woman will be randomized based on SARS-CoV-2 infection. Moreover, the purpose of the study is to characterize the clinical and pathophysiological phenomena associated with SARS-CoV-2 infection during pregnancy and infancy, not to test the efficacy of any intervention. Thus, we believe that a cohort study is the best possible study design for addressing our objectives. The lack of random allocation for comparison groups will be partially compensated by statistically adjusting for the observed imbalances. Vaccination for SARS-CoV-2 will not be an exclusion criterion because due to the vaccine’s limited accessibility and availability, there are no feasible methods for estimating the proportion of pregnant women that will receive the vaccine. However, the effects of SARS-CoV-2 vaccination can be adjusted and analyzed in small control groups that have either received or not received the vaccine.The protracted follow-up in the BORN substudy is expected to result in the dropout of several participants. We set a sample size for the study after taking into consideration a 20% loss to follow-up rate. This might ensure that a sizable number of children are available for the final assessment when they reach age of 5 years. However, we cannot avoid survival bias in the long-term data. Nevertheless, given that the continuity of multidisciplinary assistance will be guaranteed for all children in the BORN branch throughout the study period regardless of their withdrawal from the analysis or (temporary) losses to follow-up, we expect that children experiencing health problems associated with in-pregnancy COVID-19 exposure will be less likely to drop out than those who are in perfect health. Therefore, we do expect to have a sufficient number of children in the long run for identifying developmental abnormalities (should they exist), even after some amount of dropout.Several routine pediatric consultations will be emphasized in the study, such as checking the kind of alimentation that a child is receiving (human milk or formula milk) and promoting the practice of breastfeeding.The PROUDEST is a long-term, prospective cohort study designed to provide a comprehensive analysis of the effects of in-pregnancy exposure to COVID-19 on women and their offspring from a clinical and pathophysiological standpoint. Our results might contribute to the improvement of the management of SARS-CoV-2–exposed mother-child dyads—through direct means or by setting the stage for future related studies—by providing knowledge on the clinical-pathophysiological phenomena associated with COVID-19 exposure among this particular population.


Whether it is for COVID-19 primary vaccination or the administration of booster vaccines, prioritization criteria need to be established to optimize COVID-19 vaccination programs accounting for both clinical and social vulnerability risks for severe COVID-19 disease. We developed a dual socio-clinical risk model for severe COVID-19 disease in the Medicare population, which is comprised mostly of individuals aged 65 and over. Our model generated risk levels correlated with regionalized COVID-19 case hospitalization rates and mapped them at the county and zip code levels. The model and map can be used by health jurisdictions to reach out to unvaccinated individuals. Our model approach can also be applied to identify Medicare beneficiaries who were in early vaccination groups to be vaccinated to identify those who might maximally benefit from an additional dose of COVID-19 vaccine if and when vaccine immunity wanes.Recommendations for prioritizing COVID-19 vaccination have focused on the elderly at higher risk for severe disease. Existing models for identifying higher-risk individuals lack the needed integration of socio-demographic and clinical risk factors. Using multivariate logistic regression and random forest modeling, we developed a predictive model of severe COVID-19 using clinical data from Medicare claims for 16 million Medicare beneficiaries and socio-economic data from the CDC Social Vulnerability Index. Predicted individual probabilities of COVID-19 hospitalization were then calculated for population risk stratification and vaccine prioritization and mapping. The leading COVID-19 hospitalization risk factors were non-white ethnicity, end-stage renal disease, advanced age, prior hospitalization, leukemia, morbid obesity, chronic kidney disease, lung cancer, chronic liver disease, pulmonary fibrosis or pulmonary hypertension, and chemotherapy. However, previously reported risk factors such as chronic obstructive pulmonary disease and diabetes conferred modest hospitalization risk. Among all social vulnerability factors, residence in a low-income zip code was the only risk factor independently predicting hospitalization. This multifactor risk model and its population risk dashboard can be used to optimize COVID-19 vaccine allocation in the higher-risk Medicare population. The question of who should get COVID-19 vaccines was first debated by the National Academy of Medicine, the Centers for Disease Control and Prevention, and by epidemiologists and other disease experts worldwide. U.S. recommendations for the first administration of COVID-19 vaccines focused first on vaccinating individuals at risk for severe disease once health care personnel, nursing home residents, and essential workers had been vaccinated .The National Academy of Medicine recommended simultaneously prioritizing individuals living in areas with socio-economic conditions associated with disproportionate vulnerability ,4 by usiAny prioritization scheme, following on the Advisory Committee on Immunization Practices , must coWe developed a model to predict COVID-19 hospitalization and death for Medicare beneficiaries using de-identified Medicare claims which are an important national data resource for studies of the COVID-19 pandemic ,16,17,18At a time when we have most recently observed a pandemic uptick due to the SARS-CoV-2 delta variant and may see future pandemic waves due to new variants, this model can be applied to reach out to unvaccinated individuals at highest risk for severe disease to encourage them to get vaccinated. This same modeling approach can also be applied to identify vaccinated Medicare beneficiaries who were first prioritized for vaccination and who might most benefit from an additional dose of COVID-19 vaccine if their level of immunity declines over time.We constructed an observational cohort consisting of all Medicare FFS beneficiaries who since 1 January 2020, either had a COVID-19 test or a COVID-19 diagnosis (identified by ICD-10 code U071 after 1 April), or for any medical reason were hospitalized or had an emergency department, urgent care, or telehealth visit. The report is based on weekly data outputs from the Center for Medicare and Medicaid Services  Chronic Condition Warehouse from 1 October 2019 through 22 November 2020, resulting in a weekly download of over 100 million individual records to a secure government enclave of the DoD JAIC for Project Salus’ partner, Humetrix, to process and analyze.Dependent variables were confirmed COVID-19 cases and their related hospitalizations and deaths. Independent variables included beneficiary age, sex, ethnicity, insurance coverage, the number of prior hospitalizations, comorbidities, dispensed medications and local socio-economic variables from the CDC Social Vulnerability Index. We used the number of prior hospital admissions since 1 October 2019 as an indicator of frailty, and we assessed comorbidities by examining an individual’s diagnoses listed in claims data beginning 1 October 2019. To identify comorbidities, we used a set of chronic conditions flagged by CMS and compiled diagnostic categories using specific ICD-10 code algorithms to identify additional chronic conditions. Medication NDC codes  were used to identify active pharmaceutical ingredients, which were grouped by pharmaceutical class by mapping to RxNorm codes . Socio-economic variables  were defined at the individual residential zip code level after conversion from the census track based data found in the CDC Social Vulnerability Index using HUD-USPS [We used logistic regression to identify significant predictors of COVID-19-related hospitalization or COVID-19 deaths, using R statistical software, version 3.6 with rms, glmnet and pROC packages ,22,23,24Because the odds ratios derived from logistic regression models are a measure of the association between a given feature  and the outcome , we supplemented our analyses with a random forest machine learning algorithm, which produces computed Feature Importance values   and provWe used the results of our logistic regression to compute individual predicted probabilities of hospitalization in the event of SARS-CoV-2 infection for the entire analytic cohort of 16 million beneficiaries. We then computed the percentage of the cohort population with a predicted probability of hospitalization of 0.55 or higher, mapping the data at county and zip code levels for the entire country on a nationwide digital dashboard. The predicted probability threshold of 0.55 was selected as it generated higher Pearson’s R values than a threshold of 0.50 in the linear regression analysis of COVID-19 case hospitalization rates as a function of the population risk level in each zip code in six major metropolitan areas shown  are summarized in p values < 0.001; see p values < 0.001), or with the most crowded housing , chronic kidney disease, hypertension, ischemic heart disease, cerebrovascular disease, pulmonary fibrosis or pulmonary hypertension, chronic liver disease, asthma and CHF (congestive heart failure) . In contrast to income, neither crowded housing nor living in multiunit housing were independent risk factors for either hospitalization or death from COVID-19 (both ORs < 1.0). The socio-economic variables for poverty and education, the housing and transportation summary SVI ranking variable, and the overall summary SVI variable were highly correlated with either income or housing variables and thus excluded from the final models  and frailty as assessed by one or more prior hospitalization(s) since October 2019 . Morbid obesity and leukemia were leading risk factors for hospitalization; in addition, patients with chronic kidney disease, lung cancer, chronic liver disease, pulmonary fibrosis or pulmonary hypertension, or were undergoing chemotherapy had 20–30% higher risk of hospitalization see  would haThe random forest results identifying important factors for predicting hospitalization and death in the Medicare beneficiary sample are presented in We used the logistic regression results to calculate a predicted probability of hospitalization for every individual in the cohort based on their individual characteristics and applied these probabilities to map population-level risk nationwide at both zip code and county levels see . These rp < 0.0001)). We conducted the same correlation and linear regression analyses in 5 other major metropolitan areas in the U.S. All correlation coefficients in these regions had p values < 0.0001 by Chi Square. .are. see . For theThe severe COVID-19 risk models and the mapping of Medicare beneficiaries at highest risk are based, to our knowledge, on the largest COVID-19 dataset assembled to date for this purpose. Importantly, this cohort captured confirmed COVID-19 cases after 1 March 2020, their hospitalizations, and deaths amongst the total 37 million beneficiaries comprising the Medicare FFS population. All members of the study cohort were active users of health care services, presenting on average a frailer clinical profile than the general Medicare population , as showThe nationwide distribution of the population also enabled DoD’s Project Salus to produce the first county and zip code level mapping of the population at higher risk for severe COVID-19 and related hospitalizations, with the original goal of providing logistics support to hospitals predicted to experience a surge in patients. Beyond its use for pandemic mapping, the model and related mapping provide information that local health authorities can use to identify zip codes with the highest percentages of FFS beneficiaries at risk of severe COVID-19 who should be prioritized for the administration of primary series or booster doses of COVID-19 vaccines. The same regions should also be a focus of public health efforts to motivate wearing face masks in high-risk indoor settings to reduce the risk of exposure to a large infectious dose of SARS-CoV-2 sufficient to cause COVID-19 infection.Our combined use of logistic regression and random forest analyses, as applied to this very large Medicare population, allowed us to further assess the current CDC listing of clinical and socio-demographic risk factors for severe COVID-19 ,31. LogiUnlike odds ratios which are not influenced by the prevalence of the Feature in the population, Feature Importance is also more influenced by how common a Feature is within the sample. Thus, while North American Native ethnicity has one of the highest odds ratios in the hospitalization logistic regression model, its Feature Importance in the random forest model was low (ranked 42nd out of 50 variables) due to the low frequency of this feature in the sample (<1% of the sample). The random forest analysis identifies CHF, COPD and chronic kidney disease which, unlike North American Native ethnicity, are highly prevalent in this cohort  as among the most important risks for hospitalization  and death  from COVID-19 for the entire cohort, even though each of these conditions at the individual level are associated with modest risks with odds ratios all under 1.3 in the logistic regression hospitalization and death models.Both logistic regression and random forest analyses affirm the critical risk factors of ethnicity , older aHowever, contrary to prior descriptive analyses performed on smaller population sizes of hospitalized patients only ,36,37, oOne of the main limitations of our study and derived models is that it is only based on the Medicare FFS population, which represents approximately 60% of the total Medicare population, with regional variations ranging from 98% in Alaska to 51% in Minnesota. There is evidence that Medicare Advantage plans tend to enroll beneficiaries who are healthier than Medicare FFS beneficiaries, this difference in health status will limit the generalization of our model to the entire Medicare population. If the model were to be used for vaccine allocation, it could be updated using Medicare Advantage data if these were made available. Finally, fifteen percent of this FFS Medicare study cohort are beneficiaries under the age of 65 who are either disabled or have end-stage renal disease (ESRD) or amyotrophic lateral sclerosis which limits the applicability of our findings to the over 65 U.S. population.With the above limitations, the models we have developed provide important information for public health officials and advisory groups who recommend COVID-19 vaccination and other preventive behaviors to consider. Specifically, because the models integrating both socio-economic factors and individual clinical data respond to the recommendations of the NAM for prioritization and allocation of COVID-19 vaccines, they could be used to support planning a vaccination campaign. This quantitative analysis of risk for severe COVID-19 in the Medicare population provides important new insights useful for managing the COVID-19 vaccination campaign. At this time of unpredictable pandemic upticks due to new or evolving SARS-CoV-2 variants, this risk model can be applied to reach out in priority to unvaccinated individuals at highest risk of severe disease, either by area or using individual identifiers. Our risk model development approach can also be applied when considering booster administration if waning vaccine immunity takes place starting with individuals at higher risk . To be a