Recently deep learning has attained a breakthrough in model accuracy for the classification of images due mainly to convolutional neural networks. In the present study, we attempted to investigate the presence of subclinical voice feature alteration in COVID-19 patients after the recent resolution of disease using deep learning. The study was a prospective study of 76 post COVID-19 patients and 40 healthy individuals. The diagnoses of post COVID-19 patients were based on more than the eighth week after onset of symptoms. Voice samples of an ‘ah’ sound, coughing sound and a polysyllabic sentence were collected and preprocessed to log-mel spectrogram. Transfer learning using the VGG19 pre-trained convolutional neural network was performed with all voice samples. The performance of the model using the polysyllabic sentence yielded the highest classification performance of all models. The coughing sound produced the lowest classification performance while the ability of the monosyllabic ‘ah’ sound to predict the recent COVID-19 fell between the other two vocalizations. The model using the polysyllabic sentence achieved 85% accuracy, 89% sensitivity, and 77% specificity. In conclusion, deep learning is able to detect the subtle change in voice features of COVID-19 patients after recent resolution of the disease. The respiratory tract is an important site of SARS-CoV-2 infection and disease morbidity. This may be explained by the high expression of ACE2 in human epithelium2. Moreover, ACE2 is expressed in oral mucosa3 and can also cause loss of smell and taste. Human voice generation is a coordinated function of multiple body structures, including the lungs, vocal folds and laryngeal muscle. About a quarter of patients with mild to moderate COVID-19 have been found to have dysphonia, and interestingly, the expression of ACE2 has also been demonstrated in the vocal folds4. Whether there is a subclinical persistence of voice abnormality after recovery from SARS-CoV-2 infection is currently unknown. These signal analyses are an emerging noninvasive voice biomarker for COVID-19 infection.The COVID-19 pandemic has caused enormous health, social and economic burdens. SARS-CoV-2, the virus causing the disease, affects multiple body structures and organs. It infects host cells mainly through binding to ACE2, which has been established as a receptor for the SARS-CoV-2 virus as well as for SARS-CoV-1, enabling the virus to enter host cells. ACE2 is expressed in multiple tissues. The highest expression levels are reported in the small intestine and the lowest in blood vessels and muscle5, acoustic scene classification6, and audio events classification7. In the present study, we hypothesized that subtle voice changes could occur post COVID-19 infection. We attempted to investigate the presence of subclinical voice feature alteration in COVID-19 patients once the disease had resolved, and the ability of artificial intelligence using CNN to classify patients based on past history of COVID-19.Recently deep learning has attained a breakthrough in model accuracy for the classification of images due mainly to convolutional neural networks (CNN). Not limited to image classification, CNN has been widely used in converting non-image datasets into 2D or 3D datasets. For voice classification, successful implementations include the classification of singing voiceThis was a prospective study of 76 post COVID-19 patients seen at the outpatient clinic at Chakri Naruebodindra Medical Institutes (CNMI) between May and June 2020. The study was approved by the Faculty of Medicine Ramathibodi Hospital Institutional Review Board. All methods were performed in accordance with the relevant guidelines and regulations. All participants gave their written informed consent before participating in the study. All post COVID-19 patients were more than 8 weeks after onset of symptoms at the time of the study. The exclusion criteria included pregnancy, breastfeeding, uncontrolled hypertension (systolic blood pressure > 160 mmHg or diastolic blood pressure > 100 mmHg), acute myocardial infarction or stroke in past 6 months, history of substance abuse, neurological disorders, current mental health difficulties, active smoking or having stopped smoking for not more than 6 months, alcohol consumption of more than 7 units of alcohol per week, and a history of speech and/or voice disorder such as apraxia of speech, functional articulation disorder, dysarthria, cleft lip/palate, tongue or teeth abnormality, oral occlusion, laryngeal abnormality, or neurological voice disorders. For controls, 40 healthy individuals with no underlying disease were recruited from back-office staff working at CNMI.Patients who met the screening criteria were interviewed using a predefined questionnaire to collect demographic data and determine the duration of the disease. Three voice recordings were collected from each participant using a plug-in microphone on a mobile phone. The recordings consisted of a persistent ‘ah’ sound for 5 s, a Thai polysyllabic sentence selected by a voice specialist for vocal apparatus analysis, and a cough sound. The voice recordings were mono-channel and sampled at 44,100 Hz with a maximum duration of 30 s. Both the training and testing set were binary labeled.Each voice sample was divided into 100 ms (ms) subsamples and a log-mel spectrogram was computed using the Python Librosa package. The dimension of each subsample array was 128 × 32. The 2D data array was then converted to 3D suitable for downstream learning by adding a dimension containing identical 2D arrays as the original 2D array. Eighty percent of the total voice records were used as the training set, and the others as the testing set.Building and training of the neural network was performed on Tensorflow version 2 . We used the VGG19 pre-trained neural network for both pre-train transfer learning and model training. The VGG19 is a widely used CNN, particularly for image classification and computer vision problems due to its in-depth structure and good performance. For transfer and retraining of the VGG19 CNN, the output layer of the VGG19 was dropped and two dense layers of 64, 32 fully connected units, each with batch normalization were added. The new output layer was added with one output unit and a sigmoid activation. A 2D CNN layer was prepended the input of the pretrained VGG19. The input layer of the full transfer learning model was 128 × 32 × 1 in dimension. All layers of the modified VGG19 were made untrainable except for the last five layers to make the pre-trained CNN more suitable for the new voice dataset. Three-fold cross validation was used to assess the performance of the trained neural network. Each fold comprises 78 training samples and 38 training samples. We used a binary cross entropy loss function as our study was a binary classification problem. ADAM optimization was used for the gradient descent with a learning rate of 0.01. Parameters used during training were batch size 32, maximum training epochs 600, percentage of training sample set aside randomly for validation 20% and the matric monitored was area under the curve of the performance of the validation set.Shannon entropy of each voice type in all subjects was calculated using the Python AntroPy package.p value less than 0.05 was considered statistically significant. All analyses were performed using Stata Statistical Software, Release 12 .Data were expressed as mean ± SD unless specified otherwise. Multiple logistic regression models were used for assessing potential associated factors. A Clinical characteristics of study participants are shown in Table Examples of the mel-spectrogram of the 3 voice types from a study subject were shown in Fig. We further investigate if the information content of voices as measured by the Shannon entropy may in part be responsible for the better performance of the polysyllable voice. The boxplot of Shannon entropy of each type of voice from all subjects is shown in Fig. As clinical characteristics of participants with or without recent COVID-19 were not well-matched, we further used multivariate logistic regression analyses to investigate if voice can predict recent COVID-19 independently of age, gender and BMI. Clinical characteristics and the values extracted from the CNN of each fold were shown in Table 8 have been described. However, to our knowledge, the alteration in voice has been less reported. It is also important to point out that such alteration is subclinical, not obvious to either the patients or healthcare providers. For the loss of smell and taste, early resolution was reported in most patients but the abnormality can persist in some patients up to 4 weeks after the onset of symptoms9. Our study showed that the subtle change in voice could be present even 60 days after being discharged from hospital. Recently, it has been increasingly aware that some symptoms of COVID-19 can persist well beyond the recovery in infected subjects. Long COVID was characterized by symptoms of fatigue, headache, dyspnea and anosmia and was more likely with increasing age and body mass index and female sex10 and is thought to occur in approximately 10% of people infected12. However, how soon and for how long the alteration can be detected is currently unknown. Further studies are warranted, particularly to evaluate the presence of voice change early in the course of the disease, which, if present and specific, could be developed into a screening modality for long COVID.In the present study, we demonstrated that voice features represented by mel-spectrogram could distinguish patients with recent COVID-19 disease from controls, particularly with polysyllabic sentences. The results suggest that the SARS-CoV-2 may affect tissue involved in voice production well beyond the resolution of the disease. Some unique characteristics of COVID-19 such as loss of smell and taste13. There are several factors which potentially can be responsible for the changes in voices in COVID-19. Besides being a consequence of inflammation of related voice producing organs, SAR-CoV2 can potentially affect the vocal cords directly. Enriched expression of ACE2, the receptor for SAR-CoV2 has been demonstrated in the head and neck regions, particularly in sinuses, salivary glands, oral cavity epithelial cells and vocal cords14. Moreover, post viral vagal neuropathy could occur which can present as persistent shortness of breath despite normal chest radiograph15.Our results are in keeping with previous studies suggesting that perturbation of voice has recently been suggested as a manifestation of COVID-19 which can occur in up to a quarter of patients with mild to moderate disease18. In the present study, we demonstrated that voice features such as mel-spectrogram can be represented as an image and used as inputs for CNN. For the classification of images, a number of feature visualizations have been explored to better understand how CNN sees features in images19. These learned features are usually hard to identify and interpret from a human vision perspective, causing a lack of understanding of the CNN’s internal working mechanism. Similarly, features in the mel-spectrum which distinguish individuals with past COVID-19 and controls in the present study are unclear. This ‘black box’ nature of deep neural networks is one of its shortcomings and the deep understanding of features contributing to classification performance is difficult to attain.Current artificial intelligence models can achieve diagnostic performance comparable to those of medical experts in various domains20, heart failure21, and diabetes mellitus22. Currently there is no consensus on which kinds of speech or voice are more suitable for use as voice markers. For example, voice biomarkers for diabetes are varied in the literature and include matched fragments of speech23, free speech24 or vowel sounds25. The relative accuracy of using different kinds of human voices for such purposes are currently unclear. However, we demonstrated in the present study that speech utterances of a complex sentence are more accurate for the prediction of previous COVID-19 infection than simple vowels or a cough sound. The underlying basis for this difference is not clear, but it may be related to the higher variation in voice features from more complex sounds which render it more effective when used for classification by machine learning methods. To explore such a notion, we further analyzed the voice types according to their Shannon entropy. Originated from information theory, Shannon entropy is a measure to reflect information content of the variable under study27. For the proposed features selection methodology in machine learning, almost all the information-theoretic approaches are based on Shannon entropy28. Both the polysyllabic and the ‘ah’ sounds in the present study had higher Shannon entropy than the cough sound which corresponded with their apparent better performance than the cough sound. Moreover, as participants were instructed to produce sustained vowels with a continuous phonation over a certain time, it may introduce discontinuities in the pulmonic airstream in COVID-19 infected participants leading to sporadic, unintended interruptions of phonation when expressed the polysyllabic and the ‘ah’ sounds as compared to the cough sound29. Interestingly, as far as we know, most of the studies using voice to classify the presence of COVID-19 have utilized cough sounds as the study features32. It is therefore worthwhile to further explore speeches and other voice types which may have higher information content and better classification performance than cough sounds per se. Moreover, it is of note that regardless of different accuracies, all 3 voice types produced higher sensitivity compared to specificity, this would suggest that the practical use case of voices to classify past COVID would be more appropriate for screening purpose and caution should be exercised with negative results as false negative rates could be relatively high.There have been many attempts to use voices as biomarkers for diseases including Parkinson’s disease34, however only the VGG19 CNN was explored in this study. Future studies with a larger sample size, better-matched baseline characteristics between cases and controls, and varying neural network architecture are warranted.There are some limitations to the present study. First, the sample size was relatively small. However, we used transfer learning with a pre-trained model to mitigate this limitation. Second, baseline characteristics were not well matched across the two participant groups. However, after controlling for unmatched clinical parameters, the polysyllabic sentence used in this study was effectively used to distinguish patients with recent COVID-19 from controls. Third, there are a number of neural network architectures suggested for audio classificationDeep learning is able to detect the subtle change in voice features of COVID-19 patients after recent resolution of the disease.


The COVID-19 pandemic has resulted in widespread adoption of telemedicine for management of chronic conditions such as type 1 diabetes (T1D), but few data have been collected about the patient experience and perceived quality of care during this time. We surveyed members of the T1D Exchange patient registry and online community regarding their experiences with and opinions about telemedicine care during the pandemic. Among 2235 survey respondents, 65% had utilized telemedicine. The most common reasons for adopting telemedicine were providers not offering in-person care (66%), concerns about the health risks of in-person care (59%), providers offering (52%) or insurance covering (19%) telemedicine for the first time, and local or state orders to stay home (33%). Among telemedicine users, 62% felt video care was as effective as or more effective than in-person care, and 82% hoped to use telemedicine in the future. The most-cited reason for non-use of telemedicine was that providers were not offering it (49%). Our findings highlight the role of telemedicine in maintaining access to T1D care during the COVID-19 pandemic. Respondents’ satisfaction with telemedicine and interest in its continued use signifies the need for ongoing access to this care modality and for the development of telemedicine best practices within T1D care. Type 1 In the wake of this dramatic transformation in care, it is essential to examine patient perspectives about how telemedicine has made T1D care more or less patient-centered during this time. Telemedicine has the potential to facilitate more patient-centered care through increased convenience, greater ownership of and engagement with one’s own diabetes data, and involvement of family members and/or medical providers who are physically distant. However, telemedicine can also add challenges in terms of new technology interfaces, communication barriers, and a decreased sense of personal connection with medical providers. Prior publications have demonstrated high patient satisfaction and time- and cost-savings with telemedicine interventions for T1D –11, as wWe surveyed members of the T1D Exchange patient registry and T1D Exchange online community (formerly Glu) in the United States about their experiences with and opinions about the use of video encounters for T1D management during the COVID-19 pandemic. Our goals were to estimate how widespread the use of telemedicine has been for T1D management in the U.S. during this time and to learn more about the patient experience of T1D care when delivered remotely.2.Survey questions were designed by the research team to elicit information about respondents’ experiences with and opinions about the use of video telemedicine for T1D-related medical care. Invitations to participate were distributed by T1D Exchange to its online community via email, Facebook, Twitter, and Instagram over an eight-week period, and to its online patient registry participants via email and an online portal over a four-week period in the fall of 2020. The T1D Exchange online community and T1D Exchange patient registry together include over 27,000 individuals who either have T1D or are caretakers (parents/guardians) for children with T1D and who participate voluntarily in these groups. Approximately half of these individuals are connected to T1D Exchange via email, and the remainder are connected primarily via social media.™ database.Potential survey participants were asked to follow a QR code or hyperlink, which directed them to a website with additional information about the survey’s purpose, eligibility requirements, and expected time commitment for respondents (5–10 min). Eligibility requirements were an age of 18 years or older, living in the United States, and having T1D or being a caretaker for a child with T1D. An exclusion criterion was current incarceration, due to U.S. policies related to the inclusion of incarcerated individuals in scientific research. Individuals who met these criteria and chose to participate then followed an additional link and had to acknowledge their consent to participate and attest that they met eligibility requirements, at which point the survey was administered and respondent data were collected via a secure REDCapThe survey consisted of 13–18 multiple-choice questions, depending on participant responses. Only complete survey responses were included in the analysis. Univariate statistical comparisons of survey responses for sub-populations of interest were performed using the Pearson Chi-square test, with no expected—or actual—cell sizes containing fewer than five individuals. The UC Davis Institutional Review Board evaluated this study’s protocol and deemed it exempt from formal review. No personal identifiable information such as name, birth date, or contact information was collected from survey respondents.3.3.1.T1D Exchange sent email invitations for this survey to approximately 14,550 individuals. Social media impressions pertaining to this survey could not be precisely quantified but are estimated in the thousands. Overall, 2344 individuals initiated the survey and 2235 completed it; 109 incomplete survey responses were excluded from the analysis. Among our 2235 survey participants, 1974 (88%) responded as persons with diabetes (PWD) and the remaining 261 (12%) responded as caretakers of a child with T1D. Respondents were distributed across all fifty U.S. states and the District of Columbia, with the highest proportions of responses coming from California (10%) and New York (8%). Demographic and clinical characteristics of respondents are reported in 3.2.The majority of respondents  had completed a diabetes medical appointment by video, and another 10% planned to use video for their next diabetes appointment; the remaining 25% had no plans to use video for their T1D medical care. Among respondents who had completed a video visit, 96%  stated that their first video appointments took place during the COVID-19 pandemic, and they cited a variety of factors that led to their adoption of telemedicine during this time, as represented in p < 0.001), while those with private insurance were more likely to report that their providers were not offering in-person care during the pandemic . Respondents of minority race or ethnicity and those from non-college-educated households were each less likely than their counterparts to report concern about the health risks of being seen in-person .Sub-group analysis revealed that respondents with public insurance were more likely than those with private insurance to report that video care adoption during COVID-19 was related to insurance covering video visits for the first time , stress (44%), and money (29%) as compared to in-person care. When asked if they would choose to continue using video appointments for diabetes care in the future, 17% responded that they preferred to receive diabetes care by video, 17% responded that they preferred diabetes care to be in-person, and 65% responded that they would choose to use video care for some appointments or in some circumstances.p = 0.003 and 18% vs. 9%, p < 0.001, respectively) and that they preferred all their diabetes care to be in-person . In addition, respondents from non-college-educated households were more likely to report feeling that video care was less effective than in-person care . However, for each of these sub-groups, the majority of respondents still felt that video care was as effective as or more effective than in-person care, that video care had benefitted them in some way, and that they would prefer to use video care for some appointments in the future.Sub-group analysis demonstrated that respondents with hemoglobin A1c (HbA1c) levels ≥8% and those from non-college-educated households were each more likely than their counterparts to report that video care had not saved them time, money, or stress . The remaining 51% cited a variety of reasons, including preferring face-to-face care; feeling that video care would be of lower quality; or needing an HbA1c test, other laboratory tests, or a physical exam. Many respondents also reported that telemedicine felt unnecessary due to low perceived risk from COVID-19, already being in contact with their providers by phone or electronic messaging, or preferring to manage their T1D independently during this time. Sub-group analysis revealed that respondents with HbA1c ≥8% were more likely to report difficulty sharing glucose or pump data remotely  and concern about the quality of care by video . However, these reasons were rarely cited by that sub-population in comparison to the reason that their providers had not offered video care (50%).Among the 777 respondents who had not yet completed a video appointment for T1D, 49% reported that the primary reason for this was that their providers had not offered video appointments, and respondents with public insurance were more likely than those with private insurance to report this limitation  who have utilized telemedicine during this time. Our study suggests that this shift in care was driven primarily by health insurance and medical providers changing the availability of telemedicine versus in-person appointments and secondarily by individual and community concerns about the health risks posed by in-person visits. Importantly, over a quarter of publicly insured respondents felt that changes in insurance coverage for telemedicine had been a key factor in their adoption of video care for T1D management. However, respondents with public insurance who had not utilized video care were more likely than their privately insured counterparts to cite providers not offering video care as the primary barrier. This confirms that access—or perception of access—to telemedicine has not been uniform during the pandemic, even among patients with similar insurance policies. It is also notable that over half of our respondents reported their providers were not offering any in-person T1D care at some point during the pandemic.Our study suggests that among PWD who have used video care, the majority feel that it is as effective or more effective compared to in-person care (62%), that it allows them to save time in comparison to in-person visits (85%), and that they would want to continue using video telemedicine for T1D care in the future (82%). However, our sub-analyses suggest specifically that PWD from households with lower educational attainment and those with higher HbA1c levels are less likely to experience video care as convenient, effective, and desirable. In addition, many other respondents expressed feeling that video care was unnecessary because they were in contact with their providers by phone or electronic messaging or did not need provider input about T1D management during this time. These findings lead us to conclude that video telemedicine may be a patient-centered care modality for some individuals but not for all.Two other published surveys about telemedicine use during the COVID-19 pandemic serve as interesting comparators for our results. In the spring of 2020, Horrell and colleagues surveyed over 2200 U.S. adults with a variety of non-diabetes chronic conditions who were engaged in online health communities, asking about their telemedicine use and satisfaction in the prior four months . They foTo examine this latter possibility, we can compare our survey results to a global survey of youth and adults with T1D during the COVID-19 pandemic. Scott and colleagues surveyed over 7400 individuals with T1D in 89 countries (33% U.S. respondents) about telemedicine use and satisfaction . Their sThe strengths of our survey include a large study population and detailed information from respondents about the factors driving or discouraging telehealth adoption for T1D care from a patient standpoint. It adds importantly to the growing body of knowledge about how telemedicine is being used for T1D management across the U.S. and offers important insights about how much and in what ways this care modality may be patient-centered for PWD. A key limitation of our study is the fact that our survey population was predominantly White, non-Hispanic, college-educated and privately-insured, with excellent glycemic control and high use of therapeutic technology. Our results therefore reflect the use and perception of video T1D care among a very specific sub-population of PWD, and this limits their generalizability to other demographic groups. Multiple publications since the onset of the COVID-19 pandemic have demonstrated lower telemedicine use by populations with public insurance, minority race or ethnicity, and non-English language preferences –26. Thes5.In conclusion, the majority of our 2235 survey respondents used video telemedicine for T1D care during the COVID-19 pandemic and want to continue video care in the future. These findings suggest that our healthcare system and diabetes community should work to maintain and improve access to telemedicine for all PWD after the pandemic. The differences in perceived access to and benefits from telemedicine among sub-populations of our survey respondents reaffirm the existence of disparities in telehealth use that have been noted by multiple other studies over the last year. In addition, the heterogeneity of opinions expressed by survey respondents about the utility of video care, and the concerns endorsed by many about the quality of care provided remotely, suggest that clinicians and researchers should focus on how to individualize not only the content but also the modality of T1D care so that it can be maximally effective for all PWD. Ongoing investigation to examine the experience of care is essential during rapid changes in healthcare delivery in order to ensure that patient-centered outcomes are considered alongside health outcomes and cost.


Background: Shutdowns are enacted when alternative public health measures are insufficient to control the epidemic and the population is largely susceptible. An age-stratified agent-based model was developed to explore the impact of shutdowns to control SARS-CoV-2 transmission in Canada under the assumption that current efforts to control the epidemic remains insufficient and in the absence of a vaccine. Methods: We estimated the current levels of interventions in Canada to generate a baseline scenario from 7 February to 7 September 2020. Four aspects of shutdowns were explored in scenarios that ran from 8 September 2020 to 7 January 2022, these included the impact of how quickly shutdowns are implemented, the duration of shutdowns, the minimum break (delays) between shutdowns and the types of sectors to shutdown. Comparisons among scenarios were made using cases, hospitalizations, deaths and shutdown days during the 700-day model runs. Results: We found a negative relationship between reducing SARS-CoV-2 transmission and the number of shutdown days. However, we also found that for shutdowns to be optimally effective, they need to be implemented fast with minimal delay, initiated when community transmission is low, sustained for an adequate period and be stringent and target multiple sectors, particularly those driving transmission. By applying shutdowns in this manner, the total number of shutdown days could be reduced compared to delaying the shutdowns until further into the epidemic when transmission is higher and/or implementing short insufficient shutdowns that would require frequent re-implementation. This paper contrasts a range of shutdown strategies and trade-offs between health outcomes and economic metrics that need to be considered within the local context. Interpretation: Given the immense socioeconomic impact of shutdowns, they should be avoided where possible and used only when other public health measures are insufficient to control the epidemic. If used, the time it buys to delay the epidemic should be used to enhance other equally effective, but less disruptive, public health measures. While sStudies have projected that when restrictive closures are lifted in Canada, if alternative public health measures such as detection and isolation of cases, and tracing and quarantining of close contacts of cases are insufficient, subsequent waves of infections will occur –7. TheseIn this study, we used an age-stratified agent-based model developed for the Canadian population to explore restrictive shutdowns to control the epidemic when alternative public health measures are insufficient. We focused on specific aspects of shutting down including the impact of speed, duration, delays and types of shutdowns on COVID-19 transmission.. 2The methods describing the agent-based model used in this study have been published . Briefly. 2.1Four interventions were applied in the baseline; these include case detection and isolation, contact tracing and quarantine, closures and personal physical distancing , representing the Canadian situation from 7 February to 7 September 2020 . During . 2.2Building on the baseline, the model explored four shutdown scenarios separately to explore the impact of further shutdowns on the resurgence of SARS-CoV-2 transmission in Canada. The scenarios explored shutdowns occurring from 8 September 2020 day 214) to the model end ; a period of 487 days . Shutdow4 to the Scenario 1 (S1) explored the speed of shutdowns when the following triggers were reached, reflecting some Canadian thresholds that have been set to trigger shutdowns –26: (A) Scenario 2 (S2) explored the duration of shutdowns by shutting down for (A) 28 days, (B) 42 days, (C) 56 days and (D) 70 days at a time with shutdowns triggered when active cases reached 100 per 100 000 with no minimum break between consecutive shutdowns. Shutdowns were released after the corresponding period of shutdown ended regardless of the number of active cases per 100 000 remaining and re-implemented when 100 active cases per 100 000 was reached again.Scenario 3 (S3) explored the delays between shutdowns by shutting down with a minimum break between consecutive shutdowns. Shutdowns were modelled with a minimum of (A) 28 days between shutdowns; (B) 56 days between shutdowns; (C) 84 days between shutdowns and (D) 112 days between shutdowns. Shutdowns were triggered when active cases reached 100 cases per 100 000 and the minimum time between shutdowns had lapsed regardless of the number of active cases per 100 000 remaining.Scenario 4 (S4) explored the extensiveness of shutdowns by shutting down different sectors individually and in combination with each other: (A) Canadian baseline, no further shutdown, (B) all shutdown , (C) 50% workplaces only (teleworkers), (D) 100% schools only, (E) 50% mixed-age venues only  and (F) 50% mixed-age venues and 50% workplaces together. Shutdowns were modelled on the decline in mobility observed during March to May . Shutdow. 2.3The model produced daily cumulative and incident counts for each age group for each health state. The stochastic outputs are presented as medians from 50 realizations (simulations) per scenario and values from the 2.5th and 97.5th percentiles are presented as the 95% credible interval (CI). The model was developed and simulated in AnyLogic. Statistical analyses and graphs were created using StataCorp 2019, Stata Statistical Software: Release 16, College Station, TX: StataCorp LLC.. 3Results on the total attack rate, clinical attack rate, asymptomatic attack rate, total hospitalizations (acute and intensive care unit (ICU)), acute hospital admissions, ICU admissions and mortality rate by age groups for each scenario and model 16 in total) are presented in the electronic supplementary material, table. Summary tables on key model outputs for scenarios are presented in tables  in total. 3.1a), the shutdown impact was not always immediate, resulting in a larger epidemic peak despite shutdown being implemented . This phenomenon was also observed in scenarios when shutting down at 100 active cases per 100 000 (not visible as the few extreme runs are not captured in the 95% CIs) and occasionally at 150 or 200 active cases per 100 000. This is due to shutdowns having a direct impact on inter-household transmission but not within-household transmission; the latter will continue when shutdowns are implemented because household members do not physically distance from each other. Therefore, at 50 active cases per 100 000, a larger proportion of household members remain susceptible to infection, whereas at 150 or 200 active cases per 100 000, many household members have succumbed to infection and there is a high level of immunity at the population level.When current public health measures are insufficient to control an epidemic, the faster to shutdown (50 active cases per 100 000), the lower the number of cases, hospitalizations and deaths, but the higher the number of shutdown days due to shutting down more often . Earlierfigure 2. 3.2When public health interventions are insufficient, shorter shutdowns are triggered more frequently: seven complete cycles of shutdowns were observed for the 28-day shutdown model; five cycles of shutdowns for the 42-day model; four cycles of shutdowns for the 56-day model and three to four cycles of shutdowns for the 70-day model when the trigger for shutting down was set to 100 active cases per 100 000 . These c. 3.3b). In comparison, in the 84-day and 112-day break models, a larger proportion of the population were infected during the winter 2021 wave, thus, the subsequent wave in summer 2021 was smaller despite the same shutdown conditions imposed . The magnitude of subsequent waves is determined by the proportion of the population that remains susceptible. Delaying a shutdown when a large proportion of the population remains naive can result in up to ten times the number of prevalent clinical cases at peak compared to a no-delay approach (approx. 800 per 100 000 with a 112-day break compared to 80 per 100 000 with a 28-day break), thus overwhelming the healthcare system  versus panel (b)). In other words, the additional closure of 100% schools to 50% workplaces and 50% mixed-age venues contributed to a further 7% reduction in clinical cases. The closure of sectors individually contributed to reducing transmission, but contributions were not equal and combining sectors to shut down together were the most effective. Individual closures reduced the proportion of transmission in their respective locations . In this model, shutdown reduced transmission compared to the baseline (c), but the epidemic curve is flattened compared to baseline (a). Other models where shutdowns did not control the epidemic  include the 84-day break, 112-day break and schools-only shutdown models .Some shutdown strategies failed to control the epidemic as demonstrated in the workplaces-only shutdown model c. In thibaseline , but a cbaseline c, but thbaseline a. Other a), these models suggest there may be a delay between shutting down and observing a decrease in cases.In a few model realizations , the impact of shutting down was not always immediate resulting in a higher peak than observed in March to May 2020 despite shutdown being implemented figures . While tfigure 1. 4This study used an age-stratified agent-based model to explore the impact of shutdowns to control SARS-CoV-2 transmission in Canada. Shutdowns were shown to be an effective tool for reducing and delaying community transmission of SARS-CoV-2 in a largely susceptible population where alternative measures were assumed to be insufficient, and in the absence of vaccines. Effectiveness varied depending on the speed, duration, delay and extensiveness of the shutdown, but in general, there were no models in which shutdowns did not produce a better outcome in terms of the reduced number of cases, hospitalizations and deaths. Globally, there have been many examples showing shutdowns are an effective means for controlling SARS-CoV-2 . NationaThe main study findings are that there are several shutdown characteristics, health outcomes and socioeconomic costs to balance when selecting a strategy. While some scenarios clearly perform better than others and all shutdowns had some impact on the epidemic, the trade-offs are important to consider based on the local context and situation. Shutdowns were shown to largely delay the epidemic with growing cases, hospitalizations and death rates when the response is slow (either due to a higher threshold for shutting down S1) or delaying a shutdown (S3)). Whereas the lowest cases, hospitalizations and deaths were seen in scenarios that had higher shutdown days , which have substantial socioeconomic impact on society and to individuals and families ,28. We s or delayThe final scenario indicated that the design of partial shutdowns are not equal. Shutdowns of certain sectors were more effective than others, and some combinations performed well when compared to a full shutdown (S4). The stringency, that is, the sector type and the proportion of those sectors in shutdown, determines the effectiveness of a shutdown. We found workplace-only shutdowns in our models did not contribute significantly to reducing community transmission. This is supported by the fact that the proportion of Canadians who have been teleworking since March 2020 has not changed drastically, suggesting that under the initial rates of teleworking, workplaces are not a main contributor to current transmission . The shuOur study demonstrates the most effective shutdowns were those that were implemented quickly, with minimal delay S1 and S3), initiated when community transmission is low (S1), sustained for an adequate period (S2) and had a high level of stringency targeting multiple sectors, particularly those driving transmission (S4). Countries that have successfully eliminated SARS-CoV-2 transmission for months at a time have implemented extremely stringent shutdowns during times when community transmission has been low , applied for months at a time even when only a handful of cases were reported and lifting only when no locally acquired cases had been reported for an extended period  and S3, ,30. ShutStudy limitations include uncertainty in some epidemiological characteristics of SARS-CoV-2, such as the role of children and asymptomatic infections in disease transmission or how new SARS-CoV-2 variants might evolve in Canada. We rely on estimates from Canadian data and the literature and assume that these do not change over time. The model does not consider transmission in healthcare and long-term care facility settings because transmissions in these settings vary widely across Canada and are subject to unique infection control and prevention strategies that are not implemented at the population level . While lOur study explores the impact of shutdowns on the resurgence of SARS-CoV-2 transmission in Canada under the assumption that current efforts to control the epidemic remain insufficient in the absence of a vaccine. We explored and identified shutdown factors that can minimize negative health outcomes, but also showed that there is a trade-off between reducing health outcomes and the number of shutdown days and some strategies may balance both better than others. Given the immense socioeconomic impact of shutdowns, they should be avoided where possible and used wisely as needed to bolster the capacity of other less disruptive public health measures for controlling the epidemic. Although this study is Canadian, our findings are consistent with those observed beyond Canada's border  and can be generalized to any country faced with controlling SARS-CoV-2 transmission in their population.Click here for additional data file.


It is a starch-based powder that forms a gel after irrigation with saline solution and thus separates surgical sites as physical barrier for adhesion prevention.Adhesion formation after endometriosis surgery is a severe problem affecting up to 90% of patients. Possible complications include chronic pain, ileus, and secondary infertility. Therefore, effective adhesion prophylaxis is desirable, for which the adhesion barrier 4DryField® PH and the other irrigation with saline solution for adhesion prevention. Adhesion formation was directly scored during second-look interventions considering incidence, extent, and severity. Adhesion prevention treatment in the second surgery was performed corresponding to the first intervention to evaluate the long-term outcome in the later course.Fifty patients with extensive and deep infiltrating endometriosis were included in this prospective, randomized, controlled clinical trial with two-staged laparoscopic approach. The patients were randomized into two groups, one receiving 4DryField® PH group compared to the control group . Incidence of adhesion formation based on the number of affected sites was significantly reduced by 53% in the intervention vs. control group . Follow-up of secondary endpoints is not yet completed; results will become available at a later stage.Both groups were comparable with respect to relevant patient parameters. Severity and extent of adhesions were significantly reduced by 85% in the 4DryField® PH.Adhesion formation could be reduced significantly by 85% by application of the adhesion barrier 4DryFieldTrial registration main ID: DRKS00014720, secondary ID: U1111-1213-4142; date of registration 09th May 2018. Endometriosis affects between 10% and 15% of women of reproductive age –4. The pAs no clear diagnostic serum markers have been identified to date, endometriosis can only be definitely diagnosed through a histopathological evaluation providing evidence of endometrial glands and stroma showing signs of inflammation and fibrosis .The medical management of endometriosis is based on nonsteroidal anti-inflammatory drugs or endocrine treatment .Despite the pharmaceutical options, treatment often requires surgery to excise or ablate the endometrial tissue , which cMinimally invasive laparoscopic approaches can also lead to adhesions in > 80% of patients with severe endometriosis and complete posterior cul-de-sac obliteration . In caseConsequently, effective adhesion prevention after minimally invasive endometriosis surgery is highly desirable and several attempts have been made to introduce specific barrier agents into clinical routine. Laparoscopy appears to reduce adhesiogenesis , but ref® PH, a novel adhesion barrier, was investigated for adhesion prevention after endometriosis resection in a second-look design. It is a powder based on purified potato starch that transforms into a gel with saline solution. The gel then acts as a temporary physical barrier between the surgically traumatized peritoneal surfaces until mesothelial healing is completed and it is subsequently resorbed. Observational and retrospective trials from visceral [In this study, 4DryFieldvisceral , 24 and visceral , 26 showThis RCT was approved by the Ethics Committee of the Medical Faculty at our institution (no. 217/2018BO1). It is registered in the German Clinical Trial Register (DRKS) and the International Clinical Trials Registry Platform of the World Health Organization . Informed consent was obtained from all patients included. Fifty women with laparoscopic resection of endometriosis in a two-step approach were randomized into two groups between July 2018 and November 2019. All surgeries and follow-up visits were conducted at the Department for Women’s Health at the University Hospital Tübingen. As there is no placebo for the tested medical device, only the patients were blinded.The relevant inclusion criteria were histological diagnosis of deep infiltrating endometriosis (DIE) or extensive peritoneal and/or ovarian endometriosis upon diagnostic first-look laparoscopy with the indication for a definite subsequent therapeutic procedure according to our center’s practice (second-look laparoscopy). Pregnant and/or breastfeeding patients, patients with known incompatibility of starch-containing substances, and patients without resection of endometrial tissue for histological confirmation during the first laparoscopy, and therefore not requiring any adhesion prevention treatment, were excluded.The patient collectives of the two study arms were statistically tested for comparability regarding the following parameters: age, BMI, duration of first surgery, frequency of outpatient treatment (1st surgery), previous endometriosis surgeries, metabolic disorders, severity of pre-operative pain , and rASRM and ENZIAN endometriosis scores. ENZIAN scores were compared based on arithmetic means calculated for the subscores A, B, and C as their severity is assessed with a numerical value, whereas frequencies were compared for the F-subscores.The flowchart in Fig. During the first intervention, we aimed to excise endometriosis both for histological confirmation and for symptom relief. Accordingly, in some cases, several sites (endometriotic lesions and/or adhesions) that were considered relevant were treated, even if the patient would not undergo the second operation for the complete excision of deeper infiltrating lesions. For moderate lesions with only peritoneal or superficial endometriosis, resection was performed exclusively during this intervention and the patient did not require a second intervention, resulting in exclusion from the study.In contrast, if additional DIE or extensive peritoneal or ovarian endometriosis  were present upon first-look laparoscopy, endometriosis was excised locally for histological confirmation and a second surgery for definite treatment was planned. The study nurse only pronounced group assignment afterwards and an anti-adhesive treatment at the excision sites followed according to randomization. This two-stage concept for advanced endometriosis represents the practical routine in our center and allows optimized interdisciplinary planning with respect to the extent of the condition, as well as to the patient’s leading symptoms .After 3–16 weeks, the second intervention with the definitive therapeutical resection of DIE, optionally with partial removal of involved organs such as ureter, bowel, or bladder, as well as the excision of remaining peritoneal or ovarian endometriosis, was carried out. The timing of the second intervention was based on the routine interval for this surgery in our hospital. It takes into account an adequate recovery time after the first intervention and allows for completion of possible adhesion reformation for lysis during the second operation. The time interval was also chosen for optimal conditions for the second surgery. This included the peritoneal healing of the defects, as well as optimized planning and consent in cases of higher risk resections of deep infiltrating endometriosis adjacent to the ureter/bowel or even bowel interventions . A few cases were delayed due to patients’ personal reasons. In the intervention group, the mean interval between both interventions was 8.1 weeks (range 5–16 weeks), in the control group 7.4 weeks (2.9–15.6 weeks). During the second intervention, the previously resected and treated locations (first laparoscopy) with potential subsequent adhesion formation were investigated. All 50 patients that were randomized also had their second intervention to complete endometriosis resection and were therefore included in the primary outcome evaluation.® PH was applied for adhesion prevention in both surgeries. It was applied at the end of each intervention as a powder until all surgically affected areas were completely covered and then transformed into a gel by irrigation with saline solution. The mean amounts used were 3.2 g powder (range: 1–5 g) and 10.5 ml saline solution (range: 2–20 ml). The powder was applied through the corresponding laparoscopic applicator 4DFLap™ .Adhesions were assessed during both interventions with a score modified from the American Fertility Society (AFS) score . In boththe extent of possible adhesion formation sites (predilection sites) resulting from the planned endometriosis resection and/or from intended adhesiolysis was rated on a scale from 0 to 4 , 2: moderate (between 1/4 and 2/4 of the area affected), 3: pronounced (between 2/4 and 3/4 of the area affected), 4: extensive (more than 3/4 of the area affected)).During the first surgery, the severity was scored as either 0, 1, or 4 , 4: severe ). Corresponding to the AFS score, severity and extent were then multiplied to yield a site score. The sum of all site scores added up to the total score:During the second surgery, the same sixteen regions were assessed for post-operative adhesions and their extent was scored in accordance with the first surgery. Additionally, The score used in the present study deviates from the AFS score in the evaluation of sixteen (instead of four) areas and a finer extent score .The incidence of adhesion formation upon second look is given as the number of sites that were affected after the first intervention.Secondary endpoints to evaluate during follow-up include post-interventional pain  and the number of complications , necessary re-operations for adhesiolysis and for other reasons, as well as pregnancies. Data for the secondary endpoints will be collected during the 12-month follow-up after the second intervention and will become available at a later stage. In the present paper, only complications that developed in the study interval between the first surgery and second look are included.Sample size determination was performed using G*Power 3.1 . ResultsThe statistical evaluation was performed using Prism 7 for Windows (GraphPad Software Inc.). Continuous variables were tested for normality of distribution with the D’Agostino-Pearson test. If normally distributed, unpaired t-tests and if not, Mann-Whitney tests were employed . Categorical variables were evaluated using Fisher’s exact test and time-to-event variables using the Mantel-Cox test. Level of significance was always 0.05.For calculation of the effect sizes, Glass’ ∆ was used when the variances were significantly different (determined by F-test) and Cohen’s d when they were not.All outcomes presented result from analyzing all the 25 patients of the respective groups, none of which were reassigned.The basic parameters are summarized in Table extent and severity of adhesions as well as the adhesion incidence were analyzed in this clinical study.The parameters Severity and extent of adhesions that could be detected upon second look are summarized in the total adhesion score according to the calculation described above. The total adhesion score for the control group is 14.2 (SD: 18.9). In the intervention group, the score is 2.2 (SD: 3.1). This represents a reduction of 85%. The difference is statistically significant (p = 0.004). The effect size (Glass’ ∆) is 0.64.In the control group, the mean incidence is 2.3 sites (SD: 1.7) and in the intervention group 1.1 (SD: 1.2), which is equivalent to a reduction of 53%. This difference is also statistically significant p = 0.004). The effect size (Cohen’s d) is 0.87. The results are summarized in Fig. . The effSo far, none of the 50 patients had infections or wound problems. No conclusive data for other secondary outcomes has been analyzed yet, but will become available at a later stage after the completion of follow-up.No harm or unintended effects resulting from study-specific treatment could be observed.Even though various anti-adhesion agents or barriers have been shown to be effective in experimental or even human trials, they are still not used regularly in clinical practice. Apart from economic issues where reimbursement is not clearly defined in some health systems, the most important scientific reason is the lack of clinical studies with a well-designed second-look setting that produce reliable and comparative data regarding efficacy and better outcomes of competitive agents. Clearly, such evidence-based results would encourage and legitimate the use of the most efficacious products in clinical routine. The ideal adhesion barrier is beneficial, degradable in the human organism, can be applied laparoscopically, and is cost-effective.® PH vs. a control group in a second-look approach.Because of the mentioned methodical problems, this human study was designed to prospectively evaluate the anti-adhesive qualities of 4DryFieldThe results show a distinct and statistically significant reduction of adhesion extent, severity, and incidence after the application of the tested agent in comparison to irrigation with saline solution (control) only. The calculated effect sizes show a medium to large effect for the reduction of the adhesion score and a large effect for the reduction of adhesion sites. The analyzed reduction of the adhesion score of 85% is in line with previously published results from experimental animal trials, where the product achieved reductions of the adhesion score ranging from 85 to 100% –31. Prev® PH application, therefore, is unlikely to have been caused by more extensive first excisions in the control group.Adhesion formation highly depends on the peritoneal trauma caused during an intervention. Therefore, extent and incidence of trauma sites (referred to as predilection sites in our study) created in the initial surgery (first intervention) during endometriosis resection or adhesiolysis were evaluated as well. Both were higher in the intervention group, with a mean total extent score for the predilection sites of 4.1 (SD: 3.9) vs. 2.4 (SD: 1.7) in the control groups and a mean number of predilection sites of 2.5 (SD: 1.4) vs. 1.4 (SD: 0.7). Both differences are significant . This must be taken into consideration, as the statistically significant reduction of adhesion severity, extent, and incidence after 4DryField®, an oxidized regenerated cellulose-based barrier from Johnson & Johnson Medical Inc., in 16 women after laparoscopic endometriosis surgery and compared them to an equally sized, untreated control group. They only evaluated the adhesion incidence, which could be reduced by 63%. More detailed results regarding adhesion extent and severity were not reported in this publication. Sekiba et al. [®, a gel based on polyethylene oxide and sodium carboxymethylcellulose from FzioMed Inc., in 20 patients after laparoscopic surgical treatment of endometriosis and compared them to an untreated control group of 17 patients. They used the adnexal adhesion scoring system according to the AFS, which delivered values of 14.0 for the controls and 6.2 for the intervention group, a reduction of 56%. However, the scores of both groups at first surgery differed by 1.6 to the disadvantage of the control group, meaning that control patients already had higher adhesion scores at first interventions. Brown et al. [®, an icodextrin solution from Baxter Healthcare, for adhesion prevention after laparoscopic gynecological surgery and compared it to Ringer’s lactate solution. The study included a subpopulation of endometriosis patients (122 in the intervention and 119 in the control group). They used the AFS score for the assessment of adhesion severity and extent but did not report the values; they only stated the percentage of patients with clinical success (which they defined as “the percentage of patients in whom the number of sites with adhesions decreased by at least 3 or 30% of the number of sites lyzed”). This success rate was 42% in the Adept® and 37% in the control groups. None of these studies included secondary outcomes like pain or fertility development. In a Cochrane database review comprising adhesion prevention studies in pelvic surgery in general, Ahmad et al. criticized that exactly these results are generally lacking and, therefore, there is no conclusive evidence that any adhesion prevention devices could lead to respective improvements albeit these would be important [Comparable studies for adhesion prevention after endometriosis resection are scarce; only five RCTs with second look have been published yet : Mais eta et al.  also usea et al. , who inca et al.  investign et al.  used Ade® PH is not only anti-adhesive but (when applied as a powder) is also marketed as a hemostat. This capability possibly plays a major role for its advantageous adhesion prevention as the basis for adhesion development is the formation of polyfibrin meshes between surgical trauma sites and adjacent tissue. As fibrin is a component of blood, minimizing blood secretion through rapid hemostasis is a cornerstone for adhesion prevention. If conventional agents without an additional hemostatic effect are used on sites with minor but diffuse bleeding, such as those occurring during endometriosis resection, it seems to be more difficult to achieve a peritoneal condition with less fibrin products. Only one of the aforementioned other adhesion prevention agents is a gel. This is noteworthy as according to the instructions for use, a mesh such as Interceed® can take up blood from remaining bleeding sites, which leads to fibrin deposits within the mesh. These fibrin deposits are prone to initiate and promote the formation of adhesions. A solution such as Adept® may dilute the fibrin containing exudates and have an effect by further distancing opposite wound areas. However, the possible distribution of fibrin components might also promote adhesion development in areas where originally no molecular formation trigger is present.Compared to the results of previous studies cited above, the present study provides data on adhesion prevention in endometriosis surgery and efficacy values that are higher than those of the aforementioned anti-adhesion agents. Notably, 4DryField® PH is resorbed within 7 days post-operatively. In contrast, Interceed® is absorbed within 4 weeks and Oxiplex/AP® takes even 6 weeks, increasing the potential risk of disadvantageous reactions. On the other hand, the liquid Adept® is already absorbed after 3 to 4 days, which is potentially prior to the complete mesothelial healing.Adhesion formation generally occurs within about 3 to 5 days post-operatively as this is the time until mesothelial healing is completed . An adhe® PH has been examined in an animal model [submesothelial fibrous tissue and mononuclear cells indicated an active healing process with a macroscopically smooth and shiny reconstitution of the visceral and parietal peritoneal surface. Additional histopathological analyses performed during an animal study on adhesion prevention [® PH apparently does not hinder this process and is likely to support mesothelial healing. Comparative examinations of mesothelial healing for the three other barriers are not available.The degradation and impact on wound healing of 4DryFieldal model . The autevention  showed cevention , an effe2O in the pneumoperitoneum [2 to the CO2 in the pneumoperitoneum  to correct the mesothelial hypoxia induced when pure CO2 is used [It has been stated that acute inflammation can enhance adhesion formation mediated through humoral factors in the peritoneal fluid . In animritoneum , coolingritoneum , 41, addritoneum , additio is used , desicca is used , and by  is used .2O (for which a drug-like effect is assumed but has not yet been found) and cooling (which makes the cells more resistant to trauma by decreasing the metabolism) [® PH is not available yet, thus it can be speculated how the characteristics interact with the peritoneal surface: supposedly, the gel formulation (intervention group) prevents desiccation and reduces the irritating effect and hypoxia by pure CO2; however, saline solution only (control) has also demonstrated a favorable impact on peritoneal conditioning [® PH application as it binds the saline in the gel formulation and holds it back from rapid resorption by the lymphatic system.Of these, the single most important factors are the addition of Nabolism) . In an aabolism) . Specifiabolism) . In thisitioning , 47 and itioning , 49. Thiitioning . Presuma® PH exists, the operating surgeon automatically knew the group assignment of each patient when carrying out the treatment, thus preventing double blinding. Additionally, the application of the analyzed agent (4DryField® PH vs. control) in the first surgery had to be repeated in the second intervention according to the study protocol to enable the evaluation of long-term outcomes after the second surgery, which are not a part of this paper. The rationale for this design is that possible adhesions formed after the second intervention would have interfered with the adhesion prevention effects after the first intervention and therefore mislead the interpretation of follow-up results. Despite the general advantages of double blinding, trials which are not double blinded should not automatically be deemed inferior, and proper reporting of the blinding efforts should be considered crucial [TM , an even distribution of the powder is not always possible and certain areas inevitably receive a thicker coverage than others, also leading to a certain degree of variation in the amount of powder applied. In a similar manner, the volume of saline solution used to transform the powder into a gel varies interindividually and between different operative sites. Due to the difficulty of fully standardizing the application, a certain variation in the effectiveness of the product between patients can be anticipated. Furthermore, it is not yet clear if there is an optimal dose and if a thicker layer of the barrier or transformed gel is more effective than a thinner layer. Ahmad and Crescenti  describe® PH can be premixed extracorporeally and subsequently be administered as gel. This application has been described in previous publications [® PH as a premixed gel versus the intraabdominal powder transformation as well as the comparison of both methods against a control group seems to be of practical interest in future RCTs.If no extensive hemostasis is required, 4DryFieldications , 29, 31 ® PH. The outcome is in accordance with experimental studies published previously and suggests a practical benefit for endometriosis surgery. The definition of an optimum dose in relation to the peritoneal defect, the preferred application mode , as well as the evaluation of secondary endpoints are parameters for subsequent investigations. In this regard, the agent’s specific molecular impact on the peritoneal conditions is of interest and warrants further experimental and clinical trials.In this randomized, controlled clinical second-look trial, adhesion formation could be reduced significantly by 85% with the adhesion barrier 4DryField


What is the optimal time between symptom onset and treatment after aneurysmal subarachnoid hemorrhage (SAH) to maximize patient outcomes?In this cohort study, more favorable patient outcomes  were observed when treatment occurred within 12.5 hours after aneurysmal SAH symptom onset. Treatment delay did not affect neurologic complications after aneurysmal SAH.The findings of this study provide more information regarding the optimal timelines of surgical treatment for people with aSAH. Rapid access to specialized care is recommended to improve outcomes after aneurysmal subarachnoid hemorrhage (SAH), but understanding of the optimal onset-to-treatment time for aneurysmal SAH is limited.To assess the optimal onset-to-treatment time for aneurysmal SAH that maximized patient outcomes after surgery.This cohort study assessed 575 retrospectively identified cases of first-ever aneurysmal SAH occurring within the referral networks of 2 major tertiary Australian hospitals from January 1, 2010, to December 31, 2016. Individual factors, prehospital factors, and hospital factors were extracted from the digital medical records of eligible cases. Data analysis was performed from March 1, 2020, to August 31, 2021.Main exposure was onset-to-treatment time  derived from medical records.Clinical characteristics, complications, and discharge destination were extracted from medical records and 12-month survival obtained from data linkage. The associations of onset-to-treatment time (in hours) with (1) discharge destination of survivors (home vs rehabilitation), (2) 12-month survival, and (3) neurologic complications  were investigated using natural cubic splines in multivariable Cox proportional hazards and logistic regression models.df = 3.83 in the generalized additive model, χ2 test P = .002 for the 4-df cubic spline), with a similar nonlinear association remaining significant after adjustment for sex, treatment modality, severity, Charlson Comorbidity Index, history of hypertension, and hospital transfer . Both unadjusted and adjusted cox regression models showed a nonlinear association between time to treatment and 12-month mortality with the lowest hazard of death with receipt of treatment at 12.5 hours after symptom onset, although the nonlinear term became nonsignificant upon adjustment. The odds of being discharged home were higher with treatment before 20 hours after onset, with the probability of being discharged home compared with rehabilitation or other hospital increased by approximately 10% when treatment was received within the first 12.5 hours after symptom onset and increased by an additional 5% from 12.5 to 20 hours. Time to treatment was not associated with any complications.Of the 575 patients with aneurysmal SAH, 482 patients  who received endovascular coiling or neurosurgical clipping were studied. A nonlinear association of treatment delay was found with the odds of being discharged home vs rehabilitation  were achieved when surgical treatment occurred at approximately 12.5 hours. These findings provide more clarity around optimal timelines of treatment with people with aneurysmal SAH; however, additional studies are needed to confirm the findings. This cohort study of patients with aneurysmal subarachnoid hemorrhage assesses the associations between onset-to-treatment time and postsurgical outcomes. In previous studies,9 the role of important factors, such as patient age, disease severity, and complications, on outcomes and the full range of aneurysmal SAH outcomes, such as survival, discharge destination, and complications, were not always considered. Robust evidence on the optimal timing of surgery is therefore still lacking. A better understanding of the optimal onset-to-treatment time after aneurysmal SAH will facilitate improved outcomes. This study examines the time delays in treatment of aneurysmal SAH and assesses the optimal treatment window to achieve the best outcomes after aneurysmal SAH treatment, including more frequent discharges home, increased 1-year survival after surgery, and fewer complications.Neurosurgical or endovascular treatment within 24, 48, or 72 hours of onset has been associated with improved clinical outcomes.STROBE) reporting guideline.The Reducing Delays in Aneurysmal Subarachnoid Hemorrhage (REDDISH) study is a retrospective, multicenter cohort study of all cases (N = 575) of aneurysmal SAH in patients admitted to 2 comprehensive cerebrovascular centers in Australia from January 1, 2010, to December 31, 2016. Data analysis was performed from March 1, 2020, to August 31, 2021. The study was approved by the Health and Medical Human Research Ethics Committees in Victoria and Tasmania with a waiver of informed consent for patients who died. All data were deidentified. Multiple overlapping data sources were used to identify potential cases of aneurysmal SAH . Where 24-hour time estimates for onset of symptoms were missing, the first ambulance call or 24-hour time at first hospital arrival was used as a proxy (n = 30)  and (2) complications of aneurysmal SAH using National Institute of Neurological Disorders and Stroke definitions .The primary outcome was discharge destination from the cerebrovascular centers  , which is used as a proxy of functional recovery and independence in survivors.11 within a subset of these cases for the state of Tasmania suggested that the prehospital time for most people with aneurysmal SAH is very short. To ensure potentially inaccurate patient-reported date and time of aneurysmal SAH symptom onset did not bias our results, we repeated all analyses excluding the prehospital time from onset-to-treatment time  date and time at onset of aneurysmal SAH symptoms (captured by triage records and ambulance notes) and the date and time at which neurosurgical or endovascular treatment was initiated (determined from procedure notes). A previous analysis12 were selected from the literature and clinical experience. Two indexes of severity based on first in-hospital assessments conducted before any procedures were performed included (1) the World Federation of Neurosurgical Societies (WFNS) score13 and the modified Fisher scale14  was assessed with multivariable logistic regression with a random effect to account for potential dependence arising in data collected from the same centers. We used log odds coefficients from adjusted models to derive partial predicted probability plots to show the chance of developing each outcome according to onset-to-treatment time. The association of onset-to-treatment time on survival at 12 months after aneurysmal SAH was investigated using multivariable Cox proportional hazards regression with a robust sandwich estimate of SEs to account for dependence within each of the 2 clinical centers.P < .05 was considered statistically significant.In both the logistic and Cox proportional hazards regression models, we used natural cubic splines to explore the potential nonlinear, continuous association between onset to treatment and outcomes. Full details of the modeling approach, including model adjustments and interaction analyses with severity indexes and hospital transfer modality, are provided in eAppendix 3 in the Of the 575 patients with aneurysmal SAH, 482 patients  who were treated with neurosurgical or endovascular treatment were included in the study . Clinicadf = 3.83 in the generalized additive model, χ2 test P = .002 for the 4-df cubic spline), with a similar nonlinear association remaining significant after adjustment for sex, treatment modality, severity, Charlson Comorbidity Index, history of hypertension, and hospital transfer . The odds of being discharged home were higher with treatment before 20 hours after onset, with the probability of being discharged home compared with rehabilitation or other hospital increased by approximately 10% when treatment was received within the first 12.5 hours after symptom onset and increased by an additional 5% from 12.5 to 20 hours. Beyond 20 hours, it decreased until approximately 60 hours after onset  died in hospital, 203 (42.8%) were discharged home, and 199 (41.3%) were discharged to rehabilitation services or other hospitals or nursing homes . In the logistic regression model, there was a very strong nonlinear association of treatment delay with the odds of being discharged home vs rehabilitation . The lowest hazard was estimated when receiving treatment at 12.25 hours after symptom onset. Using 12.25 hours as a reference , we transformed the log HR curves to show the change in the relative risk of death at 12 months. There was evidence of decreasing hazard of death when treatment was received between 5 and 12.25 hours after onset, reaching its lowest point at 12.25 hours (risk = 1). The hazard of death then increased with treatment from 12.25 to 24 hours but still remained beneficial to survival, before plateauing at 4 times the risk, when treatment was received after 24 hours, compared with a reference time of 12.25 hours  were alive at 12 months. Among those who died, 67 deaths (81.7%) occurred with 30 days of symptom onset. Unadjusted survival models found a nonlinear association between the 12-month all-cause mortality hazard ratio (HR) on the delay in receiving aneurysmal SAH treatment  or treatment type , the nonlinear association of onset-to-treatment time was attenuated. However, the shape of the association of treatment delay with the 12-month hazard of death from the adjusted model was similar to the shape of the unadjusted model with decreasing hazard of death with treatment from 0 to 12.5 hours, which was the treatment timing associated with the lowest hazard of death at 12 months . The hazMore than half of the treated patients experienced at least 1 of the 7 predefined complications after aneurysmal SAH . TreatmeThis cohort study is the first, to our knowledge, to characterize the nonlinear association between onset-to-treatment time for aneurysmal SAH against 12-month survival, complications, and discharge destination. Our analyses suggest that the optimal time window for receiving aneurysmal SAH treatment is up to approximately 12 hours postsymptom onset with decreasing evidence of benefit with treatment from 12 to 24 hours. Only 30% of the study participants with aneurysmal SAH received treatment within this time frame, highlighting the potential need to improve timely access to care for patients presenting to the hospital with aneurysmal SAH symptoms. Acknowledging the potential limitations of our study design, our findings provide guidance to improve clinical guidelines that currently recommend early treatment without a clear time target for clinicians.8 that used arbitrary categorical definitions of early treatment as opposed to our consideration of its continuous nature. These definitions range from ultra-early  to 96 hours from onset. There is a tendency for shorter definitions of early in more recent publications,19 but these articles mostly focused on endovascular interventions only, excluding a large proportion of people with aneurysmal SAH treated neurosurgically. The analyses in our study are the first to consider the dynamic nature of onset-to-treatment time after aneurysmal SAH and a range of outcomes in a large, multicenter study.The hazard of death at 12 months was lowest when treatment occurred up to 12.25 hours after aneurysmal SAH symptom onset but then increased from 12.25 hours onward before reaching a plateau from 24 hours onward. The association of onset-to-treatment time on 12-month survival was attenuated when adjusting for covariates but maintained the same shape as in the unadjusted data. The exception was the initial increase in hazard of death in the approximately 5 hours immediately after symptom onset that was not present in adjusted models or when people who died early (<48 hours after onset) were excluded. This finding reinforces that survival after aneurysmal SAH was associated with initial aneurysmal SAH severity. In support of the importance of onset-to-treatment time on outcome after aneurysmal SAH, the probability of being discharged home compared with a rehabilitation center or another hospital, as a proxy for functional outcomes, also increased significantly when treatment was received within the first 12.5 hours after symptom onset. Of interest was that the risk of developing common secondary injuries was not associated with onset-to-treatment time, with complications largely driven by the severity of the aneurysmal SAH. Our findings are supported by previous studiesThe reasons for maximal survival benefit from treatment at approximately 12.5 hours after onset being beneficial for outcomes are unclear. In addition to the clear benefit of treatment in reducing rebleeding of the aneurysm, treatment time may be a surrogate for onset of intensive management to reduce intracranial pressure and improve cerebral perfusion, which may result in better neurologic recovery. Future research, ideally on prospective data, should be undertaken to better understand the components and mechanisms of how earlier treatment may aid recovery in aneurysmal SAH. Conducting randomized clinical trials of life-threatening conditions such as aneurysmal SAH is challenging. As an initial step, replication of our analyses in other studies with comparable measures of time to treatment, confounders, and outcomes would be warranted to confirm our findings. Advanced modeling techniques, such as inverse probability of treatment weighting to approximate randomization, could then be used in other studies if the time window identified in our study is confirmed in other cohorts.This study suggests that medical treatment for aneurysmal SAH should ideally be provided within 12.5 hours after onset but not beyond 24 hours because these results were associated with improved 12-month survival and a greater likelihood of discharge home, independent of severity of the aneurysmal SAH and other confounders. Too few people with aneurysmal SAH are treated within the 12.5- or 24-hour window associated with the best outcomes. Interventions to reduce time to treatment may be warranted after confirmation of our findings in other cohorts.The association between aneurysm severity, onset-to treatment time, and survival at 12 months is complex. Although the nonlinear effect of time-to-treatment on survival was the same among those with poor and good grade aneurysmal SAH, severity is associated with onset-to-treatment time and outcomes. We adjusted for a wide range of potentially important confounding factors associated with time to treatment and outcomes to increase the robustness of our findings. Nevertheless, it is difficult to tease apart the true association between time to treatment and survival at 12 months without introducing potential confounding by indication.20 The timing of intervention is controversial for patients with poor-grade aneurysmal SAH who are unconscious at hospital admission and potentially more prone to rebleeding because of unstable clot surrounding a ruptured aneurysm.7 Because of the high mortality and disability for poor-grade aneurysmal SAH, such patients are often treated conservatively. Our data suggest that early intervention  to secure the aneurysm together with medical treatment has the potential to increase discharge to home and survival, irrespective of severity and other patient characteristics.The debate on the timing of aneurysm treatment after aneurysmal SAH pivots on the balance of the temporal risk for fatal rebleeding vs the risk of intervention-related morbidity when intervening early on an acutely injured brain.7 This finding is supported by a previous study7 in which only half of people with aneurysmal SAH were treated within 24 hours after onset and 15% to 60% patients were treated at 48 hours or later after onset of symptoms. Advocating for intervention within 12 hours potentially requires increased use of medical imaging facilities, rapid access to neurosurgical and neurointerventional expertise, potential out-of-hours treatment that necessitates increased staffing and on-call demands, and more robust and efficient patient workflow practices from initial paramedic contact to hospital treatment. Changes in practice related to timing of treatment have previously been reported in aneurysmal SAH. For example, recent evidence that it was unnecessary to delay angiography to avoid complications from advances in technique mean that, anecdotally, few neurosurgeons now delay angiography.21 Further research to establish factors associated with receiving treatment for aneurysmal SAH earlier and whether it is cost-effective are warranted to assist with implementation of time-to-treatment targets.Only 29% of people in this study received treatment with 12.5 hours, and only 60% received treatment within 24 hours, the latter being the currently accepted target for onset-to-treatment time.3 we had consecutive cases across 2 centers, including transferred cases, and all grades of aneurysmal SAH and treatment types, thereby facilitating a more complete picture of time to treatment and outcome. Nonetheless, future prospective studies to account for selection and measurement bias incorporating patient-reported outcome measures are warranted.This study has several strengths. Missing data were minimal . In contrast to previous studies,3 that used linked administrative data, but these studies do not have the necessary time-related variables for the type of analysis undertaken here. Routinely collected clinical records lack patient-reported outcome measures. Discharge destination was used as a surrogate marker of functional outcomes. This marker assumes those discharged home are more likely to be functionally independent, which is subject to some degree of error, depending on individual patients’ housing and caregiving support situation that could not be measured in the current study. To facilitate future research and evaluation, clinical services for people with aneurysmal SAH should consider embedding patient-reported outcome measures as routine. Because our aim was to identify the treatment window that maximized patients’ prognosis after surgery, excluding the 93 participants who were not treated will not result in survivor bias for this group. However, we cannot discount that given that 16% of the starting cohort was not treated (86% of whom subsequently died), there are likely to be approximately 20% of patients with SAH who die before they reach the hospital.12 Because the group of treated participants included in our analysis have a lower risk of death compared with the total group of people with aneurysmal SAH, a survivor bias may have resulted if we tried to generalize our findings to all those patients with aneurysmal SAH admitted to cerebrovascular centers.The current study also had several limitations. Its retrospective nature may result in bias in data capture and interpretation. However, we used rigorous case finding procedures and had minimal missing data, suggesting these factors are not significant sources of bias. The sample size may appear modest compared with some other aneurysmal SAH studiesThis cohort study suggests that treatment for aneurysmal SAH should ideally be provided within 12.5 hours after onset but not beyond 24 hours because this results in improved 12-month survival and a greater likelihood of discharge home, independent of severity of the aneurysmal SAH and other confounders. Too few people with aneurysmal SAH are treated within the 12.5- or 24-hour window associated with the best outcomes. Interventions to reduce time to treatment may be warranted if these findings are confirmed in other cohorts.