Background: Birth-related post-traumatic stress disorder occurs in 4.7% of mothers. No previous study focusing precisely on the stress factors related to the COVID-19 pandemic regarding this important public mental health issue has been conducted. However, the stress load brought about by the COVID-19 pandemic could have influenced this risk. Methods: We aimed to estimate the prevalence of traumatic childbirth and birth-related PTSD and to analyze the risk and protective factors involved, including the risk factors related to the COVID-19 pandemic. We conducted a prospective cohort study of women who delivered at the University Hospitals of Geneva between 25 January 2021 and 10 March 2022 with an assessment within 3 days of delivery and a clinical interview at one month post-partum. Results: Among the 254 participants included, 35  experienced a traumatic childbirth and 15  developed a birth-related PTSD at one month post-partum according to DSM-5. Known risk factors of birth-related PTSD such as antenatal depression, previous traumatic events, neonatal complications, peritraumatic distress and peritraumatic dissociation were confirmed. Among the factors related to COVID-19, only limited access to prenatal care increased the risk of birth-related PTSD. Conclusions: This study highlights the challenges of early mental health screening during the maternity stay when seeking to provide an early intervention and reduce the risk of developing birth-related PTSD. We found a modest influence of stress factors directly related to the COVID-19 pandemic on this risk.  The coronavirus disease 2019 (COVID-19), which spread all around the world after the first case in Wuhan in November 2019, induced isolation, stressful conditions related to the fear of dying and the many bereavements and socio-economic consequences. Since the beginning of the COVID-19 pandemic, many research studies have highlighted its great impact on mental health in the general population, with increased rates of depression, anxiety and PTSD in comparison with the prevalence of these psychiatric disorders before the COVID-19 pandemic  or due tWhile between 20% and 48% of women report a traumatic experience associated with the delivery ,6, the tBirth-related PTSD and birth-related PTSS are associated with deleterious effects on breastfeeding, which is more prematurely stopped , as wellA traumatic childbirth must validate the definition of a traumatic event according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) to diagnose birth-related PTSD . AlthougIndeed, some significant conceptual changes concerning traumatic events and PTSD need to be mentioned. With DSM-5, some important differences concerning PTSD diagnoses in comparison with the last version, DSM-IV, have been highlighted . AccordiAccording to the DSM-5 criteria, a birth-related PTSD diagnosis needs to validate the definition of a traumatic event (criterion A1) and the individual needs to re-experience the traumatic event related to childbirth (criterion B1), present avoidance symptoms (criterion C1), develop alterations in cognition and mood (criterion D1), experience alterations in arousal and hyperactivity (criterion E1) and experience these symptoms for more than one month (criterion F1). The symptoms must also create distress or a functional impairment (criterion G1) and must validate an exclusion criterion regarding medication, substance use or other illnesses that could explain the symptoms (criterion H1) . Although the prevalence of birth-related PTSD and its predictors have been studied in many Western countries before COVID-19 pandemic, there are limited data reported in Switzerland  so far tWe wanted to assess whether the COVID-19 pandemic (1) increases the risks of traumatic childbirth, childbirth-related PTSD and post-partum depression; and (2) alters the influence of known factors of childbirth-related PTSD. We hypothesized that stress factors related to the COVID-19 pandemic increase the prevalence rates of traumatic childbirth-related PTSD and post-partum depression and that the influence of known factors involved in these clinical context have been modified during the COVID-19 pandemic. The study’s main objective was to assess the prevalence rates of traumatic childbirth and birth-related PTSD in women who delivered during the COVID-19 pandemic. The main secondary objective was first to analyze the already known factors related to COVID-19 associated with traumatic childbirth and birth-related PTSD, while the final secondary objectives were to evaluate whether the presence of birth-related PTSD may be associated with a greater risk of developing comorbid post-partum depression at one month post-partum and to assess the association of breastfeeding practices with birth-related PTSD.This was a prospective cohort study of all women who delivered at the University Hospitals of Geneva between 25 January 2021 and 10 March 2022 with two follow-up time-points: an early assessment within 3 days of delivery and a visit at one month post-partum. This hospital manages pregnancies and deliveries at high risk of complications and complex psychosocial situations. The eligibility criteria were any woman older than 18 years who delivered at the Geneva University Hospitals’ maternity wards after 29 weeks of amenorrhea (w.a.) and who consented to participate. We conducted a physical interview in their room during maternity to inform them of and to check the inclusion criteria. Women who did not read or speak fluent French were excluded. The recruitment started after childbirth and within 3 days of the maternity stay. Once eligible, the participating mothers received an e-mail on their smartphone and completed an online self-report questionnaire within 3 days of their maternity stay and at one month post-partum. During the first assessment, they completed self-report questionnaires for the following variables: (1) age, nationality and current profession; (2) data about delivery routes, whereby maternal or neonatal complications were collected on medical files, support and information provided by healthcare workers during delivery; (3) antenatal depression; (4) peritraumatic reactions around childbirth; (5) psychiatric history and previous psychiatric treatments; (6) questions related to COVID-19 regarding pregnancy and the maternity stay. During the second assessment, at one month post-partum, the mothers completed self-report questionnaires for the following variables: (1) birth-related PTSD; (2) previous traumatic events according to the DSM-5 criteria; (3) questions related to COVID-19 during the post-partum period; (4) breastfeeding; (5) perceived support by the patient’s entourage. They also received a teleconsultation to look for diagnoses of birth-related PTSD and post-partum depression according to DSM-5 criteria. In case of no answer, three automatic reminders were provided by e-mail. Depending on the results of the assessment of birth-related PTSD or post-partum depression, a referral to a mental health specialist was proposed, independently of the study.We describe our outcomes in detail and the tools we used above for each step of the study.At one month post-partum, the participating women were invited to a clinical interview through a teleconsultation conducted by an experimented psychologist or psychiatrist of research team that had each more than 5 years of clinical experience. To validate the criteria for the presence of traumatic childbirth (primary outcome), the clinician checked if criterion A according to DSM-5 for traumatic events corresponded to the last childbirth; then, the other diagnostic criteria for birth-related PTSD according to the DSM-5 criteria were searched (secondary outcome) . The cliWe searched known risk factors of birth-related PTSD during maternity stays, such as antenatal depression ,14 usingWe tested potential risk factors of birth-related PTSD that are related to the COVID-19 pandemic and that are not known. We provided questions using the 5-point Likert scale concerning access to care for their pregnancy and the newborn after delivery and access to care for physical or mental health, during pregnancy and the post-partum period, concerning the effects of isolation from their relatives, the economic consequences, the use of teleworking, the fear of being infected by SARS-CoV-2, the perception of the restrictions of visits during maternity stay, the presence of infected persons in close contact with delivering women during COVID-19, the impact of the COVID-19 context on the experience of pregnancy and delivery and the received social support. We also assessed for contamination by SARS-CoV-2 during pregnancy. All medical and socio-demographic data were recorded using the REDCap electronic data capture tools hosted at the University Hospitals of Geneva, Switzerland . If the We anticipated that 200 participants would be needed to be able to estimate the prevalence of birth-related PTSD at 4% with a precision of ±2.7% using a 95% confidence interval (95% CI).p < 0.25 in the univariate analyses, then we kept in the final multivariable models all variables that were significantly associated with the outcome (parsimonious) and also variables that showed a confounding effect by changing the coefficient of regression by more than 25% after being stepped out of the model. We verified the adequacy of each model using the Hosmer–Lemeshow test. We provided the pseudo-R2 value to assess the predictive value of the model. We reported the associations between the factors and outcomes using their odds ratios (ORs) and 95% confidence intervals (95% CI). All p-values below 0.05 were considered statistically significant. The continuous variables were described using the mean ± standard deviation (SD), median and interquartile range; the categorical variables by frequencies and relative proportions. We reported the prevalence of PTSD due to traumatic childbirth or breastfeeding at one month with the 95% CI using the exact binomial method. We assessed the associations between different factors  with the four outcomes  separately by applying four different logistic regression models. For each outcome, we provided univariate analyses then we constructed multivariable models if we had a minimal number of events per variable. We used a stepwise approach by choosing all variables associated with the outcome at We included 265 women between 25 January 2021 and 10 March 2022. A total of 254 (95.8%) women completed the self-report questionnaire within 3 days of their maternal stay and 225 (88.6%) at one month post-partum; 183 (81.3%) women benefited from a clinical interview with a psychologist or a psychiatrist during the second assessment . n = 196, 85.2%), and 124 (48.8%) were not Swiss. Most of the participating women were married or in a stable relationship   .Among the participating women, 138 (75.8%) had delivered by vaginal route, 40 (22.1%) received assisted delivery, 21 (11.5%) had an elective cesarean and 23 (12.6%) had an emergency cesarean . Only 6 Immediately after delivery, 252 (99.2%) women were satisfied  with the quality of support provided by the healthcare workers during their delivery and 254 (100%) were satisfied  with the quality of information provided by the healthcare workers during their delivery . n = 55, 21.7%). The mean PDI score was 18.8 ± 7.6, and more than half of the participating women  obtained a score suggestive of peritraumatic distress predicting the development of birth-related PTSD. The mean PDEQ score was 14.8 ± 6.1, and less than one-third  obtained a score suggestive of peritraumatic dissociation predicting the development of birth-related PTSD. During the clinical interview, less than one-quarter of participating women  lived their childbirth as traumatic.The results for the different tools assessing the mental health state during pregnancy and peripartum are presented in We have summarized the results of the questions focusing on potential stress factors related to the COVID-19 pandemic in The clinical interview at one month post-partum concluded that 35 women (21.1% 95% CI: 15.1–28.1%) experienced a traumatic event according to DSM-5 after checking that the traumatic event was the last childbirth (primary outcome) .p = 0.001), emergency caesarians (p = 0.042), maternal complications (p = 0.037), antenatal depression (p < 0.001), the PDI score (p = 0.001) and the PDEQ score (p < 0.001)  . We foun< 0.001) .p < 0.001), peritraumatic dissociation during and after childbirth assessed via the PDEQ score (p < 0.001) and also maternal complications (p = 0.013), after adjustment for the confounder neonatal complications  presented a diagnosis of birth-related PTSD after checking that the traumatic event was the last childbirth (primary outcome) . The meap = 0.001), neonatal complications (p = 0.004), antenatal depression as assessed via the EPDS score obtained during the first three days following childbirth (p < 0.001) and clinical reactions to traumatic childbirth assessed via the PDI score (p = 0.003) and PDEQ score (p = 0.001) (A diagnosis of birth-related PTSD showed a significant association with exposure to a traumatic event of any type once or more (= 0.001) . p = 0.004), but we found no significant associations between birth-related PTSD and the other answers related to the COVID-19 context, such as the fear of being infected by SARS-CoV-2 (p = 0.639) and isolation due to the COVID-19 context during pregnancy (p = 0.723)  . We did = 0.723) .ijerph-The assessment at one month after delivery showed that only 7  of the women suffered from a PPD according to DSM-5 . We found that most of women  declared that they were still breastfeeding their child at one month post-partum .p = 0.038) and negative experiences with restrictions of visits during the maternity stay   . To the best of our knowledge, this prospective study was the first one to explore the prevalence of birth-related PTSD and traumatic childbirth according to DSM-5 within the context of the COVID-19 pandemic. The strength of our study was to provide a mixed assessment including self-report questionnaires and clinical interviews with the application of the DSM-5 criteria for PTSD. Our results were, thus, comparable with most of the studies that focused on traumatic childbirth and birth-related PTSD using self-report questionnaires; however, they were based on the DSM-IV criteria ,13,14,16The prevalence of traumatic birth 21.1%) in our study appears to be not so high in comparison with previous studies ,16. Ayer.1% in ouWe found that 15  women presented a diagnosis of birth-related PTSD according to the DSM-5 criteria after checking that the traumatic event was the last childbirth. The birth-related PTSD rate at one month appeared to be not so high in comparison with the estimated rates of between 4% for women in the community  and 18.5% for women ‘at risk’  in Ayers’ study . HoweverA Swiss prospective study in Lausanne concluded that 20.7% of mothers had probable PTSD, regardless of the delivery mode at one month post-partum . NeverthThe other explanation for this relatively low rate of birth-related PTSD in comparison with the previous studies could be selection bias in the participant recruitment. First, bias may have occurred due to the recruitment process, involving a physical interview conducted in the maternity ward to inform the participants and to collect their consent to participate instead of only involving the completion of self-report questionnaires, as was the case in most of the previous studies ,13,14,16We confirmed some of the results related to known risk factors of birth-related PTSD, such as antenatal depression, a previous traumatic event of any type, neonatal complications, peritraumatic distress and peritraumatic dissociation ,13,14,16The early mental health assessment during the maternity stay highlighted the frequent rates of peritraumatic distress (56.9%) and peritraumatic dissociation (31.9%) related to childbirth, with the latter appearing less easy to identify because it needs to be actively researched. Peritraumatic dissociation and peritraumatic distress were both significantly associated with a traumatic childbirth experience and were predictive of birth-related PTSD. The first important lesson from these results concerning birth-related PTSD is the need to raise the awareness of medical staff and midwives involved in the delivery regarding birth-related PTSD, which is less taught in comparison with PPD, and more especially about peripartum factors of birth-related PTSD and the need for prevention strategies. Attention should be paid to the impact of early psychiatric reactions around childbirth more than the objective medical context of the women; these medical complications were not associated with birth-related PTSD in our study. More especially, attention should be paid to peritraumatic dissociation around childbirth, which is more difficult to identify without specific training. However, this clinical reaction is too often ignored and insufficiently taught during higher education. These results remind us that medical staff and midwives would need to know how to identify these symptoms clinically, their psychopathological significance and their management strategies in the context of childbirth. Peritraumatic dissociation around childbirth makes women disconnect from the present moment; for example, they can experience derealization with a very disturbing perception of the environment than can appear as disformed depersonalization, with the impression that they were not themselves and that they were acting during the childbirth and lost control, or they can present with partial or total amnesia around their childbirth. The results concerning the predictive value of the PDEQ score, EPDS score and PDI score for birth-related PTSD encourage the systematic screening of women at risk of developing birth-related PTSD during their maternity stay with the PDEQ score, which is strongly correlated both with traumatic childbirth and birth-related PTSD. The authors of previous studies focusing on peritraumatic dissociation during childbirth recommended also suggested the screening of peritraumatic dissociation to prevent birth-related PTSD . The goaOur study showed that peritraumatic dissociation around childbirth, as assessed by PDEQ score, presented good correlation with traumatic childbirth assessed by clinical interview. To the best of our knowledge, there are few previous studies focusing on birth-related PTSD ,34 that Isolation during post-partum was not associated with birth-related PTSD in our study. We also could not confirm that social support was a protective factor for birth experience . HoweverOur study specifically assessed the influence of the COVID-19 pandemic using self-report questionnaires on the main potential consequences on mental health in the context of perinatality. The COVID-19 context was expected to increase the stress load of pregnant women given the public communication concerning the growing evidence for increased risks of major physical health issues and death for women infected by SARS-CoV-2 during pregnancy. Several studies supported pregnancy as a risk factor for severe disease associated with COVID-19. COVID-19 increases the risk for pregnant women to be admitted to an intensive care unit (ICU), the risk of death and the risk of adverse pregnancy outcomes such as preeclampsia, pre-term birth and stillbirth , and preVery few of the participants considered there to be an impact of the COVID-19 pandemic context on their pregnancy or their delivery experience. The answers related to the access to prenatal and post-natal care did not show limitations for the great majority of the participants, suggesting the efficient management of care access for perinatality in Geneva, which is not representative of other countries.Surprisingly, although we could expect that COVID-19 pandemic context would increase the risk of birth-related PTSD due to the potential risk of death in cases of contamination, we did not confirm results found by others who concluded that women giving birth during the pandemic had an increased rate of traumatic childbirth and birth-related PTSD compared with women giving birth before the pandemic . Our stup = 0.6, OR = 1.5(0.32–6.29)). Finally, knowing that the PPD had been assessed in according with DSM-5 criteria, it could look low in comparison with usual PPD rates assessed by EPDS. We confirmed the probable protective factor of the COVID-19 pandemic on PPD that was also found in a previous study in comparison with women assessed before the COVID-19 pandemic , but we We found that the large majority of the participants  maintained breastfeeding at one month post-partum. This result was close to those of a previous survey focusing on breastfeeding. We can explain the high levels of breastfeeding before and during COVID-19 by the promotion of breastfeeding in the maternity wards of the Geneva University Hospitals and by the midwife visits at home until the 56th day post-partum .Breastfeeding was not associated with birth-related PTSD, although previous data showed that most women who suffered from birth-related PTSD did not initiate breastfeeding and stopped before 12 months . AvoidanWe did not find an association between breastfeeding at one month post-partum and other risk factors such as perceived social support, characteristics of delivery, peritraumatic dissociation and peritraumatic distress related to childbirth, neither did we find associations with post-partum depression. The answers related to COVID-19 did not reveal either an influence of the COVID-19 pandemic on breastfeeding. The main hypothesis is a methodological bias due to the fact that we did not collect data regarding mixed breastfeeding. In our study, all women declaring that they maintained breastfeeding were considered as actually maintaining breastfeeding, even if the breastfeeding was mixed and completed with artificial milk. Another explanation is that we assessed breastfeeding at one month given that the previous study highlighted associations between breastfeeding at 12 months and birth-related PTSD . FinallyOur study had several limitations. The main one was the lack of a control group of women screened before COVID-19. We were not able to calculate the prevalence of birth-related PTSD without the COVID-19 pandemic context, so we could not rigorously assess the impact of the COVID-19 context. However, the use of questionnaires related to the perceived impact of COVID-19 gave us the possibility to analyze factors directly related to the COVID-19 context. The other limitation of our study was the lack of an assessment of known risk factors of post-natal PTSD such as pain and previous deliveries or miscarriages, as such data would have been useful. The authors of a recent meta-analysis concluded that pain was associated with traumatic childbirth and birth-related PTSD . We asseTo the best of our knowledge, this is the first study to have explored traumatic childbirth and birth-related PTSD according to DSM-5 in Switzerland during the COVID-19 pandemic and the related risk and protective factors. The prevalence rates of traumatic childbirth and birth-related PTSD were not as high as expected. The results regarding known risk factors such as antenatal depression, a previous traumatic event of any type, neonatal complications, peritraumatic distress and peritraumatic dissociation were consistent with the literature for birth-related PTSD, but we found no influence of a psychiatric history or of the delivery route. Women who suffered from limited access to pre-natal care due to the COVID-19 pandemic during their pregnancy were more at risk of developing a birth-related PTSD, but we were not able to draw a conclusion regarding the influence of the other factors related to the COVID-19 pandemic, such as fear of contamination, isolation or socio-economic change due to COVID-19, on birth-related PTSD or traumatic childbirth. During the maternity stay, the approach for the prevention of birth-related PTSD should focus on antenatal depression screening, which appears as the main antenatal risk factor, and on peritraumatic dissociation, which appears as the main peripartum factor, so as to detect women at risk of being exposed to traumatic childbirth and to developing birth-related PTSD. Attention should be placed on the education of the medical staff and midwives regarding the post-natal PTSD risks so as to better clinically identify and manage peritraumatic dissociation around childbirth.


Severe burn injuries cause significant hypermetabolic alterations that are highly dynamic, hard to predict, and require acute and critical care. The clinical assessments of the severity of burn injuries are highly subjective and have consistently been reported to be inaccurate. Therefore, the utilization of other imaging modalities is crucial to reaching an objective and accurate burn assessment modality.We describe a non-invasive technique using terahertz time-domain spectroscopy (THz-TDS) and the wavelet packet Shannon entropy to automatically estimate the burn depth and predict the wound healing outcome of thermal burn injuries.in vivo THz-TDS images. We used the energy to Shannon entropy ratio of the wavelet packet coefficients of the THz-TDS waveforms on day 0 to create supervised support vector machine (SVM) classification models. Histological assessments of the burn biopsies serve as the ground truth.We created 40 burn injuries of different severity grades in two porcine models using scald and contact methods of infliction. We used our THz portable handheld spectral reflection (PHASR) scanner to obtain the We achieved an accuracy rate of 94.7% in predicting the wound healing outcome, as determined by histological measurement of the re-epithelialization rate on day 28 post-burn induction, using the THz-TDS measurements obtained on day 0. Furthermore, we report the accuracy rates of 89%, 87.1%, and 87.6% in automatic diagnosis of the superficial partial-thickness, deep partial-thickness, and full-thickness burns, respectively, using a multiclass SVM model.The THz PHASR scanner promises a robust, high-speed, and accurate diagnostic modality to improve the clinical triage of burns and their management. We showed that hyperspectral parameters obtained using the PHASR scanner can be utilized to longitudinally monitor the burn inflammatory process over a four-day post burn period.Over the past two decades, terahertz time-domain spectroscopy (THz-TDS) has emerged as a promising technique for the non-invasive sensing of various biological tissues.in vivo burn injuries using the PHASR scanner. This technique utilizes the maximal overlap discrete wavelet packet transform (MODWPT) to obtain a multi-scale spectral decomposition of the THz-TDS waveforms measured in vivo.In this work, we present a novel feature extraction approach to enhance the accuracy rate of diagnosis of 22.1in vivo experiments are conducted on two Landrace pigs because the porcine skin is physiologically and anatomically similar to the human skin.,,The protocol of our animal study is reviewed and approved by the Institutional Animal Care and Use Committee at Stony Brook University. The 2.2in vivo THz-TDS measurements within 1 h after the induction of the burn injuries.We use the PHASR scanner to obtain the 2.3–The data set comprises measurements from forty burns and eight healthy-skin (H) sites. At each location, a field-of-view of 2.42.4.1,There are no characteristic absorption lines in the THz spectra of biological tissues. Therefore, utilizing numerical feature extraction techniques is critical to achieving an automatic differentiation between the THz spectra of various pathologies. Wavelet transform has been used extensively for feature extraction in signal and image processing applications.2.4.2The space of the MODWPT coefficients of the THz pulses over all measurements forms a high-dimensional data set. In particular, for a THz signal of length We calculate the Shannon entropy of MODWPT coefficients following the approach described in Refs. Furthermore, we find the proportion of the energy of each sub-band with respect to the energy of its original signal Finally, the ESER is calculated as Importantly, we normalize the ESER coefficients of the tissue measurements with those of the reference air measurements to deconvolve the system response. We use the deconvolved ESER coefficients as the predictors of the wound healing outcome or the burn severity group in the machine learning algorithms.2.5,,34It has been reported that the blood perfusion unit measured using the LDI technique is the same between the burned and normal skin until 5in vivo burn assessment. We investigated the utility of the THz measurements obtained on day 0 to predict the wound healing outcome on day 28 for the first time. We achieved an average accuracy rate of 94.7% in predicting the wound healing outcome over the test set. We also reported specificity and sensitivity rates of 96.5% and 91.8% for this task. Additionally, the accuracy rates obtained using a multiclass SVM model to diagnose SPT, DPT, and FT burns were 89%, 87.1%, and 87.6%, respectively.We described a non-invasive technique utilizing the PHASR scanner and supervised machine learning to automatically estimate the severity of a burn injury and predict its wound healing outcome. Burn injuries of different severity grades, representing SPT, DPT, and FT wounds, were created by standardized scald and contact etiologies in two porcine models. We used the ESER of MODWPT coefficients of THz-TDS waveforms for Similar to other automatic medical diagnosis applications, including more observations helps to validate and improve the reported accuracy, sensitivity, and specificity rates. Therefore, expanding the available experimental data set is warranted for future studies. Moreover, investigating the longitudinal variations in the ESER coefficients on a day-to-day basis and their correlation with the histology measurements can provide further insight into the utility of the PHASR scanner for monitoring the inflammatory cascades in burn injuries. Overall, the reported experimental results promise a robust, high-speed, and affordable diagnostic modality to improve the accuracy rate of non-invasive burn assessment in clinical settings. In addition, the demonstrated techniques can be utilized for studying other forms of lesions, ranging from various forms of cancerous tissues to skin burns caused by different sources. However, different imaging applications might require certain considerations to deal with artifacts caused by sources such as skin surface variations or lack of a contact between the imager and the tissue. Finally, incorporating time-resolved, polarimetric measurements


Early intervention in kidney cancer helps to improve survival rates. Abdominal computed tomography (CT) is often used to diagnose renal masses. In clinical practice, the manual segmentation and quantification of organs and tumors are expensive and time-consuming. Artificial intelligence (AI) has shown a significant advantage in assisting cancer diagnosis. To reduce the workload of manual segmentation and avoid unnecessary biopsies or surgeries, in this paper, we propose a novel end-to-end AI-driven automatic kidney and renal mass diagnosis framework to identify the abnormal areas of the kidney and diagnose the histological subtypes of renal cell carcinoma (RCC). The proposed framework first segments the kidney and renal mass regions by a 3D deep learning architecture (Res-UNet), followed by a dual-path classification network utilizing local and global features for the subtype prediction of the most common RCCs: clear cell, chromophobe, oncocytoma, papillary, and other RCC subtypes. To improve the robustness of the proposed framework on the dataset collected from various institutions, a weakly supervised learning schema is proposed to leverage the domain gap between various vendors via very few CT slice annotations. Our proposed diagnosis system can accurately segment the kidney and renal mass regions and predict tumor subtypes, outperforming existing methods on the KiTs19 dataset. Furthermore, cross-dataset validation results demonstrate the robustness of datasets collected from different institutions trained via the weakly supervised learning schema. Kidney cancer is among the ten most common cancers. Early detection often leads to successful treatment and improves survival rates. Medical imaging, such as computer tomography (CT), can effectively reveal the internal structure of the abdomen and is commonly applied for physical examination to detect and diagnose early signs and symptoms of cancer. Finding anatomical information such as the contours, locations, and volumes of kidney tumors plays an essential role in clinical diagnosis. Among kidney masses, renal cell carcinoma (RCC) is the most common renal malignancy, causing many morbidities and mortalities ,2,3. TheArtificial intelligence has shown the potential to assist clinical care to detect and diagnose abnormal regions in an efficient way ,5. StateWe propose a novel kidney and renal mass diagnosis framework integrating 3D segmentation and renal mass subtype classification. It provides an easy-to-analyze 3D morphologic representation of the kidney and renal mass with the subtypes. The segmentation method adopts the basic 3D U-Net structure with residual blocks included for gaining the cross-layer connections. The postprocessing steps further improved the accuracy and reduced false positives by small region detection. The classification network applies the dual-path schema to combine the different fields of view for the prediction of subtypes.We propose a weakly supervised method to improve the robustness of the trained model on the datasets collected by various vendors with only a few slice-level annotations.The experimental results on the KiTs19 dataset demonstrate the state-of-the-art performance on kidney and renal mass segmentation and classification. Additionally, the results on three NIH datasets  to automatically segment kidney and renal mass regions and a subtype classification network to accurately identify the subtypes of renal masses using a dual-path approach. In addition, we introduce a simple yet effective weakly supervised training schema to improve the robustness of the proposed framework on cases from different institutions. The main contributions of this paper are summarized as follows:The remainder of this manuscript is organized as follows. 3D semantic segmentation in medical imaging refers to the voxel-wise segmentation of abnormalities in 3D imaging (such as CT or MRI). Various applications of semantic segmentation have been proposed, including targeted radiotherapy  and patiHowever, with a standard network architecture, nnU-Net (no new U-Net)  is propoSemantic segmentation tasks require precise per-pixel annotation, which is very expensive and time-consuming. Recently, weakly supervised methods have been proven efficient for training with low annotation cost and have been shown to improve training efficiency . UsuallyDeep learning-based algorithms have been applied to renal mass segmentation and classification ,39,40,41Recently, Xia et al.  proposedDespite the various studies on the effect of the above methods on the segmentation of renal tumors, few efforts have been made to propose a kidney and renal mass diagnosis framework to accurately quantify the volume of kidney and renal mass as well as predict the subtype of renal masses. Recently, Uhm et al.  proposedWe propose a novel kidney and renal mass diagnosis framework, including kidney and renal mass segmentation and subtype of kidney mass prediction. First, the proposed framework extracts the pixel-level kidney and renal mass regions from an entire CT volume via a three-dimensional (3D) segmentation network trained in a fully supervised manner. Then, a dual-path CNN-based classification model predicts subtypes of renal masses. Pathological labels of renal subtypes are used to train the classification model. Further, a weakly supervised method is applied to use annotations of only a few CT slices to improve the robustness of the diagnosis framework on datasets captured from different institutions.We employed 3D U-Net, an encoder-decoder network commonly utilized in image segmentation. Similar to the U-Net  frameworTo enrich the spatial feature representation, we employed 3D Res-UNet to directly predict the 3D volume of the kidney and renal mass from a whole 3D CT volume. The model was trained from scratch and evaluated using 5-fold cross-validation on the training set. We applied a leaked rectified linear unit (ReLU) and instance normalization to optimize the model. The losses were combined with dice loss and cross-entropy loss for a total of 300 training epochs. The network structure is shown in Unlike previous work, we designed and evaluated a deep learning framework that classifies renal masses into the most common RCCs subtypes: clear cell, chromophobe, oncocytoma, papillary, and other RCC subtypes, using abdominal CT scans as input data. The proposed framework segments kidney and renal masses, detects renal mass categories in a unified framework and diagnoses only through CT data without manual intervention, which can effectively assist clinical medical detection.We first automatically segmented the regions of kidney and renal masses at the pixel level via the 3D segmentation network. Once the kidney and renal mass regions were detected, both the regions of the renal mass with the kidney and only the renal mass were cropped from the CT images. The cropped region helped focus on only the relevant information for subtype classification. The cropped kidney and renal mass CT images were further employed as the input to the renal mass subtype classification network.A dual-path learning schema was applied to enrich feature learning, which can help the network simultaneously learn the correlation between the local and global feature representations. It is essential to preserve the global structures around the renal mass region and texture details in the renal mass region. The global path took the input of the region with both kidney and renal mass, and the local path took the input of only the renal mass region. We applied ResNet-50  as the bTo improve the robustness of the segmentation network, we applied a weakly supervised method that only requires a small number of pixel-level annotated CT slices based on a trained network. Annotations of only three slices from each volume were needed. The three slices were chosen based on empirical experiments. For qualitative assessment, we trained the network on three annotation samples: (1) the first slice, (2) the slice with the largest diameter of the renal mass, and (3) the last slice of the renal mass. The network can predict the complete 3D segmentation from only a few labeled slices, saving the cost of full annotation.To assess quantitative performance in semi-automated settings, we cross-validated all annotation slices in all different samples from the training data with five-fold cross-validation with and without batch normalization. The intersection of IoU is used as a precision measure to compare the predicted 3D volumes.The public dataset KiTs19  was applCGA-KICH  (15 caseCGA-KICH  datasetsCT images were converted from the Neuroimaging Information Technology Program (Nifti) format to DICOM. Following nnU-Net, CT scans were resampled by the standard spacing of Training. The patch size was set to Post-processing. Connected component-based post-processing has effectively eliminated falsely detected regions on medical image segmentation [entation ,51. The entation . For infWe first cropped kidney and renal mass regions from the detected CT slices. The cropped images were resized to Segmentation. The kidney and renal mass were evaluated by the following metrics. The Dice similarity coefficient was applied as an evaluation metric to calculate the spatial overlap index between the predicted 3D volume heatmap and the radiologist’s estimation. It estimates the accuracy of the structure’s volume and is sensitive to heatmaps with different shapes but similar volumes. The Dice value ranges from zero for no spatial overlap to 1 for complete overlap. In addition, we applied pixel accuracy, sensitivity, and specificity to evaluate the model performance. Pixel accuracy was calculated via the ratio of correctly classified pixels to the total number of pixels. The specificity refers to the ratios of pixels that were correctly classified to the number of pixels to all masks. The sensitivity represents the ratios of negative pixels correctly classified as negative to all negative ones.Classification. The area under the curve (AUC) was applied to evaluate the classification performance.The AUC is calculated by multiclass classification via the one-vs.-rest scheme with 95 confidence intervals. For each step, a class is considered a positive class, and others are negative classes to calculate the ROC to obtain the AUC scores. A permutation test compared the model’s performance (sensitivity and specificity). Five-fold cross-validation was conducted for the results of each dataset.Our model predicts remarkably accurate kidney segmentation on the KiTs19 testing set, with an average Dice metric of ing work ,44,45,46Additionally, we conducted experiments to assess the robustness of the proposed method on the TCGA-KICH, TCGA-KIRP, and TCGA-KIRC datasets. These three testing datasets have various tumor shapes and different tumor sizes (on average TCGA-KICH (cases with chromophobe subtypes). With the weakly supervised method, the Dice accuracy of the kidney region is 91.2%, and the Dice accuracy renal mass region is 83.4%, which represents improvements of 5.3% and 4.2% compared to without the weakly supervised method. The subtype prediction is 84.5%, representing a 2% improvement with the weakly supervised method.TCGA-KIRP (cases with papillary subtypes). With the weakly supervised method, the Dice accuracy of the kidney region is 92.8%, and the Dice accuracy of the renal mass region is 81.8%, which represents improvements of 3.3% and 5.4% compared to without the weakly supervised method. The subtype prediction is 79.5%, representing a 2% improvement with the weakly supervised method.TCGA-KIRC (cases with clear cell subtypes). With the weakly supervised method, the Dice accuracy of the kidney region is 93.2%, and the Dice accuracy of the renal mass region is 80.1%, which represents improvements of 2.5% and 1.8% compared to without the weakly supervised method. The subtype prediction is 86.1%, representing a 2.5% improvement with the weakly supervised method.The visualization of the kidney region (red) and renal mass region (blue) overlaps with the original CT images shown in We investigated the effectiveness of the proposed semantic segmentation framework with an ablation study, in which 3D U-Net was applied as a baseline model. Here, 3D Res-UNet uses the 3D U-Net network structure and involves residual connections to all convolutional blocks. 3D Res-UNet with preprocessing and post-processing are implemented individually, as shown in This paper has proposed an end-to-end kidney and renal mass diagnosis framework that can quantify renal mass morphology details to monitor disease progression. The proposed weakly supervised method improves the generalization ability of the network. The strategy of dual-path training of subtype classification not only improves the prediction accuracy but also prevents the false-positive prediction of renal masses. The experimental results demonstrate the effectiveness of the diagnosis framework and its potential to be a clinical tool.


In theoretical models of health behavior, knowledge about disease transmission and self-protective behaviors are conceptualized as important drivers of behavior change. Several studies conducted in Brazil point to an unfortunate convergence of sexual and gender minority (SGM) populations with low levels of HIV knowledge and younger age, lower education, engagement in higher-risk sexual behavior, and never having tested for HIV. Measures to assess level of HIV knowledge have been previously published, including the 12-item HIV/AIDS Knowledge Assessment (HIV-KA) tool. However, measure length can be a barrier to assessment.We started from the 12-item HIV-KA tool and developed candidate short forms using statistical procedures, evaluated their psychometric properties, and tested the equivalency of their associations with other measures of HIV knowledge compared to the 12-item version.A convenience sample of SGM was recruited during September 2020 to complete an online survey through advertisements on two social networking apps (Grindr and Hornet). The survey instrument included items on sociodemographic information, prior HIV testing and HIV test results, preexposure prophylaxis (PrEP) and antiretroviral treatment use, sexual behavior, and 3 HIV knowledge measures: the HIV-KA, World Health Organization Knowledge About HIV Transmission Prevention Indicator, and the Brief HIV Knowledge Questionnaire. We used exploratory factor analysis and confirmatory factor analysis (CFA) to assess the factor structure of the of the HIV-KA. We used optimal test assembly (OTA) methods to develop candidate short forms of the HIV-KA and evaluated them based on prespecified reliability, concurrent validity, and statistically equivalent convergent validity criteria.Among 2552 SGM individuals from Brazil, mean age was 35.1 years, 98.2% (2507/2552) cisgender men and 1.8% (45/2552) transgender/nonbinary, 56.5% (1441/2552) White, and 31.0% (792/2552) self-reported HIV positive. CFA indicated a 1-factor structure for the 12-item HIV-KA. Concurrent validity correlations were high for all short forms with 6 items, but only versions with 9 items were as reliable as the full-length form and demonstrated equivalency for convergent validity correlations. Suggesting post hoc convergent validity, HIV knowledge scores using the 9- and 10-item short forms were higher for participants who perceived the Undetectable Equals Untransmittable (U=U) slogan as completely accurate versus not accurate. Suggesting post hoc concurrent validity, participants of younger age, of Black, Pardo or indigenous race, and reporting lower education and lower income scored lower on HIV knowledge. Participants who never tested for HIV scored lower than those who tested negative or positive, while those currently using PrEP scored higher than those reporting past or never use.OTA methods were used to shorten the 12-item HIV-KA to 9-item and 10-item versions while maintaining comparable reliability and validity among a large sample of Brazilian SGM. However, these short forms did not shorten sufficiently to justify deviation from the full measure. Mirroring the dynamics of the HIV epidemic in Latin America, North America, and Western Europe, the Brazilian HIV epidemic is concentrated in key populations, such as gay, bisexual, and other men who have sex with men (MSM) ,2 and trAlthough mixed results exist on the direct link between knowledge and engagement in risky sexual behavior, a study conducted among men in Cape Town, South Africa, where HIV knowledge was low, showed that HIV testing combined with greater HIV knowledge led to reduced engagement in risky sexual behaviors . SeveralSeveral measures to assess level of HIV knowledge have been published. A widely used measure is the World Health Organization Knowledge about HIV Transmission Prevention Indicator (WHO-KI), a 5-item measure proposed in a United Nations General Assembly Special Session that assesses knowledge of essential facts about transmission including correctly identifying ways of preventing sexual transmission of HIV and rejection of major misconceptions about HIV transmission . AnotherThe study of an individual’s sexual practices and its possible determinants, including HIV transmission knowledge, requires the concomitant measurement of multiple behaviors  and knowledge-based and psychological constructs  which yield long study instruments. Importantly, we have observed that young, less-educated SGM who are most vulnerable to HIV acquisition are less likely to complete surveys . Hence, This is a cross-sectional study of users of social networking apps for gay, bisexual, and other cisgender MSM and transgender and nonbinary or gender nonconforming individuals in Brazil. Our objective was to assess the psychometric properties of the HIV-KA among SGM and develop short forms of the tool using statistical procedures. To reach these objectives, we started with the 12-item HIV-KA from Guimarães et al  and deveA convenience sample of SGM was recruited during September 2020 to complete an online survey through advertisements on two social networking apps (Grindr and Hornet). Grindr is a location-based social networking and online dating app launched in 2009 that has since become the largest and most popular gay mobile app in the world. Hornet, another location-based social networking and online dating platform, was launched in 2011 and is available as an app and on the web. For Grindr, advertisement banners were randomly displayed to users for 2 weeks. Hornet users received 1 inbox message with a link to the survey. Participants needed to provide electronic informed consent before initiating the survey. No compensation was provided, and no personally identifiable information was collected except for IP address. Participant eligibility included age 18 years and older and residency in Brazil. Exclusion criteria were self-identifying as a cisgender woman and an incorrect response to any of 3 attention questions that were included throughout the survey instrument at approximately every 15 items . A full This study was approved by the National Institute of Infectious Diseases Programa Inova at the Oswaldo Cruz Foundation (FIOCRUZ) institutional review board (#CAAE 01777918.0.0000.5262) in accordance with all applicable regulations.The survey was programmed on Alchemer survey software. The survey was in Portuguese and contained 55 questions, with certain questions conditionally presented using branching logic. Survey links remained active for 1 month. Respondents were able to change and review answers. Four authors systematically checked the usability and technical functionality of the electronic questionnaire on different platforms and operating systems before starting the survey.The survey instrument was divided into 3 sections. Section 1 included items on sociodemographic information . Section 2 included items referring to prior HIV testing and HIV test results. HIV-negative and unknown-status participants were questioned about preexposure prophylaxis (PrEP) use , and those who were not currently using PrEP responded to 2 questions about sexual behavior during the previous 6 months . HIV-positive participants were questioned about use of antiretroviral treatment (ART), and if in use, adherence prior 7 days) was measured using the 3-item WebAd-Q instrument . Section days wasHIV-KA  is a 12-HIV-KQ  is an 18WHO-KI  is a 5-iWe assessed whether respondents correctly perceived the accuracy of the prevention benefits of U=U through the question “With regard to HIV-positive individuals transmitting HIV through sexual contact, how accurate do you believe the slogan Undetectable=Untransmissible is?” as used in previous studies -29. RespDescriptive statistics of the study population are provided. We randomly split the study population in half and assessed the factor structure of all items of the HIV-KA together as a single measure with exploratory factor analysis (EFA) in the first half followed by confirmatory factor analysis (CFA) in the second half. EFA was used to identify the number of factors and assess item factor loadings. EFA was performed using robust weighted least squares estimator given the categorical nature of the survey items, chi-square test statistic, and geomin oblique rotation . A CatteThen, with the whole sample, a generalized partial credit item response theory model (GPCM)  was fit We used methods described by Harel et al . BrieflyEach of the candidate short forms and the full-length form were scored using two procedures to obtain estimates of each participant’s level of HIV knowledge. First, the summed scores across all items included in the form were calculated by adding item scores for each item included in the form. Second, factor scores, which estimate a level of a latent construct, were estimated from the GPCM for each participant for each form through an application of Bayes theorem. Both summed scores and factor scores were used due to the reliance on the former in research and the improved measurement properties of the latter ,43.Resulting from the OTA procedure are candidate shortened forms, each with the applicable optimal items. Removal of items implies a reduced amount of test information as compared to the full-length form. The selection of the final form was based on 5 criteria: reliability, concurrent validity based on summed scores, concurrent validity based on factor scores, convergent validity based on summed scores, and convergent validity based on factor scores. Applying these 5 criteria concurrently ensured that the final selected shortened version maintained desirable measurement properties across these categories.Accordingly, we first generated the candidate shortened forms and assessed each form’s reliability against the full-length form using a Cronbach alpha coefficient . The shoNext, for convergent validity, we used two different criteria based on 2 HIV knowledge measures . Additionally, we calculated mean scores with 95% confidence intervals of the candidate shortened forms according to select variables. As observed in a prior study , we hypoAll analyses were conducted in R software  . The GPCOf 3368 participants who initiated the survey, 2552 answered all items of the 3 HIV knowledge measures of interest and were included in analyses .266=1352.1, P<.001; CFI=0.94; TLI=0.93; RMSEA=0.03; SRMR=0.11. The item loadings ranged from 0.18 (item 8) to 0.75 (item 5).The EFA of the 12-item HIV-KA  yielded 1 eigenvalue of factor greater than 1 . Based on examination of the scree plot, we judged that a 1-factor solution provided the most interpretable model. Results from the CFA  indicated that a 1-factor structure showed reasonably good fit: χThe GPCM was fit on the 12 items of the HIV-KA. Item content with the discrimination parameters estimated from the GPCM are provided in Table S2 of Short forms with at least 8 items had Cronbach α=.59 or higher, suggesting a moderate level of reliability compared with full-length , treatment as prevention (item 2: “An HIV-infected person who is taking HIV/AIDS medications has a lower risk of transmitting the virus to another person”), and postexposure prophylaxis  to justify recommendation as these would not be directly comparable to existing studies that have used the full-length version.The OTA method is a replicable method that maintains performance standards based on objective criteria and, as such, selected short forms can be said to fulfill prespecified reliability and concurrent and convergent validity. The reliability of the shortened forms was of the same magnitude as the full-length form while showing high concurrent validity with the full-length form. Statistically equivalent convergent validity correlations using 2 HIV knowledge measures (HIV-KQ and WHO-KI) were also shown for both summed and factor scores.The selected short forms included the items addressing recent paradigms of HIV prevention and treatment, such as preexposure prophylaxis, treatment as prevention, and postexposure prophylaxis. The 3 items removed from the short forms showed the lowest discriminative ability, indicating that they were less useful in the construction of the HIV knowledge score. Notwithstanding, semantic aspects of the items may have impacted the results. Particularly, for item 8, the item with the lowest discriminative ability, the wording may have caused confusion. Item 8 states that the risk of infection is lower when it would have been more appropriate to say that the risk is null . Moreover, the use of the word lower suggests that it is lower than some other situation that the item does not specify. For example, compared to complete sexual abstinence, the risk may be higher, although it is lower compared to other sexual behaviors.Our results also indicate post hoc convergent validity for the shortened forms using the 1-item measure on the perceived accuracy of U=U, a slogan launched in 2016 by the Prevention Access Campaign to translate scientific evidence into a community message that highlights how people living with HIV on antiretroviral treatment with suppressed viral load cannot transmit HIV to their sexual partners . The sciAlthough only slightly shorter than the original 12-item HIV-KA measure, the 9-item or 10-item shortened forms may be preferred as they reduce participant burden, which is particularly important for participants who may have difficulty completing self-reported questionnaires. As observed in this study (Ad hoc construct validity of the HIV-KA shortened forms showed that those of younger age, non-White race, reporting lower education and lower income scored lower on HIV knowledge. A study from Brazil on 4129 MSM recruited by respondent-driven sampling in 12 Brazilian cities in 2016 observed that not only was the prevalence of unprotected receptive anal intercourse higher among younger participants, they scored lower on HIV knowledge and were less likely to have been tested for HIV in the past, despite having more years of schooling . This loThere are several study limitations that must be considered. This study used cross-sectional data, and therefore the sensitivity to change and test-retest reliability of the HIV-KA short forms could not be assessed. All collected data were self-reported by participants and may be subject to measurement errors that can arise in the collection, recall, or recording of information. Participants were recruited from a convenience online sample and may not reflect other SGM populations in Brazil. As for any study design, online samples have strengths that should be acknowledged which include the reaching geographically diverse populations as well as individuals from remote regions and those completely disconnected from HIV prevention services . The chaIn conclusion, this study showed how OTA methods might be used to shorten the 12-item HIV-KA to 9-item and 10-item versions while maintaining comparable reliability and validity among a large sample of Brazilian SGM. While OTA was primarily used for the development of high-stakes educational testing, it has now been used, as well, to successfully shorten patient-reported outcome measures in several patient populations. This study is the first, to our knowledge, to use OTA to shorten a knowledge assessment tool. Although the shortened forms in this study did not represent substantial reductions in items, OTA represents an important methodology as we attempt to maximize the information we collect in the least burdensome way possible, which can be supported by reducing the number of items in surveys.


Does randomization protect randomized clinical trials (RCTs) comparing transcatheter aortic valve implantation (TAVI) and surgical aortic valve replacement (SAVR) from biases other than nonrandom allocation?This systematic review and meta-analysis of 8 RCTs including 8849 participants and comparing TAVI vs SAVR found substantial overall proportions of deviation from assigned treatment, loss to follow-up, additional procedures, and additional myocardial revascularization together with a systematic selective imbalance in the same direction characterized by significantly lower proportions among participants undergoing TAVI.This study suggests that RCTs comparing TAVI and SAVR show serious methodological imbalances with a common selective pattern, and should be considered at high risk of performance and attrition bias that may affect internal validity. Recent European Society of Cardiology/European Association for Cardio-Thoracic Surgery (ESC/EACTS) guidelines highlighted some concerns about the randomized clinical trials (RCTs) comparing transcatheter aortic valve implantation (TAVI) and surgical aortic valve replacement (SAVR) for aortic stenosis. Quantification of these biases has not been previously performed.To assess whether randomization protects RCTs comparing TAVI and SAVR from biases other than nonrandom allocation.A systematic review of the literature between January 1, 2007, and June 6, 2022, on MEDLINE, Embase, and Cochrane Central Register of Controlled Trials was performed. Specialist websites were also checked for unpublished data.The study included RCTs with random allocation to TAVI or SAVR with a maximum 5-year follow-up.Data extraction was performed by 2 independent investigators following the PRISMA guidelines. A random-effects meta-analysis was used for quantifying pooled rates and differential rates between treatments of deviation from random assigned treatment (DAT), loss to follow-up, and receipt of additional treatments.The primary outcomes were the proportion of DAT, loss to follow-up, and patients who were provided additional treatments and myocardial revascularization, together with their ratio between treatments. The measures were the pooled overall proportion of the primary outcomes and the risk ratio (RR) in the TAVI vs SAVR groups.P < .001). The pooled proportion of loss to follow-up was 4.8% . Meta-regression showed a significant association between the proportion of participants lost to follow-up and follow-up time . There was an imbalance of loss to follow-up favoring TAVI . The pooled proportion of patients who had additional procedures was 10.4% : 4.6%  in the TAVI group and 16.5%  in the SAVR group . The imbalance between groups also favored TAVI for additional myocardial revascularization .The search identified 8 eligible trials including 8849 participants randomly assigned to undergo TAVI (n = 4458) or SAVR (n = 4391). The pooled proportion of DAT among the sample was 4.2% , favoring TAVI (pooled RR vs SAVR, 0.16; 95% CI, 0.08-0.36; This study suggests that, in RCTs comparing TAVI vs SAVR, there are substantial proportions of DAT, loss to follow-up, and additional procedures together with systematic selective imbalance in the same direction characterized by significantly lower proportions of patients undergoing TAVI that might affect internal validity. This systematic review and meta-analysis assesses whether randomization protects randomized clinical trials comparing transcatheter aortic valve implantation and surgical aortic valve replacement from biases other than nonrandom allocation. This difference is also known as deviations from random assigned treatment (DAT).19 The erosion of the unbiased ITT groups generated by nonrandom loss of participants produces biases related to the violation of the principle of randomization, particularly if nonrandom loss of participants is selectively represented in the treatments.21 In RCTs designed for evaluating outcomes at follow-up, the main source of exclusion is loss to follow-up, as participants might withdraw from the study or might not be located.23 Each loss impairs internal validity, especially if it is differential among treatment groups. The imbalance related to patients’ exclusion for nonadherence to treatments or loss to follow-up could lead to attrition bias,23 which might undermine the advantages of randomization, thereby challenging the comparability of the treatment groups.The literature on the comparison between transcatheter and surgical approaches for aortic valve stenosis comprises 7 randomized clinical trials (RCTs) conducted since 2007 in progressively lower-risk populations that demonstrated noninferiority and, in some cases, superiority of transcatheter aortic valve implantation (TAVI) compared with the standard of care.18 quality assessment by version 2 of the Cochrane risk-of-bias tool for randomized trials (RoB 2 tool) is the risk of performance bias that occurs if additional treatments are provided preferentially to a single group, potentially leading to biased outcomes.23 An imbalance in concomitant procedures  between patients who underwent TAVI and those who underwent surgical aortic valve replacement (SAVR) is present in almost all the RCTs. Although some of these procedures cannot be defined as protocol deviation because they are allowed according to the protocol, each treatment other than isolated aortic valve replacement may affect short- and long-term outcomes, and differential rates of additional procedures may selectively affect the results.Another major issue that emerged in the 2021 European Society of Cardiology/European Association for Cardio-Thoracic Surgery (ESC/EACTS) guidelines’24 we performed a quantitative assessment of DAT, loss to follow-up, and receipt of additional treatments for the TAVI vs SAVR trials and an evaluation of their differential rates between treatments.Although the assessment of methodological quality of RCTs by the RoB 2 tool is mostly qualitative,PRISMA) reporting guideline.25 The protocol has been registered in PROSPERO.26This meta-analysis study is exempt from ethics approval as we collected and synthesized data published from previous clinical trials in which informed consent had already been obtained by the trial investigators. The study protocol adhered to the Preferred Reporting Items for Systematic Reviews and Meta-analyses  was used as effect size for evaluating differential rates of the primary outcomes between TAVI and SAVR (with SAVR as the control group).Two independent investigators (F.B. and D.R.) identified trials that fulfilled the prespecified inclusion criteria. Eligible trials were then reviewed in duplicate and disagreement was resolved by a third investigator (A.P.). Extracted data from the text and appendixes of eligible trials were trial characteristics, patients’ baseline data and comorbidities, device type, and implantation access.18 was then updated by 2 researchers (F.B. and A.P.), with a third researcher (A.A.) designated to resolve potential disagreements using the RoB 2 tool,24 incorporating information provided by outcomes of this meta-analysis.This meta-analysis quantitatively evaluated 2 domains of the RoB 2 tool. The risk of bias among trials included in the ESC/EACTS 2021 Guidelines for Management of Heart Valve Disease by the 4 delegates32 The between-study variance was estimated with the Hartung-Knapp-Sidik-Jonkman method, while the Cochran Q test and the I2 statistics were applied to evaluate between-study heterogeneity.Random-effects proportion meta-analysis was used to estimate the pooled overall proportions of the primary outcomes.33 Between-study variance was estimated with the Hartung-Knapp-Sidik-Jonkman method, while the Cochran Q test and the I2 statistics were applied to evaluate between-study heterogeneity. The association between loss to follow-up and follow-up time was explored with random-effects meta-regression. Analyses were performed with R, version 4.2.0 .34 All P values were from 2-sided tests and results were deemed statistically significant at P < .05.Random-effects meta-analysis was used to pool the RR of primary outcomes in the TAVI vs SAVR groups.36 The STACCATO  trial35 was excluded as it was prematurely terminated by the data safety monitoring board. The remaining 8 trials  fulfilled the prespecified inclusion criteria and were included in the meta-analysis . DAT showed a selective pattern, being 6.2-fold lower in the TAVI group compared with the SAVR group      . Only thP < .001) ( < .001) .P < .001), indicating that TAVI had a significant 2.56-fold lower risk of patients lost to follow-up. The selective loss to follow-up appears to decrease with increasing follow-up time, although meta-regression does not confirm the significance of this association  . There were differential rates of receipt of additional treatments in the 2 groups; the pooled proportion in the TAVI group was 4.6%  and in the SAVR group was 16.5%  , indicating that TAVI has a 3.7-fold lower proportion of participants who undergo additional procedures    , with significant heterogeneity among studies  are relatively rare in the study populations, the attrition bias introduced by significant loss to follow-up can be potentially amplified. Incompleteness of follow-up data is somehow inevitable; however, for minimizing incompleteness, the sample size should be estimated taking into account the length of follow-up and potential rates of loss, and the protocol should include methods for reducing and handling losses, including selection of centers with a history of excellent retention and use of statistical methods for analysis of missing data, such as imputation.24Third, attrition bias may be the most substantial threat to internal validity. Loss to follow-up threatens the ITT principle for guaranteeing an unbiased treatment comparison and should be minimized to preserve proper randomization. Although only 0% of losses ensures the benefit of randomization, 5% is the proposed cutoff for differentiating between little risk and intermediate risk of bias, while loss exceeding 20% could pose critical threats to validity.24 To obviate this risk, the Cochrane Rob 2 tool recommends estimating the effect of assignment to the intervention group by ITT analysis, which is a de facto standard for a clinical trial, and when as-treated analysis is performed.37 The use of ITT analysis, where all patients are counted according to their randomized group, ensures comparability between groups as obtained through randomization, maintains sample size, and eliminates bias. This approach measures both the efficacy of the intervention as assigned and overall adherence. In contrast, as-treated analysis refers to inclusion in the analysis of only patients who received the assigned intervention and per-protocol analysis refers to inclusion in the analysis of only patients who strictly adhered to the protocol. Although per-protocol analysis provides an estimate of the true efficacy of an intervention, it can be subject to bias as randomization has been violated. Poor trial quality  might bias results toward the null. In superiority studies, ITT analysis is therefore conservative, favoring the null hypothesis of no difference. However, in noninferiority trials , where the alternative hypothesis is that of no difference, ITT analysis is no longer conservative as it can lead to false-positive results by favoring the alternative hypothesis. Consequently, noninferiority trials often consider both ITT and per-protocol analyses concurrently. Randomized clinical trials comparing TAVI and SAVR have chosen different approaches; nonetheless, in this case, the selective imbalance of DAT between TAVI and SAVR might raise concerns regarding internal validity in trials that primarily report as-treated or per-protocol analyses.Both the absolute rate of DAT and selective DAT can be associated with the ITT principle and undermine unbiased comparison groups at baseline.22 Although most of the additional treatments are allowed by the protocol design and the formal definition of protocol deviation does not apply, selective application of additional procedures biases outcomes, as it expresses imbalanced baseline myocardial disease or systematic differences in the provided care. Myocardial revascularization strategies should be equally applicable to the 2 groups and patients requiring coronary revascularization should be included unless only surgical revascularization is considered appropriate,36 to avoid selective administration of adjunctive treatments. The high difference in rates of concomitant myocardial revascularization in TAVI groups vs SAVR groups is inconsistent with the equality of treatments; the trialists of PARTNER 2A acknowledge this point as they attribute such imbalanced rates to the undertreatment of significant coronary artery disease in the TAVI group.4Performance bias is another critical issue in RCTs comparing TAVI and SAVR.18 This position is debatable based on the results of the ISCHEMIA  trial, which demonstrated that medical therapy holds a lower risk of adverse events in the short term while invasive treatment seems to yield a morbidity or mortality advantage only in the midterm and long term, confirming that each invasive maneuver holds an intrinsic risk of invasiveness-related adverse events.38 The more invasive the procedure, the higher the short-term risk of complications, while the potential advantage of an invasive treatment is likely to emerge in the midterm to long-term follow-up.40 As it is well expressed by EuroSCORE  and STS PROM  score, the adjunct of coronary artery bypass graft as well as other additional procedures significantly increases perioperative risk and represents an intrinsic baseline gap vs the isolated procedure, as also confirmed by the US Food and Drug Administration exploratory analysis of PARTNER 1A, where adding concomitant procedures to SAVR nearly doubled the risk of mortality , biasing short-term results in favor of TAVI.41 The potential unfavorable effect of selective undertreatment reported in the TAVI groups will likely be unmasked only in the midterm, well beyond 1- to 2-year follow-up of the RCTs as evaluated in primary or secondary outcome measures.Similar considerations may be made with respect to the concomitant performance of thoracic aortic surgery or nonaortic valve procedures among patients undergoing SAVR; these procedures occurred at discrete, nonnegligible rates in PARTNER 3 and the Evolut Low Risk Trial. In other words, the administration of different therapeutic strategies to the same disease is in itself a selective protocol deviation with an intrinsic high risk of performance bias. The ESC/EACTS delegates interpreted the different proportion of myocardial revascularization in favor of SAVR and the different proportion of other additional procedures in favor of TAVI.The quantitative estimation of overall rates and selective imbalance of DAT, loss to follow-up, and receipt of additional procedures of our meta-analysis may help to revise at least some domains of the RoB 2 tool (eFigure 11 and eAppendix in This meta-analysis has some limitations. The main limitation is that we cannot predict how these imbalances act in the magnitude and direction of bias and overall benefit. Although it is described that selective rates of withdrawal may favor the treatment compared with the control, only analyses of individual patient data can confirm it. At this point of evidence, we can simply highlight that RCTs show serious methodological imbalances with a common selective pattern that can increase the risk of bias. The association of the risk of performance and attrition biases with trials’ primary outcomes is far beyond the aims of the present meta-analysis, which is focused on methodological issues and has been designed to quantify the key factors that might inflate performance and attrition biases. Only data sharing and an independent evaluation may overcome the existing limitations, permitting a deep understanding of the association between risk of bias and results.This systematic review and meta-analysis found that the RCT design does not protect from biases other than nonrandom allocation. In RCTs comparing TAVI vs SAVR, there were systematic imbalances in the proportion of DAT, loss to follow-up, and receipt of additional procedures and additional myocardial revascularization that can pose a serious threat to internal validity due to high risk of performance and attrition biases. The potential associations of this risk of bias with trials’ primary outcomes are beyond the aims of the present meta-analysis and need data sharing to be evaluated.


Integrated care is expected to improve patient experience, patient outcomes and assist with the increasing demand on health services from those with long term conditions including mental disorder. Few studies have evaluated health care utilization as a consequence of increased integration of mental health care. This study considers the factors known to influence secondary health service utilization and investigated the impact of a locality based mental health integrated model of care (ILoC) providing specialist consultation and liaison advice to primary care, to support early diagnosis and treatment.Using existing hospital databases, the study-cohort was identified  care between 2017– 2018) and compared on health services utilization with a matched-cohort .The length-of-care in the non-acute MHS was 71% shorter for the ILoC study-cohort, and differences increased in the subgroup taking antidepressants. The ILoC study-cohort was less likely to be admitted to acute MHS on first referral post ILoC intervention and had a 25% lower relative risk of acute MHS admissions at any time in follow-up. There was no difference in the average MHS inpatient length-of-stay. The risk of general hospital acute inpatient admission was marginally higher in the ILoC study-cohort.ILoC appears to shorten non-acute length-of-specialist-care and reduce acute mental health admission. The study provides a first step in understanding the clinical characteristics and specialist services health-care utilization of patients supported by an integrated mental care approach. Integrated care is expected to improve patient experience, patient outcomes and assist with the increasing health services demand from those with long term conditions, including mental health needs 2345678. 234567Integration and collaborative care are terms often used together in the literature. A Cochrane review  of 79 raOther literature describes a range of impacts of integration initiatives on health service utilization including a decrease in non-acute service utilization and an increase in acute general hospital services utilization 1314.13Counties Manukau Health (CMH) is a district health board in South Auckland New Zealand and serves a multi-ethnic community including Maaori, Pacific and Asian communities with significant socio-economic deprivation .CMH aims to deliver the triple aims of improved quality, safety and patient experience of care, improved health and equity for all populations, and better value 16.A locality based integrated care model ) was implemented in late 2016 as one component of a wider ‘whole of system’ change in the mental health services aiming to make specialist services support accessible to a larger part of the CMH population 16.An earlier collaborative project in the service had changed all position descriptions from ‘case manager’ to ‘mental health clinician in scope’ aiming to reposition the specialist workforce to be ‘facing’ primary care, to build stronger relationships with primary care and so to develop new responses to the challenges facing access to specialist mental health systems in Aotearoa – New Zealand 1819.18The ILoC implementation expected that the specialists services working closely with primary care would, in time, shift specialist staff focus to integration and adapt their practice to greater collaboration and ‘sharing the care’ with primary care partners . ILoC foILoC activities include telephone and face-to-face consultation with primary care providers; some one-off patient assessments or joint sessions in a GP practice, a marae clinic-,  or with a school counsellor; some brief therapeutic interventions, and the ‘signposting’ of relevant alternative community-based resources to providers and service users. Contact for liaison support were made by ‘request’, rather than formal referral, and the primary care clinical record is shared and used by all parties. Care delivery remains substantially with the primary care practitioner , or marae-based clinics).This service is provided by a multidisciplinary team including Psychiatrists, Occupational therapists, Registered nurses and Social workers, Community Support workers (non-government-organization (NGO)) staff and Community Alcohol and Drug Service (CADS) clinicians. ILoC currently serves approximately 30% of general practices within the CMH area, as well as 10 high schools, 20 aged residential care providers (ARC) and one marae-based clinic. Clinical psychologists also provided clinical supervision to some ILoC teams.One typical scenario of an ILoC request is from a school nurse requiring guidance on a student. After verbal consultation and a brief assessment with an ILoC clinician, the student was referred to the non-acute mental health service. If this was usual care, the student will need to see a GP first and wait for GP to refer them to specialist secondary care. If the student’s condition was assessed to be acute, they would be referred immediately to the crisis mental health team.We conducted a matched-cohort observational study to investigate the impact of ILoC on secondary-care utilization, including specialist mental health community care service units and inpatient hospital care services and to identify other factors that affected health services utilization.CMH specialist mental health services (MHS) provides both acute care pathway service (acute-MHS) and non-acute ‘integrated’ specialist care service (non-acute MHS). The acute pathway includes the mental health inpatient unit and acute community mental health specialist care service .The study used evidence from the literature to inform the design, including identifying other factors known to associate with the utilization of mental health and inpatient hospital services.Factors affecting utilization of unscheduled hospital admission for mental health service users, include service users’ demographics 22, socia2123242114Systematic reviews of primary care features identified that proximity influenced patterns of unscheduled secondary care use . We used2930We used a quantitative approach, conducted a retrospective cohort study with a matched cohort.The ILoC primary-cohort: service users of CMH exposed to an ILoC intervention through their primary care/school health providers between Jan 2017 and June 2018.The ILoC study-cohort: a subset of the primary-cohort only included those who were referred to CMH mental health specialist care (MHS) within 6 months.The matched -cohort: selected from those who were referred to MHS during the same period but without receiving ILoC support, matched by demographics and referral month.Each participant was followed for a period of 6 months – 1 year from the date of their referral to MHS.The study was approved by the CMH locality and New Zealand Health and Disability Ethics Committee (19/CEN/41/AM01).Using the information and data linkage from two major Counties Manukau Health databases HCC and iPIM, the ILoC primary-cohort and the ILoC study-cohort were identified. The ILoC study and the matched-cohort were selected from the same referral database, in the same period using a ratio 1:4 between ILoC study and matched-cohorts . These wThe primary outcomes assessed were non-acute MHS length-of-care, admission/readmission to acute MHS and acute admission from the first MHS referral. The secondary outcomes were length-of-care in acute MHS, MHS inpatient length-of-stay, and general hospital inpatient admission.For general hospital inpatient admission, we extracted the hospital inpatient admission records, one-year before the earliest first referral and all records post first MHS referral in the study period. We then reviewed the reasons for inpatient admission to identify those who were admitted during follow-up for suicide attempts, those admitted for any other reasons associated with a mental health condition, and those admitted for other non-mental health reasons.Based on the literature described in 2.0, we included predisposing factors , enabling factors , clinical needs factors , socioeconomic status, previous self-harm or suicidal attempts, and country of birth. Prescribed medication, classified as benztropine, antidepressant, antipsychotic, hypnotic, mood stabilization and anxiolytic, was used as a proxy for mental health condition and clinical need indicator.The collated information of both cohorts included: referral to and discharge dates from mental health specialist (MHS) service, referral reasons and referral sources, previous number of admissions to MHS, hospital inpatient admission diagnoses, other MHS service referral information, inpatient admission dates, reasons for admission and demographics.A pilot study using an ILoC subset and its unmatched-cohort was used to investigate the concept and feasibility. Based on the pilot and sample size estimation, a matched-control by ethnicity, age group and referral time was proposed to eliminate these confounding effects and enhance the statistical power.The outcomes of non-acute or acute MHS length-of-care, and inpatient MHS length-of-stay were analysed using the mixed effect model to account for the repeated mental health referral episodes and were adjusted for confounding effects , matched factors  and the exposure factor (ILoC intervention). The likelihood of an acute first MHS admission was compared between the ILoC study and ILoC matched-cohort using a multiple logistic regression. Length-of-stay and length-of-care were log-transformed in the mix effect models.The other outcomes  were compared between the ILoC study and matched-cohort using the Cox regression model with a robust variance to account for the re-occurring admissions and adjusted by the same abovementioned confounding effects, matched factors and the exposure factor.Pre-specified subgroup analyses were conducted for those prescribed antidepressants and antipsychotics after the first referral. Known confounders are all included in the models.In the result, p value < 0.05 was considered to be statistically significant. Outcome estimates were all provided with their 95% confidence intervals. SAS institute released software version 9.4 and R version 4.0.0 were used in the analysis.Between Jan 2017-June 2018, 373 service users received ILoC intervention through primary care providers . Of the 373 service users, 101 had a referral to specialist MHS within the following 6 months. A matched-cohort of 404 service users was selected from the same MHS referral population in the same period. As shown in The ILoC study-cohort and matched-cohort had similar pre-referral hospital inpatient admission rates (43/101 (43%) vs. 54/404 (38%), p = 0.48), and a similar proportion of previous suicide attempts (6/101 (5.9%) vs. 14/404 (3.5%), p = 0.39). The ILoC study-cohort had a significant higher proportion of general hospital inpatient admission for reasons related to mental health than the matched-cohort before first referral to MHS (9/101 (8.9%), 12/404 (3.0%), p = 0.01), but there were no significant differences in the admissions due to “any reason” between the two cohorts (37 (36.6%) vs. 116 (28.7%), p = 0.12). A comparison in cohorts’ medication profiles after the first referral (including continuing medications) to MHS  shows thThe length-of-care in non-acute community MHS was the period a service user was under care of the community MHS specialist teams.The episodes of admission to MHS during the study period are compared in After controlling for the confounding effects and covariates, the predicted average length-of-care in non-acute MHS was 55 days for the ILoC study-cohort and 76 days for the matched-cohort. The length-of-care in the ILoC cohort was therefore about 71% of the length-of-care in matched-cohort  of the ratio: 0.47 to 1.08, p = 0.11). Service users in both the study and matched-cohorts who were prescribed antidepressants at any time during the study period  had on average a significant 67% longer length-of-care in non-acute MHS than those not prescribed antidepressants  .A subgroup analysis including only those prescribed antidepressants showed that the ILoC study-cohort had 28.6% shorter non-acute length-of-care than the matched- cohort .The ILoC study-cohort had a lower risk of acute MHS admission at any time during the follow-up period, than the matched-cohort , with a marginal statistical significance. All service users had significantly higher risk of an acute MHS admission if they were prescribed antipsychotics medication, or antidepressants or if they live in regions with higher deprivation index .Subgroup analyses were conducted for service users who were prescribed antidepressants and those prescribed antipsychotics. Service users prescribed antidepressants in the ILoC study-cohort, had marginally lower risk of acute MHS admission than those in the matched-cohort . There was no significant difference in the risk of admission to acute MHS between service users prescribed antipsychotics in the two cohorts .The ILoC study-cohort was significantly less likely to have an acute MHS admission immediately post referral when compared to their matched-cohort  and matched-cohort 21 (5.2%)) .Service users with Maaori or Pacific prioritized ethnicities, female service users, service users living in the high deprivation index areas, service users prescribed antidepressants, and service users prescribed antipsychotics were all more likely to be admitted to the acute MHS in their first MHS episodes .In service users prescribed antidepressants, the likelihood of an acute MHS admission in their first referral was significantly lower in the ILoC cohort than the matched-cohort . In service users prescribed antipsychotics, the likelihood was also lower in the ILoC cohort .Of all service users in the ILoC study and matched-cohort who had a general hospital inpatient admission after their first MHS referral during follow-up period, only 1 from the ILoC study-cohort (1%) and 5 from the matched-cohort (1.2%) were admitted for suicide attempts. There was a marginal difference in the proportion of people who had at least 1 general hospital inpatient admission due to mental health reasons or self-harm between the two cohorts (10/101 (9.9%) vs. 20/404 , and no significant differences in admissions for any reason  (29 (28.7%) vs. 93 (23.0%), p = 0.23).After controlling for the confounding effects and covariates, the ILoC study-cohort had an overall 1.60–fold higher risk  of general hospital admission for any reasons post referral than the matched-cohort. The other significant contributing factors associated with a higher risk of general hospital admission were older age, higher derivation index and shorter distance-to-hospital.The median acute-MHS length-of-care was 5 days for the ILoC study-cohort and 5 days for the matched-cohort, and 13 days versus 12 days for inpatient length of stay . There wService users supported by Integrated locality care (ILoC) before referral to specialist mental health services (the ILoC study-cohort) had higher frequency of antidepressant, antipsychotic, hypnotic, and anxiolytic prescription, compared to those not referred on. This ILoC study group also appeared to have a higher risk of general hospital inpatient admission , compared to service users with a similar demographic profile who had not received ILoC support, before being referred to mental health specialist. The ILoC study group had shorter periods of care in the non-acute mental health services and were less likely to be admitted acutely. These results are consistent with the findings of the 2 Cochrane reviews.Archer’s Cochrane review and meta-analysis  of endpoReilly’s review  reportedOur study compared mental health re-admission within 6 months after the first specialist care referral (following ILoC intervention) and identified different patterns in secondary care utilizations. Consistent with Bauers’ finding , the ILoBusse and Stahl  evaluateA comparison of the ILoC model to the six elements of the chronic care model (CCM) 34 in pri33There was insufficient data to allow separate analysis by ethnicity in this study. Further adaptions to the ILoC integration approach should specifically consider the needs of the Maaori and Pacific communities who together make up about half of the CMH populations. These communities experience significant inequity in mental health outcomes. Models such as Durie’s Te Whare Tapa Wha Maaori health approach could inform this work 38.Huntley, Lasserson  completeOur finding of the significant association between prescription of antipsychotic medication and inpatient mental health length-of-stay was also consistent with findings of Siskind et al.‘s  study. IThis study is the first to investigate the secondary care utilization of an integrated mental health care model using a matched cohort design. It has completed data in primary and secondary outcomes; it used two major databases to provide information and assessed the outcomes independently. However, the study was retrospective and relied on the available information from the administrative databases. We cannot use a parallel control group to compare with the intervention group as would occur in a randomized control trial. There were limits to the available information we can use. For example, we cannot provide accurate information for analysis of living conditions. We have used prescription of medication as a proxy for mental health condition/diagnosis. Prescription of medication was also shown to be a potential mediator for length of care. These phenomena made interpretation more difficult.The ILoC approach should implement further changes consistent with the six elements of the CCM model, and with a holistic Maaori health model such as Te Whare Tapa Wha. Qualitative and quantitative method can be used in evaluation and research to assess the impact of any such changes. In particular, future studies must have sufficient participants to consider the effects of integration on the outcomes for the Maaori and Pacific population.A future study should focus on a larger cohort with longer prospective follow-up of patient outcomes post ILoC intervention and acquire information  that is not currently available in the existing databases.The study provides a first step in understanding the clinical characteristics and health-care utilization of patients with mental health needs supported by an integrated locality care model. ILoC appears to shorten non-acute length- of-specialist care and reduce acute mental health admission. Future application includes continued improvements in the integrated system and the model of care. These need to reflect the clinical needs, and other factors influencing health service utilization identified from the study.