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Kidney failure is common in patients with Coronavirus Disease-19 (COVID-19), resulting in increased morbidity and mortality. In an international collaboration, 284 kidney biopsies were evaluated to improve understanding of kidney disease in COVID-19. Diagnoses were compared to five years of 63,575 native biopsies prior to the pandemic and 13,955 allograft biopsies to identify diseases that have increased in patients with COVID-19. Genotyping for APOL1 G1 and G2 alleles was performed in 107 African American and Hispanic patients. Immunohistochemistry for SARS-CoV-2 was utilized to assess direct viral infection in 273 cases along with clinical information at the time of biopsy. The leading indication for native biopsy was acute kidney injury (45.4%), followed by proteinuria with or without concurrent acute kidney injury (42.6%). There were more African American patients (44.6%) than patients of other ethnicities. The most common diagnosis in native biopsies was collapsing glomerulopathy (25.8%), which was associated with high-risk APOL1 genotypes in 91.7% of cases. Compared to the five-year biopsy database, the frequency of myoglobin cast nephropathy and proliferative glomerulonephritis with monoclonal IgG deposits was also increased in patients with COVID-19 (3.3% and 1.7%, respectively), while there was a reduced frequency of chronic conditions (including diabetes mellitus, IgA nephropathy, and arterionephrosclerosis) as the primary diagnosis. In transplants, the leading indication was acute kidney injury (86.4%), for which rejection was the predominant diagnosis (61.4%). Direct SARS-CoV-2 viral infection was not identified. Thus, our multi-center large case series identified kidney diseases that disproportionately affect patients with COVID-19 and demonstrated a high frequency of APOL1 high-risk genotypes within this group, with no evidence of direct viral infection within the kidney.

Early diagnosis and appropriate management of Cesarean scar pregnancy (CSP) are crucial to prevent severe complications, such as uterine rupture, severe hemorrhage and placenta accreta spectrum disorders. In this article, we provide a step‐by‐step tutorial for the standardized sonographic evaluation of CSP in the first trimester. Practical steps for performing a standardized transvaginal ultrasound examination to diagnose CSP are outlined, focusing on criteria and techniques essential for accurate identification and classification. Key sonographic markers, including gestational sac location, cardiac activity, placental implantation and myometrial thickness, are detailed. The evaluation process is presented according to assessment of the uterine scar, differential diagnosis, detailed CSP evaluation and CSP classification. This step‐by‐step tutorial emphasizes the importance of scanning in two planes (sagittal and transverse), utilizing color or power Doppler and differentiating CSP from other low‐lying pregnancies. The CSP classification is described in detail and is based on the location of the largest part of the gestational sac relative to the uterine cavity and serosal lines. This descriptive classification is recommended for clinical use to stimulate uniform description and evaluation. Such a standardized sonographic evaluation of CSP in the first trimester is essential for early diagnosis and management, helping to prevent life‐threatening complications and to preserve fertility. Training sonographers in detailed evaluation techniques and promoting awareness of CSP are critical. The structured approach to CSP diagnosis presented herein is supported by a free e‐learning course available online. © 2024 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the ability of the Assessment of Different NEoplasias in the adneXa (ADNEX) model and the International Ovarian Tumour Analysis (IOTA) two‐step strategy to predict malignancy in adnexal masses detected in an outpatient low‐risk setting, and to estimate the risk of complications in masses with benign ultrasound morphology managed using clinical and ultrasound follow‐up. Methods: This single‐center study was performed at Hospital Universitari Dexeus, Barcelona, Spain, using interim data from the ongoing prospective observational IOTA Phase‐5 (IOTA5) study. The primary aim of the IOTA5 study is to describe the cumulative incidence of complications during follow‐up of adnexal masses classified as benign on ultrasound examination. Consecutive patients with an adnexal mass detected between June 2012 and September 2016 in a private center offering screening for gynecological cancer were included and followed up until February 2020. Tumors were classified as benign or malignant based on histology (if patients underwent surgery) or the outcome of clinical and ultrasound follow‐up at 12 (range, 10–14) months. Multiple imputation was used when outcomes were uncertain. The ability of the ADNEX model without CA125 and of the IOTA two‐step strategy to distinguish benign from malignant masses was evaluated retrospectively using the prospectively collected data. We assessed performance with regard to discrimination (area under the receiver‐operating‐characteristics curve (AUC)), calibration, classification (sensitivity and specificity) and clinical utility (Net Benefit). In the group of patients with a mass judged to be benign who were selected for conservative management, we evaluated the occurrence of spontaneous resolution or any mass complication during the first 5 years of follow‐up by assessing the cumulative incidence of malignancy, torsion, cyst rupture and minor mass complications (inflammation, infection or adhesions) and the time to occurrence of an event. Results: A total of 2654 patients were recruited to the study. After application of exclusion criteria, 2039 patients with a newly detected mass were included for the model validation. Of those, 1684 (83%) masses were benign, 49 (2%) masses were malignant and, for 306 (15%) masses, the outcome was uncertain and therefore imputed. The AUC was 0.95 (95% CI, 0.89–0.98) for ADNEX without CA125 and 0.94 (95% CI, 0.88–0.97) for the two‐step strategy. Calibration performance could not be meaningfully interpreted because the small number of malignancies resulted in very wide confidence intervals. The two‐step strategy had better clinical utility than did the ADNEX model at malignancy risk thresholds < 3%. There were 1472 (72%) patients whose mass was judged to be benign based on pattern recognition by an experienced ultrasound examiner and were managed with clinical and ultrasound follow‐up. In this group, the 5‐year cumulative incidence was 66% (95% CI, 63–69%) for spontaneous resolution of the mass, 0% (95% CI, 0–0.2%) for torsion, 0.1% (95% CI, < 0.1–0.4%) for cyst rupture, 0.2% (95% CI, 0.1–0.6%) for a borderline tumor and 0.2% (95% CI, 0.1–0.6%) for invasive malignancy. Conclusions: The ADNEX model and IOTA two‐step strategy performed well to distinguish benign from malignant adnexal masses detected in a low‐risk population. Conservative management is safe for masses with a benign ultrasound appearance in this population. © 2024 International Society of Ultrasound in Obstetrics and Gynecology. [ABSTRACT FROM AUTHOR]

Preoperative sonographic staging in patients with suspected parametrial endometriosis is essential to plan surgical intervention and anticipate the need for a multidisciplinary approach, and thus optimize surgical outcome. The results of a recent meta‐analysis suggest that there is a need to define more accurately the ultrasonographic criteria for parametrial involvement in endometriosis. This addendum to the International Deep Endometriosis Analysis (IDEA) consensus highlights the sonographic characteristics of the parametrium and identifies ultrasound techniques to diagnose deep endometriosis in this area. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology. [ABSTRACT FROM AUTHOR]

The International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) and International Deep Endometriosis Analysis (IDEA) group, the European Endometriosis League (EEL), the European Society for Gynaecological Endoscopy (ESGE), the European Society of Human Reproduction and Embryology (ESHRE), the International Society for Gynecologic Endoscopy (ISGE), the American Association of Gynecologic Laparoscopists (AAGL) and the European Society of Urogenital Radiology (ESUR) elected an international, multidisciplinary panel of gynecological surgeons, sonographers and radiologists, including a steering committee, which searched the literature for relevant articles in order to review the literature and provide evidence‐based and clinically relevant statements on the use of imaging techniques for non‐invasive diagnosis and classification of pelvic deep endometriosis. Preliminary statements were drafted based on review of the relevant literature. Following two rounds of revisions and voting orchestrated by chairs of the participating societies, consensus statements were finalized. A final version of the document was then resubmitted to the society chairs for approval. Twenty statements were drafted, of which 14 reached strong and three moderate agreement after the first voting round. The remaining three statements were discussed by all members of the steering committee and society chairs and rephrased, followed by an additional round of voting. At the conclusion of the process, 14 statements had strong and five statements moderate agreement, with one statement left in equipoise. This consensus work aims to guide clinicians involved in treating women with suspected endometriosis during patient assessment, counseling and planning of surgical treatment strategies. © 2024 The Authors. Published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology, by Universa Press, by The International Society for Gynecologic Endoscopy, by Oxford University Press on behalf of European Society of Human Reproduction and Embryology, by Elsevier Inc. on behalf of American Association of Gynecologic Laparoscopists and by Elsevier B.V. [ABSTRACT FROM AUTHOR]

Objectives: To assess the ability of the International Endometrial Tumor Analysis (IETA)‐1 polynomial regression model to estimate the risk of endometrial cancer (EC) and other intracavitary uterine pathology in women without abnormal uterine bleeding. Methods: This was a retrospective study, in which we validated the IETA‐1 model on the IETA‐3 study cohort (n = 1745). The IETA‐3 study is a prospective observational multicenter study. It includes women without vaginal bleeding who underwent a standardized transvaginal ultrasound examination in one of seven ultrasound centers between January 2011 and December 2018. The ultrasonography was performed either as part of a routine gynecological examination, during follow‐up of non‐endometrial pathology, in the work‐up before fertility treatment or before treatment for uterine prolapse or ovarian pathology. Ultrasonographic findings were described using IETA terminology and were compared with histology, or with results of clinical and ultrasound follow‐up of at least 1 year if endometrial sampling was not performed. The IETA‐1 model, which was created using data from patients with abnormal uterine bleeding, predicts four histological outcomes: (1) EC or endometrial intraepithelial neoplasia (EIN); (2) endometrial polyp or intracavitary myoma; (3) proliferative or secretory endometrium, endometritis, or endometrial hyperplasia without atypia; and (4) endometrial atrophy. The predictors in the model are age, body mass index and seven ultrasound variables (visibility of the endometrium, endometrial thickness, color score, cysts in the endometrium, non‐uniform echogenicity of the endometrium, presence of a bright edge, presence of a single dominant vessel). We analyzed the discriminative ability of the model (area under the receiver‐operating‐characteristics curve (AUC); polytomous discrimination index (PDI)) and evaluated calibration of its risk estimates (observed/expected ratio). Results: The median age of the women in the IETA‐3 cohort was 51 (range, 20–85) years and 51% (887/1745) of the women were postmenopausal. Histology showed EC or EIN in 29 (2%) women, endometrial polyps or intracavitary myomas in 1094 (63%), proliferative or secretory endometrium, endometritis, or hyperplasia without atypia in 144 (8%) and endometrial atrophy in 265 (15%) women. The endometrial sample had insufficient material in five (0.3%) cases. In 208 (12%) women who did not undergo endometrial sampling but were followed up for at least 1 year without clinical or ultrasound signs of endometrial malignancy, the outcome was classified as benign. The IETA‐1 model had an AUC of 0.81 (95% CI, 0.73–0.89, n = 1745) for discrimination between malignant (EC or EIN) and benign endometrium, and the observed/expected ratio for EC or EIN was 0.51 (95% CI, 0.32–0.82). The model was able to categorize the four histological outcomes with considerable accuracy: the PDI of the model was 0.68 (95% CI, 0.62–0.73) (n = 1532). The IETA‐1 model discriminated very well between endometrial atrophy and all other intracavitary uterine conditions, with an AUC of 0.96 (95% CI, 0.95–0.98). Including only patients in whom the endometrium was measurable (n = 1689), the model's AUC was 0.83 (95% CI, 0.75–0.91), compared with 0.62 (95% CI, 0.52–0.73) when using endometrial thickness alone to predict malignancy (difference in AUC, 0.21; 95% CI, 0.08–0.32). In postmenopausal women with measurable endometrial thickness (n = 848), the IETA‐1 model gave an AUC of 0.81 (95% CI, 0.71–0.91), while endometrial thickness alone gave an AUC of 0.70 (95% CI, 0.60–0.81) (difference in AUC, 0.11; 95% CI, 0.01–0.20). Conclusion: The IETA‐1 model discriminates well between benign and malignant conditions in the uterine cavity in patients without abnormal bleeding, but it overestimates the risk of malignancy. It also discriminates well between the four histological outcome categories. © 2023 International Society of Ultrasound in Obstetrics and Gynecology. [ABSTRACT FROM AUTHOR]

Objectives: Ectopic pregnancy (EP) is a major high‐risk outcome following a pregnancy of unknown location (PUL) classification. Biochemical markers are used to triage PUL as high vs low risk to guide appropriate follow‐up. The M6 model is currently the best risk‐prediction model. We aimed to update the M6 model and evaluate whether performance can be improved by including clinical factors. Methods: This prospective cohort study recruited consecutive PUL between January 2015 and January 2017 at eight units (Phase 1), with two centers continuing recruitment between January 2017 and March 2021 (Phase 2). Serum samples were collected routinely and sent for β‐human chorionic gonadotropin (β‐hCG) and progesterone measurement. Clinical factors recorded were maternal age, pain score, bleeding score and history of EP. Based on transvaginal ultrasonography and/or biochemical confirmation during follow‐up, PUL were classified subsequently as failed PUL (FPUL), intrauterine pregnancy (IUP) or EP (including persistent PUL (PPUL)). The M6 models with (M6P) and without (M6NP) progesterone were refitted and extended with clinical factors. Model validation was performed using internal–external cross‐validation (IECV) (Phase 1) and temporal external validation (EV) (Phase 2). Missing values were handled using multiple imputation. Results: Overall, 5473 PUL were recruited over both phases. A total of 709 PUL were excluded because maternal age was < 16 years or initial β‐hCG was ≤ 25 IU/L, leaving 4764 (87%) PUL for analysis (2894 in Phase 1 and 1870 in Phase 2). For the refitted M6P model, the area under the receiver‐operating‐characteristics curve (AUC) for EP/PPUL vs IUP/FPUL was 0.89 for IECV and 0.84–0.88 for EV, with respective sensitivities of 94% and 92–93%. For the refitted M6NP model, the AUCs were 0.85 for IECV and 0.82–0.86 for EV, with respective sensitivities of 92% and 93–94%. Calibration performance was good overall, but with heterogeneity between centers. Net Benefit confirmed clinical utility. The change in AUC when M6P was extended to include maternal age, bleeding score and history of EP was between −0.02 and 0.01, depending on center and phase. The corresponding change in AUC when M6NP was extended was between −0.01 and 0.03. At the 5% threshold to define high risk of EP/PPUL, extending M6P altered sensitivity by −0.02 to −0.01, specificity by 0.03 to 0.04 and Net Benefit by −0.005 to 0.006. Extending M6NP altered sensitivity by −0.03 to −0.01, specificity by 0.05 to 0.07 and Net Benefit by −0.005 to 0.006. Conclusions: The updated M6 model offers accurate diagnostic performance, with excellent sensitivity for EP. Adding clinical factors to the model improved performance in some centers, especially when progesterone levels were not suitable or unavailable. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology. [ABSTRACT FROM AUTHOR]

The article discusses the misuse of the term "arteriovenous malformation" (AVM) to describe myometrial vascularity after a recent intrauterine pregnancy. The authors argue that the term "enhanced myometrial vascularity" (EMV) should be used instead, as AVM and EMV are two different entities with distinct pathophysiologies and management approaches. AVMs are rare congenital vascular malformations that require surgery or interventional radiology, while EMV is a normal physiological condition associated with retained pregnancy tissue. The article provides guidance on the management of EMV, emphasizing the importance of accurate preoperative mapping and surgical removal of retained tissue. [Extracted from the article]

This article discusses a study that compared the performance of handheld point of care ultrasound (POCUS) with high-specification ultrasound in gynecology. The study involved 155 patients at a London teaching hospital, with one sonologist using POCUS and another using the standard high-specification machine. The results showed moderate correlation in uterine measurements, fair agreement for endometrial thickness, and slight agreement on ovary visualization. However, POCUS had improved performance when a cyst was present. The article concludes that POCUS may be a useful adjunct in gynecology, particularly in settings with limited access to ultrasound, but more data is needed for certain populations. [Extracted from the article]

This article discusses a study that used machine learning to develop a clinical decision support tool for predicting the success of expectant or medical management of miscarriage. The study involved a retrospective analysis of 1075 patients across two hospital early pregnancy units, and 14 clinical variables were collected, including patient demographics, history, and ultrasound features. The study found that the machine learning algorithms performed well in predicting outcomes, with area under the curve (AUC) scores ranging from 0.63 to 0.71. The authors conclude that this method could be used in future clinical trials to provide personalized outcome predictions for patients deciding on their miscarriage management. [Extracted from the article]

This article discusses a study that aimed to identify radiomic ultrasound features from early pregnancy images that could predict subsequent loss. The study included 500 cases of early pregnancy of unknown viability (PUV) and used a combination of machine learning models and traditional radiomics features to develop a prediction model. The best performing model achieved a recall of 0.81 and an AUC of 0.68, indicating its potential to predict miscarriage from early pregnancy ultrasound images. The study suggests that this machine learning method could help patients navigate the uncertainty of a PUV early pregnancy diagnosis. [Extracted from the article]