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Systematic Review of Artificial Intelligence for Abnormality Detection in High-volume Neuroimaging and Subgroup Meta-analysis for Intracranial Hemorrhage Detection
Agarwal, S., Wood, D., Grzeda, M., Suresh, C., Din, M., Cole, J., Modat, M., Booth, T. C.
Clinical neuroradiology. 2023;:1-14
Abstract
PURPOSE Most studies evaluating artificial intelligence (AI) models that detect abnormalities in neuroimaging are either tested on unrepresentative patient cohorts or are insufficiently well-validated, leading to poor generalisability to real-world tasks. The aim was to determine the diagnostic test accuracy and summarise the evidence supporting the use of AI models performing first-line, high-volume neuroimaging tasks. METHODS Medline, Embase, Cochrane library and Web of Science were searched until September 2021 for studies that temporally or externally validated AI capable of detecting abnormalities in first-line computed tomography (CT) or magnetic resonance (MR) neuroimaging. A bivariate random effects model was used for meta-analysis where appropriate. This study was registered on PROSPERO as CRD42021269563. RESULTS Out of 42,870 records screened, and 5734 potentially eligible full texts, only 16 studies were eligible for inclusion. Included studies were not compromised by unrepresentative datasets or inadequate validation methodology. Direct comparison with radiologists was available in 4/16 studies and 15/16 had a high risk of bias. Meta-analysis was only suitable for intracranial hemorrhage detection in CT imaging (10/16 studies), where AI systems had a pooled sensitivity and specificity 0.90 (95% confidence interval [CI] 0.85-0.94) and 0.90 (95% CI 0.83-0.95), respectively. Other AI studies using CT and MRI detected target conditions other than hemorrhage (2/16), or multiple target conditions (4/16). Only 3/16 studies implemented AI in clinical pathways, either for pre-read triage or as post-read discrepancy identifiers. CONCLUSION The paucity of eligible studies reflects that most abnormality detection AI studies were not adequately validated in representative clinical cohorts. The few studies describing how abnormality detection AI could impact patients and clinicians did not explore the full ramifications of clinical implementation.
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Comparison of quantitative and calculated postpartum blood loss after vaginal delivery
Madar, H., Sentilhes, L., Goffinet, F., Bonnet, M. P., Rozenberg, P., Deneux-Tharaux, C.
American journal of obstetrics & gynecology MFM. 2023;:101065
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Full text
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Editor's Choice
Abstract
BACKGROUND Because there is no consensual method of assessing postpartum blood loss, the comparability and relevance of the postpartum hemorrhage-related literature is questionable. Quantitative blood loss assessment using a volumetric technique with a graduated collector bag has been proposed to overcome limitations of intervention-based outcomes but remains partly subjective and potentially biased by amniotic fluid or missed out-of-bag losses. Calculated blood loss based on laboratory parameters has been published and used as an objective method expected to reflect total blood loss, but few studies have compared quantitative with calculated blood loss. OBJECTIVE This study aimed to compare the distribution of postpartum blood loss after vaginal delivery assessed by two methods - quantitative and calculated blood loss - and the incidence of abnormal blood loss with each method. STUDY DESIGN The data came from the merged database of 3 multicenter, randomized controlled trials, all testing different interventions to prevent postpartum blood loss in individuals with a singleton live fetus ≥ 35 weeks, born vaginally. All 3 trials measured blood loss volume by using a graduated collector bag. Hematocrit was measured in the eighth or ninth month of gestation and on day 2 postpartum. The two primary outcomes were: quantitative blood loss defined by the total volume of blood loss measured in a graduated collector bag, and calculated blood loss mathematically defined from the peripartum hematocrit change (estimated blood volume × [(antepartum hematocrit - postpartum hematocrit)/antepartum hematocrit], where estimated blood volume (mL) = booking weight (kg) × 85). We modelled the association between positive quantitative blood loss and positive calculated blood loss with polynomial regression and calculated the Spearman correlation coefficient. RESULTS Among the 8341 individuals included in this analysis, the median quantitative blood loss (100 mL, interquartile range 50-275) was significantly lower than the median calculated blood loss (260 mL, interquartile range 0-630) (P<.05). The incidence of abnormal blood loss was lower with quantitative blood loss than calculated blood loss for blood loss ≥ 500 mL, ≥ 1000 mL and ≥ 2000 mL, respectively, it was 9.6% (799/8341) vs 32.3% (2691/8341), 2.1% (176/8341) vs 11.5% (959/8341), and 0.1% (10/8341) vs 1.4% (117/8341); (P<.05). Quantitative blood loss and calculated blood loss were significantly but moderately correlated (Spearman coefficient=0.44; P<.05). The association between them was not linear, and their difference tended to increase with blood loss. Negative calculated blood loss values occurred in 23% (1958/8341) of individuals; among them, more than 99% (1939/1958) had quantitative blood loss ≤ 500 mL. CONCLUSION Quantitative and calculated blood loss were significantly but moderately correlated after vaginal delivery. However, clinicians should be aware that quantitative blood loss is lower than calculated blood loss, with a difference that tended to rise as blood loss increased.
PICO Summary
Population
Patients who gave birth vaginally, participating in the TRACOR, CYTOCINON, and TRAAP randomised controlled trials (RCTs) in several French maternity units (n= 8,341).
Intervention
This study aimed to compare the distribution of postpartum blood assessed by two methods - quantitative and calculated blood loss - and the incidence of abnormal blood loss with each method.
Comparison
Outcome
The data came from 3 RCTs testing different interventions to prevent postpartum blood loss. All 3 trials measured blood loss volume by using a graduated collector bag. The authors modelled the association between positive quantitative blood loss and positive calculated blood loss with polynomial regression and calculated the Spearman correlation coefficient. The median quantitative blood loss (100 mL, IQR= 50, 275) was significantly lower than the median calculated blood loss (260 mL, IQR= 0, 630). The incidence of abnormal blood loss was lower with quantitative blood loss than calculated blood loss. Quantitative blood loss and calculated blood loss were significantly but moderately correlated (Spearman coefficient= 0.44). The association between them was not linear, and their difference tended to increase with blood loss. Negative calculated blood loss values occurred in 23% (1,958/8,341) of individuals; among them, more than 99% (1,939/1,958) had quantitative blood loss ≤ 500 mL.
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Quantification of blood loss for the diagnosis of postpartum hemorrhage: a systematic review and meta-analysis
Ruiz, M. T., Azevedo, N. F., Resende, C. V., Rodrigues, W. F., Meneguci, J., Contim, D., Wernet, M., Oliveira, C. J. F.
Revista brasileira de enfermagem. 2023;76(6):e20230070
Abstract
OBJECTIVE to compare the effectiveness of different diagnostic methods to estimate postpartum blood volume loss. METHODS a systematic review of effectiveness according to PRISMA and JBI Protocol. Searches in PubMed/MEDLINE, LILACS, Scopus, Embase, Web of Science and CINAHL, with descriptor "Postpartum Hemorrhage" associated with keyword "Quantification of Blood Loss". Tabulated extracted data, presented in metasynthesis and meta-analysis was applied to quantitative data. To assess risk of bias, JBI Appraisal Tools were applied. RESULTS fourteen studies were included, published between 2006 and 2021. Quantification of loss by any method was superior to visual estimation and is highly recommended, however the studies' high heterogeneity did not allow estimating this association. CONCLUSION the studies' high heterogeneity, with a probable margin of error given the uncontrolled factors, indicates the need for further studies, however quantification proved to be effective in relation to visual estimate. PROSPERO registration CRD 42021234486.
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Targeted Bleeding Management Guided by Non-Invasive Haemoglobin Measurement in Surgical Patients
Akdag S, Zengin SU, Cakmak G, Umuroglu T, Aykac ZZ, Saracoglu A
Journal of the College of Physicians and Surgeons--Pakistan : JCPSP. 2022;32(10):1242-1248
Abstract
OBJECTIVE To assess blood transfusion decisions in blood losses using a continuous total haemoglobin (SpHb) and non-invasive haemoglobin (Hb) device. STUDY DESIGN Double-blinded randomised controlled trial. PLACE AND DURATION OF STUDY Marmara University Hospital, Istanbul, Turkey, from March 2018 to December 2019. METHODOLOGY One hundred and twenty adult patients scheduled for elective major surgery and expected to experience a blood loss greater than 20% of their total blood volume were divided into two groups. These groups were compared for bleeding management with conventional blood gas sampling (Group Hb, the control group) according to Hb monitoring versus SpHb measurement (Group SpHb, the study group). RESULTS In the postoperative measurement, there were fewer red blood cells (RBC) in the SpHb group than in the Hb group (p=0.020). There was a greater change in the amount of RBC from the perioperative to the postoperative period in the SpHb group compared to the Hb group (p<0.001). Postoperative Hb levels of patients in the intensive care unit (ICU) were higher in the SpHb group than in the Hb group (p<0.05). CONCLUSION SpHb can provide effective patient blood management in cases of major surgery. It does not cause a delay in the decision of blood transfusion during surgery. KEY WORDS Haemorrhage, Anaemia, Blood transfusion, General surgery.
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A predictive model for blood transfusion during liver resection
Cao B, Hao P, Guo W, Ye X, Li Q, Su X, Li L, Zeng J
European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology. 2022
Abstract
BACKGROUND A predictive model that can identify patients who are at increased risk of intraoperative blood transfusion could guide preoperative transfusion risk counseling, optimize health care resources, and reduce medical costs. Although previous studies have identified some predictors for particular populations, there is currently no existing model that uses preoperative variables to accurately predict blood transfusion during surgery, which could help anesthesiologists optimize intraoperative anesthetic management. METHODS We collected data from 582 patients who underwent elective liver resection at a university-affiliated tertiary hospital between January 1, 2018, and December 31, 2020. The data set was then randomly divided into a training set (n = 410) and a validation set (n = 172) at a 7:3 ratio. The least absolute shrinkage and selection operating regression model was used to select the optimal feature, and multivariate logistic regression analysis was applied to construct the transfusion risk model. The concordance index (C-index) and the area under the receiver operating characteristic (ROC) curve (AUC) were used to evaluate the discrimination ability, and the calibration ability was assessed with calibration curves. In addition, we used decision curve analysis (DCA) to estimate the clinical application value. For external validation, the test set data were employed. RESULTS The final model had 8 predictor variables for intraoperative blood transfusion, which included the following: preoperative hemoglobin level, preoperative prothrombin time >14 s, preoperative total bilirubin >21 μmol/L, respiratory diseases, cirrhosis, maximum lesion diameter >5 cm, macrovascular invasion, and previous abdominal surgery. The model showed a C-index of 0.834 (95% confidence interval, 0.789-0.879) for the training set and 0.831 (95% confidence interval, 0.766-0.896) for the validation set. The AUCs were 0.834 and 0.831 for the training and validation sets, respectively. The calibration curve showed that our model had good consistency between the predictions and observations. The DCA demonstrated that the transfusion nomogram was reliable for clinical applications when an intervention was decided at the possible threshold across 1%-99% for the training set. CONCLUSION We developed a predictive model with excellent accuracy and discrimination ability that can help identify those patients at higher odds of intraoperative blood transfusion. This tool may help guide preoperative counseling regarding transfusion risk, optimize health care resources, reduce medical costs, and optimize anesthetic management during surgery.
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A randomized controlled pilot trial of video-modelling versus telementoring for improved hemorrhage control wound packing
Kirkpatrick AW, McKee JL, Tomlinson C, Donley N, Ball CG, Wachs J
American journal of surgery. 2022
Abstract
INTRODUCTION Exsanguination is the most preventable cause of death. Paradigms such as STOP THE BLEED recognize increased responsibility among the less experienced with Wound Packing (WP) being a critical skill. As even trained providers may perform poorly, we compared Video-modelling (VM), a form of behavioural modelling involving video demonstration prior to intervention against remote telementoring (RTM) involving remote real-time expert-guidance. METHODS Search and Rescue (SAR-Techs), trained in WP were asked to pack a wound on a standardized simulator randomized to RMT, VM, or control. RESULTS 24 SAR-Techs (median age 37, median 16.5 years experience) participated. Controls were consistently faster than RTM (p = 0.005) and VM (p = 0.000), with no difference between RTM and VM. However, 50% (n = 4) Controls failed to pack properly, compared to 100% success in both VM and RTM, despite all SAR-Techs feeling the task was "easy". DISCUSSION Performance of a life-saving technique was improved through either VM or RTM, suggesting that both techniques are beneficial and complementary to each other. Further work should be extended to law enforcement/lay public to examine logistical challenges.
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Clinical usefulness of Red Dichromatic Imaging in hemostatic treatment during endoscopic submucosal dissection: first report from a multicenter, open-label, randomized controlled trial
Fujimoto A, Saito Y, Abe S, Hoteya S, Nomura K, Yasuda H, Matsuo Y, Uraoka T, Kuribayashi S, Tsuji Y, et al
Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society. 2021
Abstract
OBJECTIVES To verify the efficacy and safety of Red Dichromatic Imaging (RDI) in hemostatic procedures during endoscopic submucosal dissection (ESD). METHODS This is a multicenter randomized controlled trial of 404 patients who underwent ESD of the esophagus, stomach, colorectum. Patients who received hemostatic treatments by RDI during ESD were defined as the RDI group (n=204), and those who received hemostatic treatments by white light imaging (WLI) were defined as the WLI group (n=200). The primary endpoint was a shortening of the hemostasis time. The secondary endpoints were a reduction of the psychological stress experienced by the endoscopist during the hemostatic treatment, a shortened treatment time, and a non-inferior perforation rate, in RDI versus WLI. RESULTS The mean hemostasis time in RDI (n=860) was not significantly shorter than that in WLI (n=1049) (62.3±108.1 versus 56.2±74.6 seconds; p=0.921). The median hemostasis time was significantly longer in RDI than in WLI (36.0 (18.0-71.0) versus 28.0 (14.0-66.0) seconds; p=0.001) in a sensitivity analysis. The psychological stress was significantly lower in RDI than in WLI (1.71±0.935 versus 2.03±1.038; p<0.001). There was no significant difference in the ESD treatment time between RDI (n=161) and WLI (n=168) (58.0 (35.0-86.0) versus 60.0 (38.0-88.5) minutes; p=0.855). Four perforations were observed, but none of them took place during the hemostatic treatment. CONCLUSIONS Hemostatic treatment using RDI does not shorten the hemostasis time. RDI, however, is safe to use for hemostatic procedures and reduces the psychological stress experienced by endoscopists when they perform hemostatic treatment during ESD. UMIN000025134.
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The Recognition of Excessive blood loss At ChildbirTh (REACT) Study: A two-phase exploratory, sequential mixed methods inquiry using focus groups, interviews, and a pilot, randomised crossover study
Hancock A, Weeks AD, Furber C, Campbell M, Lavender T
BJOG : an international journal of obstetrics and gynaecology. 2021
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Editor's Choice
Abstract
OBJECTIVES To explore how childbirth-related blood loss is evaluated and excessive bleeding recognised; and develop and test a theory of postpartum haemorrhage (PPH) diagnosis. DESIGN Two-phase, exploratory, sequential mixed methods design using focus groups, interviews and a pilot, randomised crossover study. SETTING Two hospitals in North West England. SAMPLE Women (following vaginal birth with and without PPH), birth partners, midwives and obstetricians. METHODS Phase 1 (qualitative): 8 focus groups and 20 one-to-one, semi-structured interviews were conducted with 15 women, 5 birth partners, 11 obstetricians, 1 obstetric anaesthetist and 19 midwives (n=51). Phase 2 (quantitative): 11 obstetricians and 10 midwives (n=21) completed two simulations of fast and slow blood loss using a high-fidelity childbirth simulator. RESULTS Responses to blood loss were described as automatic, intuitive reactions to the speed, nature and visibility of blood flow. Health professionals reported that quantifying volume was most useful after a PPH diagnosis, to validate intuitive decisions and guide on-going management. During simulations, PPH treatment was initiated at volumes at or below 200ml (fast mean blood loss 79.6ml, SD 41.1; slow mean blood loss 62.6ml, SD 27.7). All participants treated fast, visible blood loss, but only half treated slow blood loss, despite there being no difference in volumes (difference 18.2ml, 95% CI -5.6 to 42.2ml, p=0.124). CONCLUSIONS Experience and intuition, rather than blood loss volume, inform recognition of excessive blood loss after birth. Women and birth partners want more information and open communication about blood loss. Further research exploring clinical decision-making and how to support it is required.
PICO Summary
Population
Women following vaginal birth, birth partners, midwives and obstetricians in two centres in the UK (n= 51).
Intervention
Simulation of ‘slow blood loss followed by fast blood loss’ (n= 10).
Comparison
Simulation of ‘fast blood loss followed by slow blood loss’ (n= 11).
Outcome
This mixed methods study had a qualitative phase involving focus groups and interviews, and a quantitative phase consisting in a randomised crossover study. Responses to blood loss were described as automatic, intuitive reactions to the speed, nature and visibility of blood flow. Health professionals reported that quantifying volume was most useful after a postpartum haemorrhage (PPH) diagnosis, to validate intuitive decisions and guide on-going management. During simulations, PPH treatment was initiated at volumes at or below 200ml (fast mean blood loss 79.6ml, SD 41.1; slow mean blood loss 62.6ml, SD 27.7). All participants treated fast, visible blood loss, but only half treated slow blood loss, despite there being no difference in volumes (difference 18.2ml).
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Techniques for blood loss estimation in major non-cardiac surgery: a systematic review and meta-analysis
Tran A, Heuser J, Ramsay T, McIsaac DM, Martel G
Canadian journal of anaesthesia = Journal canadien d'anesthesie. 2020
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Full text
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Editor's Choice
Abstract
PURPOSE Estimated blood loss (EBL) is an important tool in clinical decision-making and surgical outcomes research. It guides perioperative transfusion practice and serves as a key predictor of short-term perioperative risks and long-term oncologic outcomes. Despite its widespread clinical and research use, there is no gold standard for blood loss estimation. We sought to systematically review and compare techniques for intraoperative blood loss estimation in major non-cardiac surgery with the objective of informing clinical estimation and research standards. SOURCE A structured search strategy was applied to Ovid Medline, Embase, and Cochrane Library databases from inception to March 2020, to identify studies comparing methods of intraoperative blood loss in adult patients undergoing major non-cardiac surgery. We summarized agreement between groups of pairwise comparisons as visual estimation vs formula estimation, visual estimation vs other, and formula estimation vs other. For each of these comparisons, we described tendencies for higher or lower EBL values, consistency of findings, pooled mean differences, standard deviations, and confidence intervals. PRINCIPLE FINDINGS We included 26 studies involving 3,297 patients in this review. We found that visual estimation is the most frequently studied technique. In addition, visual techniques tended to provide lower EBL values than formula-based estimation or other techniques, though this effect was not statistically significant in pooled analyses likely due to sample size limitations. When accounting for the contextual mean blood loss, similar case-to-case variation exists for all estimation techniques. CONCLUSIONS We found that significant case-by-case variation exists for all methods of blood loss evaluation and that there is significant disagreement between techniques. Given the importance placed on EBL, particularly for perioperative prognostication models, clinicians should consider the universal adoption of a practical and reproducible method for blood loss evaluation. TRIAL REGISTRATION PROSPERO (CRD42015029439); registered: 18 November 2015.PROSPERO (CRD42015029439); registered: 18 November 2015.
PICO Summary
Population
Adult patients undergoing major non-cardiac surgery (26 studies, n= 3,297).
Intervention
Visual estimation of blood loss.
Comparison
Formula estimation of blood loss, and other tecnniques for estimating blood loss.
Outcome
Visual estimation was the most frequently studied technique. Visual techniques tended to provide lower estimated blood loss values than formula-based estimation or other techniques, though this effect was not statistically significant in pooled analyses. When accounting for the contextual mean blood loss, similar case-to-case variation existed for all estimation techniques.
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The accuracy of aneurysm size in predicting rebleeding after subarachnoid hemorrhage: a meta-analysis
Yu Z, Zheng J, Guo R, Li M, Li H, Ma L, You C
Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology. 2020
Abstract
BACKGROUND Aneurysmal subarachnoid hemorrhage (SAH) is a severe cerebrovascular disease. Rebleeding is an independent predictor of unfavorable outcome after aneurysmal SAH. However, the accuracy of aneurysm size for predicting rebleeding after aneurysmal SAH is still unclear. Hence, we conducted this meta-analysis to evaluate the predictive accuracy of large aneurysm for rebleeding after SAH. METHODS We performed a literature search in PubMed and Embase. Original studies about aneurysm size and rebleeding after SAH were included. Two reviewers completed data extraction and quality assessment. Pooled sensitivity, specificity, and their 95% confidence intervals (CIs) of large aneurysm for predicting rebleeding were calculated and shown in a forest plot. The overall accuracy of large aneurysm for predicting rebleeding after SAH was shown using a summary receiver operating characteristic (SROC) curve. Publication bias were assessed using Deeks' funnel plot. RESULTS A total of ten studies with 3889 patients met eligibility criteria and were included in this meta-analysis. The pooled sensitivity and specificity of large aneurysm for predicting rebleeding were 0.39 (95% CI 0.25-0.56) and 0.75 (95% CI 0.67-0.82), respectively. The area under SROC curve was 0.67 (95% CI 0.62-0.71). Deeks' funnel plot did not show obvious publication bias among included studies in this meta-analysis. CONCLUSION The specificity of large aneurysm for predicting rebleeding after SAH is relatively high. However, its overall accuracy for predicting aneurysm rebleeding is not very satisfying. A comprehensive model should be developed to improve the accuracy of rebleeding prediction after SAH.