Respiratory Tract (Lung and Bronchial) Diseases

All Conditions

Symptoms and General Pathology

Wounds and Injuries

Diseases and Abnormalities at or Before Birth

Neoplasms

Infections

Heart and Blood Diseases

Nutritional and Metabolic Diseases

Pleural Effusion

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Fractures, Bone

Congenital Abnormalities

Lung Neoplasms

Lung Diseases

Pulmonary Atelectasis

Pneumonia

Cardiomegaly

Calcinosis

Pneumothorax

Rib Fractures

Pulmonary Edema

Respiratory Tract Diseases

Pleural Diseases

Heart Diseases

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Pharmaceutical Solutions

All Drugs and Chemicals

To collect the CXR data for retrospective study, we addressed a municipal hospital in the Czech Republic that provides healthcare services to up to 130,000 residents of a medium-sized city (approximately 70,000 inhabitants) and the surrounding area. 127 anonymized CXR images were collected between August 15 and 17, 2022, and subsequently submitted to five independent radiologists of varying experience for annotation. The selected radiologists were asked to assess whether the CXR image shows any of the 12 abnormalities mentioned above. Pediatric CXR images (under 18 years of age), scans with technical problems (poor image quality, rotation), and images in lateral projection were excluded from the dataset.

Carebot AI CXR is a deep learning-based software that assists radiologists in the interpretation of chest radiographs in posterior-anterior (PA) or anterior-posterior (AP) projections. The solution with artificial intelligence automatically detects abnormality based on visual patterns for the following findings: atelectasis, consolidation, cardiomegaly, mediastinal widening, pneumoperitoneum, pneumothorax, pulmonary edema, pulmonary lesion, bone fracture, hilar enlargement, subcutaneous emphysema, and pleural effusion.

Carebot AI CXR

The purpose of this study is to describe the design, methodology and evaluation of the preclinical test of Carebot AI CXR software, and to provide evidence that the investigated medical device meets user requirements in accordance with its intended use. Carebot AI CXR is defined as a recommendation system (classification "prediction") based on computer-aided detection. The software can be used in a preclinical deployment at a selected site before interpretation (prioritization, display of all results and heatmaps) or after interpretation (verification of findings) of CXR images, and in accordance with the manufacturer's recommendations. Given this, a retrospective study is performed to test the clinical effectiveness on existing CXRs.

The performance of the trained and internally validated Carebot AI CXR software is tested on a set of 127 CXR images from target population. This is compared to common clinical practice, i.e., image assessment by a radiologist in a hospital. Patients may have a variety of findings; at this stage of the evaluation, an abnormal finding is considered to be an abnormality in any of the defined classes. False negative images incorrectly predicted by Carebot AI CXR software result in a clinical impact determination.

To collect the CXR data for retrospective study, investigators addressed a municipal hospital in the Czech Republic that provides healthcare services to up to 130,000 residents of a medium-sized city (approximately 70,000 inhabitants) and the surrounding area. 127 anonymized CXR images were collected between August 15 and 17, 2022, and subsequently submitted to five independent radiologists of varying experience for annotation. The selected radiologists were asked to assess whether the CXR image shows any of the 12 pre-selected abnormalities. Pediatric CXR images (under 18 years of age), scans with technical problems (poor image quality, rotation), and images in lateral projection were excluded from the dataset.

Retrospective Study of Carebot AI CXR Performance in Preclinical Practice

Chest X-Ray Abnormality Detection Using Artificial Intelligence: Retrospective Study of Carebot AI CXR Performance in Preclinical Practice

The results of the retrospective study are used to validate the Carebot AI CXR software for the target population prior to deployment in the workplace.

Comparison of the accuracy of radiologist and Carebot AI CXR image assessment.

Comparison of the accuracy of radiologis with different experience vs. Carebot AI CXR. Weakness assessment of Carebot AI CXR.

Carebot s.r.o.

Blood and Lymph Conditions

Immune System Diseases

Rare Diseases

Dyspnea

Acute Lung Injury

Lung Injury

Transfusion-Related Acute Lung Injury

Respiration Disorders

Signs and Symptoms, Respiratory

Acute Respiratory Distress Syndrome

Acute Graft Versus Host Disease

Idit Matot, MD

Yifat Klein, PhD

Shlomo Dadia, MD

Alex Gorodetsky, MD

Currently Transfusion-related acute lung injury (TRALI) is the leading cause of transfusion-related mortality in the United States, and one of major post-transfusion complications. TRALI is defined as new ALI occurring within 6 hours from the onset of transfusion. It is manifested by acute dyspnea, hypoxemia and bilateral infiltrates in chest radiograph. TRALI may be caused by any blood product and is not dose-dependent. Associated risk factors include prolonged storage of blood products and underlying conditions such as severe IHD hematologic malignancies or active infections. Since TRALI has only recently been defined as a clinical entity, and its prevalence has been largely underestimated - the epidemiology of TRALI is not well established. Therefore the objective of this work is to study the incidence of TRALI in a patient population that receive blood products frequently, namely orthopedic-oncologic.

Background

The transfusion of blood products is occasionally complicated by acute lung injury (ALI), which can progress to the acute respiratory distress syndrome (ARDS). Such transfusion-related acute lung injury, abbreviated TRALI, has been defined by both a National Heart, Lung, and Blood Institute (NHLBI) working group, and by a Canadian consensus conference (CCC), as new ALI occurring during or within six hours after a transfusion \[1-2\]. This definition is based entirely on clinical and radiological criteria and includes \[2-4\]:

1. ALI, as defined by \[4\]:

   A. The sudden onset of respiratory distress symptoms (dyspnea). B. Hypoxemia: as defined by a ratio of partial pressure of arterial oxygen to the fraction of inspired oxygen (PaO2/FiO2) below 300mmHg, or oxygen saturation (SpO2) below 90% on room air, or other clinical evidence of hypoxemia C. Bilateral infiltrates on frontal chest X-ray, without cardiomegaly. D. No clinical evidence of left atrial hypertension (congestive heart disease).
2. No preexisting ALI before transfusion.
3. During or within 6 hr after transfusion of any blood product.
4. No temporal relationship to an alternative risk factor for ALI. All types of blood products have been associated with TRALI, however, the plasma-rich components, such as fresh frozen plasma (FFP), whole blood, packed red blood cells (PC) and platelets, have been most frequently implicated \[3, 5-10\].

Prolonged storage of transfused products, use of FFP, and the presence of an underlying condition such as recent surgery, cytokine treatment, thrombocytopenia, massive blood transfusion, hematologic malignancies or cardiovascular disease requiring cardiopulmonary bypass (CABG) surgery, and active infection have been reported as risk factors for the development of TRALI \[11-18\].

The pathogenesis of TRALI involves the presence of anti-leukocyte antibodies and/or biologically active lipids from cell membrane fragments (and cytokines) in the donor's blood, triggering an inflammatory response within the recipient's pulmonary microvasculature, which in turn leads to lung injury \[2,13,16,19-27\].

The incidence of TRALI is not well established \[28\]. Nevertheless, using the NHLBI/CCC definition of TRALI, several retrospective studies reported the incidence of TRALI to be one case for every 1000-2400 units transfused \[29-30\]. This incidence estimate of 0.04% to 0.1% (or up to 0.85% among transfused patients) is comparable to other estimates from earlier studies that used older case definitions \[6,12,31\]. The only prospective cohort clinical surveillance study to use current diagnostic guidelines for TRALI reported an 8% incidence of TRALI in their intensive care unit (ICU) \[32\]. These data suggest that passive reporting systems greatly under-estimate the number of TRALI cases.

Even though underdiagnosed, TRALI is currently the leading cause of transfusion-related mortality in the United States \[1,7,11\]. The estimated mortality rate for recognized TRALI is 5%-8% \[20\]. However, most survivors recover completely with appropriate supportive care and can receive additional blood products in the future \[11,20\].

Due to the lacking epidemiology, and the increasing significance of TRALI as a major transfusion-associated complication, we stress the need for additional prospective surveillance studies.

Taken together, we wish to conduct a prospective observative study in order to evaluate the incidence of TRALI among patients undergoing elective orthopedic-oncology procedures. This patients' population receives blood product transfusions frequently, and may thus provide an adequate cohort for such study.

Study Objectives This work aims to study the prevalence of TRALI-associated morbidity and mortality in patients undergoing elective orthopedic-oncology procedures, and are transfused with blood products in the perioperative period.

In addition, we wish to evaluate whether:

A.The incidence of TRALI is higher in patients operated for malignancies (versus benign neoplasms) B.The incidence of TRALI is higher in patients treated with C.chemotherapy/radiation prior to surgery (versus non-treated) The incidence of TRALI is increasing with older blood products

Methods Study design An informed consent will be obtained from all orthopedic-oncology patients scheduled to have an elective surgery, except for those who require minor procedures (e.g., biopsies) which normally do not require transfusions. Diuretics and oral hypoglycemics will be discontinued the day prior to surgery, as dictated by the routines in our patients.

Peri-operative management Anesthetic and surgical management as well as blood product transfusion will adhere to standard practice.

Postoperatively, the patients will be transferred to the post-anaesthesia care unit and later to the orthopedic-oncology department, unless otherwise indicated.

In the postoperative period, departmental routines will guide blood product transfusions, pain management and fluid therapy.

Monitoring of patients who received transfusions

Every patient that receives blood products will be included in the study, whether it occurred pre-operatively, intra-operatively or post-operatively as long as they are hospitalized. For these patients we will document:

A.General demographics, including chronic diseases, medications and treatments (e.g., chemotherapy/radiotherapy).

B.Blood product information, including type, dosage and storage age. C.Intra- and post-operative data, including operative time, volume of crystalloids (and colloids) given during surgery and afterwards, urine output, the need for vasopressors, inotropes or diuretics, re-intubations, transfer to ICU and hospital length of stay (LOS).

For each unit of blood product transfused, we will commence patient monitoring for the next 6 hours. If several units are given in a sequel we will monitor the patient since the beginning of the first transfusion until 6 hours after the last transfusion. Monitoring will include:

1. Clinical symptoms of dyspnea.
2. PaO2/FiO2, or SpO2 on room air if arterial line is not obtainable - every 2 hours or when indicated by clinical signs.

   2.1. If PaO2/FiO2\< 300mmHg, or SpO2\< 90% on room air, or clinical signs of lung injury occur - chest X-ray will be obtained and diagnosed by two radiologists.
3. Hb (gr/dl) will be assessed according to the physician's decision.

Study size In the orthopedic-oncology department of Tel Aviv Sourasky Medical Center approximately 550 patients are operated annually, about 20% of whom receive transfusions. Accordingly, the study is planned for 5 years. Therefore the anticipated sample size is approximately 550 patients.

blood from arterial line to test for PaO2

The Incidence of TRALI in Patients Undergoing Orthopedic-Oncology Surgery

The Incidence of Transfusion-Related Acute Lung Injury (TRALI) Following Blood Product Transfusion in Patients Undergoing Elective Orthopedic-Oncology Procedures

Tel-Aviv Sourasky Medical Center

Prof Idit Matot

Digestive System Diseases

Stomach Neoplasms

Syndrome

Liver Diseases

Respiratory Distress Syndrome

Respiratory Distress Syndrome, Newborn

Pancreatic Diseases

Airway Obstruction

Gastrointestinal Diseases

Gastrointestinal Neoplasms

Digestive System Neoplasms

Stomach Diseases

Stomach Cancer

Respiratory Distress Syndrome, Infant

Hematinics

Liver Extracts

Marc Bodenstein

The purpose of this study is to determine whether Electrical Impedance Tomography can be used as sensitive and specific predictor in the detection of postoperative pulmonary complications (e.g. pneumonia, bronchitis, acute respiratory distress syndrome, pleural effusion, pneumothorax, pulmonary edema, atelectasis, pulmonary embolism, hypoxemia, hypercapnia, spasms and obstructions of the airway) in patients undergoing epigastric surgery.

* Study cycle:

  1. Check of criteria of inclusion/exclusion
  2. Informed consent
  3. Recording preoperative data via paper case report form
  4. Preoperative EIT measurement
  5. Postoperative EIT measurement
  6. Recording postoperative data via paper case report form

     Patients therapy and any diagnostic investigation during hospital stay (apart from EIT measurement) are performed appropriate to patients individual clinical needs and are independent from participation in this clinical trial. As PPC may result from surgical complications (e.g. intra- /postoperative bleeding, anastomotic leak, infection of the wound, injury of neighboring organs) they are monitored.
* Statistical analysis:

Sample size:

After consultation of Johannes-Gutenberg-University Institute of Medical Biometry and Epidemiology the following procedure was developed: Pre-analysis with 20 patients, then determination of definitive sample size (advised 80 patients).

Population:

Any registered patient is included in population even if no study-treatment was performed. To fulfill Pre-Protocol-Population-criteria EIT-measurement has to be performed before and after elective epigastric surgery and information about PPC must be revealable from patients medical file/records.

* Analysis of efficacy:

  1. Primary objective:

     (A) Incidence of any PPC (postoperative pulmonary complication) until postoperative day 7; Acquisition of PPC might require diagnostic investigation during hospital stay; investigations are only performed appropriate to patients individual clinical needs. As PPC are defined:
     * I: desaturation, increased oxygen demand (data from electronic health record)
     * II: dys-/atelectasis, pleural effusion, pneumothorax, pulmonary vein congestion (data from thoracic x-ray)
     * III: detected respiratory infection/pneumonia, pulmonary edema, Aspiration, non-invasive/CPAP-Ventilation, necessity of pleural drain/of bronchoscopy (data from electronic health record, x-ray)
     * IV: Reintubation (data from electronic health record), ARDS (according to Berlin Definition)

     (B) regional Distribution of Ventilation (Analysis of EIT raw data pre- and postoperative in 4 regions of interest: ventral, mid-ventral, mid-dorsal, dorsal; correlation between PPC and difference in regional Distribution of Ventilation at defined moment)
  2. Secondary objective: post-hoc Analysis (see down Secondary Outcome Measure)

     Average, Median, Quartile, Standard Deviation are detected and shown in Box-plots (type of graphic). Explorative comparison of parameters is effected by t-Test, Mann-Whitney-U-Test, Fisher-Test dependent on normal distribution.
* Quality assurance and data management Design, execution and analyzation of the study is ICH-GCP-conform (Good-Clinical-Practice-Guideline of the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use). All responsible persons are obliged to good clinical practice. All changes in study protocol are to be authorized by responsible Ethics Committee. The P.I. is responsible for source data verification to assess the accuracy, completeness, or representativeness of registry data by comparing the data to external data sources (e.g., medical records, paper or electronic case report forms).

Prior to written informed consent all patients are to be informed about character and consequences of the study. With their signature patients permit collection and use of source data. Every patient receives an Identification code for pseudonymization of data. Analyzation and publication of data is effected anonymously only. Data collection is mainly provided in an electronic data base, besides in a paper-based Case Report Form. All electronic and paper-based data and archived in our Clinical Research Center and are accessible for authorized persons (Monitor, Auditor). The study protocol does not provide audits.

Amendment after Pre-analysis:

We conducted a preliminary study of 23 patients for sample size calculation, aligned with the goal of predicting probability of relevant PPC. Power calculation was based on the assumption that 50 % of patients would develop relevant PPC. We performed a power analysis using the Wilcoxon test. The assumption was that AUC of EIT-parameters for distinguishing PPC-affected patients from non-affected patients would be at least 0.65. In order to demonstrate that AUC is indeed above 0.5, a Wilcoxon test can be applied. AUC=0.65 translates into P(X\<Y)=0.65. To demonstrate this at the 5%-significance level with a power of 80%, 116 patients are needed. Considering that approximately 10% of patients may not be evaluable, a total sample size of 130 patients was determined. Interim analysis revealed, that incidence of relevant PPC in the study cohort was lower than assumed in sample size calculation. Therefore a higher sample size was necessary than expected. Furthermore, recruiting was slow. We therefore switched from a confirmatory to a descriptive approach.

Screening of Postoperative Pulmonary Complications by Electrical Impedance Tomography

Screening of Postoperative Pulmonary Complications by Electrical Impedance Tomography in Intensive Care Patients Undergoing Epigastric Surgery

Comparison of the changed regional ventilation partition to the occurence of postoperative pulmonary complications =\> calculation of sensitivity and specifity of the primary outcome measure to predict PPC. Statistical analysis: receiver operating characteristic (ROC curve).

Sensitivity and specifiy for appearance of PPC (Postoperative Pulmonary Complications) within Postoperative Day 1-7.

Statistical analysis: Sensitivity, Specificity, ROC-curve

Correlation of pre-existing pathologic pulmonary conditions with specific postoperative changes in regional distribution of lung ventilation and perfusion assessed by EIT Statistical analysis: Sensitivity, Specificity, ROC-curve

Appearance of all different forms of PPC within Postoperative Day 1-7 and relation to postoperative EIT-measure (ROI analysis in 8 pulmonary ROIs).

Statistical analysis: Sensitivity, Specificity, ROC-curve

Sensitivity and specifity of postoperative EIT-measure for mortality. Statistical analysis: Sensitivity, Specificity, ROC-curve

Sensitivity and specifity of postoperative EIT-measure for time of intensive care therapy.

Statistical analysis: Sensitivity, Specificity, ROC-curve

Sensitivity and specifity of postoperative EIT-measure for Ventilator-obligatory-free days.

Statistical analysis: Sensitivity, Specificity, ROC-curve

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Retrospective Study of Carebot AI CXR Performance in Preclinical Practice	NCT05594485	Artificial Inte... Lung Diseases Pneumothorax Pleural Effusio... Cardiomegaly Lung Cancer Pulmonary Edema Consolidation Pneumonia Atelectasis Hilar Calcifica... Fracture Rib	Carebot AI CXR	18 Years -	Carebot s.r.o.
The Incidence of TRALI in Patients Undergoing Orthopedic-Oncology Surgery	NCT00914784	Dyspnea Pulmonary Edema		18 Years - 90 Years	Tel-Aviv Sourasky Medical Center
Screening of Postoperative Pulmonary Complications by Electrical Impedance Tomography	NCT02337673	Pulmonary Disea... Postoperative R... Malignant Neopl... Liver Diseases Pancreatic Dise...		18 Years -	Johannes Gutenberg University Mainz

Spots Global Cancer Trial Database for pulmonary edema