Israel Medical Association Journal

Despite recent advances in the pharmacological and endoscopic treatments for obesity, bariatric surgery is still considered one of the most effective and safe treatments for morbid obesity with over 250,000 bariatric procedures performed each year in the United States. While these procedures are considered safe, they are not free of complications. It has been reported that the primary short-term major complication after Roux-en-Y gastric bypass (RYGB), one-anastomosis (Mini) gastric bypass (OAGB), or sleeve gastrectomy (SG) is gastrointestinal leakage, with a reported leak rate of 0.1–8.3%, 0–5.1%, and 0–7%, respectively [1,2]. While the etiology of gastrointestinal leakage following bariatric procedure is multifactorial, including preoperative, intraoperative, and postoperative factors, a single factor can rarely be attributed to this misfortunate complication. We describe a case of a 30-year-old woman who presented on postoperative day (POD) 10 of a OAGB with a gastrointestinal leakage after treated with a high dose of oral misoprostol.

Takotsubo syndrome (TTS) or Takotsubo cardiomyopathy (TCM) is a cardiomyopathy that develops rapidly and is usually caused by mental or physical stress. It is usually a transient cardiomyopathy. The presumed cause of the onset of the syndrome is the increase and extreme secretion of adrenaline and norepinephrine due to extreme stress. An infectious disease such as sepsis can also be the cause [1].

One of the most widespread diagnostic tools is the revised version of Mayo Clinic Diagnostic Criteria for TTS (2008) [2], which incorporates transient wall-motion abnormalities, absence of a potential coronary culprit, myocarditis, and pheochromocytoma. The prognosis for TTS is usually favorable and resolves with complete recovery in 4–8 weeks in more than 90% of patients.

Since 1980 dermatologists have been interested in the exceptional healing reported by patients who underwent treatments at the Dead Sea. Tens of thousands of patients have visited this area and more than 10,000 cases have been the subject of clinical and laboratory studies since this natural therapeutic option was discovered for psoriasis management. Through evaluation of the published articles on climatotherapy, we tried to reach a global assessment of the usefulness of this approach and to discover whether this treatment still can be recommended in the era of biologic treatments. I conducted a review of the available literature on clinical trials through PubMed, Medline, and Google Scholar using the terms psoriasis and Dead Sea. I found 26 studies published between 1982 and 2021. Assessment of patients showed major improvement through several selected parameters. Length of the stay and medical supervision positively influenced the major outcomes observed. Duration of improvement and possible long-term side effects of this natural treatment still need to be more precisely determined. Exposure to the unique climatic factors of the region, essentially the sun and the sea, induces fast and significant results with high clearance rates of psoriasis plaques. Dead Sea climatotherapy still has its place for the control of psoriasis symptoms.

A 69-year-old woman with a 30-year history of rheumatoid arthritis (RA) on leflunomide presented with dizziness and weakness. Vital signs, cardiopulmonary auscultation, and laboratory studies were normal. The serological status of her RA was unknown. She exhibited ulnar deviation and swan-necking of the hands but no nodular skin lesions. She was an active smoker. Chest radiography revealed an opacity in the right lung. Computed tomography (CT) showed multiple pulmonary nodules and a dominant thick-walled cavitary mass in the periphery of the right lower lobe [Figure 1A]. Due to concern for a malignancy or infection, she underwent a bronchoscopy with a biopsy of the mass, which was non-diagnostic. A subsequent transthoracic needle biopsy demonstrated a central zone of necrosis surrounded by a cuff of palisading epithelioid histiocytes with the presence of occasional giant cells [Figure 1B]. There was no malignancy, and stains for micro-organisms were negative. In this clinical context, biopsy results were consistent with a pulmonary rheumatoid nodule (PRN).

In this special issue of Israel Medical Association Journal (IMAJ) we expose readers to the topic of artificial intelligence (AI) in medicine. AI has become a powerful tool, which enables healthcare professionals to personalize treatment based on many factors, including genetic analyses of tumors, and to consider other co-morbidities affecting a specific patient. AI gives physicians the ability to analyze huge amounts of data and to combine data from different sources. AI can be implemented make a diagnosis based on computed tomography (CT) scans and magnetic resonance imaging (MRI) scans using deep machine learning and data that are stored in the memory of mega computers. AI assists in tailoring more precise surgery to train surgeons before surgery and to support surgeons during procedures. This advancement may benefit surgical procedures by making them more accurate and faster without cutting unnecessary tissues (e.g., nerves and blood vessels); thus, patients face fewer complications, lower rates of infection, and more operation theater time. In this issue, we include three original studies that describe the use of AI in academia and eight review articles that discuss applications of AI in different specialties in medicine. One of the review articles addresses ethical issues and concerns that are raised due to the more advanced use of AI in medicine.

Background: Completing internal medicine specialty training in Israel involves passing the Israel National Internal Medicine Exam (Shlav Aleph), a challenging multiple-choice test. multiple-choice test. Chat generative pre-trained transformer (ChatGPT) 3.5, a language model, is increasingly used for exam preparation.

Objectives: To assess the ability of ChatGPT 3.5 to pass the Israel National Internal Medicine Exam in Hebrew.

Methods: Using the 2023 Shlav Aleph exam questions, ChatGPT received prompts in Hebrew. Textual questions were analyzed after the appeal, comparing its answers to the official key.

Results: ChatGPT 3.5 correctly answered 36.6% of the 133 analyzed questions, with consistent performance across topics, except for challenges in nephrology and biostatistics.

Conclusions: While ChatGPT 3.5 has excelled in English medical exams, its performance in the Hebrew Shlav Aleph was suboptimal. Factors include limited training data in Hebrew, translation complexities, and unique language structures. Further investigation is essential for its effective adaptation to Hebrew medical exam preparation.

In the grand theater of modern medicine, artificial intelligence (AI) has swiped the lead role, with a performance so riveting it deserves an Oscar, or at least a Nobel. From the intricate labyrinths of our arteries to the profound depths of our peepers, AI is the new maestro, conducting symphonies of data with the finesse of a seasoned virtuoso [1,2].

Artificial intelligence (AI) has emerged as a powerful technology in medicine, with a potential to revolutionize various aspects of disease management. In recent years, substantial progress has been made in the development and implementation of AI algorithms and models for the diagnosis, screening, and monitoring of retinal diseases. We present a brief update on recent advancements in the implementation of AI in the field of retinal medicine, with a focus on age-related macular degeneration, diabetic retinopathy, and retinopathy of prematurity. AI algorithms have demonstrated remarkable capabilities in automating image analysis tasks, thus enabling accurate segmentation and classification of retinal pathologies. AI-based screening programs hold great promise in cost-effective identification of individuals at risk, thereby facilitating early intervention and prevention. Future integration of multimodal imaging data including optical coherence tomography with additional clinical parameters, will further enhance the diagnostic accuracy and support the development of personalized medicine, thus aiding in treatment selection and optimizing therapeutic outcomes. Further research and collaboration will drive the transformation of AI into an indispensable tool for improving patient outcomes and enhancing the field of retinal medicine.

A rise in the incidence of chronic health conditions, notably heart failure, is expected due to demographic shifts. Such an increase places an onerous burden on healthcare infrastructures, with recurring hospital admissions and heightened mortality rates being prominent factors. Efficient chronic disease management hinges on regular ambulatory care and preemptive action. The application of intelligent computational models is showing promise as a key resource in the ongoing management of chronic diseases, particularly in forecasting disease trajectory and informing timely interventions. In this review, we explored a pioneering intelligent computational model by Diagnostic Robotics, an Israeli start-up company. This model uses data sourced from insurance claims to forecast the progression of heart failure. The goal of the model is to identify individuals at increased risk for heart failure, thus enabling interventions to be initiated early, mitigating the risk of disease worsening, and relieving the pressure on healthcare facilities, which will result in economic efficiencies.

Over the last decade the use of artificial intelligence (AI) has reformed academic research. While clinical diagnosis of psoriasis and psoriatic arthritis is largely straightforward, the determining factors of a clinical response to therapy, and specifically to biologic agents, have not yet been found. AI may meaningfully impact attempts to unravel the prognostic factors that affect response to therapy, assist experimental techniques being used to investigate immune cell populations, examine whether these populations are associated with treatment responses, and incorporate immunophenotype data in prediction models. The aim of this mini review was to present the current state of the AI-mediated attempts in the field. We executed a Medline search in October 2023. Selection and presentation of studies were conducted following the principles of a narrative–review design. We present data regarding the impact AI can have on the management of psoriatic disease by predicting responses utilizing clinical or biological parameters. We also reviewed the ways AI has been implemented to assist development of models that revolutionize the investigation of peripheral immune cell subsets that can be used as biomarkers of response to biologic treatment. Last, we discussed future perspectives and ethical considerations regarding the use of machine learning models in the management of immune-mediated diseases.

Medical imaging data has been at the frontier of artificial intelligence innovation in medicine with many clinical applications. There have been many challenges, including patient data protection, algorithm performance, radiology workflow, user interface, and IT integration, which have been addressed and mitigated over the last decade. The AI products in imaging now fall into three main categories: triage artificial intelligence (AI), productivity AI, and augmented AI, each providing a different utility for radiologists, clinicians, and patients. Adoption of AI products into the healthcare system has been slow, but it is growing. It is typically dictated by return on investment, which can be demonstrated in each use case. It is expected to lead to wider adoption of AI products in imaging into the clinical workflow in the future.

In recent years, we have been experiencing a technological revolution, which signifies an ethical and societal transformation. Artificial intelligence (AI) based technologies have gradually permeated all aspects of life and solidified their position. Within this context, the emergence of these technologies offers new opportunities in the medical field, including palliative care, which is aimed at alleviating suffering and improving the quality of life for terminally ill patients and their families. In Israel, the Dying Patient Act of 2005 (the law), which promotes values such as the sanctity of life and individual autonomy, allows terminally ill patients to determine their preferred treatment, and withhold life-saving treatment under certain circumstances. The law represents a significant step toward improving care for terminally ill patients, reducing pain and suffering, and respecting the patient's wishes and worldviews in their final days. However, the practical implementation of the law has encountered numerous challenges, ranging from lack of familiarity among doctors and healthcare professionals and the requirement to determining life expectancy to fulfilling the law's purpose. These challenges are associated with ethical, cultural, and religious perspectives. In this article, we describe how AI-based technologies hold immense potential in applying the law and providing palliative care based on their predictive capabilities, prognostic accuracy, and optimization of treatment as well as communication between patients and healthcare providers. However, as an innovative, developing, and complex technology, it is crucial not to overlook the ethical, societal, and legal challenges inherent in implementing and using AI-based technologies in the context of palliative care.

Background: The use of proprotein convertase subtilisin/kexin type 9 monoclonal antibodies (PCSK9 mAbs) is emerging for lowering low-density lipoprotein cholesterol (LDL-C). However, real-world data is lacking for their use among elderly patients.

Objective: To define the characteristics of elderly patients treated with PCSK9 mAbs and to evaluate the efficacy and tolerability compared with younger patients.

Methods: We conducted a retrospective cohort study of elderly patients (≥ 75 years at enrollment) treated with PCSK9 mAbs for primary and secondary cardiovascular prevention. Data were retrieved for demographic and clinical characteristics; indications for treatment; agents and dosages; concomitant lipid lowering treatment; LDL-C levels at baseline, 6, 12 months, and at the end of follow up. Data also included achieving LDL-C target levels and adverse effects.

Results: The cohort included 91 elderly patients and 92 younger patients, mean age 75.2 ± 3.76 and 58.9 ± 7.4 years (P < 0.0001). Most patients (82%, 80%) were in high/very high-risk categories. For almost all (98%, 99%), the indication was statin intolerance, with PCSK9 mAb monotherapy the most prevalent regimen. The average follow-up was 38.1 ± 20.5 and 30.9 ± 15.8 months (P = 0.0258). Within 6 months the LDL-C levels were reduced by 57% in the elderly group and by 59% in the control group (P = 0.2371). Only 53% and 57% reached their LDL-C target levels. No clinically significant side effects were documented.

Conclusion: PCSK9 mAbs have similar effects and are well tolerated among elderly patients as in younger patients.

To the reviewers of 2023, who gave of their time to constructively assess the articles sent to them.

Twenty-five years ago, we, the undersigned together with the chairman of the Israel Medical Association at the time, Prof. Yoram Blachar, and the Secretary General of the Israel Medical Association, Adv. Leah Wapner, joined forces to found an Israeli medical journal in English. The purpose of this journal was to present to the world Israeli clinical medicine and medical research. That journal is none other than the Israel Medical Association Journal (IMAJ), and in 2023 its 300th issue was published. In 2024 we keep going, taking pride in the fact that every one of those past 300 issues has been published and dispatched on time, without delay, regardless of any circumstances.