Using Artificial Intelligence to Predict Mechanical Ventilation Weaning Success in Patients with Respiratory Failure, Including Those with Acute Respiratory Distress Syndrome.

The management of mechanical ventilation (MV) remains a challenge in intensive care units (ICUs). The digitalization of healthcare and the implementation of artificial intelligence (AI) and machine learning (ML) has significantly influenced medical decision-making capabilities, potentially enhancing patient outcomes. Acute respiratory distress syndrome, an overwhelming inflammatory lung disease, is common in ICUs. Most patients require MV. Prolonged MV is associated with an increased length of stay, morbidity, and mortality. Shortening the MV duration has both clinical and economic benefits and emphasizes the need for better MV weaning management. AI and ML models can assist the physician in weaning patients from MV by providing predictive tools based on big data. Many ML models have been developed in recent years, dealing with this unmet need. Such models provide an important prediction regarding the success of the individual patient's MV weaning. Some AI models have shown a notable impact on clinical outcomes. However, there are challenges in integrating AI models into clinical practice due to the unfamiliar nature of AI for many physicians and the complexity of some AI models. Our review explores the evolution of weaning methods up to and including AI and ML as weaning aids.

Breath of Health: spectroscopy-based breath test for the detection of SARS-CoV-2.

BACKGROUND: Nucleic acid amplification tests (NAAT) are considered the gold standard for COVID-19 diagnosis. These tests require professional manpower and equipment, long processing and swab sampling which is unpleasant to the patients. Several volatile organic compounds (VOCs) have been identified in the breath of COVID-19 patients. Detection of these VOCs using a breath test could help rapidly identify COVID-19 patients. OBJECTIVE: Assess the accuracy of 'Breath of Health' (BOH) COVID-19 Fourier-transform infra-red (FTIR) Spectroscopy-based breath test. METHODS: Breath samples from patients with or without symptoms suggestive for COVID-19 who had NAAT results were collected using Tedlar bags and were blindly analysed using BOH FTIR spectroscopy. BOH Measures several VOCs simultaneously and differentiating positive and negative results. BOH results were compared to NAAT results as gold standard. RESULTS: Breath samples from 531 patients were analysed. The sensitivity of BOH breath test was found to be 79.5% and specificity was 87.2%. Positive predictive value (PPV) was 74.7% and negative predictive value (NPV) 90.0%. Calculated accuracy rate was 84.8% and area under the curve 0.834. Subgroup analysis revealed that the NPV of patients without respiratory symptoms was superior over the NPV of symptomatic patients (94.7% vs 80.7%, P-value < 0.0001) and PPV of patients with respiratory symptoms outranks the PPV of individuals without symptoms (85.3% vs 69.2%, P-value 0.0196). CONCLUSION: We found BOH COVID-19 breath test to be a patient-friendly, rapid, non-invasive diagnostic test with high accuracy rate and NPV that could efficiently rule out COVID-19 especially among individuals with low pre-test probability.

Residual symptoms, lung function, and imaging findings in patients recovering from SARS-CoV-2 infection.

Symptoms following acute COVID-19 infection are common, but their relationship to initial COVID-19 severity is unclear. We hypothesize that residual symptoms are related to disease severity, and severe acute COVID-19 infection is more likely to cause residual pulmonary damage. This study aims to evaluate symptoms, lung function, and abnormal imaging within 3 months following COVID-19 infection, and to determine whether they are related to initial disease severity. A cross-sectional study was carried out at a designated post-COVID clinic in Hadassah Medical Center, Jerusalem, Israel. Patients with PCR-confirmed SARS-CoV-2 infection were evaluated within 12 weeks following infection and included both admitted and non-admitted subjects. All study participants underwent assessment of symptoms, quality of life (SGRQ), pulmonary function tests, and imaging. A total of 208 patients (age 49.3 ± 16 years) were included in the study. Initial disease severity was mild in 86, moderate in 49, and severe in 73 patients. At the time of follow-up, there were no differences in frequency of residual symptoms or in SGRQ score between groups. Patients with severe COVID-19 were more likely to have residual dyspnea (p = 0.04), lower oxygen saturation (p < 0.01), lower FVC and TLC (p < 0.001, p = 0.03 respectively), abnormal CXR (p < 0.01), and abnormal CT scan (p < 0.01) compared to other groups.Frequency of symptoms and impairment of quality of life at 12 week follow-up are common and are not related to severity of initial COVID-19 disease. In contrast, reduced lung function and abnormal pulmonary imaging are more common in patients with more severe acute COVID-19 infection.

Intramuscular mRNA BNT162b2 vaccine against SARS-CoV-2 induces neutralizing salivary IgA.

Intramuscularly administered vaccines stimulate robust serum neutralizing antibodies, yet they are often less competent in eliciting sustainable "sterilizing immunity" at the mucosal level. Our study uncovers a strong temporary neutralizing mucosal component of immunity, emanating from intramuscular administration of an mRNA vaccine. We show that saliva of BNT162b2 vaccinees contains temporary IgA targeting the receptor-binding domain (RBD) of severe acute respiratory syndrome coronavirus-2 spike protein and demonstrate that these IgAs mediate neutralization. RBD-targeting IgAs were found to associate with the secretory component, indicating their bona fide transcytotic origin and their polymeric multivalent nature. The mechanistic understanding of the high neutralizing activity provided by mucosal IgA, acting at the first line of defense, will advance vaccination design and surveillance principles and may point to novel treatment approaches and new routes of vaccine administration and boosting.

Operative treatment of hepatic hydatid cysts: A single center experience.

BACKGROUND: Hydatid cyst is a zoonotic disease caused by Echinococcus genera. Surgery is needed in most cases. We aimed to describe our center's experience in the surgical management of hepatic hydated cysts (HHC). METHODS: Data was retrospectively collected for patients who underwent operative management for HHC between the years 1994-2014. RESULTS: Sixty-nine underwent surgical treatment for HHC. Group A included 34 treated with an unroofing procedure, group B included 24 patients who underwent hepatectomy and group C included 11 patients who underwent peri-cystectomy. The median ± (range) age for groups A, B and C were 39.5 (6.5-69), 40 (17-74) and 32 (20-62), respectively (P > 0.1). Post-operative complications occurred in 16, 11 and 5 patients in group A, B and C, respectively, as assessed by clavien-dindo classification (CDC). The average CDC was significantly higher in the hepatectomy group as compared to the unroofing group (2.3 vs.1.5, P = 0.04). Recurrence was significantly higher after the unroofing procedure as compared to the hepatectomy group (P = 0.05). CONCLUSION: Surgery remains the mainstay of treatment for HHC, once surgery is pursued, the results are satisfactory.

Catheter-associated candiduria: Risk factors, medical interventions, and antifungal susceptibility.

BACKGROUND: Catheter-associated candiduria is a common clinical finding in hospitalized patients, especially in the intensive care unit. The objective of this study was to obtain demographic and clinical data regarding the prevalence of Candida spp in catheterized in-patients and the medical interventions provided to these patients in a northern Israeli hospital between 2011 and 2013. METHODS: Isolation and identification of microorganisms were performed on 1,408 urine culture samples 48 hours after catheter insertion. Antifungal Etest susceptibility tests were carried out on every Candida-positive urine sample. Demographic and clinical data were gathered to determine risk factors and medical interventions. RESULTS: Candiduria was detected in 146 catheterized in-patients out of the 1,408 patients included in this study. C albicans was detected in most cases (69.1%). Fever was observed in 52 (35.61%) patients, and leukocyturia was observed in 48 cases (32.87%). Diabetes mellitus was associated with C albicans candiduria. There were 93 patients (63.69%) who did not receive any medical intervention for their candiduria. CONCLUSION: Candida is the second leading pathogen causing catheter-associated urinary tract infection or asymptomatic colonization, whereas previous studies showed Candida as the third leading pathogen. Clinical signs and symptoms, such as fever and laboratory tests, cannot distinguish between asymptomatic colonization and infection. Because the management of catheter-associated candiduria is still controversial, additional studies should be carried out.