Neuraxial Anesthesia for Combined Left Nephrectomy and Left Hemicolectomy in a One-Lung Patient.

Monopulmonary patients undergoing major abdominal surgery represent a high-risk population. While general anesthesia is typically the standard approach, mechanical ventilation can cause significant complications, particularly in patients with pre-existing lung conditions. Tailored anesthesia strategies are essential to mitigate these risks and preserve respiratory function. We present the case of a 71-year-old female with a history of prior right pneumonectomy for lung cancer. She was scheduled for combined left nephrectomy and left hemicolectomy laparotomic surgery because of extended colon cancer. The patient was prepared according to the local Enhanced Recovery After Surgery (ERAS) protocol and underwent thoracic neuraxial anesthesia with sedation maintaining spontaneous breathing, so avoiding general anesthesia and mechanical ventilation. Anesthesia in the surgical field was effective, and no respiratory problems occurred intraoperatively. The patient's rapid recovery and early discharge underscore the success of our "tailored anesthesia strategy." Our experience highlights the feasibility and benefits of tailored anesthesia in monopulmonary patients undergoing major abdominal surgery. By avoiding general anesthesia and mechanical ventilation, we mitigated risks and optimized patient outcomes, emphasizing the importance of individualized approaches in high-risk surgical populations.

Perceptive SARS-CoV-2 End-To-End Ultrasound Video Classification through X3D and Key-Frames Selection.

The SARS-CoV-2 pandemic challenged health systems worldwide, thus advocating for practical, quick and highly trustworthy diagnostic instruments to help medical personnel. It features a long incubation period and a high contagion rate, causing bilateral multi-focal interstitial pneumonia, generally growing into acute respiratory distress syndrome (ARDS), causing hundreds of thousands of casualties worldwide. Guidelines for first-line diagnosis of pneumonia suggest Chest X-rays (CXR) for patients exhibiting symptoms. Potential alternatives include Computed Tomography (CT) scans and Lung UltraSound (LUS). Deep learning (DL) has been helpful in diagnosis using CT scans, LUS, and CXR, whereby the former commonly yields more precise results. CXR and CT scans present several drawbacks, including high costs. Radiation-free LUS imaging requires high expertise, and physicians thus underutilise it. LUS demonstrated a strong correlation with CT scans and reliability in pneumonia detection, even in the early stages. Here, we present an LUS video-classification approach based on contemporary DL strategies in close collaboration with Fondazione IRCCS Policlinico San Matteo's Emergency Department (ED) of Pavia. This research addressed SARS-CoV-2 patterns detection, ranked according to three severity scales by operating a trustworthy dataset comprising ultrasounds from linear and convex probes in 5400 clips from 450 hospitalised subjects. The main contributions of this study are related to the adoption of a standardised severity ranking scale to evaluate pneumonia. This evaluation relies on video summarisation through key-frame selection algorithms. Then, we designed and developed a video-classification architecture which emerged as the most promising. In contrast, the literature primarily concentrates on frame-pattern recognition. By using advanced techniques such as transfer learning and data augmentation, we were able to achieve an F1-Score of over 89% across all classes.

The Role of Lung Ultrasound in Low-Resource Settings During the Coronavirus (SARS-CoV-2) Pandemic.

Lung ultrasound (LUS) has proven to be a helpful diagnostic tool for evaluating lung involvement in respiratory pathologies. The usage of this imaging technique became even more widespread during the SARS-CoV-2 pandemic. The latest generation ultrasound scanners are conveniently portable and this permits ultrasound examinations to be performed even in extreme environments where no other diagnostic tool is available. Our team has developed the first guide that assists the clinician while operating in low-resource settings, in managing a SARS-CoV-2 patient based on the clinical examination and the LUS findings.

Deep learning and lung ultrasound for Covid-19 pneumonia detection and severity classification.

The Covid-19 European outbreak in February 2020 has challenged the world's health systems, eliciting an urgent need for effective and highly reliable diagnostic instruments to help medical personnel. Deep learning (DL) has been demonstrated to be useful for diagnosis using both computed tomography (CT) scans and chest X-rays (CXR), whereby the former typically yields more accurate results. However, the pivoting function of a CT scan during the pandemic presents several drawbacks, including high cost and cross-contamination problems. Radiation-free lung ultrasound (LUS) imaging, which requires high expertise and is thus being underutilised, has demonstrated a strong correlation with CT scan results and a high reliability in pneumonia detection even in the early stages. In this study, we developed a system based on modern DL methodologies in close collaboration with Fondazione IRCCS Policlinico San Matteo's Emergency Department (ED) of Pavia. Using a reliable dataset comprising ultrasound clips originating from linear and convex probes in 2908 frames from 450 hospitalised patients, we conducted an investigation into detecting Covid-19 patterns and ranking them considering two severity scales. This study differs from other research projects by its novel approach involving four and seven classes. Patients admitted to the ED underwent 12 LUS examinations in different chest parts, each evaluated according to standardised severity scales. We adopted residual convolutional neural networks (CNNs), transfer learning, and data augmentation techniques. Hence, employing methodological hyperparameter tuning, we produced state-of-the-art results meeting F1 score levels, averaged over the number of classes considered, exceeding 98%, and thereby manifesting stable measurements over precision and recall.

Can Alveolar-Arterial Difference and Lung Ultrasound Help the Clinical Decision Making in Patients with COVID-19?

BACKGROUND: COVID-19 is an emerging infectious disease, that is heavily challenging health systems worldwide. Admission Arterial Blood Gas (ABG) and Lung Ultrasound (LUS) can be of great help in clinical decision making, especially during the current pandemic and the consequent overcrowding of the Emergency Department (ED). The aim of the study was to demonstrate the capability of alveolar-to-arterial oxygen difference (AaDO2) in predicting the need for subsequent oxygen support and survival in patients with COVID-19 infection, especially in the presence of baseline normal PaO2/FiO2 ratio (P/F) values. METHODS: A cohort of 223 swab-confirmed COVID-19 patients underwent clinical evaluation, blood tests, ABG and LUS in the ED. LUS score was derived from 12 ultrasound lung windows. AaDO2 was derived as AaDO2 = ((FiO2) (Atmospheric pressure - H2O pressure) - (PaCO2/R)) - PaO2. Endpoints were subsequent oxygen support need and survival. RESULTS: A close relationship between AaDO2 and P/F and between AaDO2 and LUS score was observed (R2 = 0.88 and R2 = 0.67, respectively; p < 0.001 for both). In the subgroup of patients with P/F between 300 and 400, 94.7% (n = 107) had high AaDO2 values, and 51.4% (n = 55) received oxygen support, with 2 ICU admissions and 10 deaths. According to ROC analysis, AaDO2 > 39.4 had 83.6% sensitivity and 90.5% specificity (AUC 0.936; p < 0.001) in predicting subsequent oxygen support, whereas a LUS score > 6 showed 89.7% sensitivity and 75.0% specificity (AUC 0.896; p < 0.001). Kaplan-Meier curves showed different mortality in the AaDO2 subgroups (p = 0.0025). CONCLUSIONS: LUS and AaDO2 are easy and effective tools, which allow bedside risk stratification in patients with COVID-19, especially when P/F values, signs, and symptoms are not indicative of severe lung dysfunction.

Lung ultrasound presentation of COVID-19 patients: phenotypes and correlations.

Bedside lung ultrasound (LUS) can play a role in the setting of the SarsCoV2 pneumonia pandemic. To evaluate the clinical and LUS features of COVID-19 in the ED and their potential prognostic role, a cohort of laboratory-confirmed COVID-19 patients underwent LUS upon admission in the ED. LUS score was derived from 12 fields. A prevalent LUS pattern was assigned depending on the presence of interstitial syndrome only (Interstitial Pattern), or evidence of subpleural consolidations in at least two fields (Consolidation Pattern). The endpoint was 30-day mortality. The relationship between hemogasanalysis parameters and LUS score was also evaluated. Out of 312 patients, only 36 (11.5%) did not present lung involvment, as defined by LUS score < 1. The majority of patients were admitted either in a general ward (53.8%) or in intensive care unit (9.6%), whereas 106 patients (33.9%) were discharged from the ED. In-hospital mortality was 25.3%, and 30-day survival was 67.6%. A LUS score > 13 had a 77.2% sensitivity and a 71.5% specificity (AUC 0.814; p < 0.001) in predicting mortality. LUS alterations were more frequent (64%) in the posterior lower fields. LUS score was related with P/F (R2 0.68; p < 0.0001) and P/F at FiO2 = 21% (R2 0.59; p < 0.0001). The correlation between LUS score and P/F was not influenced by the prevalent ultrasound pattern. LUS represents an effective tool in both defining diagnosis and stratifying prognosis of COVID-19 pneumonia. The correlation between LUS and hemogasanalysis parameters underscores its role in evaluating lung structure and function.

Lung ultrasound for the early diagnosis of COVID-19 pneumonia: an international multicenter study.

PURPOSE: To analyze the application of a lung ultrasound (LUS)-based diagnostic approach to patients suspected of COVID-19, combining the LUS likelihood of COVID-19 pneumonia with patient's symptoms and clinical history. METHODS: This is an international multicenter observational study in 20 US and European hospitals. Patients suspected of COVID-19 were tested with reverse transcription-polymerase chain reaction (RT-PCR) swab test and had an LUS examination. We identified three clinical phenotypes based on pre-existing chronic diseases (mixed phenotype), and on the presence (severe phenotype) or absence (mild phenotype) of signs and/or symptoms of respiratory failure at presentation. We defined the LUS likelihood of COVID-19 pneumonia according to four different patterns: high (HighLUS), intermediate (IntLUS), alternative (AltLUS), and low (LowLUS) probability. The combination of patterns and phenotypes with RT-PCR results was described and analyzed. RESULTS: We studied 1462 patients, classified in mild (n = 400), severe (n = 727), and mixed (n = 335) phenotypes. HighLUS and IntLUS showed an overall sensitivity of 90.2% (95% CI 88.23-91.97%) in identifying patients with positive RT-PCR, with higher values in the mixed (94.7%) and severe phenotype (97.1%), and even higher in those patients with objective respiratory failure (99.3%). The HighLUS showed a specificity of 88.8% (CI 85.55-91.65%) that was higher in the mild phenotype (94.4%; CI 90.0-97.0%). At multivariate analysis, the HighLUS was a strong independent predictor of RT-PCR positivity (odds ratio 4.2, confidence interval 2.6-6.7, p < 0.0001). CONCLUSION: Combining LUS patterns of probability with clinical phenotypes at presentation can rapidly identify those patients with or without COVID-19 pneumonia at bedside. This approach could support and expedite patients' management during a pandemic surge.

Age-related tilt test responses in patients with suspected reflex syncope.

AIMS: Tilt testing (TT) is recognized to be a valuable contribution to the diagnosis and the pathophysiology of vasovagal syncope (VVS). This study aimed to assess the influence of age on TT responses by examination of a large patient cohort. METHODS AND RESULTS: Retrospective data from three experienced European Syncope Units were merged to include 5236 patients investigated for suspected VVS by the Italian TT protocol. Tilt testing-positivity rates and haemodynamics were analysed across age-decade subgroups. Of 5236 investigated patients, 3129 (60%) had a positive TT. Cardioinhibitory responses accounted for 16.5% of positive tests and were more common in younger patients, decreasing from the age of 50-59 years. Vasodepressor (VD) responses accounted for 24.4% of positive tests and prevailed in older patients, starting from the age of 50-59. Mixed responses (59.1% of cases) declined slightly with increasing age. Overall, TT positivity showed a similar age-related trend (P = 0.0001) and was significantly related to baseline systolic blood pressure (P < 0.001). Tilt testing was positive during passive phase in 18% and during nitroglycerine (TNG)-potentiated phase in 82% of cases. Positivity rate of passive phase declined with age (P = 0.001), whereas positivity rate during TNG remained quite stable. The prevalence of cardioinhibitory and VD responses was similar during passive and TNG-potentiated TT, when age-adjusted. CONCLUSIONS: Age significantly impacts the haemodynamic pattern of TT responses, starting from the age of 50. Conversely, TT phase-passive or TNG-potentiated-does not significantly influence the type of response, when age-adjusted. Vagal hyperactivity dominates in younger patients, older patients show tendency to vasodepression.

Bedside wireless lung ultrasound for the evaluation of COVID-19 lung injury in senior nursing home residents.

Lung Ultrasound (LUS) is regarded to be potentially useful to diagnose lung injury in older adults living in nursing homes with suspected COVID-19 pneumonia. We aimed at evaluating presence lung injury among senior nursing home residents by LUS performed with portable wireless scanner echography. The study population consisted of 150 residents with a mean age of 88 years (85% female) residing in 12 nursing homes in Northern Italy. Subjects had to have a history of recent onset of symptoms compatible with COVID-19 pneumonia or have been exposed to the contagion of patients carrying the disease. COVID-19 testing was performed with SARS-CoV-2 nasal-pharyngeal (NP) swabs. Positive subjects to LUS scanning were considered those with non-coascelent B-lines in >3 zones, coalescent B-lines in >3 zones and with iperdensed patchy non-consolidated lungs. Sixty-three percent had positive NP testing and 65% had LUS signs of pulmonary injury. LUS had a sensitivity of 79% in predicting positive NP testing. Sixteen percent of residents tested negative for SARSCoV-2 carried the signs of COVID-19 lung injury at LUS. There were 92 patients (61%) with current or recent symptoms.Positivity to LUS scanning was reported in 73% of residents with symptoms, while it was 53% in those without (P=0.016). A positive NP testing was observed in 66% of residents with symptoms and in 57% of those without (P=0.27). We conclude that assessment of LUS by portable wireless scanner echography can be profitability utilized to diagnose lung injury among senior nursing home residents with or without symptoms compatible with COVID-19 pneumonia.

Clinical characteristics and prognostic impact of atrial fibrillation in patients with chronic heart failure.

AIM: To assess the prevalence, clinical characteristics and independent prognostic impact of atrial fibrillation (AF) in chronic heart failure (CHF) patients, and the potential protective effect of disease-modifying medications, particularly beta-blockers (BB). METHODS: We retrospectively reviewed the charts of patients referred to our center since January 2004, and collected all clinical information available at their first visit. We assessed mortality to the end of June 2015. We compared patients with and without AF, and assessed the association between AF and all-cause mortality by multivariate Cox regression and Kaplan-Meyer analysis, particularly accounting for ongoing treatment with BB. RESULTS: A total of 903 patients were evaluated (mean age 68 ± 12 years, 73% male). Prevalence of AF was 19%, ranging from 10% to 28% in patients ≤ 60 and ≥ 77 years, respectively. Besides the older age, patients with AF had more symptoms (New York Heart Association II-III 60% vs 44%), lower prevalence of dyslipidemia (23% vs 37%), coronary artery disease (28% vs 52%) and left bundle branch block (9% vs 16%). On the contrary, they more frequently presented with an idiopathic etiology (50% vs 24%), a history of valve surgery (13% vs 4%) and received overall more devices implantation (31% vs 21%). The use of disease-modifying medications (i.e., BB and ACE inhibitors/angiotensin receptor blockers) was lower in patients with AF (72% vs 80% and 71% vs 79%, respectively), who on the contrary were more frequently treated with symptomatic and antiarrhythmic drugs including diuretics (87% vs 69%) and digoxin (51% vs 11%). At a mean follow-up of about 5 years, all-cause mortality was significantly higher in patients with AF as compared to those in sinus rhythm (SR) (45% vs 34%, P value < 0.05 for all previous comparisons). However, in a multivariate analysis including the main significant predictors of all-cause mortality, the univariate relationship between AF and death (HR = 1.49, 95%CI: 1.15-1.92) became not statistically significant (HR = 0.98, 95%CI: 0.73-1.32). Nonetheless, patients with AF not receiving BB treatment were found to have the worst prognosis, followed by patients with SR not receiving BB therapy and patients with AF receiving BB therapy, who both had similarly worse survival when compared to patients with SR receiving BB therapy. CONCLUSION: AF was highly prevalent and associated with older age, worse clinical presentation and underutilization of disease-modifying medications such as BB in a population of elderly patients with CHF. AF had no independent impact on mortality, but the underutilization of BB in this group of patients was associated to a worse long-term prognosis.