Introduction. Mortality among critically ill COVID‐19 patients remains relatively high despite different potential therapeutic modalities being introduced recently. The treatment of critically ill patients is a challenging task, without identified credible predictors of mortality. Methods. We performed an analysis of 160 consecutive patients with confirmed COVID‐19 infection admitted to the Respiratory Intensive Care Unit between June 23, 2020, and October 2, 2020, in University Hospital Center Bezanijska kosa, Belgrade, Serbia. Patients on invasive, noninvasive ventilation and high flow oxygen therapy with moderate to severe ARDS, according to the Berlin definition of ARDS, were selected for the study. Demographic data, past medical history, laboratory values, and CT severity score were analyzed to identify predictors of mortality. Univariate and multivariate logistic regression models were used to assess potential predictors of mortality in critically ill COVID‐19 patients. Results. The mean patient age was 65.6 years (range, 29–92 years), predominantly men, 68.8%. 107 (66.9%) patients were on invasive mechanical ventilation, 31 (19.3%) on noninvasive, and 22 (13.8%) on high flow oxygen therapy machine. The median total number of ICU days was 10 (25^th to 75^th percentile: 6–18), while the median total number of hospital stay was 18 (25^th to 75^th percentile: 12–28). The mortality rate was 60% (96/160). Univariate logistic regression analysis confirmed the significance of age, CRP, and lymphocytes at admission to hospital, serum albumin, D‐dimer, and IL‐6 at admission to ICU, and CT score. Serum albumin, D‐dimer, and IL‐6 at admission to ICU were independently associated with mortality in the final multivariate analysis. Conclusion. In the present study of 160 consecutive critically ill COVID‐19 patients with moderate to severe ARDS, IL‐6, serum albumin, and D‐dimer at admission to ICU, accompanied by chest CT severity score, were marked as independent predictors of mortality.

The utilization of intraoperative ultrasound (IOUS) in breast cancer surgery is a relatively new concept in surgical oncology. Over the last few decades, the field of breast cancer surgery has been striving for a more rational approach, directing its efforts towards removing the tumor entirely yet sparing tissue and structures not infiltrated by tumor cells. Further progress in objectivity and optimization of breast cancer excision is possible if we make the tumor and surrounding tissue visible and measurable in real time, during the course of the operation; IOUS seems to be the optimal solution to this complex requirement. IOUS was introduced into clinical practice as a device for visualization of non-palpable tumors, and compared to wire-guided localization (WGL), IOUS was always at least a viable, or much better alternative, in terms of both precision in identification and resection and for patients’ and surgeons’ comfort. In recent years, intraoperative ultrasound has been used in the surgery of palpable tumors to optimize resection procedures and overcome the disadvantages of classic palpation guided surgery. The aim of this review is to show the role of IOUS in contemporary breast cancer surgery and its changes over time. A PubMed database comprehensive search was conducted to identify all relevant articles according to assigned key words. Over time, the use of IOUS has been transformed from being the means of localizing non-palpable lesions to an instrument yielding a reduced number of positive resection margins, with a smaller volume of healthy breast tissue excided around tumor, by making the excision of the tumor optimal and objectively measurable.

Introduction. Risk stratification is an important aspect of COVID‐19 management, especially in patients admitted to ICU as it can provide more useful consumption of health resources, as well as prioritize critical care services in situations of overwhelming number of patients. Materials and Methods. A multivariable predictive model for mortality was developed using data solely from a derivation cohort of 160 COVID‐19 patients with moderate to severe ARDS admitted to ICU. The regression coefficients from the final multivariate model of the derivation study were used to assign points for the risk model, consisted of all significant variables from the multivariate analysis and age as a known risk factor for COVID‐19 patient mortality. The newly developed AIDA score was arrived at by assigning 5 points for serum albumin and 1 point for IL‐6, D dimer, and age. The score was further validated on a cohort of 304 patients admitted to ICU due to the severe form of COVID‐19. Results. The study population included 160 COVID‐19 patients admitted to ICU in the derivation and 304 in the validation cohort. The mean patient age was 66.7 years (range, 20–93 years), with 68.1% men and 31.9% women. Most patients (76.8%) had comorbidities with hypertension (67.7%), diabetes (31.7), and coronary artery disease (19.3) as the most frequent. A total of 316 patients (68.3%) were treated with mechanical ventilation. Ninety‐six (60.0%) in the derivation cohort and 221 (72.7%) patients in the validation cohort had a lethal outcome. The population was divided into the following risk categories for mortality based on the risk model score: low risk (score 0–1) and at‐risk (score > 1). In addition, patients were considered at high risk with a risk score > 2. By applying the risk model to the validation cohort (n = 304), the positive predictive value was 78.8% (95% CI 75.5% to 81.8%); the negative predictive value was 46.6% (95% CI 37.3% to 56.2%); the sensitivity was 82.4% (95% CI 76.7% to 87.1%), and the specificity was 41.0% (95% CI 30.3% to 52.3%). The C statistic was 0.863 (95% CI 0.805‐0.921) and 0.665 (95% CI 0.598‐0.732) in the derivation and validation cohorts, respectively, indicating a high discriminative value of the proposed score. Conclusion. In the present study, AIDA score showed a valuable significance in estimating the mortality risk in patients with the severe form of COVID‐19 disease at admission to ICU. Further external validation on a larger group of patients is needed to provide more insights into the utility of this score in everyday practice.

We present a surgical technique and the preliminary results of breast cancer excision after insertion of a specially constructed marking needle into the tumor, controlled by intraoperative ultrasound. Resection margins were projected in six directions by ultrasound measurements, determined in relation to the needle, and resection was done in accordance with those measurements. The main objective was to obtain resection margins similar (equal) to those projected by intraoperative ultrasound (10 mm). Detailed description of the technique is given. Thirty-two female patients undergoing breast-conserving surgery, up to 30 mm in diameter, for palpable and non-palpable invasive breast cancer, were operated on using this technique. Its feasibility was tested by analyzing the success (rate) of needle placement in the tumor, the measurements executed, and the performance of the excision. All stages of the technique were successfully performed to completion on all 32 patients. The procedure of needle placement and ultrasound measurement of distances took 11 min on average (between 6 and 20 min). The average distance of the tumor margin from the resection margin was 12.9 mm (2 to 30 mm, 95% confidence interval [11.9, 14.06]). There was one patient with a positive resection margin (3%). The technique of excising palpable and non-palpable breast cancer by intraoperative ultrasound and an especially constructed marking needle is feasible and comfortable to perform. Preliminary results imply that resection volume can be rationalized, with the same or better oncological safety.

Macrophages are a heterogenous population of cells that adopt specific phenotypes in response to signals from their dynamic microenvironment. Apart from being key players in innate immunity and in the maintenance of tissue homeostasis, macrophages are also important drivers of low-grade inflammation, which is associated with different chronic conditions including stress and cancer. The activation of macrophages during chronic stress and cancer results in their multifaceted pathogenic roles. Macrophages residing in the tumor microenvironment are commonly known as tumor-associated macrophages and favor or inhibit tumor growth depending on the microenvironmental cues and their activation state. Activated macrophages display a continuum of properties rather than a distinct proinflammatory or anti-inflammatory dichotomy. Emerging evidence suggests that prolonged tissue residency restricts the plasticity of macrophages, while recruited monocytes are more plastic and their differentiation into tumor-associated macrophages during stress can result in a dual imprinting from both the existing stress-induced inflammation and the tumor microenvironment. In addition, the immunomodulation of the tumor microenvironment and reprogramming of tumor-associated macrophages toward the anti-tumor phenotypes have emerged as promising therapeutic approaches. In this review, we will focus on how the persistent inflammatory state underlying chronic stress affects macrophages as well as the macrophages’ contribution to various aspects of tumor growth and progression, highlighting a therapeutic potential of modulation of the macrophage-mediated immunosuppressive tumor microenvironment.