After a three-year quarantine from the deadliest global pandemic of the last century, ASTES is organizing to gather all health professionals in Tirana, The 6th Albanian Congress of Trauma and Emergency Surgery(ACTES 2022) on 11-12 November 2022, with the topic Trauma & Emergency Surgery and not only...with the aim of providing high quality, the best standards, and the best results, for our patients ...ACTES 2022 is the largest event that ASTES (Albanian Society for Trauma and Emergency Surgery) has organized so far with 230 presentations, and 67 foreign lecturers with enviable geography, making it the largest national and wider scientific event.The scientific program is as strong as ever, thanks to the inclusiveness, where all the participants with a mix of foreign and local lecturers, select the best of the moment in medical science, innovation, and observation.The scientific committee has selected all the presentations so that the participants of each medical discipline will have something to learn, discuss, debate, and agree with updated methods, techniques, and protocols.I hope you will join us on Friday morning, and continue the journey of our two-day event together.

Background: Painful and damaged nipples are frequently associated with breastfeeding cessation in the early postpartum period. The results of researchers’ studies utilizing different treatments have been inconclusive. Research Aim: To compare the intensity of nipple pain and the healing of damaged nipples during the first 10 days postpartum using either lanolin or human milk treatments. Methods: This single-blind randomized controlled trial included participants (N = 206) who were primiparous with painful and damaged nipples. Participants were recruited from the tertiary teaching hospital within the first 72 hr after delivery and randomized to the intervention group with lanolin (n = 103) and a human milk control group (n = 103). Data were collected in the maternity ward, 3 and 7 days after randomization. The primary outcome was nipple pain intensity and quality measured 3 and 7 days after randomization by the McGill Pain Questionnaire – short form. The nipple damage self-assessment questionnaire was used for the assessment of nipple healing. Breastfeeding self-efficacy, breastfeeding duration, and exclusivity were assessed as secondary outcomes. Results: Participants in both groups reported a statistically nonsignificant reduction in pain (quality and intensity of pain) as well as improved nipple healing 7 days after randomization. Participants in the lanolin group exclusively breastfed their infants 3 days after randomization—significantly more often than participants in the control group (p = .026). The study did not reveal any statistically significant differences for other secondary outcomes. Conclusion: Both lanolin and human milk are equally effective in treating painful and damaged nipples. Registered with Clinicaltrials.gov (NCT04153513)

After a long period of no excessive ground shaking in Croatia and the region of ex-Yugoslavia, an earthquake that woke up the entire region was the one that shook Croatia on 22 March 2020. More than 25,000 buildings were severely damaged. A process of reconstruction and strengthening of existing damaged buildings is underway. This paper presents proposed strengthening measures to be conducted on a cultural-historical building located in the city of Zagreb, which is under protection and located in zone A. After a detailed visual inspection and on-site experimental investigations, modeling of the existing and strengthened structure was performed in 3Muri. It is an old unreinforced masonry building typical not only for this region but for relevant parts of Europe (north, central, and east). The aim was to strengthen the building to Level 3 while respecting the ICOMOS recommendations and Venice Charter. Some non-completely conservative concessions had to be made, to fully retrofit the building as requested. The structural strengthening consisted of a series of organic interventions relying on—in the weakest direction—a new steel frame, new steel-ring frames, and FRCM materials, besides fillings the cracks. Such intervention resulted in increasing the ultimate load in the X and Y directions, respectively, more than 650 and 175% with reference to the unstrengthened structure. Good consistency was obtained between the numerical modeling, visual inspection, and on-site testing.

The European building stock presents pertinent issues needing suitable strategies to be solved. In detail, this regards seismic safety and energy efficiency of buildings to ensure more liveable and safe cities, which represents an important goal for modern societies. Energy performance includes both comfort and saving, the latter required for a more responsible resource consumption within the building sector, having a considerable contribution to the total demand. Current strategies do not seem to be able to simultaneously solve such aspects satisfactorily, both for higher economic requirements and poor technical feasibility implied by separated and disharmonious interventions. Thus, a holistic perspective should be adopted to pursue such an ambitious objective, which has recently gained increasing attention among researchers. Current requirements are firstly highlighted to show the need for an integrated approach to building retrofit. Secondly, a critical review of integrated strategies combining seismic and energy refurbishment proposed in the literature is reported. Then, special issues are discussed, including the feasibility of an integrated approach applied to heritage buildings. This study revealed that a fully efficient strategy for integrated retrofit has not still been proposed in the literature and there are several open issues to be solved. However, current solutions may be further developed to improve them and the several options currently available demonstrated the increasing attention and importance of the topic. Finally, concluding remarks on this research topic have been drawn to promote future studies.

The respiratory rate is a vital sign indicating breathing illness. It is necessary to analyze the mechanical oscillations of the patient's body arising from chest movements. An inappropriate holder on which the sensor is mounted, or an inappropriate sensor position is some of the external factors which should be minimized during signal registration. This paper considers using a non-invasive device placed under the bed mattress and evaluates the respiratory rate. The aim of the work is the development of an accelerometer sensor holder for this system. The normal and deep breathing signals were analyzed, corresponding to the relaxed state and when taking deep breaths. The evaluation criterion for the holder's model is its influence on the patient's respiratory signal amplitude for each state. As a result, we offer a non-invasive system of respiratory rate detection, including the mechanical component providing the most accurate values of mentioned respiratory rate.

Entre 2019 y 2021 el equipo de Global Digital Heritage (GDH), en colaboración con la Universidad de Sarajevo y el Museo Nacional de Bosnia y Herzegovina, ha llevado a cabo la digitalización 3D de un importante conjunto de stećci conservados tanto en el Museo Nacional de Bosnia y Herzegovina como en algunos cementerios medievales cercanos a la ciudad de Sarajevo y a la zona oriental de Bosnia. Los cementerios medievales de stećci constituyen un valioso patrimonio arqueológico de gran interés histórico pero poco conocido a nivel internacional pese a que algunos de ellos han sido declarados Patrimonio Mundial en 2016. A pesar de tratarse de un patrimonio en peligro apenas se han acometido trabajos de documentación 3D sistemáticos. Este artículo expone la metodología empleada y los resultados obtenidos por GDH, incluyendo las dificultades que ha sido necesario resolver y los retos que todavía han de abordarse para poder acometer la paulatina digitalización 3D del mayor número posible de cementerios medievales de stećci en Bosnia y Herzegovina. 

Background A potential benefit of intravenous thrombolysis (IVT) before mechanical thrombectomy (MT) is pre-interventional reperfusion. Currently, there are few data on the occurrence of pre-interventional reperfusion in patients randomized to IVT or no IVT before MT. Methods SWIFT DIRECT (Solitaire With the Intention For Thrombectomy Plus Intravenous t-PA vs DIRECT Solitaire Stent-retriever Thrombectomy in Acute Anterior Circulation Stroke) was a randomized controlled trial including acute ischemic stroke IVT eligible patients being directly admitted to a comprehensive stroke center, with allocation to IVT with MT versus MT alone. The primary endpoint of this analysis was the occurrence of pre-interventional reperfusion, defined as a pre-interventional expanded Thrombolysis in Cerebral Infarction score of ≥2a. The effect of IVT and potential treatment effect heterogeneity were analyzed using logistic regression analyses. Results Of 396 patients, pre-interventional reperfusion occurred in 20 (10.0%) patients randomized to IVT with MT, and in 7 (3.6%) patients randomized to MT alone. Receiving IVT favored the occurrence of pre-interventional reperfusion (adjusted OR 2.91, 95% CI 1.23 to 6.87). There was no IVT treatment effect heterogeneity on the occurrence of pre-interventional reperfusion with different strata of Randomization-to-Groin-Puncture time (p for interaction=0.33), although the effect tended to be stronger in patients with a Randomization-to-Groin-Puncture time >28 min (adjusted OR 4.65, 95% CI 1.16 to 18.68). There were no significant differences in rates of functional outcomes between patients with and without pre-interventional reperfusion. Conclusion Even for patients with proximal large vessel occlusions and direct access to MT, IVT resulted in an absolute increase of 6% in rates of pre-interventional reperfusion. The influence of time strata on the occurrence of pre-interventional reperfusion should be studied further in an individual patient data meta-analysis of comparable trials. Trial registration number clinicaltrials.gov NCT03192332.

Introduction: Dementia prevention trials have so far shown little benefit of multidomain interventions against cognitive decline. Recruitment strategies in these trials often centre around dementia risk or cardiovascular risk profile, but it is uncertain whether this leads to inclusion of individuals who may benefit most from the intervention. We determined the effects of eligibility criteria on the recruitment of potential trial participants in the general population. Methods: In a systematic search until January 1, 2022, we identified all published and ongoing large (≥500 participants), phase-3 multidomain trials for the prevention of cognitive decline or dementia. We applied trial eligibility criteria to 5,381 participants of the population-based Rotterdam Study (mean age: 72 years, 58% women), to compare participant characteristics, predicted risk of cardiovascular disease, and dementia risk, between trial eligible and ineligible persons. Results: We identified 10 trials, of which 5 had been published (DR’s EXTRA, FINGER, preDIVA, MAPT, and HATICE) and 5 are ongoing (US-POINTER, MIND-CHINA, MYB, AgeWell.de, and J-Mint). Among all Rotterdam Study participants, eligibility across published trials ranged from 48% for MAPT to 87% for preDIVA, in line with original trial reports. Variability in eligibility was wider for ongoing trials, from 1% for US-POINTER to over 94% for MYB trial. Over 70% of trial eligible individuals are recommended preventive intervention in routine care based on their cardiovascular risk, similar for lipid-lowering (71%) and blood pressure-lowering treatment (73%). Ten-year risks of dementia were similar for eligible compared to ineligible individuals (12 vs. 11%). Conclusion: Multidomain dementia prevention trials fail to preferentially include those at the highest risk of dementia and mostly include individuals who qualify for interventions already on the basis of cardiovascular prevention guidelines. These findings call for better targeted enrolment of individuals for whom trial results can improve clinical decision-making.

Circulating cell-free DNA (ccfDNA) sequencing for low-burden cancer monitoring is limited by sparsity of circulating tumor DNA (ctDNA), the abundance of genomic material within a plasma sample, and pre-analytical error rates due to library preparation, and sequencing errors. Sequencing costs have historically favored the development of deep targeted sequencing approaches for overcoming sparsity in ctDNA detection, but these techniques are limited by the abundance of ccfDNA in samples, which imposes a ceiling on the maximal depth of coverage in targeted panels. Whole genome sequencing (WGS) is an orthogonal approach to ctDNA detection that can overcome the low abundance of ccfDNA by supplanting sequencing depth with breadth, integrating signal across the entire tumor mutation landscape. However, the higher cost of WGS limits the practical depth of coverage and hinders broad adoption. Lower sequencing costs may thus allow for enhanced ctDNA cancer monitoring via WGS. We therefore applied emerging lower-cost WGS (Ultima Genomics, 1USD/Gb) to plasma samples at ∼120x coverage. Copy number and single nucleotide variation profiles were comparable between matched Ultima and Illumina datasets, and the deeper WGS coverage enabled ctDNA detection at the parts per million range. We further harnessed these lower sequencing costs to implement duplex error-corrected sequencing at the scale of the entire genome, demonstrating a ∼1,500x decrease in errors in the plasma of patient-derived xenograft mouse models, and error rates of ∼10−7 in patient plasma samples. We leveraged this highly de-noised plasma WGS to undertake cancer monitoring in the more challenging context of resectable melanoma without matched tumor sequencing. In this context, duplex-corrected WGS allowed us to harness known mutational signature patterns for disease monitoring without matched tumors, paving the way for de novo cancer monitoring.

Today's extensive requirements for the storage, management, and analysis of complex, dynamic, evolving, distributed, and heterogeneous data from different sources and platforms, e.g., Big data, generate enormous challenges for IT, especially database applications. That is why the demand for data reduction is increasingly coming from the world of databases, intending to reduce the costs of storing, processing, and querying Big data. There is a large number of different techniques for Big data reduction that can cause confusion and complicate this process. Because of that, the authors proposed a Big data reduction framework to structure and present both data reduction techniques and necessary components essential for a better understanding of the process. The importance and the components of the proposed framework are explained in this paper.

In order to find the optimal solution for the drainage of rainwater from roads in urban areas, as well as for the evaluation and ranking of conceptual solutions, appropriate mathematical models and software packages were used in this research. For relevant rain episodes, i.e. rainfall of appropriate duration and intensity, runoff coefficients and flows were taken into account and analyzed according to the rational method, all for the purpose of obtaining data on the amount of rainwater entering the sewage system. Through this research, very good correlations and regressions were established between the cross slope of the road and the parameters of rainwater drainage from the road, as well as the correlation and regression relationships of the cross slope of the road and the efficiency of the drain. Likewise, the dependences of the drainage parameters, the efficiency of the drains and the cross slope of the road were determined, expressed through mathematical functions.

This paper presents the results of detailed geological investigations of the Middle Triassic dolomite deposit of Nikolin Potok, which is located west of Bugojno. Based on the established borders of surface distribution and research results, geological reserves of about 4.6 million m3 have been determined in the wider area of the deposit. The dolomite reserves that have been established so far in this area are at a low level of geological exploration. For this reason, the level of research should be significantly increased, because the calculated and confirmed reserves are very modest compared to the potential possibilities. The paper contains a description of the geological characteristics of the area and the qualitative-quantitative characteristics of dolomite. The results of the conducted research point that the general geological and technical-exploitation factors are favorable and indicate profitable exploitation of the deposit in the coming period as well. Taking into account the significant raw material potential, and the possibility of expanding the existing raw material base, this area has a special significance for the perspective development of dolomite exploitation and its use in the production of technical-building stone.

Air pollution is a major problem in developing countries and around the world causing lung diseases such as asthma, chronic bronchitis, emphysema, and chronic obstructive pulmonary disease. Therefore, innovative methods and systems for predicting air pollution are needed to reduce such risks. Some Internet of Things (IoT) technologies have been developed to assess and monitor various air quality parameters. In the context of IoT, Artificial intelligence is one of the main segments of smart cities that enables collecting a large amount of data to make recommendations, predict future events and help make decisions. Big data, as part of artificial intelligence, greatly contributes to making further decisions, determining the necessary resources, and identifying critical places thanks to the large amount of data it collects. This paper proposes a solution, with the integration of the Internet of Things (IoT), to predict pollution for any given day. This paper aims to show how sensor-derived data in smart air pollution monitoring solutions can be used for intelligent pollution management. By collecting data from the air pollution sensor that sends the data to the server via. NET 6 REST API endpoint and places it in a SQL Server database together with additional weather data that is collected from REST API for that part of the day, a dataset is created through the ETL process in Jupyter notebook. Linear regression algorithms will be used for making predictions. By detecting the largest sources of air pollution, artificial intelligence solutions can proactively reduce pollution and thus improve health conditions and reduce health costs.