Routine Inspection Research Articles

Improving Best Practices in Assessing the Usage Conditions of Hospital and Long-Term Care Mattresses

Background: Inadequate mattresses can pose risks to users, and the routine inspection of mattresses often falls short in various healthcare settings. Objectives: To evaluate the physical condition of mattresses in hospitals and long-term care facilities and to explore the association with management practices regarding procurement, handling, and maintenance. Methods: This analytical descriptive cross-sectional study was conducted in 13 hospitals and 5 long-term care facilities, examining a total of 278 mattresses through proportional stratified sampling. The Mann-Whitney U test, Kruskal-Wallis test, and Multiple Regression Analysis were utilized for data analysis. Results: A mere 9.9% of the mattresses met the physical evaluation criteria, revealing a significant gap in mattress management standardization. The highest compliance was noted in the utilization of waterproof coverings, whereas the lowest was in mattress labeling. Factors significantly influencing the scores included the involvement of nurses in the evaluation process, periodic replacement of coverings, type of administration, assessment of mattress and covering integrity during bed making, and the nature of the institution. Conclusions: Due to inadequate physical conditions in both hospital and long-term care settings, the low approval rate of mattresses underscores the urgent need for standardized mattress management practices. Descriptors: Beds, Hospital Infection, Disinfection, Long-Term Care Facilities for the Elderly, Patient Safety.

Retroperitoneal hernia following laparoscopic living-donor nephrectomy: a case report and review of literature

BackgroundThe laparoscopic approach is the standard of care for living-donor nephrectomy. A rare postoperative complication is small bowel obstruction due to a retroperitoneal hernia. We present a case of an incidental finding of a retroperitoneal hernia in a patient with a history of laparoscopic donor nephrectomy.Case presentationAn adult male presented with diffuse abdominal pain, vomiting, and obstipation for 12 h. He had undergone laparoscopic donor nephrectomy two months prior. Plain abdominal radiograph revealed a dilated small bowel with homogenous opacity in the left lumbar region. Due to worsening diffuse abdominal pain and a high clinical suspicion of intestinal strangulation and ischemia after conservative management, an exploratory laparotomy was performed. Intraoperatively, an incarcerated small bowel segment herniating through an 8 cm descending mesocolon defect into the retroperitoneal space was discovered, forming a closed-loop obstruction. The bowel segment was reduced, and the mesocolon defect was repaired. The patient was discharged five days postoperatively with good recovery.ConclusionRetroperitoneal hernia following laparoscopic living-donor nephrectomy is a rare but significant complication. Mitigation to prevent mesenteric defect creation, routine inspection, and closure of the defect can reduce the risk of hernia. Non-specific abdominal pain in patients with a history of laparoscopic donor nephrectomy prompts rapid imaging evaluation to aid in the early diagnosis of possible retroperitoneal hernia and its intervention.

Isolation and Characterization of Bacterial Contaminants from Bone Marrow-Derived Mesenchymal Stem Cell Cultures

This study aimed to assess and manage bacterial contamination in multiple batches of mesenchymal stem cell (MSC) cultures derived from rabbit bone marrow. Routine visual inspection and microscopic examination were employed for the detection of the contaminated cultures. The contaminated cultures were inoculated on Nutrient agar and multiple isolated colonies were subjected to Gram staining and biochemical characterization. Further, molecular identification of the bacterial isolates was performed using polymerase chain reaction. The determination of antibiotic susceptibility patterns was conducted using the Kirby-Bauer disc diffusion method. Among the 351 mesenchymal stem cell culture (SCC) flasks monitored, only 1.42% were found to be contaminated. Based on the phenotypic and biochemical characterization, the major bacterial contaminants were identified as Staphylococcus aureus, Bacillus spp., and Escherichia coli infiltrating during various stages of cell processing. Antibiotic susceptibility patterns revealed varying responses among isolates, crucial for effective antimicrobial strategies and maintaining aseptic conditions in SCCs. The study emphasizes the importance of regular monitoring to maintain sterile environments, validate culture quality, and uphold safety standards. The findings indicate the need to establish stringent quality control measures, crucial for the successful translation of MSC research into clinical applications. The research advocates for continuous monitoring, adherence to SOPs, and further investigations into preventive strategies for ensuring the safety and efficacy of MSC-based therapies.

Combined navigation system for substation inspection robot based on DGPS/DR multi-sensor fusion

To realize the routine inspection work of the capacitor tower inspection operation robot on the capacitor tower in the substation, and to guarantee the accuracy and safety of the robot’s movement in the substation, a multi-sensor combination navigation system and the corresponding Kalman fusion filter are designed. Combined with the overall structure of the substation and the working environment of the inspection robot, the navigation and positioning requirements of the robot are analyzed and compared, and the multi-sensor combination positioning technology using a combination of DGPS, attitude sensors and velocity sensors is determined. The Kalman fusion filter based on the constant velocity model is used to fuse the positioning information of multiple sensors, and more accurate and reliable navigation information is obtained compared with the single-sensor positioning system. According to the working environment of the substation, an outdoor planar robot mobile navigation experiment is carried out to collect the positioning information of multiple sensors and carry out data fusion processing to verify the accuracy and robustness of multi-sensor combination navigation and positioning.

Transient Tests for Checking the Trieste Subsea Pipeline: Toward Field Tests

Subsea pipelines are vital arteries transporting oil, gas, and water over long distances and play a critical role in the global resource supply chain. However, they are the most vulnerable to damage from both human-made and natural causes and are characterized by inherent inaccessibility. As a result, routine inspection and monitoring technologies, both reliable and at the lowest possible cost, are needed to ensure their longevity. To fill this need, the use of transient-test-based techniques is proposed. In this first paper of a set of two companion papers, attention is focused on the selection of the appropriate maneuver that generates pressure waves and then on the planned steps—i.e., the sequence of actions—functional to the execution of the transient tests in the best flow conditions for effective fault detection. A brief review of the available fault detection technologies with their limitations is also offered. Finally, the performance of the proposed procedure is evaluated mainly in terms of the stability of the pressure regime prior to the execution of the transient test.

Configuring Taiwan’s highway bridge performance indicator: a semi-quantitative risk assessment approach

The Taiwan Bridge Management System (TBMS) calculates the condition index (CI) of every highway bridge in its inventory using the latest findings from biennial routine inspections. However, the computational approach for CI can yield skewed results and make a bridge appear healthier than it actually is. To address this issue, a highway bridge performance indicator called the bridge risk index (RI) is presented. The RI is determined by combining the risks associated with the failure of each bridge component, which are evaluated using a semi-quantitative risk assessment approach. This evaluation considers the probability and consequence of a bridge component’s failure as a function of a component's deterioration state and criticality to the bridge’s overall structural safety and serviceability, respectively. To validate the effectiveness of the RI, inspection data from a sample of seven highway bridges were extracted from the TBMS and used to compare the RI with the CI. The results showed that the RI and its associated parameters can mitigate the inherent issues observed with the CI. Hence, the RI has the potential to be a valuable decision-support tool for transport agencies that rely on similar routine inspection processes to enhance their bridge management systems.

Eye Drop Quality Issues: Can the FDA See This One Through?

The Food and Drug Administration (FDA) has long suffered from a lack of resources limiting their inspection capacity. They have fallen behind on proactive surveillance inspections of foreign manufacturing sites, relying instead on for-cause inspections after a problem has been discovered. Over-the-counter (OTC) products are especially vulnerable because the FDA considers them lower priority. This issue recently made big news after improperly manufactured OTC eye drops harmed users across the country, in some cases causing blindness. To prevent future harm to Americans, it is imperative that the FDA receives enough resources to keep up with their routine inspections.

Damage Detection of Gantry Crane with a Moving Mass Using Artificial Neural Network

Gantry cranes play a pivotal role in various industrial applications, and their reliable operation is paramount. While routine inspections are standard practice, certain defects, particularly in less accessible components, remain challenging to detect early. In this study, first a finite element model is presented, and the damage is introduced using random changes in the stiffness of different parts of the structure. Contrary to the assumption of inherent reliability, undetected defects in crucial structural elements can lead to catastrophic failures. Then, the vibration equations of healthy and damaged models are analyzed to find the displacement, velocity, and acceleration of the different crane parts. The learning vector quantization neural network is used to train and detect the defects. The output is the location of the damage and the damage severity. Noisy data are then used to evaluate the network performance robustness. This research also addresses the limitations of traditional inspection methods, providing early detection and classification of defects in gantry cranes. The study’s relevance lies in the need for a comprehensive and efficient damage detection method, especially for components not easily accessible during routine inspections.

Comparative Analysis of Machine Learning Models for Predictive Maintenance of Ball Bearing Systems

In the era of Industry 4.0 and beyond, ball bearings remain an important part of industrial systems. The failure of ball bearings can lead to plant downtime, inefficient operations, and significant maintenance expenses. Although conventional preventive maintenance mechanisms like time-based maintenance, routine inspections, and manual data analysis provide a certain level of fault prevention, they are often reactive, time-consuming, and imprecise. On the other hand, machine learning algorithms can detect anomalies early, process vast amounts of data, continuously improve in almost real time, and, in turn, significantly enhance the efficiency of modern industrial systems. In this work, we compare different machine learning and deep learning techniques to optimise the predictive maintenance of ball bearing systems, which, in turn, will reduce the downtime and improve the efficiency of current and future industrial systems. For this purpose, we evaluate and compare classification algorithms like Logistic Regression and Support Vector Machine, as well as ensemble algorithms like Random Forest and Extreme Gradient Boost. We also explore and evaluate long short-term memory, which is a type of recurrent neural network. We assess and compare these models in terms of their accuracy, precision, recall, F1 scores, and computation requirement. Our comparison results indicate that Extreme Gradient Boost gives the best trade-off in terms of overall performance and computation time. For a dataset of 2155 vibration signals, Extreme Gradient Boost gives an accuracy of 96.61% while requiring a training time of only 0.76 s. Moreover, among the techniques that give an accuracy greater than 80%, Extreme Gradient Boost also gives the best accuracy-to-computation-time ratio.

Diagnostic Challenges during Inflammation and Cancer: Current Biomarkers and Future Perspectives in Navigating through the Minefield of Reactive versus Dysplastic and Cancerous Lesions in the Digestive System.

In the setting of pronounced inflammation, changes in the epithelium may overlap with neoplasia, often rendering it impossible to establish a diagnosis with certainty in daily clinical practice. Here, we discuss the underlying molecular mechanisms driving tissue response during persistent inflammatory signaling along with the potential association with cancer in the gastrointestinal tract, pancreas, extrahepatic bile ducts, and liver. We highlight the histopathological challenges encountered in the diagnosis of chronic inflammation in routine practice and pinpoint tissue-based biomarkers that could complement morphology to differentiate reactive from dysplastic or cancerous lesions. We refer to the advantages and limitations of existing biomarkers employing immunohistochemistry and point to promising new markers, including the generation of novel antibodies targeting mutant proteins, miRNAs, and array assays. Advancements in experimental models, including mouse and 3D models, have improved our understanding of tissue response. The integration of digital pathology along with artificial intelligence may also complement routine visual inspections. Navigating through tissue responses in various chronic inflammatory contexts will help us develop novel and reliable biomarkers that will improve diagnostic decisions and ultimately patient treatment.

Detection of Sarcocystis hominis, Sarcocystis bovifelis, Sarcocystis cruzi, Sarcocystis hirsuta and Sarcocystis sigmoideus sp. nov. in carcasses affected by bovine eosinophilic myositis

Bovine eosinophilic myositis is an inflammatory myopathy characterized by multiple focal or diffuse grey to green patches leading to condemnation of affected carcasses. Although its etiology is still uncertain, there is evidence that Sarcocystis species may play a role in the development of eosinophilic myositis. The goal of the present study was to identify Sarcocystis spp. in intralesional and extralesional tissues of condemned cattle carcasses, in order to evaluate the possible role of different bovine Sarcocystis spp. in the etiology of bovine eosinophilic myositis. Muscle samples (n = 100) of 26 affected carcasses were collected in Northern Italy. One to five samples with lesions and two aliquots of tissue without lesions were collected from each carcass; lesions were grossly categorized in green focal lesions and green diffuse patches. Genomic DNA was extracted and analyzed by multiplex-PCR targeting different Sarcocystis spp. Unidentified species were characterized morphologically (light microscopy, histology), ultrastructurally (scanning and transmission electron microscopy) and on the molecular level (complete 18S rRNA gene and partial cox1 gene sequencing). A bovine eosinophilic myositis prevalence of 0.017% was visually assessed by routine carcass inspection between 2014 and 2019 in Italy (184/1,108,150 slaughtered cattle). Out of 26 carcasses, 25 revealed the presence of at least one Sarcocystis species (96.2%). The presence of Sarcocystis spp. DNA was significantly more frequent in intralesional than in extralesional samples. Considering the different species, Sarcocystis bovifelis and Sarcocystis hominis were significantly more frequent in intralesional (41.7% and 50%, respectively) than in extralesional samples (1.9% and 15.4%, respectively), while there was no significant difference between the presence of Sarcocystis cruzi and Sarcocystis hirsuta in intralesional (27.1% and 2.1%, respectively) and extralesional (30.8% and 1.9%, respectively) samples. The presence of an unnamed Sarcocystis sp. showing thick-walled (3.7–5.4 μm) cysts with densely packed, flattened, undulating and narrow protrusions, which showed an S-shape in side view, was recorded in the diaphragm of two carcasses. Genomic DNA from individual sarcocysts isolated from the diaphragm was successfully amplified and further sequenced. Sequence comparison revealed <94.6% and 83.4% identity at 18S rRNA and cox1 genes, respectively, with other named Sarcocystis spp., while the phylogenetic analysis clearly separated the unnamed Sarcocystis sp. from the other Sarcocystis spp. using cattle as intermediate hosts. The present study contributes to the understanding of the importance of different Sarcocystis spp. in the pathogenesis of bovine eosinophilic myositis. The results emphasize the association of Sarcocystis hominis and Sarcocystis bovifelis with bovine eosinophilic myositis and highlight the presence of a new Sarcocystis sp. using cattle as intermediate hosts. The name Sarcocystis sigmoideus sp. nov. is proposed for the newly described Sarcocystis species.

Weakly Supervised Fatigue Crack Detection in Steel Bridge Girders Using a Proposed Two-Stage Network Training with a Segmentation Refinement Module

Existing semantic segmentation methods for fatigue cracks in steel bridge girders are fully supervised and thus demand manual annotation of pixel-level labels, which is time-consuming. Recently, there have been remarkable developments in semantic segmentation under image-level tag supervision. However, these weakly supervised approaches are still inferior to the fully supervised manner in terms of accuracy. To mitigate this gap, this paper commits to improving the correlation between high-level semantics to low-level appearance. A two-stage training manner with a segmentation refinement module for progressively refining pseudolabels and training the segmentation network was proposed. First, an activation modulation and recalibration scheme was recommended, which leverages a spotlight branch and a compensation branch to locate both the discriminative and less-discriminative object regions. Then, the generated pseudolabels were used as supervision to train the segmentation network in the proposed two-stage manner. In the first stage, the network was pretrained to learn all essential information and provide a basic segmentation performance, aiming to facilitate network convergence in the following training. To develop the inference quality, in the second stage, the pretrained network was further trained recursively with the designed segmentation refinement module to improve the labels using two postprocessing algorithms between each iteration. Overall, our method achieves comparable inference results to fully supervised approaches while significantly reducing annotation workload, which improves the efficiency of routine bridge inspection.

Safety assessment in dams due to downstream slope anomalies

Recent cases of tailings dam failure in Brazil have demonstrated in the current methods of safety assessment of these structures. One of the most employed methods is the evaluation through routine inspections and audits, but this method is considered non-deterministic and affected by the expertise of the evaluator. This paper presents the results of numerical simulations of anomalies commonly found in safety inspections to measure the impact of these anomalies on the dam safety factor. The study was limited to numerical simulations of five types of dams (three downstream and two upstream dams), with varying embankment and tailings strength parameters, simulating different magnitudes of downstream slope anomalies (cracks, scour, and resurgence), totaling a sample space of 270 analyses. The results show that there were average reductions in safety ranging from 4% to 10% for scour simulations, 8% to 25% for resurgence, and 9% to 24% for cracking. The sample standard deviation of the analyses ranged from 8 to 12%. It was also observed that the combined effect of the anomalies showed proportional overlapping effects in reducing the range of safety. It was concluded that the simulated failures are important variables to be evaluated in inspections, not only for demonstrate deviations in the operation and maintenance of structures, but also to predict the magnitude of these failures in dam designs.

Sarcocystis spp. – an underestimated parasite with zoonotic potential associated with food of animal origin

The protozoa of the genus Sarcocystis are worldwide distributed parasites affecting a wide range of animals. They life cycle requires two hosts: definitive and intermediate. Over 250 species of Sarcocystis have been described but three of them are known to have a zoonotic potential. These are: S. hominis, S. heydorni and S. suihominis. Domestig pigs and wild boars can be intermediate hosts for S. suihominis, wheras cattle for S. hominis and S. heydorni. Therefore, people can become infected after eating raw or insufficiently heat-treated pork, wild boar meat or beef. Human sarcocystosis is generally asymptomatic but in some cases can induce the syptoms of intestinal illness. People can also become accidental intermediate hosts after ingesting sporocysts from feces-contaminated food or water leading to muscular sarcocystosis. The cysts of Sarcocystis spp. (sarcocysts), which with some exceptions, are not visible and therefore they are rarely detected during routine veterinary meat inspection consisting of visual assessment of muscle tissue and digestion (in case of examination of pig and wild boar meat). The presence of visible cysts of Sarcocystis spp. can lead to meat condemnation and it generates economic losses for farmers. Food safety regulations require the control of the parasites presence in meat intended for human consumption but there are no regulations regarding the control of Sarcocystis spp. Nevertheless, European Food Safety Authority (EFSA) encourage to monitor and characterise Sarcocystis ssp. in animal and foodstuffs.

Integrity Assessment of an In-Service Gas Pipeline Featuring Dent Defect at a Highway Crossing

Underground pipelines are susceptible to different types of damage/flaws such as metal loss, buckling, dents, gouges, cracks, etc. during installation and operation. The structural integrity of the pipelines featuring such defects needs to be ensured for safe operation and to avoid serious hazards (fire/explosion/fatality/injury etc.). This paper discusses the integrity assessment of an actual case of an in-service gas pipeline featuring dent damage located at a highway crossing. A routine in-line inspection (ILI) of the considered pipeline showed the presence of a dent type of damage with a maximum depth of 5% spread over an area of 325 mm x 275 mm. Since the pipeline is located approximately 7.5 m below a 10-lane expressway with heavy traffic, dig verification of the dent was found to be not feasible. Level-3 integrity assessment based on API 579-1/ASME-FFS-1 2021 Fitness-For-Service standard has been performed using commercial finite element (FE) software ABAQUS/CAE. The considered pipeline is subjected to overburden pressure of soil embankment and cyclic loads such as vehicular loads (as per IRC: 6-2017) and internal pressure. The dented pipeline segment was assessed for potential failure modes i.e., protection against plastic collapse, local failure, collapse from buckling, and fatigue damage. FE analysis of the pipeline-soil system has been carried out considering the material and geometric nonlinearity, and contact interactions. The study suggests the pipeline is safe for further operation with existing dented defects. The methodology presented in this paper can act as a guide for the integrity assessment of pipelines with dent damage located at highway crossings.

Damage Detection and Condition Assessment of Civil Engineering Structures Using Structural Health Monitoring

Damage identification is critical in evaluating the condition and performance of the existing civil infrastructure. This requires not just routine or critical event-based inspections, but rather a means of continuous monitoring of a structure to provide an assessment of changes as a function of time and an early warning of an unsafe condition using real-time data. Health monitoring plays an important role in the construction and maintenance of the infrastructure. It employs in situ, continuous, or regular measurements and analyses of key structural and environmental parameters under the operating conditions to identify if a damage has occurred, define its location, and estimate its severity, evaluate its consequences on the residual life of the structure also to provide warning of impending abnormal states or accidents to avoid casualties and to inform maintenance and rehabilitation decisions. SHM takes advantage of the new technologies in sensing, instrumentation, communication, and modelling to integrate them into an intelligent system. Structural Health Monitoring for civil structures is becoming increasingly popular in Europe and worldwide because of the opportunities that it offers in the fields of construction management and maintenance. Reduction of inspection costs, research, with the possibility to better understand the behaviour of structures under dynamic loads, seismic protection, observation, in real or near real-time, of the structural response and of evolution of damage, so that it is possible to produce post-earthquake scenarios and support rescue operations, are the main advantages related to the implementation of such techniques.

Non-destructive corrosion inspection of reinforced concrete structures using an autonomous flying robot

Autonomous non-destructive testing (NDT) on reinforced concrete structures has a large potential to overcome the limitations of current routine inspection techniques, often not capable of detecting corrosion at an early stage. Here, the development and validation of two probes, tailored to acquire contact-based NDT data with the help of a hexacopter, is presented. Each probe allows the combined measurement of two essential parameters in the condition assessment: half-cell potentials and concrete electrical resistivity. Strategies are presented to monitor probe functionality during operation and detect loss of contact between probe and structure, which is considered essential for autonomous NDT. The presented approach enables effective and reliable autonomous corrosion inspection, surpassing traditional visual inspections by localizing corrosion at an early stage, allowing engineers a better planning of maintenance. The successful application in a concrete bridge inspection sets the stage for future research in autonomous inspections with robots in various fields of applications.

DISASTER PREPAREDNESS OF THE HISTORIC CHURCHES (HOUSE OF WORSHIP) IN THE PROVINCE OF CAVITE

Cavite is a historical province in the Philippines the province is also known for historical Churches. This study assessed the disaster preparedness of the historical churches. The method is qualitative in nature and utilized interviews as the instrument of the study. The respondents are representatives of each historical church. The results show that NHCP is aware of the ancient churches' vulnerability to disasters based on their findings. Disaster response is a problem since historical churches aren't given priority and because of the geographical characteristics that rendered them vulnerable. Due to their significance to religion, culture, history, and identity, historic churches have social significance. Due to its age, worth to the community, and importance, historic museums must be prepared for disasters. While local governments have developed measures to reduce flooding, floods can be avoided provided that government policies and regular water level monitoring are put into practice. Earthquakes can cause the historical churches to shake. For disaster readiness in the event of ground shaking, the NHCP and the local government coordinate. Finally, since ground shaking cannot be entirely avoided, precautions like routine structural inspections are made.

Failure analysis and reliability assessment of a type of aero-engine combustion chamber thermal barrier coatings

During a routine hole probe inspection, the aviation division found that the combustion chamber flame tube of a V2500 aero engine had failed early and that the TBCs around the vent holes on the flame tube liner panel 4 had peeled off over a large area, causing the flame tube liner to burn through. This work studies the premature failure of the V2500 aero-engine flame tube and, using modeling and simulation tests, finds the reason for premature failure as a substantial area of thermal barrier coating peeling owing to sintering. The sintering procedure significantly increases the thermal barrier coating's Young's modulus, which reduces the coating's resistance to thermal mismatch strain. The reliability of the TBCs was then evaluated using a probabilistic approach. Owing to the non-uniformity of temperature distribution induced by the hot airflow, the lifetime of the TBCs in the high temperature region is only around 3000 h, but the lifetime in the low temperature region is at least 25,000 h. Using the method of hole-probing, the values of the calculated and real outcomes are compared. The relative error is less than 5 %, demonstrating that the suggested approach for evaluating dependability has high credibility and applicability.

Relation between EP-like lesions and pleurisy with pluck and gut lesions in slaughtered pigs in Northern Portugal

Respiratory diseases have a great impact in the swine production industry. Macroscopic lesions in lungs are often detected during routine post-mortem inspection in the slaughterhouse, with enzootic pneumonia-like lesions (EP-like lesions) and pleuritic lesions being the most common. EP-like lesions, which are primary related with Mycoplasma hyopneumoniae infection, are characterised by consolidation areas, demarcated purple or grey areas in the lungs. Actinobacillus pleuropneumoniae is a respiratory pathogen and the suggestive lesions associated with previous infections of this agent are commonly chronic pleurisy lesions located in the dorso-caudal regions from the lungs. This type of lesion is commonly evaluated by the Slaughterhouse Pleurisy Evaluation System (SPES). The aim of this study was to determine the occurrence of EP-like lesions and pleurisy in 2,142 finishing pigs from 18 different farms (central Portugal, southern Portugal, and northern Spain), the association between EP-like lesions and pleurisies, and the relationship with pluck lesions (lobe scars, emphysema, lung congestion, pericarditis, liver milk spots lesions, and steatosis) and gut lesions (splenitis, pancreatitis, enteritis). For this purpose, EP-like lesions were classified per lobe under the method of enzootic pneumonia–like lesions. Pleurisy lesions were classified under the SPES score method. The presence of other lesions such as pericarditis, liver milk spots, splenitis, pancreatitis, lymphadenitis, and enteritis were also evaluated. Descriptive and multivariate logistic regression analyses were carried out. A variable was considered statistically significant when its P-value≤ 0.05, i.e. its 95% confidence interval of the Odds Ratio (OR) does not contain 1. Among the sample, 41.1% pigs presented EP-like lesions (20.5% registered EP-like lesions scored 1–3, and 20.7% scored 4–24). Around 12% of the sample presented pleurisy, of which 4.8% were of a degree 4 level. Following the EP-like lesions and pleurisy, liver milk spots and pericarditis were the most frequent lesions (4.8% and3.6%, respectively). In this study, the most affected lobes by EP-like lesions were the medial and cranial lobes. The higher the EP-like lesion score, the lower the incidence of presenting an SPES score of 4 (OR=0.38, P&amp;lt;0.001). The higher the SPES scores, the lower the incidence of an EP-like lesion score of category 1 (OR=0.86, P=0.031) or category 2 (OR=0.71, P&amp;lt;0.0001). Pericarditis was associated with a higher incidence of SPES scores 1 (OR=8.57, P&amp;lt;0.001), 2 (OR=7.29, P&amp;lt;0.001), or 4 (OR=26.55, P&amp;lt;0.001). Consolidated pneumonia lesions were the most common cause of partial rejection for human consumption, followed by pleuritic lesions, milk spot lesions, and pericarditis. This study reinforces the importance of monitoring respiratory findings of pig carcasses at the slaughterhouse. It is advantageous to assess the animal’s production performance and welfare. Moreover, lung lesions are closely associated with other findings in tissues and organs with economic value, which can be subclinical or difficult to diagnose in live animals. Furthermore, to the best of our knowledge, this is the only study of its kind carried out in Portugal.