Despite advanced analytical methods and increasing data availability, most intensive care unit (ICU) prediction models rely on static measurements. However, longitudinal monitoring of biomarkers may better capture disease progression and support timely, individualized interventions within the framework of predictive, preventive, and personalized medicine (PPPM). Since the COVID-19 pandemic, interest in both static and dynamic modelling has expanded. Therefore, this review aimed to summarize current evidence on the use of longitudinal blood biomarker data in ICU prediction models, assess how the pandemic shaped this research, and report validation strategies. This scoping review followed the PRISMA-ScR guidelines. PubMed and Google Scholar were searched for studies on blood biomarker trajectory analysis in the ICU published between 2014 and 2025, covering five years before and after the onset of the COVID-19 pandemic. Forty-seven studies were included, mainly from North America (47

Traditional and COVID-19-specific severity scores are applied in intensive care units (ICUs) to guide decision-making and predict mortality. Since traditional severity scores (APACHE II, SAPS II, SAPS 3, and SOFA) were not originally designed for SARS-CoV-2, this study compared their performance with COVID-19-specific models (Shang-COVID and SEIMC), including a novel distinction between early (<= 7 days) and late (>7 days) ICU mortality. Adult ICU COVID-19 patients from the first two pandemic waves in Portugal were included (n = 286). Six scores were calculated, and four outcomes assessed: hospital, ICU, early ICU, and late ICU mortality. Discrimination was assessed using ROC curves with AUCs, 95% CIs, and p-values. AUCs were compared using the Delong test (early vs. late ICU mortality and across scores within each wave) and the Hanley & McNeil test (between waves for each score). Traditional scores demonstrated robust mortality prediction. SEIMC performed well for hospital (AUC(wave1) = 0.808; AUC(wave2) = 0.724) and ICU mortality (AUC(wave1) = 0.805; AUC(wave2) = 0.706). SEIMC (AUC(wave1) = 0.786; AUC(wave2) = 0.800) and Shang-COVID (AUC(wave1) = 0.617; AUC(wave2) = 0.736) showed potential for early mortality prediction but require further validation and recalibration. Overall performance was superior during the first wave, likely reflecting differences in patient characteristics, viral variants, and health measures. Traditional severity scores demonstrated stable robust prediction of ICU and hospital mortality in COVID-19 cases. Disease-specific scores did not significantly outperform established models, though also showed good predictive ability in some contexts, particularly early ICU mortality. These findings highlight the need for continuous validation and recalibration of predictive tools as clinical contexts evolve.

Predicting disease states and outcomes—and anticipating the need for specific procedures—enhances the efficiency of patient management, particularly in the dynamic and heterogenous environments of intensive care units (ICUs). This study aimed to develop robust predictive models using small sets of blood analytes to predict disease severity and mortality in ICUs, as fewer analytes are advantageous for future rapid analyses using biosensors, enabling fast clinical decision-making. Given the substantial impact of inflammatory processes, this research examined the serum profiles of 25 cytokines, either in association with or independent of nine routine blood analyses. Serum samples from 24 male COVID-19 patients admitted to an ICU were divided into three groups: Group A, including less severe patients, and Groups B and C, that needed invasive mechanical ventilation (IMV). Patients from Group C died within seven days after the current analysis. Naïve Bayes models were developed using the full dataset or with feature subsets selected either through an information gain algorithm or univariate data analysis. Strong predictive models were achieved for IMV (AUC = 0.891) and mortality within homogeneous (AUC = 0.774) or more heterogeneous (AUC = 0.887) populations utilizing two to nine features. Despite the small sample, these findings underscore the potential for effective prediction models based on a limited number of analytes.

Background/Objectives: Heart rate variability (HRV) has been widely investigated as a predictor of disease and mortality across diverse patient populations; however, there remains no consensus on the optimal set or combination of time and frequency domain nor on nonlinear features for reliable prediction across clinical contexts. Given the relevance of the COVID-19 pandemic and the unique clinical profiles of these patients, this retrospective observational study explored the potential of HRV analysis for early prediction of in-hospital mortality using ECG signals recorded during the initial moments of ICU admission in COVID-19 patients. Methods: HRV indices were extracted from four ECG leads (I, II, III, and aVF) using sliding windows of 2, 5, and 7 min across observation intervals of 15, 30, and 60 min. The raw data posed significant challenges in terms of structure, synchronization, and signal quality; thus, from an original set of 381 records from 321 patients, after data pre-processing steps, a final dataset of 82 patients was selected for analysis. To manage data complexity and evaluate predictive performance, two feature selection methods, four feature reduction techniques, and five classification models were applied to identify the optimal approach. Results: Among the feature aggregation methods, compiling feature means across patient windows (Method D) yielded the best results, particularly for longer observation intervals (e.g., using LDA, the best AUC of 0.82±0.13 was obtained with Method D versus 0.63±0.09 with Method C using 5 min windows). Linear Discriminant Analysis (LDA) was the most consistent classification algorithm, demonstrating robust performance across various time windows and further improvement with dimensionality reduction. Although Gradient Boosting and Random Forest also achieved high AUCs and F1-scores, their performance outcomes varied across time intervals. Conclusions: These findings support the feasibility and clinical relevance of using short-term HRV as a noninvasive, data-driven tool for early risk stratification in critical care, potentially guiding timely therapeutic decisions in high-risk ICU patients and thereby reducing in-hospital mortality.

Background: ANCA-associated vasculitis (AAV) with glomerulonephritis (AAV-GN) still carries poor prognosis despite treatment improvement over the years. Currently, improving assessment of disease activity and severity and defining risk factors for ESKD pose challenges. Objectives: In this study we aimed to determine and characterize risk factors associated with progression to ESKD or death in patients with AAV-GN. Methods: We retrospectively analyzed all AAV-GN cases of our Center. ESKD was considered as a composite outcome of eGFR<15 or dialysis dependency. Biopsies were classified according to Berden's classification (BC), Brix's renal risk score (RRS), Mayo Clinic Chronicity Score (MCCS) and AAV-GN combined score (AAV-GN-CS). Categorical variables were analysed by non-parametric chi-square or fisher's exact test; and continuous variables by Mann-Whitney U test. Cox regression models were applied for death and Kaplan-Meier estimator. Significance value α=0.05 was considered. Results: A total of 74 patients, 56,8% male, 69 years-old median age were included. Of them, 81.2% were MPO, 11.6% PR3 and 7.2% negative. At presentations, 35.3% had alveolar haemorrhage, 13.4% GI and 66.7% constitutional manifestations. At diagnosis, median eGFR was 7.5 mL/min/1.73m2 (5.0-13.0), proteinuria 2.2g/g (0.45-4.17) and all patients had haematuria. Initial median ANCA titer (ATi) was 100 UI/mL (51-134) and at last follow-up 44 (15-101). 64.2% of all patients required dialysis at presentation. Of these, 14,0% recovered until discharge. We also analyzed biopsies of 57 patients According to BC, 15.8% were focal, 40.4% crescentic, 26.3% mixed, and 17.5% focal. ESKD risk were medium in 28.3% and high in 69.8 %, as determined by RRS; whereas low in 31%, intermediate in 42.3% and high in 19% as per AAV-GN-CS. Induction treatment (IT) used was CYC in 46.3%, CYC+RTX in 18.3% and RTX in 3.3%. Only 17 patients (26.2%) were added PLEX. Only 28% achieved kidney remission (KRm), 7% relapsed and 68.7% developed ESKD. Of them, 95.5% had eGFR<15 at diagnosis, 30% low C3, 37.5% crescentic pattern, 28.1% mixed and 28.1% sclerotic. 87% of ESKD patients had <25% normal glomeruli (NG), and 87.1% high ESKD risk (RRS). Progression to ESKD was associated with lower eGFR (p<0.001) and low C3 at diagnosis (p=0.026), lower %NG (p=0.004), higher %CG (p=0.004), higher %IFTA (p=0.011), worse BC (p=0.012), higher RRS (p<0.001) and MCCS categories (p=0.010). AAV-GN-CS was not. ATi reduction seems to determine better renal outcome (p=0.042). No significant differences were seen with IT or maintenance treatment, nor with PLEX addition. No patient treated with RTX or combined treatment developed ESKD. Mortality was 32.8% and the best predictive model includes age, GI manifestations and KRm (p<0.001). Age (p=0.004), lower eGFR at diagnosis(p=0.016) and GI manifestations (p=0.003) were predictive of death, while achieving KRm improved survival (p=0.009). Conclusion: Our results show that AAV-GN patients have poor kidney outcome when presenting with severe kidney dysfunction, high ANCA titers and low C3 levels. Worse histological scoring is determinant of ESKD. The prediction power of RRS and AAV-GN-CS must be demonstrated in large cohorts, adding clinical and laboratory data. RTX effectivity on kidney survival must be further supported. Patient survival is related with older age, clinical presentation, and achievement of kidney remission.REFERENCES: NIL. Acknowledgements: NIL. Disclosure of Interests: None declared.

Background: COVID-19 caused a pandemic, due to its ease of transmission and high number of infections. The evolution of the pandemic and its consequences for the mortality and morbidity of populations, especially the elderly, generated several scientific studies and many research projects. Among them, we have the Predictive Models of COVID-19 Outcomes for Higher Risk Patients Towards a Precision Medicine (PREMO) research project. For such a project with many data records, it is necessary to provide a smooth graphical analysis to extract value from it. Methods: In this paper, we present the development of a full-stack Web application for the PREMO project, consisting of a dashboard providing statistical analysis, data visualization, data import, and data export. The main aspects of the application are described, as well as the diverse types of graphical representations and the possibility to use filters to extract relevant information for clinical practice. Results: The application, accessible through a browser, provides an interactive visualization of data from patients admitted to the intensive care unit (ICU), throughout the six waves of COVID-19 in two hospitals in Lisbon, Portugal. The analysis can be isolated per wave or can be seen in an aggregated view, allowing clinicians to create many views of the data and to study the behavior and consequences of different waves. For instance, the experimental results show clearly the effect of vaccination as well as the changes on the most relevant clinical parameters on each wave. Conclusions: The dashboard allows clinicians to analyze many variables of each of the six waves as well as aggregated data for all the waves. The application allows the user to extract information and scientific knowledge about COVID-19’s evolution, yielding insights for this pandemic and for future pandemics.

Background and Objectives: Given the wide spectrum of clinical and laboratory manifestations of the coronavirus disease 2019 (COVID-19), it is imperative to identify potential contributing factors to patients' outcomes. However, a limited number of studies have assessed how the different waves affected the progression of the disease, more so in Portugal. Therefore, our main purpose was to study the clinical and laboratory patterns of COVID-19 in an unvaccinated population admitted to the intensive care unit, identifying characteristics associated with death, in each of the first three waves of the pandemic. Materials and Methods: This study included 337 COVID-19 patients admitted to the intensive care unit of a single-center hospital in Lisbon, Portugal, between March 2020 and March 2021. Comparisons were made between three COVID-19 waves, in the second (n = 325) and seventh (n = 216) days after admission, and between discharged and deceased patients. Results: Deceased patients were considerably older (p = 0.021) and needed greater ventilatory assistance (p = 0.023), especially in the first wave. Differences between discharged and deceased patients' biomarkers were minimal in the first wave, on both analyzed days. In the second wave significant differences emerged in troponins, lactate dehydrogenase, procalcitonin, C-reactive protein, and white blood cell subpopulations, as well as platelet-to-lymphocyte and neutrophil-to-lymphocyte ratios (all p < 0.05). Furthermore, in the third wave, platelets and D-dimers were also significantly different between patients' groups (all p < 0.05). From the second to the seventh days, troponins and lactate dehydrogenase showed significant decreases, mainly for discharged patients, while platelet counts increased (all p < 0.01). Lymphocytes significantly increased in discharged patients (all p < 0.05), while white blood cells rose in the second (all p < 0.001) and third (all p < 0.05) waves among deceased patients. Conclusions: This study yields insights into COVID-19 patients' characteristics and mortality-associated biomarkers during Portugal's first three COVID-19 waves, highlighting the importance of considering wave variations in future research due to potential significant outcome differences.

ANCA-associated vasculitis (AAV) with glomerulonephritis (AAV-GN) carries poor prognosis despite treatment improvement. Current challenges include improving assessment of disease activity/severity and define risk factors for ESKD. We aim to characterize and determine factors associated with progression to ESKD or death.

Identifying high-risk patients, particularly in intensive care units (ICUs), enhances treatment and reduces severe outcomes. Since the pandemic, numerous studies have examined COVID-19 patient profiles and factors linked to increased mortality. Despite six pandemic waves, to the best of our knowledge, there is no extensive comparative analysis of patients’ characteristics across these waves in Portugal. Thus, we aimed to analyze the demographic and clinical features of 1041 COVID-19 patients admitted to an ICU and their relationship with the different SARS-Cov-2 variants in Portugal. Additionally, we conducted an in-depth examination of factors contributing to early and late mortality by analyzing clinical data and laboratory results from the first 72 h of ICU admission. Our findings revealed a notable decline in ICU admissions due to COVID-19, with the highest mortality rates observed during the second and third waves. Furthermore, immunization could have significantly contributed to the reduction in the median age of ICU-admitted patients and the severity of their conditions. The factors contributing to early and late mortality differed. Age, wave number, D-dimers, and procalcitonin were independently associated with the risk of early death. As a measure of discriminative power for the derived multivariable model, an AUC of 0.825 (p < 0.001; 95

Abstract Background and Aims nutritional status clearly has a great impact on the prognosis of maintenance hemodialysis patients. Therefore, its management should be a priority and risk screening frequent and easily implemented, based on the biochemical and clinical routine parameters already available. Many tools fit these simple criteria, namely simple Protein Energy Wasting score (sPEW), Geriatric Nutritional Risk Index (GNRI) and Creatinine Index (Cr Index). These scores are associated with a high mortality and morbidity risk in hemodialysis (HD) patients. The objective of this study was to assess the performance of these tools regarding the estimation of all-cause mortality, in a 45-months follow-up of a large patient cohort. Method Historical cohort study of HD pts from 25 outpatient clinics. sPEW, GNRI and Cr Index were estimated. Kaplan-Meier estimator and univariable Cox regression models to analyze time until death were used. To compare survival curves the log-rank test or Tarone test were used, as appropriate. The level of significance α = .05 was considered. All data were analyzed using SPSS 22.0 (IBM Corp. Released 2013. IBM SPSS Statistics for Windows. Armonk, NY, USA: IBM Corp). Results We analyzed 2322 pts, 59% males, 31.7% diabetic, with a median age of 70 years (P25 = 60, P75 = 79) followed up for a maximum of 45-month (P25 = 31; P75 = 45). All-cause mortality was observed in 778 pts (33.5%). To assess the mortality risk, the exposures GNRI and CR Index, were discretized using quartiles. GNRI The median was 106.6 (P25 = 99.4, P75 = 114.2). The log-rank test results showed a significantly lower survival for patients in GNRI Q1 category (GNRI ≤ 99.4). A p-value <0.001 was obtained when comparing patients in Q4, Q3 and Q2 with patients in Q1. The univariable Cox regression model showed that patients in Q1 had a 2-fold increased risk of death, when compared with Q4 (HR = 2.1, 95% CI: 1.7-2.6, p<0.001). Creatinine Index The median was 12.648 (P25 = 11.908, P75 = 13.406). The log-rank test for the equality of survival functions for the different levels was considered statistically significant and showed a significantly lower survival for patients in CR Index Q1 category, when compared with the remaining categories (p<0.001). The univariable Cox regression model showed that comparatively with Q4, patients in Q1 had a 5-fold increased risk of death (HR = 4.8, 95% CI: 3.7-6.0, p<0.001), patients in Q2 a 3-fold increased risk of death (HR = 3.1, 95% CI:2.4– 3.9, p<0.001), and patients in Q3 a 2-fold increased risk of death (HR = 1.9, 95% CI: 1.4 – 2.4, p<0.001). sPEW The frequency of each score from 0 to 4 was 306, 380, 111, 1369 and 156, respectively. The log-rank test for the equality of survival functions corresponding to the different levels showed a significantly higher survival for patients with a sPEW score of 4 when comparing with the remaining levels (p<0.001). The univariable Cox regression model showed that comparatively with a score of 4, patients with a: score of 0 had an 8-fold increased risk of death (HR = 7.7, 95% CI: 4.5-13.3, p<0.001), score of 1 a 6-fold increase risk of death (HR = 5.6, 95% CI: 3.3– 9.7, p<0.001), score of 2 a 4-fold increase risk of death (HR = 4.1, 95% CI: 2.2– 7.7, p<0.001), and a score of 3, almost a 4-fold increased risk of death (HR = 3.7, 95% CI: 2.2– 6.3, p<0.001). Conclusion In this exploratory analysis, the three tools showed a significant association with mortality during follow-up. These tools, if adequately validated in future studies, may select patients for further intervention to modify the outcome.

Besides the pandemic being over, new SARS-CoV-2 lineages, and sub-lineages, still pose risks to global health. Thus, in this preliminary study, to better understand the characteristics of COVID-19 patients and the effect of certain hematologic biomarkers on their outcome, we analyzed data from 337 patients admitted to the ICU of a single-center hospital in Lisbon, Portugal, in the first three waves of the pandemic. Most patients belonged to the second (40.4%) and third (41.2%) waves. The ones from the first wave were significantly older and relied more on respiratory techniques like invasive mechanic ventilation and extracorporeal membrane oxygenation. There were no significant differences between waves regarding mortality in the ICU. In general, non-survivors had worse laboratory results. Biomarkers significantly associated with death changed depending on the waves. Increased high-sensitivity cardiac troponin I results, and lower eosinophil counts were associated to death in all waves. In the second and third waves, the international normalized ratio, lymphocyte counts, and neutrophil counts were also associated to mortality. A higher risk of death was linked to increased myoglobin results in the first two waves, as well as increased creatine kinase results, and lower platelet counts in the third wave.

Studies analyzing the relationship between BK polyomavirus (BKV) or JC polyomavirus (JCV) infection and kidney transplant (KT) long term clinical outcomes are scarce. Therefore, we evaluated this relationship in a single-center retrospective cohort of 288 KT patients followed for 45.4(27.5; 62.5) months. Detection of BKV viremia in two consecutive analyses led to discontinuation of antimetabolite and initiation of mammalian target of rapamycin inhibitor. Outcome data included de novo BKV and/or JCV viremia and/or viruria after KT, death-censored graft survival and patient survival. BKV viruria and viremia were detected in 42.4% and 22.2% of KT recipients, respectively. BKV viremic patients had higher urinary BKV viral loads at the onset of viruria, when compared to nonviremic patients (7 log10 vs. 4.9 log10  cp/mL, p < 0.001). JCV viruria was identified in 38.5% of KT patients; the 5.9% of KT recipients who developed JCV viremia had higher JCV urinary viral loads at the onset of viruria, when compared to non-viremic patients (5.3 vs. 3.7 log10 cp/mL, p = 0.034). No differences were found in estimated glomerular filtration rate at the end of follow up, when comparing BKV or JCV viruric or viremic patients with nonviremic patients. No association was found between JCV or BKV viruria or viremia and death/graft failure. Therefore, higher BKV urinary viral loads at the onset could serve as an early maker of over immunosuppression. JCV and BKV replication was not associated with inferior clinical outcomes in KT patients with the above-mentioned immunosuppression strategy.

Abstract BACKGROUND Studies on acute kidney injury (AKI) in hematopoietic stem cell transplant (HSCT) consider several haematologic diagnoses in their cohorts and heterogeneous definitions for AKI not taking into consideration urinary output (UO). We aimed to evaluate the incidence and risk factors of the first AKI episode in patients with leukaemia submitted to allogeneic HSCT occurring in the first 100 days post-HSCT, considering both SCr and UO criteria in KDIGO classification. METHODS We conducted a single-center retrospective cohort study, including patients with leukaemia admitted for allogeneic HSCT between 2005 and 2015. KDIGO classification was used for AKI diagnosis considering daily values of SCr and 6-h UO from admission day for HSCT until hospital discharge, and weekly evaluations within the first 100 days beyond hospital discharge. To estimate AKI cumulative incidence and to establish AKI risk factors, survival analysis methods considering death as a competing risk were used. RESULTS A total of 164 patients, 54.3% female, 91.5% Caucasian, median age 39.1 (P25 = 28.1–P75 = 50.4), body mass index 23.2(20.9–25.3), HCT-CI (haematopoietic cell transplantation-specific comorbidity index) < 2 in 85.4% of patients. Of them, 55.5% had acute myeloid leukaemia, 33.5% had acute lymphoblastic leukaemia, 8.5% had chronic myeloid leukaemia and 2.4% had rare forms of leukaemia. A total of 6.7% had been submitted to radiotherapy in the past, median number of chemotherapy cycles was 3 (2–4). A total of 71.3% were prescribed a reduced-intensity conditioning regimen, 56.1% had a related donor and peripheral blood was the source of progenitor cells in 13.4%. In the 100 days post-HSCT, 89.6% developed sepsis, 82.9% were exposed to nephrotoxic drugs, 39.0% had hypovolemia, 25.0% complicated with shock and 7.9% went to intensive care unit. A total of 71.3% developed graft versus host disease, 32.3% registered cytomegalovirus infection. The cumulative incidence of AKI was 58.5% at 30 days post-HSCT and 63.4% at 100 days post-HSCT. AKI diagnosis was first made by SCr criteria in 76.9%, by UO criteria in 15.4% and by both in 7.7%. The highest stage of AKI was 1 in 61.8%, 2 in 21.6% and 3 in 16.7%. A total of 12.5% underwent renal replacement therapy. In our multivariable model, variables independently associated with a higher incidence of AKI were: HCT-CI < 2 [HR 1.88, 95% confidence interval (95% CI) 1.13–3.11; P = .015], previous radiotherapy (HR 2.07, 95% CI 1.06–4.03; P = .034), shock (HR 1.57, 95% CI 1.02–2.39; P = .039), LDH (HR 1.51, 95% CI 1.03–2.21; P = .035) and sepsis (HR 3.36, 95% CI 1.22–9.24; P = .019). CONCLUSIONS AKI incidence affects almost two-thirds of patients with acute and chronic leukaemia submitted to allogeneic HSCT. More than 25% of AKI patients reach stages 2–3. HCT-CI, previous radiotherapy, shock, LDH and sepsis are important independent AKI risk factors. This should bring the attention to the need of developing prevention strategies towards these aspects. This is the first study considering both SCr and UO for defining AKI by KDIGO classification in HSCT, as well as focusing specifically on patients with leukaemia. This approach contributes for a more accurate evaluation and bias reduction.

Tinnitus is a phantom sound perceived in the absence of external acoustic stimulation. It is described in a variety of ways (e.g., buzzing, ringing, and roaring) and can be a single sound or a combination of different sounds. Our study evaluated associations between audiological parameters and the presence or severity of tinnitus, to improve tinnitus diagnosis, treatment, and prognosis. Our sample included 122 older participants (63 women and 59 men), aged 55–75 years from the Portuguese population, with or without sensory presbycusis and with or without tinnitus. All participants underwent a clinical evaluation through a structured interview, Ear, Nose, and Throat observation, and audiological evaluation (standard and extended audiometry, psychoacoustic tinnitus evaluation, auditory brainstem responses, and distortion product otoacoustic emissions). The Tinnitus Handicap Inventory was used to measure tinnitus symptom severity. Our data confirmed that the odds of developing tinnitus were significantly higher in the presence of noise exposure and hearing loss. Also, participants who had abrupt tinnitus onset and moderate or severe hyperacusis featured higher odds of at least moderate tinnitus. However, it was in the ABR that we obtained the most exciting and promising results, namely, in wave I, which was the common denominator in all findings. The increase in wave I amplitude is a protective factor to the odds of having tinnitus. Concerning the severity of tinnitus, the logistic regression model showed that for each unit of increase in the mean ratio V/I of ABR, the likelihood of having at least moderate tinnitus was 10% higher. Advancing knowledge concerning potential tinnitus audiological biomarkers can be crucial for the adequate diagnosis and treatment of tinnitus.

Kidney transplant patients (KT) are at high risk for severe COVID‐19 and presented attenuated antibody responses to vaccination when compared to immunocompetent individuals. Torquetenovirus (TTV) has recently gained attention as a potential surrogate marker of the net state of immunosuppression. We evaluated the association between pre‐vaccination TTV viral load and anti‐spike total antibody response to SARS‐CoV‐2 vaccination in KT.

Abstract BACKGROUND AND AIMS Nutritional status management and rehabilitation are significant concern treating maintenance haemodialysis (HD) patients. Oral nutritional supplements are essential to complement insufficient dietary intake, namely of energy and protein, and to rehabilitate a patient's nutritional status. Therefore, the objective of this preliminary study was to assess the impact of oral nutritional supplementation (ONS) prescription patterns on patients’ nutritional status. METHOD We did a cross-sectional analysis of HD patients’ first oral nutritional supplementation with commercial formulas between October 2018 and March 2020 in 25 outpatient HD clinics. The registered nutritionist dietitian decided to initiate, choosing the type of supplement and dose as part of a routine protocol of a comprehensive nutritional intervention and assessment. We assessed albumin, normalized protein catabolic rate, potassium and phosphate at the beginning (t = 0) and end (t = 1) of the supplementation period to understand the nutritional impact. We also estimated the daily proportion of energy, and protein contribution of each oral nutritional supplementation implemented, categorizing in cut-offs of 100 kcal and 5 g of protein. RESULTS We analyzed 398 patients, 217 (54.5%) males, 165 (41.5%) diabetic, with a median age of 79 years. Concerning feeding support status, 24.6% were autonomous, 54.8% had family care and 20.6% were institutionalized. Globally, the ONS impact was significant in the increment of albumin (P < 0.001) and nPCR (P = 0.002), although nPCR was not significant in the categorized group providing <5 g of protein/day (Table 2). The increment of K was also significant (P < 0.001) but not clinically relevant in increasing the risk of hyperkalaemia. There was no significant difference in P (P = 0.086). CONCLUSION ONS significantly impacted nutritional rehabilitation, with an albumin and nPCR increase (except for the categorized group of < 5 g protein/day). Although the increment of potassium was statistically significant, it was not clinically relevant in increasing the risk of hyperkalaemia. Further analyses are needed to understand the best targets for the energy and protein contribution of ONS.

Hydropressor systems are of paramount importance in keeping water supplies running properly. A typical such device consists of two (or more) identical electropumps operating alternately, so as to avoid downtime as much as possible. A first challenge was, considering a dual pump configuration, to identify the ideal usage proportion of each pump (from 0%-100%, meaning interchange only upon failure, to 50%-50%, where each pump works half the time) in order to improve availability, accounting solely for corrective maintenance. A second challenge, related to the first one, consisted of improving the availability of a single pump under the hazard of failure in three different ways (with their own occurrence frequencies), while accounting also for preventive maintenance. Each challenge was tackled through Monte-Carlo simulation and the models were implemented with the Python programming language. The results seem to indicate that significant improvements to standard industry practice can be made.

OBJECTIVE:Since its development, cumulative evidence has accumulated regarding the prognostic value of the Malnutrition-Inflammation Score (MIS/Kalantar score) prognostic value; however, there is a shortage of recent and large studies with comprehensive statistical methodologies that contribute to support a higher level of evidence and a consensual cutoff. The aim of this study was to assess the strength of MIS association with hospitalization and mortality in a nationwide cohort.METHODS:This was a historical cohort study of hemodialysis patients from 25 outpatient centers followed up for 48 months. Univariable and multivariable Cox additive regression models were used to analyze the data. The C-index was estimated to assess the performance of the final model.RESULTS:Two thousand four hundred forty-four patients were analyzed, 59.0% males, 32.0% diabetic, and median age of 71 years (P25 = 60, P75 = 79). During a median period of 45-month follow-up, with a maximum of 48 months (P25 = 31; P75 = 48), 875 patients presented an MIS <5 (35.8%) and 860 patients (35.2%) died. The proportion of deaths was 23.1% for patients with the MIS <5 and 41.9% if the MIS ≥5 (P < .001). A total of 1,528 patients (62.5%) were hospitalized with a median time to the first hospitalization of 26 months (P25 = 9; P75 = 45). A new cutoff point regarding the risk of death, MIS ≥6, was identified for this study data set. In multivariable analysis for hospitalization risk, a higher MIS, higher comorbidity index, and arteriovenous graft or catheter increased the risk, whereas higher Kt/V and higher albumin had a protective effect. In multivariable analysis for mortality risk, adjusting for age, albumin, normalized protein catabolic rate, Charlson comorbidity index, interdialytic weight gain, Kt/V, diabetes, hematocrit, and vascular access, patients with the MIS ≥6 showed a hazard ratio of 1.469 (95% confidence interval: 1.262-1.711; P < .001). Higher age, higher interdialytic weight gain, higher comorbidity index, and catheter increased significantly the risk, whereas higher Kt/V, higher albumin, and higher normalized protein catabolic rate (≥1.05 g/kg/d) reduced the risk.CONCLUSION:The MIS maintains its relevant and significant association with hospitalization and mortality.

Background: Adherence to PAP treatment is a mainstay in the management of patients (pts) with OSA, although this is often difficult to attain and to maintain in the long term. At our outpatient clinic each patient is evaluated along the time by a multidisciplinary team, being expected that this follow-up program will allow an improved adherence to PAP therapy. Methods: An observational and retrospective longitudinal study was conducted analyzing age, anthropometric, clinical, diagnostic and treatment-related variables over a predefined timeline (initial, 3, 6 and 12 months). Multilevel mixed-effects linear regression models were used to analyze data, and a significance level, α = 0.05, was used. Results: Were analyzed 133 pts. OSA severity was: Severe (70%); Moderate (22%); Mild (8%). Most prevalent PAP mode was Auto-CPAP (86%), with nasal mask (65%) and the most frequent prescribed pressures were 4-12 cmH2O. PAP usage ≥ 90% of total time / usage ≥ 4h/night was 66%/70%, 69%/81%, 71%/90% and 69%/88%, at initial, 3, 6 and 12 M, respectively. The usage ≥ 4h/night had an increasing trend with the time of therapy (p <0.001, comparing initial with 3M, 6M and 12M). AIH and Epworth scale have been significantly improved to normal values (p <0.001). The most frequent complications were excessive leakage, nasal obstruction, excessive pressure and dry mouth. Multivariate analysis showed that higher adherence values (usage ≥ 4h/night) are associated with older ages, higher oxygen dessaturation index and absence of complications (p≤0.001). Conclusion: Our program has a good performance regarding treatment efficacy, with a low prevalence of complications and improved in-night adherence.

IntroductionThe use of perioperative chemotherapy (CT) in patients with advanced gastric carcinoma increases their overall survival. This therapy may also increase the number of patients with R0 resection. Potential drawbacks of this therapy, besides its toxicity, include increased surgical morbidity.MethodsWe retrospectively evaluated the records of patients undergoing gastrectomy with curative intent, for carcinoma, at our institution between January 2009 and August 2018. They were divided into two groups: direct surgery (SURG) and perioperative CT (CHEMO). Patients with other neoadjuvant therapies and cardia Siewert I and II carcinomas were excluded.The primary objective was to evaluate the impact of perioperative CT on surgical morbidity. As secondary objectives, resection radicality and total lymph node count were compared between the two groups.ResultsA total of 307 patients (97 direct surgery and 210 perioperative CT) were evaluated. Median age was 67 years old.The overall major surgical morbidity (Clavien-Dindo 3–5) was 10.6% in the CHEMO group and 12.4 in the SURG group (p=0.643).There was no statistically significant difference between the surgical radicality (R0 98% in the SURG group vs 97.5% CHEMO group (p=0.865). There was an increase in the total number of lymph nodes retrieved in the specimen in the CHEMO group (25 vs 22, p=0.001), a difference that was not maintained in the subgroup analysis as a function of the surgery performed.ConclusionsPerioperative CT in gastric carcinoma does not increase surgical morbidity, surgical radicality and total lymph node count.