Łukasz Jerzy Krzych

Background: Prognosis prediction in adult intensive care units (ICUs) guides clinical decision-making, realistic goal-setting with families, and resource allocation, but is challenged by the marked heterogeneity of critically ill patients in multi-speciality wards. Methods: This narrative review critically analyses commonly used prognostic scoring systems by clinical application timeline. Results: Admission prognostic models, including the Acute Physiology and Chronic Health Evaluation (APACHE II/III/IV), Simplified Acute Physiology Score (SAPS II/SAPS 3) and Mortality Probability Model (MPM), estimate in-hospital mortality from acute physiological derangement and comorbidity; the Clinical Frailty Scale (CFS) adds prognostic value. During the ICU stay, organ dysfunction is tracked with the Sequential Organ Failure Assessment (SOFA/SOFA-2), designed for repeated reassessment, and the Multiple Organ Dysfunction Score (MODS), while the Therapeutic Intervention Scoring System (TISS-28) quantifies nursing workload. At discharge, the Barthel Index, Glasgow Outcome Scale (GOS) and Cerebral Performance Category (CPC) measure functional independence and neurological outcome. Admission-based mortality models use an initial assessment window and may require local recalibration, and discrimination alone does not establish clinical utility. Conclusions: Future directions include trajectory-based models, phenotyping, biomarkers, time-limited trials and machine learning. Prognostic estimates should inform multidisciplinary evaluation and shared decision-making, rather than independently determine treatment intensity or withdrawal.

Background: Severity-of-illness scores and registry-derived risk models assume that the association between a baseline characteristic and death is stable over time. Methods: A retrospective analysis of 25,344 admissions (2010–2020) to 34 intensive care units in the Silesian Registry of Anaesthesiology and Intensive Care, with unchanged variable definitions and intra-ICU death as the outcome, was conducted. For each of 48 characteristics, a characteristic-by-time interaction was tested by likelihood ratio under four implementations of time-chronological quintiles, fixed calendar periods, linear and spline continuous time, each independently Benjamini–Hochberg corrected. Results: Twenty-two of 48 characteristics showed significant heterogeneity in the primary quintile analysis (q < 0.05), with 11 under all four. Adjustment for centre left 12 significant, 6 of which also survived adjustment for case mix. An adjusted model retained discrimination out of period but over-predicted risk in the final quintile. Conclusions: For nearly half of the characteristics, the crude association with intra-ICU death is not temporally stable, although most of the movement tracks a changing population. Out of period, a fixed model loses the level of predicted risk, not the weighting of its predictors-level rather than structural drift. Multi-year registry analyses should test temporal homogeneity rather than assume it.

Background: This study evaluates whether maximal and mean lactate-to-albumin (LAR), C-reactive protein-to-albumin (CAR), and procalcitonin-to-albumin (PAR) ratios during ICU stay improve mortality prediction beyond admission values in critically ill, cardiovascularly burdened patients, and compares their performance against individual biomarkers. Methods: We conducted a retrospective single-center cohort study of consecutive adult ICU admissions (2024) in a tertiary cardiac center, using temporally aligned (±12 h) albumin-based ratios derived from serial laboratory measurements. Maximal and mean in-ICU values were analysed per admission. The primary endpoint was ICU mortality. Associations and discriminative performance were evaluated using ROC analysis and multivariable logistic regression. Results: Of 212 screened ICU admissions, 137 patients were included. The ICU mortality was 48.9%. Both maximum and mean values of biomarkers and composite ratios were more abnormal in non-survivors, with the strongest independent associations observed for maximum LAR and CAR. In adjusted analyses, maximum LAR and CAR remained independently associated with ICU mortality and showed moderate discrimination (AUC 0.704 and 0.712). Mean CAR and LAR performed numerically slightly better in ROC analysis, whereas PAR showed weaker and less consistent prognostic utility. Conclusions: Maximal and mean LAR and CAR were independently associated with ICU mortality, whereas PAR showed weaker performance. These ratios may serve as simple tools for dynamic risk stratification but require prospective multicenter validation.

Background: Subarachnoid hemorrhage (SAH) can cause remote organ failure through complex systemic reactions. Acute respiratory failure (ARF) in the course of SAH may have a diverse etiology, including cardiogenic origin. The aim of the study was to evaluate the utility of urine metanephrine measurement in identifying the ARF phenotype in patients with SAH. Methods: A prospective single-center study was conducted between January 2022 and February 2023. The study included consecutive adult patients admitted to the Intensive Care Unit (ICU) within 24 h of SAH diagnosis and requiring mechanical ventilation due to ARF within the first 48 h of stay. Demographic and clinical data were collected. Metanephrine (MET) was determined in 24-h urine collection. The inflammatory profile was assessed by measuring serum levels of interleukin-6 (IL-6), CRP, and PCT. Cardiogenic ARF phenotype was diagnosed when concomitant elevation of hsTpI, CK-MB, and NT-proBNP was observed upon admission. Results: The study group consisted of 18 patients. The cardiogenic etiology group (n = 4) was characterized by higher MET concentrations (249 vs. 63.5 ng/mL; p = 0.007) and a lower oxygenation index (190 vs. 296 mmHg; p < 0.05) on admission. In the non-cardiogenic etiology group (n = 14), higher levels of IL-6 were found (34 vs. 8.3 pg/mL; p = 0.013). MET significantly correlated with the oxygenation index (R = −1.0; p < 0.001) on day 1 and with lactate levels on days 2 and 3 of stay (R = 1.0; p < 0.001). Baseline MET concentration accurately predicted the ARF phenotype (AUC 0.93; 95% CI 0.786–1.000, p = 0.008). Conclusions: Urine metanephrine levels show potential in differentiating the etiology of ARF and correlate with severity markers in critically ill SAH patients at an early stage. These preliminary results highlight the importance of a targeted approach to ARF diagnostics after SAH, which could support appropriate therapeutic decisions, although further validation in larger cohorts is required.

Background/Objectives: Critically ill adults in intensive care units (ICUs) remain at high risk of death, while commonly used severity scores are complex and not always available at admission. We evaluated peri-admission lactate-to-albumin (LAR), C-reactive protein-to-albumin (CAR) and procalcitonin-to-albumin (PAR) ratios at ICU entry to predict ICU mortality in a cardiovascularly burdened cohort. Methods: We performed a single-centre retrospective observational cohort study in a tertiary cardiac ICU including adult admissions in 2024 with complete peri-admission lactate, C-reactive protein, procalcitonin and albumin. Results: Of 212 ICU admissions, 137 met the inclusion criteria. ICU mortality was 48.9%. Non-survivors had higher composite ratios and lower albumin than survivors. In multivariable models, LAR and CAR, but not PAR, remained independently associated with ICU mortality after adjustment for age, sex, and admission category. Receiver operating characteristic areas under the curve (AUC) were 0.692 for LAR, 0.677 for CAR and 0.625 for PAR. Cut-offs of LAR ≥ 0.106, CAR ≥ 3.18 and PAR ≥ 0.143 identified high-risk subgroups, with odds ratios for death of 6.18, 4.20 and 2.70, respectively, compared with lower-ratio patients, and LAR provided the best overall discrimination. Conclusions: Peri-admission LAR, CAR and PAR derived from routine tests in the ICU are associated with ICU mortality in critically ill adults, with LAR and CAR providing independent prognostic information and LAR showing the best discrimination. These simple composite ratios may complement severity scores for early risk stratification and warrant external validation.

Background: ICU care is time critical and data dense, making it a promising but high-risk setting for AI decision support when tools are weakly validated. ICU AI evidence is heterogeneous, with limited external validation, inconsistent clinically actionable reporting, and scarce real-world impact data, yielding fragmented review conclusions. We mapped five prespecified ICU domains and assessed clinical and implementation maturity to identify key translational gaps. Methods: We performed a PRIOR-aligned overview of systematic reviews with prespecified maturity constructs. PubMed, Embase, and Web of Science were searched (title and abstract) on 13 December 2025, supplemented by backward citation searching. Two reviewers screened and extracted data with arbitration, assessed the review-level risk of bias using ROBIS, and synthesized findings without meta-analysis using a SWiM-guided narrative prioritizing AUROC ranges. Results: We included 34 systematic reviews (2017–2025) across five ICU domains, dominated by prognostic and early warning applications, mostly in adult populations and commonly using EHR and multimodal inputs. Reporting focused on discrimination, with AUROC ranges roughly 0.54–0.99 for prognostic tasks and 0.64–0.99 for diagnostic tasks, while calibration and clinical utility were rarely addressed and overlap suggested partial dependence. Maturity signals clustered at low-to-intermediate levels, with no evidence for routine, and regulated CDS deployment at the review level. Conclusions: Review-level evidence indicates a translational gap between retrospective performance and clinically mature, safely deployable ICU AI, supporting priorities for external validation, prospective impact studies, standardized reporting including calibration, and governance-focused implementation.

Background: Malnutrition is a common yet often underestimated risk factor for adverse outcomes in hospitalized patients, including heart transplant recipients. Assessing nutritional status in this population is challenging due to comorbidities, pharmacotherapy, and the urgent nature of surgery. This study aimed to evaluate the reliability of routinely measured laboratory and anthropometric parameters in diagnosing malnutrition in heart transplant patients. Methods: This retrospective study included 53 adult patients who underwent orthotopic heart transplantation between 2021 and 2024 at the Silesian Center for Heart Diseases in Zabrze, Poland. Anthropometric data (gender, age, BMI) and laboratory parameters—albumin, total protein, hemoglobin, cholesterol, C-reactive protein (CRP), and neutrophil-to-lymphocyte ratio (NLR)—were analyzed. Malnutrition was defined as BMI < 22 kg/m². Cut-off points were based on literature data. Correlations between laboratory parameters and nutritional status were assessed, and concordance in malnutrition classification was evaluated. Results: Malnutrition criteria were met by 15% of patients. Only CRP predicted malnutrition risk, though its values did not differ significantly between BMI groups (p = 0.106). Negative correlations were found between CRP and total protein (−0.342; p = 0.012), albumin (−0.666; p < 0.0001), cholesterol (−0.287; p = 0.037), and hemoglobin (−0.383; p = 0.0046). A positive correlation was observed between CRP and NLR (0.333; p = 0.014). Conclusions: Malnutrition assessment in heart transplant recipients should not rely solely on individual laboratory parameters. A multifactorial approach integrating biochemical, anthropometric, and clinical data is necessary. Further research is needed to identify novel biomarkers to improve malnutrition risk evaluation and guide nutritional interventions in this population.

Wstęp: Cukrzyca (diabetes mellitus – DM) jest chorobą przewlekłą, której powikłania są przyczyną dodatkowych hospitalizacji, inwalidztwa i przedwczesnych zgonów. Celem pracy była ocena częstości występowania, cech klinicznych i rokowania pacjentów z DM leczonych w śląskich oddziałach intensywnej terapii (intensive care units – ICUs).Materiał i metody: Praca jest retrospektywnym, wieloośrodkowym badaniem wykorzystującym dane pacjentów ze Śląskiego Rejestru Oddziałów Intensywnej Terapii. Pacjenci byli leczeni w wieloprofilowych ICUs na terenie województwa śląskiego. Rejestr gromadził dane kliniczne pacjentów przed przyjęciem na ICU, w trakcie hospitalizacji, a także wyniki prowadzonego leczenia. Aby określić wpływ cukrzycy na analizowane zmienne (51 zmiennych), pacjentów podzielono na dwie grupy: pacjenci z DM w wywiadzie (niezależnie od jej typu) i pacjenci bez DM. Różnice międzygrupowe porównywano w przypadku zmiennych ilościowych za pomocą testów parametrycznych (test t-Studenta) lub nieparametrycznych (test U Manna–Whitneya), zależnie od typu rozkładu.Wyniki: Spośród 25 456 chorych DM występowała u 6393 (25,1%). Pacjenci z DM byli starsi (71 vs. 64 lata, p = 0,001), częściej były to kobiety (49% vs. 39%, p < 0,001). U pacjentów z DM znamiennie częściej występowały (p < 0,001): choroba wieńcowa (OR = 2,96), nadciśnienie tętnicze (OR = 3,62), przewlekła niewydolność nerek (OR = 4,29; z koniecznością dializoterapii, OR = 2,98) oraz otyłość olbrzymia (OR = 4,01). Wśród pierwotnych przyczyn przyjęcia na ICU istotnie częstsze były (p < 0,001): niewydolność wielonarządowa (OR = 1,18), wstrząs (OR = 1,20) oraz infekcja/sepsa (OR = 1,35/1,16). U pacjentów z DM stwierdzono zwiększone o 24% ryzyko zgonu na ICU (p < 0,001).Wnioski: Wyniki podkreślają istotny wpływ DM na stan kliniczny i efekt leczenia krytycznie chorych, nawet jeżeli pozostaje ona chorobą współistniejącą, a nie głównym powodem hospitalizacji.

Introduction: Refeeding syndrome (RS) is a serious complication of nutritional therapy in critically ill patients, to which patients on surgical wards are particularly vulnerable. It is a potentially life-threatening, complex metabolic disorder that occurs in response to the implementation of overly aggressive, inadequate adaptive patient nutritional therapy, often exacerbated by malnutrition. Moreover, if an appropriate diagnostic and therapeutic process is not undertaken, RS itself becomes the cause of subsequent systemic complications such as respiratory failure, neurological disorders, circulatory failure or seizures. Identified risk factors for RS are mostly modifiable.Aim: The article reviews the literature on the current knowledge and recommendations regarding RS and provides practical recommendations to assist surgeons in effectively diagnosing and managing the syndrome during the perioperative period.Methods: A database query was conducted to identify the most recent information related to the topic of this study.Results: Treatment of RS in critically ill patients undergoing surgery is challenging due to overlapping symptoms of the underlying disease and coexisting severe metabolic disorders. Current guidelines recommend a gradual increase in energy intake and regular monitoring of a patient's metabolic status (especially phosphorus, potassium, and magnesium levels) during nutritional treatment.Conclusions: It is necessary to regularly follow the recommendations of scientific societies, which will take into account the specificity of the treatment of patients in the perioperative period with Refeeding Syndrome in the context of coexisting diseases to improve the quality and safety of care of these patients.

Introduction: Due to the characteristics of brain-injured patients, early complications of aneurysmal subarachnoid hemorrhage (aSAH) can easily go undetected for a period of time, resulting in the delay of accurate treatment. Serum biomarkers of neuronal damage, such as glial fibrillary acidic protein (GFAP), neuron-specific enolase (NSE), and S100B protein, may serve as diagnostic tools to improve care in neurocritical illness. This preliminary observation aimed to evaluate the absolute values of those markers of neuronal damage in aSAH or a planned embolization. Material and methods: The study group consisted of 12 patients in need of emergency (i.e. due to aneurysmal aSAH) (n = 4) or planned (n = 8) embolization. GFAP, NSE, and S100B were assessed before and 24 hours after the procedure completion. Descriptive statistics were applied to elucidate the dynamics of markers in the peri-procedural period. Results: Brain aneurysm embolization was associated with an increase in NSE and S100B, but not GFAP. A greater increase in the concentrations of these proteins is observed in emergency procedures. Conclusions: Brain aneurysm embolization is likely to be associated with an increase in NSE and S100B, but not GFAP. There are differences in the concentrations of these proteins between patients with aSAH and controls. More research is needed to assess the impact of their dynamics on the clinical consequences of neuronal injury. Keywords: subarachnoid hemorrhage biomarker brain injury diagnostics