The COVID-19 pandemic prompted widespread non-pharmaceutical interventions (NPIs) like lockdowns and masking in Poland (2020–2022), significantly alt

Background: Iron deficiency (ID) is prevalent in congestive heart failure (CHF), worsening outcomes. While European guidelines recommend screening using ferritin and transferrin-saturation (TSAT), inconsistent diagnostic criteria, especially regarding functional deficiency (ferritin 100-299 µg/L + TSAT <20%) and hyperferritinemia, limit prognostic accuracy. This study evaluated iron status definitions, including guideline criteria and a combined Ferritin-TSAT model, for predicting 365-day mortality in hospitalized CHF patients. Methods: This retrospective analysis used MIMIC-IV data from 1,839 CHF patients. Iron status within 24h of admission was categorized using: 1) Guideline ID vs. non-ID; 2) Ferritin categories; 3) TSAT categories; 4) Combined Ferritin-TSAT model (Low: guideline ID; Intermediate: ferritin 100-299 + TSAT ≥20%; High: ferritin ≥300 µg/L). Adjusted Cox models assessed mortality associations. Results: Guidelines-defined iron deficiency (33.65% prevalence) independently associated with higher 1-year mortality (56.1% vs. 29.4%; adjusted HR 4.36, 95%CI 3.35-5.34). The combined Ferritin-TSAT model showed significant prognostic value, differentiating true iron deficiency (reference) from hyperferritinemia (adjusted HR 0.50 vs. iron deficiency) and intermediate group (adjusted HR 0.36 vs. ID), indicating varying risk relative to the most deficient group. This combined model better distinguished hyperferritinemic and iron-replete subgroups than the binary guideline definition. Conclusion: Iron status, including deficiency and hyperferritinemia, independently predicts 1-year mortality in CHF. While guideline iron deficiency is a strong predictor, a combined Ferritin-TSAT classification offers finer risk stratification by identifying distinct phenotypes (true deficiency, hyperferritinemia, intermediate). Nuanced iron-status assessment could improve prognostic evaluation and guide personalized therapies (e.g., IV iron for deficiency, investigation for hyperferritinemia) to enhance CHF outcomes. Prospective validation is needed.

Objectives: The aim of this study was to identify factors that affect the clinical course, outcome, and duration of hospital stay in patients with a brain abscess. Methods: Eighty-four inpatients with a confirmed brain abscess were the subjects of this retrospective study. The impact of several factors on the length of hospital stay was evaluated and multiple linear regression analysis was used. Results: Several factors affecting the length of hospitalization were identified. These were older age and larger abscess diameter. Conclusions: Proper handling of preexisting infections and early consideration of CNS infection, especially in high-risk groups, may reduce the incidence of brain abscess and improve its prognosis. The factors affecting the length of hospitalization shown in this study should be considered upon admission to reduce patients’ unfavorable outcomes.

Introduction: The COVID-19 pandemic prompted widespread implementation of non-pharmaceutical interventions (NPIs) to limit SARS-CoV-2 transmission. These interventions, including lockdowns, face covering, movement restrictions, and school closures, also altered circulation patterns of other pathogens. These measures were enforced on a large scale in Poland beginning in 2020 and persisted through 2022, introducing a rare opportunity to assess broader impacts on other communicable diseases. Previous research frequently addressed short-term alterations in disease incidence, yet knowledge of extended effects remains limited. Aim: The study aimed to assess how the pandemic and associated measures changed the incidence of 17 notifiable infectious diseases in Poland from January 2014 to December 2022. The analysis investigated whether NPIs were correlated with immediate declines, sustained decreases, or rebounds in disease activity, with particular attention to changes in disease dynamics across pre-pandemic and pandemic phases, identifying severity of resurgent trends once restrictions were lifted. Materials and Methods: Biweekly case counts for 17 notifiable diseases were collected from the National Institute of Public Health–National Institute of Hygiene, then aggregated into monthly intervals. The study period encompassed five phases: 2014–2018, 2019 (baseline), and each pandemic year (2020, 2021, 2022). Crude annual incidences were calculated and converted to percentage changes, with comparisons between baseline and pandemic periods as well as among individual pandemic years. Seasonality was removed with X13-ARIMA-SEATS, enabling clearer detection of incidence fluctuations. A two-stage negative binomial generalized linear model (GLM) controlled for autocorrelation and potential confounders, producing incidence rate ratios (IRRs) relative to the 2019 reference phase. The analysis evaluated nine NPIs, including school closure, stay-at-home orders, public gathering bans, and an overall stringency index. Spearman correlation coefficients measured associations between the deseasonalized disease time series, COVID-19 case counts, and each of the nine NPIs. Results: Thirteen of the 17 diseases exhibited cumulative declines from 2020 to 2022 when compared to 2014–2019, ranging from 10.48% (syphilis) to 87.63% (whooping cough). The largest single-year drop appeared in 2021 for whooping cough, which showed a 94.56% decrease from 2019. Statistical modeling revealed an IRR of 0.32 (95%CI 0.24–0.42, p<0.001) in 2020 and 0.11 (95%CI 0.08–0.15, p<0.001) in 2021, exhibiting a significant, sustained reduction in incidence. Scarlet fever, chickenpox, and mumps followed a similar pattern, with IRRs persistently below 0.5 throughout at least one pandemic phase. Invasive Streptococcus pneumoniae remained reduced in 2020 (IRR 0.33 [0.24–0.46], p<0.001), yet rebounded in 2022 with an 88.94% rise over 2019. Clostridium difficile diverged from most other diseases, showing a 2.88% increase in 2020 and a jump of over 117% in 2021 compared to 2019, alongside an IRR of 1.84 (1.64–2.07, p<0.001). Noteworthy surges in norovirus (84.5% in 2021 vs. 2019), HIV (63.5% in 2022 vs. 2019), and syphilis (34.92% in 2022 vs. 2019) aligned with relaxation of NPIs. Correlations generally showed strong negative associations between respiratory pathogens and higher NPI stringency, while C. difficile displayed a positive relationship with COVID-19 case counts and several NPIs. These contrasting trends reflected the multifaceted ways that reduced mobility, physical distancing, and masking influenced various modes of disease transmission. Conclusion: Long-term observation confirmed that widespread NPIs had a strong suppressive effect on many communicable diseases beyond SARS-CoV-2, particularly those transmitted via respiratory droplets. Several infections rebounded when NPIs were relaxed, indicating potential shifts in susceptibility within the population. Future strategies aiming to balance public health protection with social and economic priorities may benefit from these findings, although additional research is needed to clarify how evolving interventions and changing pathogen transmission patterns influence disease resurgence over extended timeframes.

Background Congestive heart failure (CHF) is a chronic syndrome with high mortality rates, necessitating risk stratification tools. Existing models are complex and may not incorporate crucial inflammatory and nutritional biomarkers. The Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) score and modified HALP (mHALP) score, which reflect nutritional status and systemic inflammation, emerged as potential prognostic tools. This study aimed to evaluate the predictive performance of HALP and mHALP scores for 90-day mortality in CHF patients. Methods This retrospective study utilized the MIMIC-IV database for 1000 adult CHF patients. HALP was calculated as [Hemoglobin (g/L) * Albumin (g/L) * Lymphocytes (/L)] / Platelets (/L), and mHALP by multiplying these components. The primary outcome was 90-day all-cause mortality. Univariate and multivariate logistic regression analyses were performed, and models were assessed using Receiver Operating Characteristic (ROC) analysis and Youden’s Index. Results Non-survivors (13.2%) had significantly lower median HALP (19.69 vs. 27.18) and mHALP (583,920.75 vs. 1,151,898.94) scores compared to survivors. In univariate analysis, HALP had an AUC of 0.63 and an OR of 0.25 for 90-day mortality, while mHALP showed a higher AUC of 0.68 and an OR of 0.22. After confounder adjusting, both log-transformed HALP (OR: 0.44) and mHALP (OR: 0.57) remained significant predictors of mortality. mHALP demonstrated better overall predictive performance. Conclusion Both HALP and mHALP scores are significantly associated with 90-day mortality in CHF patients, with mHALP exhibiting superior prediction. Easily calculable scores, derived from routine laboratory tests, offer a cost-effective, early risk stratification in CHF, potentially aiding in tailoring interventions.