Pathophysiology and Clinical Management of Fungal Infections

Topic Information

Dear Colleagues,

Fungal infections represent an escalating global health concern due to the rising prevalence of immunocompromised populations and the emerging threat of antifungal resistance. These infections range from superficial skin conditions to invasive, life-threatening systemic mycosis, affecting a diverse population globally but predominantly immunosuppressed individuals, including those with HIV/AIDS, cancer, or undergoing organ transplants. Understanding the pathophysiology of fungal infections is critical for developing targeted therapeutic strategies. Key areas of current research focus on the molecular and cellular processes that drive fungal pathogenicity, such as biofilm formation, and cellular differentiation processes, such as spore production and host invasion. Additionally, the role of the microbiome and host genetic factors in host–pathogen interactions and disease progression, and the modulation of immune responses hold paramount promise for novel therapeutic interventions. Clinical management remains challenging due to the lack of rapid and specific diagnosis, limited antifungal classes, and the rise of multidrug-resistant species. Therefore, advances in rapid diagnostics, such as molecular assays and biomarker-based tools, are critical for timely intervention. Therapeutically, there is growing interest in exploring combination antifungal regimens, drug repurposing, immunotherapies, and the development of new antifungal agents with novel mechanisms of action. We encourage submissions that provide insights into fungal biology, pathogenesis, diagnostic innovations, antifungal resistance mechanisms, and cutting-edge therapeutic advances, aiming to improve patient outcomes and expand our understanding and management of these complex infections.

Dr. Allan J. Guimarães
Dr. Marcos de Abreu Almeida
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Journal of Fungi jof	4.0	8.4	2015	18.2 Days	CHF 2600	Submit
Microbiology Research microbiolres	2.2	2.8	2010	20.7 Days	CHF 1600	Submit
Microorganisms microorganisms	4.2	7.7	2013	15.2 Days	CHF 2700	Submit
Pathogens pathogens	3.3	6.8	2012	13.5 Days	CHF 2200	Submit

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13 pages, 1525 KB  

Open AccessArticle

Construction of a Risk Assessment Model for Short-Term Mortality in Patients with Invasive Fungal Diseases Post-Cardiac Surgery Based on Multivariate Analysis

by Dong Wei, Qi Shen and Qian Zhai

Pathogens 2025, 14(11), 1116; https://doi.org/10.3390/pathogens14111116 - 3 Nov 2025

Viewed by 241

Abstract

To develop and validate a predictive model for assessing the risk of short-term mortality in patients with invasive fungal diseases (IFDs) following cardiac surgery. This retrospective study analyzed clinical data from patients diagnosed with postoperative IFDs in the cardiac surgical intensive care unit [...] Read more.

To develop and validate a predictive model for assessing the risk of short-term mortality in patients with invasive fungal diseases (IFDs) following cardiac surgery. This retrospective study analyzed clinical data from patients diagnosed with postoperative IFDs in the cardiac surgical intensive care unit (ICU) of Qilu Hospital of Shandong University (QLH), between January 2020 and December 2023. A total of 98 patients were included and divided into a non-survival group (n = 42) and a survival group (n = 56) based on 28-day mortality. Demographic, clinical, and postoperative parameters were collected. The Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for variable selection, and selected variables were then entered into multivariate logistic regression to identify independent risk factors. A nomogram was developed, and its predictive performance was evaluated using the receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and clinical impact curve (CIC). Multivariate logistic regression, following variable selection by LASSO, identified a history of smoking, an elevated SOFA score, mean arterial pressure (MAP) below 70 mmHg, and tachyarrhythmia as independent risk factors for short-term mortality in this cohort (p < 0.05). The prediction model demonstrated excellent discrimination, with an area under the ROC curve (AUC) of 0.886 (95% CI: 0.816–0.957). The calibration curve showed good agreement between predicted and observed outcomes, with a mean absolute error of 0.023. Decision curve analysis indicated a net clinical benefit across a threshold probability range of 0.1 to 0.87. The clinical impact curve confirmed a high concordance between predicted mortality and actual outcomes. A history of smoking, an elevated SOFA score, MAP below 70 mmHg, and tachyarrhythmia independently predict short-term mortality in patients with IFDs after cardiac surgery. Therefore, the nomogram constructed from these factors provides an accurate and clinically applicable tool for risk stratification. Full article

(This article belongs to the Topic Pathophysiology and Clinical Management of Fungal Infections)

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