Predicting Mental Health Disorders Post Long COVID Diagnosis Using Advanced Machine Learning Techniques DOI
Manoj Purohit, Praveen Madiraju

2021 IEEE International Conference on Big Data (Big Data), Journal Year: 2023, Volume and Issue: unknown, P. 4954 - 4962

Published: Dec. 15, 2023

After the global spread of COVID-19, enduring effects Long COVID and its health implications have emerged as a significant issue, affecting people worldwide. The lingering symptoms post COVID-19 infection can significantly affect individuals who had previously contracted virus, exerting considerable influence over their mental well-being. Prolonged recuperation associated with has been connected emergence such depression anxiety, all which adverse on emotional health. This paper delves into an in-depth analysis healthcare data pertaining to from Froedtert Health Medical System in Wisconsin. Through application advanced Machine Learning (ML) techniques, we present predictive models aimed at assessing risk developing Mental Disorders (MHD) patients diagnosed COVID. Our study also encompasses identification pivotal features impacting MHD. To thoroughly investigate factors that substantial impact MHD, employed Recursive Feature Elimination (RFE) technique carefully pick out essential attributes our dataset. Given dataset's inherent imbalance, Synthetic Minority Over-sampling Technique Edited Nearest Neighbors (SMO-TEEN) effectively address this issue. Multiple ML meticulously constructed validated using cross-validation methodologies. results indicate Random Forest (RF) Classifier shows better performance comparison other area under ROC curve (AUC) 0.97, precision 0.90, recall 0.89. Remarkably, XGBoost demonstrates strong abilities for achieving AUC 0.79, 0.82. Ultimately, crucial identified through hold potential identify facilitating delivery targeted preventive care resources.

Language: Английский

Mortality of Post-COVID-19 Condition: 2025 Update DOI Creative Commons
Giuseppe Lippi, Fabián Sanchis‐Gomar

COVID, Journal Year: 2025, Volume and Issue: 5(1), P. 11 - 11

Published: Jan. 14, 2025

Background: The coronavirus disease 2019 (COVID-19) pandemic has generated profound health, societal, and economic consequences, which have been further compounded by long-term sequelae commonly referred to as post-COVID-19 or long-COVID syndrome. Understanding the real-world impact of mortality is therefore critical for effective healthcare planning resource allocation. Methods: A descriptive epidemiological study was conducted using data from US National Center Health Statistics identify deaths attributed condition, classified ICD-10 code U09.9, October 2021 December 2024. Demographic factors such gender, age, place death were also extracted. Results: By 2024, 2653 under corresponding an age-adjusted rate 0.089 × 100,000. Mortality significantly higher in males compared females (0.098 vs. 0.081 100,000; p < 0.001). clear age-related gradient observed, with rates increasing almost linearly advancing age. largest fraction occurred at home (33.0%), followed nursing homes (26.3%) medical facilities (24.1%). Conclusions: These findings highlight substantial yet complex condition on mortality, observed males, older adults, individuals home, highlighting need targeted interventions allocation, particularly these higher-risk groups.

Language: Английский

Citations

1
COVID-19: Lessons from the Past to Inform the Future of Healthcare DOI Creative Commons
Camilla Mattiuzzi, Giuseppe Lippi

COVID, Journal Year: 2024, Volume and Issue: 5(1), P. 4 - 4

Published: Dec. 26, 2024

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its global spread have left an indelible mark, disrupting multiple aspects human life. It is therefore crucial to retrospectively analyze the factors that contributed more initial inefficiency response, thus enhancing preparedness proactively addressing risk similar events occurring in future. Critical areas were identified based on our expertise. Relevant bibliographic references subsequently gathered through open search scientific databases substantiate concepts discussed this article. key issues hindered effective response disease 2019 (COVID-19) are numerous multifaceted, some these will be critically examined article, including delayed identification pathogen, inadequate public health preparedness, therapeutic management, deficiencies laboratory diagnostics. From analysis, for improvement emerge ensure efficient responses future crises, (i) strengthening information systems, (ii) improving pandemic planning, (iii) developing a resilient healthcare workforce, (iv) increasing investment research development, (v) expanding use telemedicine digital health, (vi) ensuring universal access healthcare, (vii) communication trust.

Language: Английский

Citations

2
Management of patients with Long Covid: A qualitative study exploring the roles of nurses in healthcare pathways DOI Creative Commons
Linda Kamdem, Jessica Guyot, Caroline Dupré

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Feb. 12, 2024

Abstract Aim Investigate the various roles played by nurses in care of patients afflicted with Long COVID. Background Effectively managing Covid requires a multidisciplinary approach - healthcare pathway that necessitates collaboration among members medical profession to monitor patient. Among these professions, nursing plays crucial role. This article compiles information on how are involved Covid: What do they play enhancing patients? Are distinct from those perform other chronic conditions? Methods We conducted qualitative study professionals France and enrolled eighteen participants our study. Semi-structured interviews were working across sectors France, including private practice, hospitals, schools, research. A thematic content analysis was performed, emerging themes subsequently discussed until most significant categories identified. accordance COREQ checklist. Results Nurses wide range within their practices, depending practice settings. For instance, nurse practitioner may work settings such as hospital outpatient clinics, group inpatient units, or urgent units. Depending environment, nurses' pathways encompass screening guidance, clinical patient monitoring, providing relational support, education, collaborative coordination well involvement Conclusion The predominant role identified involves coordinating management syndrome. next step would be implementation city-hospital pathway. Implication for Nursing & Health Policy Perspectives is difficult specify, it includes numerous recognised unrecognised aspects. results this highlight new essential which health suffering Covid.

Language: Английский

Citations

0
SARS-CoV-2 is here to stay: do not lower our guard DOI Open Access
Giuseppe Lippi, Mario Plebani

Clinical Chemistry and Laboratory Medicine (CCLM), Journal Year: 2024, Volume and Issue: 62(6), P. 1017 - 1018

Published: March 26, 2024

Language: Английский

Citations

0
Predicting Mental Health Disorders Post Long COVID Diagnosis Using Advanced Machine Learning Techniques DOI
Manoj Purohit, Praveen Madiraju

2021 IEEE International Conference on Big Data (Big Data), Journal Year: 2023, Volume and Issue: unknown, P. 4954 - 4962

Published: Dec. 15, 2023

After the global spread of COVID-19, enduring effects Long COVID and its health implications have emerged as a significant issue, affecting people worldwide. The lingering symptoms post COVID-19 infection can significantly affect individuals who had previously contracted virus, exerting considerable influence over their mental well-being. Prolonged recuperation associated with has been connected emergence such depression anxiety, all which adverse on emotional health. This paper delves into an in-depth analysis healthcare data pertaining to from Froedtert Health Medical System in Wisconsin. Through application advanced Machine Learning (ML) techniques, we present predictive models aimed at assessing risk developing Mental Disorders (MHD) patients diagnosed COVID. Our study also encompasses identification pivotal features impacting MHD. To thoroughly investigate factors that substantial impact MHD, employed Recursive Feature Elimination (RFE) technique carefully pick out essential attributes our dataset. Given dataset's inherent imbalance, Synthetic Minority Over-sampling Technique Edited Nearest Neighbors (SMO-TEEN) effectively address this issue. Multiple ML meticulously constructed validated using cross-validation methodologies. results indicate Random Forest (RF) Classifier shows better performance comparison other area under ROC curve (AUC) 0.97, precision 0.90, recall 0.89. Remarkably, XGBoost demonstrates strong abilities for achieving AUC 0.79, 0.82. Ultimately, crucial identified through hold potential identify facilitating delivery targeted preventive care resources.

Language: Английский

Citations

0