An Application for Spatial Frailty Models: An Exploration with Data on Fungal Sepsis in Neonates

Paramasivam, Palaniyandi and Jaganathasamy, Nagaraj and Ramalingam, Srinivasan and Mahalingam, Vasantha and Nagarajan, Selvam and Fayaz Ahamed, Shaik and Karuppasamy, Sundarakumar and Bhaskar, Adhin and Srinivasan, Padmanaban and Manoharan, Tamizhselvan and Natesan, Adalarasan and Chinnaiyan, Ponnuraja (2025) An Application for Spatial Frailty Models: An Exploration with Data on Fungal Sepsis in Neonates. An Application for Spatial Frailty Models: An Exploration with Data on Fungal Sepsis in Neonates, 3 (13).

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Abstract

Globally, neonatal fungal sepsis (NFS) is a leading cause of neonatal mortality, particularly among vulnerable opulations in neonatal intensive care units (NICU). The use of spatial frailty models with a Bayesian approach to identify hotspots and risk factors for neonatal deaths due to fungal sepsis has not been explored before. Methods: A cohort of 80 neonates admitted to the NICU at a Government Hospital in Tamil Nadu, India and diagnosed with fungal sepsis through blood cultures between 2018–2020 was considered for this study. Bayesian spatial frailty models using parametric distributions, such as Log-logistic, Log-normal, and Weibull proportional hazard (PH) models, were employed to identify associated risk factors for NFS deaths and hotspot areas using the R version 4.1.3 software and QGIS version 3.26 (Quantum Geographic Information System). Results: The spatial parametric frailty models were found to be good models for analyzing NFS data. Abnormal levels of activated thromboplastin carried a significantly higher risk of death in neonates across all PH models (Log-logistic, Hazard Ratio (HR), 95% Credible Interval (CI): 22.12, (5.40, 208.08); Log-normal: 20.87, (5.29, 123.23); Weibull: 18.49, (5.60, 93.41). The presence of hemorrhage also carried a risk of death for the Log-normal (1.65, (1.05, 2.75)) and Weibull models (1.75, (1.07, 3.12)). Villivakkam, Tiruvallur, and Poonamallee blocks were identified as high-risk areas. Conclusions: The spatial parametric frailty models proved their effectiveness in identifying these risk factors and quantifying their association with mortality. The findings from this study underline the importance of the early detection and management of risk factors to improve survival outcomes in neonates with fungal sepsis.

Affiliation:	ICMR-National Institute for Research in Tuberculosis
Item Type:	Article
Uncontrolled Keywords:	spatial; Bayesian; frailty; hazard; activated thromboplastin; neonatal sepsis
Subjects:	Tuberculosis > Biostatistics Tuberculosis
Divisions:	Statistics
Depositing User:	Mrs. N Lakshmi
Date Deposited:	27 Mar 2025 17:04
Last Modified:	27 Mar 2025 17:04
URI:	http://eprints.nirt.res.in/id/eprint/2025

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