Journal of Infection and Public Health最新文献

Background: Acute mountain sickness (AMS) is a frequent concern for climbers at high altitudes. Since the COVID-19 pandemic, questions have emerged regarding whether prior infection increases susceptibility to AMS.

Methods: We conducted a prospective observational study at the Paiyun Lodge medical station (3402 m) on Jade Mountain (Yushan, 3952 m) between 2023 and 2024. All climbers presenting for medical services were screened. Demographics, comorbidities, ascent characteristics, sleep duration, prophylactic medication, and self-reported COVID-19 history were recorded. AMS was diagnosed clinically and validated using the 2018 Lake Louise AMS Score. Logistic regression and multiple propensity score methods were used to assess associations between COVID-19 history and AMS occurrence and severity.

Results: A total of 871 patients were included; 52.4 % were aged 20-40 years, 57.3 % were male, and 74.7 % reported a history of COVID-19 infection. Clinically diagnosed AMS occurred in 64.1 % (n = 558), with 274 mild and 284 severe cases. Although crude analyses suggested a borderline association between COVID-19 history and AMS (OR = 1.36, 95 % CI: 1.00-1.87), this was not statistically significant after multivariable adjustment (adjusted OR = 1.34, 95 % CI: 0.96-1.88) or propensity score methods.

Conclusion: Prior COVID-19 infection was not significantly associated with the occurrence and severity of AMS among climbers who sought medical services on Jade Mountain. These findings suggest that a history of mild COVID-19 does not independently increase AMS susceptibility, providing reassurance to mountaineers and aligning with contemporary expert consensus.

Background: Despite the widespread implementation of vaccination programs, pertussis continues to spread and remains a major health threat to infants. The present study aimed to identify risk factors of severe pertussis in children to inform clinical decision-making and the development of prevention strategies.

Methods: This retrospective cohort study included data from paediatric patients diagnosed with pertussis at Beijing You'an Hospital, Capital Medical University (Beijing, China), between January 2006 and December 2023. Multivariable logistic regression was performed to identify independent predictors of severe pertussis, and receiver operating characteristic (ROC) analysis was used to assess discriminative performance.

Results: Data from 219 children with pertussis were divided in 2 groups according to predefined clinical criteria: severe (n = 21) and non-severe (n = 198). Compared with non-severe cases, severe cases experienced longer hospital stays (median 12 versus [vs.] 8 days) and higher rates of fever, cyanosis, sputum production, and respiratory distress. Marked inflammatory differences were observed, as follows: higher neutrophil counts (median 6.83 vs. 3.65 ×10⁹/L); elevated C-reactive protein (median 3.50 vs. 1.00 mg/L); procalcitonin (median 0.12 vs. 0.04 ng/mL); increased neutrophil-to-lymphocyte ratio (NLR; median 0.61 vs. 0.29); and a lower lymphocyte percentage (median 56.9 % vs. 69.5 %) (all p < 0.05). Multivariable analysis identified elevated NLR as an independent predictor of severe pertussis (adjusted odds ratio [OR] 1.884; 95 % confidence interval [CI] 1.157-3.066; P = 0.011). ROC curve analysis yielded an area under the curve (AUC) of 0.745 (95 % CI 0.640-0.850), with an optimal NLR cut-off of 0.475, yielding a sensitivity of 66.7 % and a specificity of 75.5 %.

Conclusion: Elevated NLR was an independent predictor of severe pertussis in children. Future multicentre prospective studies with standardised follow-up periods are warranted to validate these findings.

Background: Burkholderia cepacia complex bacteria are intrinsically multidrug-resistant opportunistic pathogens that pose a growing threat in hospital settings, particularly among immunocompromised patients. Despite its clinical significance, data on sporadic Burkholderia cepacia complex infections outside cystic fibrosis populations and hospital outbreaks remain limited.

Methods: A 22-year retrospective observational cohort study (May 2001-April 2023) was carried out at a tertiary care academic center in the Eastern Province of Saudi Arabia. Adults hospitalized with confirmed Burkholderia cepacia infection and ≥ 72 h of antibiotic therapy were included. Demographics, comorbidities, infection type, microbiological resistance profiles, treatment outcomes, and mortality predictors were analyzed using logistic regression and Kaplan-Meier survival estimates.

Results: Of 189 identified cases, 151 patients met the inclusion criteria (mean age 53 ± 21 years; 57.6 % male). The majority of infections were hospital-acquired (84.8 %), with bloodstream infections (33.1 %) and ventilator-associated pneumonia (26.5 %) being the most prevalent. Resistance was high to piperacillin/tazobactam (73.6 %), ceftazidime (58.6 %), levofloxacin (57.4 %), carbapenems (42.0 %), and trimethoprim-sulfamethoxazole (30.3 %). Clinical resolution was achieved in 82.1 %, but bacteriological eradication occurred in only 56.9 %, with a recurrence rate of 17.2 %. Mortality reached 9.9 % at 14 days, 17.2 % at 30 days, and 35.8 % at one year. Independent predictors of 30-day mortality included advanced age, critical care admission, central venous catheter insertion, mechanical ventilation, and resistance to fluoroquinolones or carbapenems.

Conclusions: Our findings indicate that Burkholderia cepacia complex infections represent a significant clinical challenge due to antibiotic resistance and elevated mortality rates. The data highlight the importance of improving diagnostic and treatment approaches, as well as implementing effective infection control policies, especially for vulnerable hospitalized populations.

Mycobacterium tuberculosis remains one of the world's most persistent pathogens, responsible for over a million deaths each year despite effective drugs and decades of research. Disease progression varies widely among individuals, reflecting interactions between pathogen, physiology, host immunity, and pharmacological response. We propose a digital twin framework for tuberculosis that integrates clinical, immunological, and pharmacokinetic data into a continuously adaptive computational model. The twin would simulate host-pathogen dynamics from granuloma formation to systemic immune regulation, linking these processes with individualised drug exposure and treatment response. By forecasting outcomes and identifying early indicators of relapse or resistance, such a system could guide precision therapy and accelerate discovery of host-directed interventions. The tuberculosis digital twin thus represents a bridge between infection biology, computation, and clinical translation, presenting an evolving model capable of transforming how this ancient disease is understood and managed. However, translation will require further longitudinal clinical and immunological datasets and systematic validation of model predictions in real-world treatment settings.

Background: Lactate dehydrogenase (LDH) has emerged as a potential biomarker for COVID-19 severity, but the diagnostic value of its dynamic changes (ΔLDH) remains unclear. This study aimed to determine the predictive value of ΔLDH for clinical outcomes in hospitalized patients with COVID-19.

Methods: We performed a retrospective cohort study of 5635 adults with confirmed COVID-19, analyzing LDH measurements. The patients were stratified by ΔLDH quartiles (Q1-Q4). Multivariable logistic regression was used to assess the associations with mortality and ICU admission, while ROC analysis was used to determine the predictive performance.

Results: A U-shaped relationship was observed, with both extreme reductions (Q1: ΔLDH ≤ -196 U/L) and elevations (Q4: ΔLDH ≥ 108 U/L) predicting adverse outcomes. Q4 patients had a higher risk of mortality (aOR = 6.72, 95 % CI: 5.31-8.51) and a higher risk of ICU admission (aOR = 6.63, 95 % CI: 5.26-8.36) compared to Q1. ΔLDH revealed excellent discrimination for mortality (AUC = 0.78) with an optimal cutoff at 181.5 U/L (sensitivity = 66.7 %, specificity = 88.9 %).

Conclusion: ΔLDH is a powerful, independent predictor of COVID-19 severity, revealing a novel U-shaped risk pattern. The 181.5 U/L threshold offers clinically actionable guidance for risk stratification. These findings support the incorporation of serial LDH monitoring into COVID-19 management protocols.