https://orcid.org/0009-0003-7820-5102
Figures
Abstract
Background
Meningitis in neonates remains a major public health concern, particularly in low- and middle-income countries. Despite its high morbidity and mortality, evidence on treatment outcomes and determinants of poor prognosis is limited. This study aimed to assess treatment outcomes of meningitis and its associated factors among neonates admitted to public hospitals in Harar town, Ethiopia.
Methods
A facility-based cross-sectional study was conducted among 506 neonates diagnosed with meningitis admitted between October 2020 and October 2024. Data were extracted from medical records. Treatment outcomes were categorized as good or poor. Binary and multivariable logistic regression analyses were performed to identify factors associated with poor treatment outcomes. Statistical significance was declared at a p-value <0.05 using adjusted odds ratios (AORs) with 95% confidence intervals (CIs).
Results
A total of 169 (33%) neonates experienced poor treatment outcomes. Assisted vaginal delivery (AOR = 3.70; 95% CI: 1.42–9.69), positive cerebrospinal fluid (CSF) culture (AOR = 3.74; 95% CI: 1.76–7.96), elevated CSF white blood cell count >2500 cells/mm³ (AOR = 6.10; 95% CI: 2.54–14.69), high CSF protein >400 mg/dL (AOR = 5.43; 95% CI: 2.84–10.36), low CSF glucose <10 mg/dL (AOR = 3.57; 95% CI: 1.64–7.80), seizures at admission (AOR = 5.07; 95% CI: 2.71–9.46), seizures after admission (AOR = 3.88; 95% CI: 1.82–8.25), early-onset neonatal sepsis (AOR = 4.27; 95% CI: 2.03–8.99), and non-exclusive breastfeeding (AOR = 2.20; 95% CI: 1.06–4.57) were predictor of poor treatment outcomes.
Conclusion
About one-third of neonates with meningitis experienced poor treatment outcomes. Factors associated with poor outcomes included assisted vaginal delivery, severe CSF abnormalities (positive culture, high white blood cell count, elevated protein, and low glucose), seizures at or after admission, early-onset neonatal sepsis, and non-exclusive breastfeeding. These findings highlight the need for early risk stratification and timely interventions to improve neonatal care and treatment outcomes.
Citation: Yirsaw GT, Tafesse TB, Bune AJ, Amare SN (2026) Treatment outcomes of meningitis and its associated factors among neonates admitted to public hospitals in Harar Town, Ethiopia: Cross-sectional study. PLoS One 21(8): e0355843. https://doi.org/10.1371/journal.pone.0355843
Editor: Dominic Umoru, Maitama District Hospital, NIGERIA
Received: March 9, 2026; Accepted: July 27, 2026; Published: August 11, 2026
Copyright: © 2026 Yirsaw et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The de-identified minimal dataset underlying the findings of this study is publicly available in the Zenodo repository via https://doi.org/10.5281/zenodo.21490590. All data necessary to reproduce the analyses and support the conclusions reported in this manuscript are available without restriction.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Meningitis is a serious infection that causes inflammation of the subarachnoid space of the brain and spinal cord. It is usually caused by bacteria, viruses, fungi, or parasites [1]. Newborns are especially vulnerable due to immature immunity, with neonatal meningitis classified as early-onset (≤72 hours after birth) or late-onset (>72 hours) [2,3].
The pathogens causing neonatal meningitis depend on gestational age, postnatal age, and location [3]. Early-onset cases are mainly due to Group B Streptococcus (GBS) and Escherichia coli (E. coli) [2,4–7]. Late-onset pathogens vary by gestational age, birth weight, and healthcare setting: GBS and E. coli are common in community-acquired cases, while staphylococci, Staphylococcus aureus (S. aureus), and Klebsiella species are frequent in healthcare-associated infections [7–10].
Globally, the incidence and mortality rates of neonatal meningitis were estimated at 854 and 137.2 per 100,000 population, respectively, in 2019 [11]. The disease also imposes a substantial economic burden, with healthcare expenditures ranging from US$222 to US$33,635 per patient worldwide [12]. The incidence and mortality of neonatal meningitis are disproportionately higher in low- and middle-income countries, with 0.5–6 cases per 1,000 live births and mortality rates of 20–37%, compared to 0.3–0.4 cases per 1,000 live births and 2–10% mortality in high-income countries [5,6,13–18]. Among survivors, 20–50% develop long-term neurological sequelae, including hearing loss, blindness, epilepsy, hydrocephalus, subdural empyema, and psychomotor developmental delay [19–21].
Sub-Saharan Africa, part of the global “meningitis belt,” continues to bear a disproportionately high burden, with reported incidence and mortality rates including 96 per 1,000 live births in Kenya [22], and mortality rates of 24.0% in Angola [23], 29.4% in Tanzania [24], and 37% in Gambia [16]. Ethiopia ranks third globally in meningitis mortality, with treatment for bacterial meningitis costing a median of 98,812 ETB (≈US$3,593.2) per patient [25,26].
Multiple clinical factors have been identified as predictors of poor prognosis in neonatal meningitis, including seizures, elevated CSF protein, low birth weight or prematurity, early onset of disease, and low CSF glucose levels [18,19,27].
Predictors of neonatal meningitis outcomes can differ across populations and healthcare settings. Although the disease causes substantial morbidity and mortality in low-income countries, studies on treatment outcomes and prognostic factors are scarce, especially in Ethiopia. To the best of the author’s knowledge, only one Ethiopian study has examined this issue [28], but its small sample size and limited representativeness restrict the generalizability of its findings.
Given the scarcity of evidence and the high burden of disease, context-specific data are essential to improve neonatal care and clinical outcomes. Therefore, this study aimed to assess treatment outcomes of meningitis and its associated factors among neonates admitted to public hospitals in Harar town, Ethiopia. The main research question was: Which clinical, demographic, and healthcare-related factors are associated with adverse outcomes in neonatal meningitis in this setting? Given the limited prior data, this study is primarily exploratory, generating evidence to inform clinical practice and guide future confirmatory research.
Materials & methods
Study design and settings
A cross-sectional study design was conducted in Hiwot Fana Comprehensive Specialized University Hospital (HFCSUH) and Jugal General Hospital (JGH) from February 10 to March 20, 2025. Harar is the capital city of the Harari regional administration. It is located in the eastern part of the country, around 500 kilometers from the Ethiopian capital city, Addis Ababa. HFCSH was founded in 1948 and transitioned to a university-specialized hospital in 2010. JGH was founded in 1909. Both hospitals provide medical, surgical, pediatric, obstetric, and gynecologic services and have neonatal intensive care units.
Study population and variables
All medical records of neonates admitted to the Neonatal Intensive Care Units (NICUs) of HFCSUH and JGH with a confirmed diagnosis of meningitis between October 1, 2020, and October 31, 2024, were included in this study. Records with incomplete information, such as missing diagnosis, treatment regimen, or discharge summary, as well as those who discontinued treatment within the first 72 hours, and those referred to other facilities, were excluded. Data were collected on socio-demographic factors (admission site, sex, age at admission, birth weight, and gestational age); clinical factors, including pre-existing medical conditions (congenital heart defects, Down syndrome, congenital hydrocephalus), maternal conditions and complications during delivery (history of premature rupture of membranes (PROM), meconium-stained amniotic fluid, and chorioamnionitis), and mode of delivery (spontaneous vaginal delivery, cesarean section, or assisted vaginal delivery (Forceps Delivery or Vacuum Extraction); diagnostic information such as symptoms at presentation, blood test results, CSF findings, type of pathogen, and specific isolated organisms; and treatment-related factors, including antimicrobial therapy (choice of antimicrobials) and supportive care (nutritional support and management of complications).
Outcome measurement
In this study, treatment outcomes were categorized as either good or poor. Outcomes were assessed at the time of hospital discharge or in-hospital death, representing short-term in-hospital outcomes.
A good treatment outcome was defined as clinical recovery or improvement at discharge without documented complications. A poor treatment outcome was defined as in-hospital death, discharge without clinical improvement, or discharge with documented neurological complications as recorded in the treating clinician’s discharge summary.
Sample size determination and sampling technique
A single-population proportion formula was used to estimate the sample size for the primary outcome variable, while double-population proportion formulas were applied to determine sample sizes for the associated factors. For the treatment outcome, the calculation was based on the assumptions of a 95% confidence interval, a 5% margin of error, and a previously reported proportion of poor outcomes (20.7%) from a study conducted at Tibebe Ghion Comprehensive Specialized Hospital in Bahir Dar, Ethiopia [28].
Sample size for associated factors (i.e., seizure [29], preterm [30], early-onset neonatal sepsis (EONS) [31], prolonged shock [32], mechanical ventilation [33], and congenital heart disease [34] were computed using Epi Info V.7. 1.4, with considered the following assumptions: a 95% confidence interval, a 5% margin of sampling error tolerated, and an 80% power.
The largest sample size obtained from the single- and double-population proportion calculations was selected as the final sample size. EONS yielded the highest estimate; therefore, it was used to determine the required sample size. After adding a 5% contingency to account for incomplete records, the final sample size was 506, and these 506 medical records were subsequently reviewed. Study participants from each hospital were selected using a simple random sampling method. First, the registration numbers of eligible neonates were obtained from the admission logbooks. These numbers were then entered into Microsoft Excel, and a lottery method was applied to randomly select the required records. Proportional allocation was used to distribute the sample across HFCSUH and JGH, based on the number of neonates admitted with meningitis during the study period (HFCSUH = 725 and JGH = 321). Accordingly, 351 records were selected from HFCSUH and 155 from JGH.
Data collection tool and procedure
A structured tool based on relevant literature was used to extract socio-demographic, clinical, and treatment-related data from medical records. Eligible records from neonates admitted to the NICUs of HFCSUH and JGH between October 1, 2020, and October 31, 2024, were identified from registry logbooks, retrieved from the card rooms, and records meeting the eligibility criteria were retrieved and reviewed using the data abstraction tool. Data extraction was conducted from February 10 to March 20, 2025, ensuring completeness and consistency.
Data quality assurance
Before data collection, a pretest was conducted with 5% of the sample at Haramaya General Hospital, and the data collection tool was modified based on the findings. Four clinical pharmacists were involved in the data collection process. Before data collection, they received appropriate orientation on the objectives of the study and the use of the data abstraction tool. Throughout the data collection period, the completeness and consistency of the extracted information were checked continuously and reviewed again before data processing to ensure data quality.
Statistical analysis
Data were entered into EpiData version 7.2 to ensure accuracy and completeness, then exported to SPSS version 27 for analysis. Descriptive statistics were computed using frequencies and percentages for categorical variables and means with standard deviations for continuous variables. Binary logistic regression was first conducted to assess the association of each variable with treatment outcomes, and variables with p < 0.25 in the binary analysis were included in the multivariate logistic regression to identify independent predictors. The final model’s goodness of fit was confirmed using the Hosmer-Lemeshow test (p = 0.53), and multicollinearity was assessed using the variance inflation factor (VIF = 1.74), indicating no problematic correlations. Associations were reported as crude odds ratios (COR) and adjusted odds ratios (AOR) with 95% confidence intervals, and a p-value < 0.05 was considered statistically significant.
Operational definitions
Neonatal meningitis was classified by diagnostic certainty into confirmed, probable, and suspected (possible) cases.
Confirmed neonatal meningitis was defined as the presence of clinical features suggestive of meningitis (e.g., fever, seizures, poor feeding, or thermal instability) together with microbiological evidence from CSF, including a positive CSF culture and/or a positive CSF Gram stain [35,36].
Probable neonatal meningitis were neonates presented with clinical features suggestive of meningitis and abnormal CSF findings, such as leukocyte count >32/mm³ in term and >29/mm³ in preterm neonates, glucose <34 mg/dL in term and <24 mg/dL in preterm neonates, or protein >170 mg/dL in term and >150 mg/dL in preterm neonates, but without microbiological confirmation [35,36].
Suspected (possible) neonatal meningitis is defined by the presence of clinical signs and symptoms consistent with meningitis, but CSF analysis was normal despite a high clinical suspicion [35,36].
Neurological sequelae were defined as any secondary conditions resulting from meningitis, including persistent seizure disorder after treatment, subdural effusion, brain abscess, hearing loss, hydrocephalus, and subdural empyema.
Ethical considerations
This study was approved by the Institutional Health Research Ethics Review Committee (IHRERC) of the College of Health and Medical Sciences, Haramaya University, under reference number IHRERC/041/2025, for the study entitled “Treatment Outcomes of Meningitis and Its Associated Factors among Neonates Admitted to Public Hospitals in Harar Town, Ethiopia: Cross-sectional Study.” The study was conducted between February 10 and March 20, 2025. Official cooperation letters were sent to HFCSUH and JGH to facilitate access to medical records. Patients’ privacy and confidentiality were strictly maintained: no personal identifiers were recorded, and direct consent from parents or guardians was not obtained due to unregistered phone numbers and the absence of direct interaction or interviews. Institutional consent was obtained from the hospitals, and all data were handled confidentially to ensure that patients’ identities remained protected.
Results
Socio-demographic characteristics of patients
A total of 506 neonates with meningitis were included in this study, with 351 (69.4%) from HFCSUH and 155 (30.6%) from JGH. Of these, 278 (54.9%) were male, resulting in a male-to-female ratio of 1.22:1. The majority of neonates were in the early neonatal period (<7 days old), with a mean age of 8.91 ± 5.92 days. Regarding place of delivery, most neonates were born in specialized/tertiary hospitals (167, 33.0%) or health centers (152, 30.0%) (Table 1).
Neonatal and maternal characteristics of health
Among the neonates, 181 (36.2%) had coexisting sepsis at admission, including 116 (22.9%) with EONS; 65 (12.8%) with late-onset neonatal sepsis (LONS). The mean birth weight was 3099 ± 393 g, and the mean gestational age was 36.9 ± 1.13 weeks; 69 (13.6%) were low birth weight, and 130 (25.7%) were preterm. Pre-existing medical conditions were observed in 42 (8.3%) neonates. Most were delivered via spontaneous vaginal delivery (314; 62.1%). Maternal complications occurred in 119 (23.5%) cases, mainly PROM (71; 14.0%) and eclampsia (31; 6.1%) (Table 2).
Laboratory and CSF findings
The mean CSF white blood cell count was 1764.3 ± 833.3 cells/μL, with 70 (14.2%) neonates exceeding 2500 cells/mm³. Elevated CSF protein (>400 mg/dL) was observed in 118 (23.3%) neonates, while 79 (15.6%) had glucose levels below 10 mg/dL; mean CSF protein and glucose were 300.2 ± 108.2 mg/dL and 15.4 ± 6.9 mg/dL, respectively. Gram staining was positive in 113 (22.3%) cases, predominantly Gram-positive cocci (63; 12.5%) and Gram-negative rods (40; 7.9%). CSF cultures were positive in 71 (14.0%) neonates, with GBS in 30 (5.9%) and E. coli in 20 (4.0%). Hematologic abnormalities included thrombocytopenia in 35 (6.9%), anemia in 199 (39.3%), and leukocytosis in 134 (26.5%) neonates (Table 3).
Clinical findings, treatment and outcome
The most common clinical manifestations among neonates with meningitis were fever (475/506, 93.9%), failure to suck (419/506, 82.8%), vomiting (302/506, 59.7%), and irritability (298/506, 58.9%) (Fig 1). Among the 506 neonates treated for meningitis, 416 (82.2%) received ampicillin plus gentamicin as the initial empirical antibiotic regimen, while 54 (10.7%) received ampicillin plus cefotaxime. During hospitalization, 143 (28.3%) neonates developed one or more complications, the most common being seizures (62/506, 12.3%), renal failure (17/506, 3.4%), and septic shock (16/506, 3.2%). Among the survivors, 73 (17.8%) were discharged with neurological sequelae, predominantly seizures (49/411, 12.0%) and hydrocephalus (11/411, 2.7%). Overall, 339 (67.0%) neonates had good treatment outcomes, whereas 167 (33.0%) had poor treatment outcomes, including 95 (18.8%) who died during hospitalization (Table 4).
Factors associated with poor treatment outcomes
Multivariate logistic regression analysis identified several independent predictors of poor treatment outcomes among neonates with meningitis. Assisted vaginal delivery (AOR = 3.70; 95% CI: 1.42–9.69), positive CSF culture (AOR = 3.74; 95% CI: 1.76–7.96), elevated CSF white blood cell count >2500 cells/mm³ (AOR = 6.10; 95% CI: 2.54–14.7), high CSF protein >400 mg/dL (AOR = 5.43; 95% CI: 2.84–10.4), low CSF glucose <10 mg/dL (AOR = 3.57; 95% CI: 1.64–7.80), seizures at admission (AOR = 5.07; 95% CI: 2.71–9.46), seizures after admission (AOR = 3.88; 95% CI: 1.82–8.25), EONS (AOR = 4.27; 95% CI: 2.03–8.99), and non-exclusive breastfeeding (AOR = 2.20; 95% CI: 1.06–4.57) were significant associated with poor treatment outcomes (Table 5).
Discussion
This study found that approximately one-third of neonates with meningitis experienced poor treatment outcomes, including in-hospital death or discharge with documented neurological complications, while nearly one-fifth died (18%) during hospitalization. These findings indicate that neonatal meningitis remains a major cause of morbidity and mortality in eastern Ethiopia despite the availability of neonatal intensive care services. The mortality observed in this study was lower than that reported in studies from Angola (24.0%) [23], Gambia (37.0%) [16], Tanzania (29.4%) [24], Tunisia (40.0%) [37], and India (29.1%) [38], but higher than findings from Taiwan (10.3%) [7], Colombia (9.5%) [39], and China (4.2%) [36]. The observed differences may reflect variations in healthcare infrastructure, early access to neonatal intensive care, timeliness of diagnosis and treatment, and antimicrobial resistance patterns across study settings.
Neurological sequelae were identified in 17.8% of survivors at discharge, primarily seizures and hydrocephalus. Although this proportion was comparable to reports from Tunisia (16.4%) [37], it was lower than the rates reported in studies from Canada (72.4%) [40], Taiwan (41.6%) [18], India (30.4%) [37], Nigeria (22.5%) [41], and Tunisia (21.6%) [42]. This difference should be interpreted cautiously because our assessment was limited to the period of hospitalization. Many neurodevelopmental impairments, including cognitive, hearing, language, and motor deficits, become evident only after months or years of follow-up [18,40]. Consequently, the burden of long-term disability is likely underestimated in the present study. Differences in access to neuroimaging, hearing assessment, specialist follow-up, spectrum of pathogens, and rehabilitation services may also contribute to the variability reported across studies.
Assisted vaginal delivery was independently associated with poor treatment outcomes. Because vacuum-assisted delivery is generally performed in pregnancies complicated by fetal distress, prolonged labor, or difficult delivery, the observed association is more likely to reflect underlying obstetric complications than the delivery procedure itself [36]. These complications may increase susceptibility to severe infection or neurological injury before hospital admission. In addition, exposure to healthcare-associated or antimicrobial-resistant pathogens during delivery may contribute to worse outcomes, particularly in resource-limited settings where infection prevention practices and access to timely microbiological diagnosis may be suboptimal [13,41]. Therefore, improvements in obstetric care and timely neonatal assessment may reduce subsequent adverse outcomes.
Culture-confirmed meningitis was another predictor of poor treatment outcomes. Culture positivity may indicate viable bacterial infection despite host immune responses and therefore may identify neonates with more severe disease. Previous studies conducted in China and Taiwan have reported similar associations between culture-confirmed bacterial meningitis and adverse clinical outcomes [27,43]. However, the relatively low culture positivity observed in this study may have resulted from antibiotic administration before lumbar puncture, a common challenge in routine clinical practice. Consequently, culture-negative cases should not be assumed to represent milder disease, and strengthening microbiological diagnostic capacity remains an important priority.
Severe CSF abnormalities, including markedly elevated WBC count, increased protein concentration, and profoundly reduced glucose levels, were also associated with poor treatment outcomes. These laboratory abnormalities reflect severe meningeal inflammation, blood-brain barrier disruption, and impaired glucose metabolism within the central nervous system, all of which have been linked to increased mortality and long-term neurological sequelae [27,43]. Similar observations have been reported in studies from Tunisia and Taiwan [42,43,44]. Their strong association with adverse outcomes in the present study supports the importance of comprehensive CSF analysis for early risk stratification and clinical decision-making, particularly where advanced diagnostic tools are limited.
Seizures, whether present at admission or developing during hospitalization, were also associated with poor treatment outcomes. Seizures are an important marker of severe central nervous system involvement and often indicate extensive brain injury resulting from meningitis [45]. Their occurrence after admission may also indicate progression of disease despite treatment or the development of neurological complications. This finding is consistent with studies from Canada [46], India [13], and Taiwan [43], which identified seizures as a predictor of mortality and neurological sequelae among affected neonates. This finding reinforces the need for continuous neurological monitoring, prompt seizure control, and early neuroimaging when available to minimize irreversible brain injury.
EONS was another determinant of poor treatment outcomes, supporting findings from Taiwan and Nigeria [7,41]. This association likely reflects the rapid progression of systemic infection during the first week of life and the limited physiological reserve of newborns. Early recognition and aggressive management of neonatal sepsis should therefore remain an integral component of meningitis care [27]. Similarly, non-exclusive breastfeeding was associated with poorer outcomes, reinforcing evidence that exclusive breastfeeding provides passive immune protection and reduces the severity of neonatal infections.
In contrast, prematurity, low birth weight, anemia, and thrombocytopenia were not independently associated with poor treatment outcomes after adjustment for other factors. This suggests that the severity of central nervous system infection and systemic illness may have a greater influence on prognosis than baseline neonatal characteristics. Alternatively, the effects of prematurity and low birth weight may have been mediated through other clinical variables included in the multivariable model. Because of the cross-sectional design, causal relationships cannot be established, and prospective longitudinal studies are warranted to clarify these pathways.
Overall, the findings indicate that poor outcomes in neonatal meningitis are driven primarily by severe infection and neurological involvement rather than demographic characteristics alone. Strengthening intrapartum care, ensuring prompt diagnosis of meningitis and neonatal sepsis, improving access to microbiological and CSF diagnostic services, closely monitoring high-risk neonates, and promoting exclusive breastfeeding are likely to reduce mortality and neurological complications in similar resource-limited settings.
Conclusion
Neonatal meningitis was associated with substantial adverse outcomes. Assisted vaginal delivery, severe CSF abnormalities, seizures, EONS, and non-exclusive breastfeeding were independent predictors of poor treatment outcomes. Strengthening early detection, neonatal care, and breastfeeding promotion may improve survival and reduce neurological complications.
Limitations and strengths of the study
This study has many main limitations. First, its retrospective cross-sectional design relied on routinely documented medical records, which limited the availability and completeness of clinical information and precluded establishing causal relationships between identified predictors and treatment outcomes. Important maternal and neonatal variables, including maternal age, education, occupation, residence, socioeconomic status, infections during pregnancy, antenatal care utilization, duration of labour, vaginal discharge, spina bifida, and prior antibiotic exposure, and clinical factors such as the sensitivity pattern of the isolate pathogens and blood glucose, were incompletely documented and therefore could not be assessed.
Secondly, the evaluation of treatment outcomes only considered the period of hospitalization. As a result, the study could not assess long-term neurodevelopmental outcomes. These outcomes include cognitive impairments, behavioral problems, or delays in motor and language development, which may only show up months or years later. Third, the study did not differentiate between community-acquired and hospital-acquired infections. This distinction is important because the organisms causing these infections, their resistance patterns, and their prognostic implications often differ. Fourth, excluding neonates with incomplete medical records may have introduced selection bias. Consequently, the true frequency of poor treatment outcomes may have been underestimated.
Fifth, the study was conducted in only two public referral hospitals in eastern Ethiopia. Although these hospitals provide care for a large number of neonates, the findings may not be generalizable to other healthcare settings, including primary or private hospitals.
Finally, the timing of lumbar puncture relative to the initiation of empirical antibiotic therapy was not consistently documented in the medical records. This may have reduced cerebrospinal fluid culture yield and led to an underestimation of microbiologically confirmed meningitis cases.
Despite these limitations, the study has important strengths. It included a relatively modest sample of neonates from two major public hospitals. These strengths improve the reliability of the findings and provide valuable evidence on treatment outcomes and their associated factors in a resource-limited setting where such data are scarce.
Acknowledgments
The authors would like to express their sincere gratitude to the administrators, data collectors, and card room staff at Hiwot Fana Comprehensive Specialized University Hospital and Jugal General Hospital for their support and assistance during data collection.
References
- 1. World Health Organization. Meningitis. https://www.who.int/news-room/fact-sheets/detail/meningitis. Accessed 2025 October 25.
- 2. Bedetti L, Miselli F, Minotti C, Latorre G, Loprieno S, Foglianese A, et al. Lumbar puncture and meningitis in infants with proven early- or late-onset sepsis: an Italian prospective multicenter observational study. Microorganisms. 2023;11(6):1546. pmid:37375048
- 3.
Bundy LM, Noor A. Neonatal meningitis. StatPearls. Treasure Island (FL): StatPearls Publishing. 2023.
- 4. Aleem S, Greenberg RG. When to include a lumbar puncture in the evaluation for neonatal sepsis. Neoreviews. 2019;20(3):e124–34. pmid:31261050
- 5. Mashau RC, Meiring ST, Dramowski A, Magobo RE, Quan VC, Perovic O. Culture-confirmed neonatal bloodstream infections and meningitis in South Africa, 2014–19: a cross-sectional study. The Lancet Global Health. 2022;10(8):e1170–8.
- 6. Yulieth AZ, Vélez-Martínez LF, Leidy CL, Beltrán CP, Cornejo-Ochoa W. Bacterial meningitis in neonates: a multicentric descriptive study in the city of Medellín, Colombia. Iatreia. 2023;36(4).
- 7. Lee W-J, Tsai M-H, Hsu J-F, Chu S-M, Chen C-C, Yang P-H, et al. The epidemiology, management and therapeutic outcomes of subdural empyema in neonates with acute bacterial meningitis. Antibiotics (Basel). 2024;13(4):377. pmid:38667053
- 8. Giannoni E, Agyeman PKA, Stocker M, Posfay-Barbe KM, Heininger U, Spycher BD, et al. Neonatal sepsis of early onset, and hospital-acquired and community-acquired late onset: a prospective population-based cohort study. J Pediatr. 2018;201:106-114.e4. pmid:30054165
- 9. Wu I-H, Tsai M-H, Lai M-Y, Hsu L-F, Chiang M-C, Lien R, et al. Incidence, clinical features, and implications on outcomes of neonatal late-onset sepsis with concurrent infectious focus. BMC Infect Dis. 2017;17(1):465. pmid:28673280
- 10. Wong CH, Duque JR, Wong JSC, Chan C-MV, Lam CSI, Fu YM, et al. Epidemiology and trends of infective meningitis in neonates and infants less than 3 months old in Hong Kong. Int J Infect Dis. 2021;111:288–94. pmid:34217874
- 11. GBD 2019 Meningitis Antimicrobial Resistance Collaborators. Global, regional, and national burden of meningitis and its aetiologies, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Neurol. 2023;22(8):685–711. pmid:37479374
- 12. Salman O, Procter SR, McGregor C, Paul P, Hutubessy R, Lawn JE, et al. Systematic review on the acute cost-of-illness of sepsis and meningitis in neonates and infants. Pediatr Infect Dis J. 2020;39(1):35–40. pmid:31738319
- 13. Wondimu MN, Toni AT, Zamanuel TG. Magnitude of neonatal meningitis and associated factors among newborns with neonatal sepsis admitted to the University of Gondar Comprehensive Specialized Hospital, North Gondar, Ethiopia. PLoS One. 2023;18(9):e0290639. pmid:37699035
- 14. Xu M, Hu L, Huang H, Wang L, Tan J, Zhang Y, et al. Etiology and clinical features of full-term neonatal bacterial meningitis: a multicenter retrospective cohort study. Front Pediatr. 2019;7:31. pmid:30815433
- 15. Guillén-Pinto D, Málaga-Espinoza B, Ye-Tay J, Rospigliosi-López ML, Montenegro-Rivera A, Rivas M, et al. Neonatal meningitis: a multicenter study in Lima, Peru. Rev Peru Med Exp Salud Publica. 2020;37(2):210–9. pmid:32876208
- 16. Ikumapayi UN, Hill PC, Hossain I, Olatunji Y, Ndiaye M, Badji H, et al. Childhood meningitis in rural Gambia: 10 years of population-based surveillance. PLoS One. 2022;17(8):e0265299. pmid:35947593
- 17. Sturgeon JP, Zanetti B, Lindo D. C-Reactive Protein (CRP) levels in neonatal meningitis in England: an analysis of national variations in CRP cut-offs for lumbar puncture. BMC Pediatr. 2018;18(1):380. pmid:30509228
- 18. Ou-Yang M-C, Tsai M-H, Chu S-M, Chen C-C, Yang P-H, Huang H-R, et al. The clinical characteristics, microbiology and risk factors for adverse outcomes in neonates with gram-negative bacillary meningitis. Antibiotics (Basel). 2023;12(7):1131. pmid:37508227
- 19. Sampe DG, Mahalini DS, Witarini KA. Characteristics of risk factors for bacterial meningitis in neonates at RSUP Prof. Dr. I.G.N.G. Ngoerah Denpasar. E-Jurnal Medika Udayana. 2024;13(6):95–101.
- 20. Gordon SM, Srinivasan L, Harris MC. Neonatal meningitis: overcoming challenges in diagnosis, prognosis, and treatment with omics. Front Pediatr. 2017;5:139. pmid:28670576
- 21. El Tahir O, de Jonge R, Ouburg S, Morré S, van Furth A. Study protocol: the Dutch 20| 30 postmeningitis study: a cross-sectional follow-up of two historical childhood bacterial meningitis cohorts on long-term outcomes. BMC Pediatrics. 2019;19:1–8.
- 22. Mwaniki MK, Talbert AW, Njuguna P, English M, Were E, Lowe BS, et al. Clinical indicators of bacterial meningitis among neonates and young infants in rural Kenya. BMC Infect Dis. 2011;11:301. pmid:22044635
- 23. Pelkonen T, Urtti S, Dos Anjos E, Cardoso O, de Gouveia L, Roine I, et al. Aetiology of bacterial meningitis in infants aged <90 days: prospective surveillance in Luanda, Angola. Int J Infect Dis. 2020;97:251–7. pmid:32534141
- 24. Pishori T, Furia FF, Manji K. A cross-sectional study of clinical features of bacterial meningitis among neonates presumed to have sepsis in a tertiary hospital, Dar es Salaam, Tanzania. Pan Afr Med J. 2023;46:123. pmid:38465011
- 25. GBD 2016 Meningitis Collaborators. Global, regional, and national burden of meningitis, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2018;17(12):1061–82. pmid:30507391
- 26. Chala TK, Lemma TD, Godana KT, Arefayine MB, Abdissa A, Gudina EK. The cost of suspected and confirmed bacterial meningitis cases treated at Jimma University Medical Center, Ethiopia. Ethiopian Journal of Health Sciences. 2022;32(4):765–72.
- 27. Mao DH, Miao JK, Zou X, Chen N, Yu LC, Lai X. Risk factors in predicting prognosis of neonatal bacterial meningitis-a systematic review. Frontiers in Neurology. 2018;9:929.
- 28.
Habeneyom T. Treatment outcome and its associated factors among neonates admitted for meningitis at Tibebegion Comprehensive Specialized Hospital. University of Gondar. 2020. http://ir.bdu.edu.et/bitstream/handle/123456789/13694/Habeneyom%20Tebeje.pdf?sequence=1&isAllowed=y
- 29. Weldegerima K, Gebremariam DS, Haftu H, Berhe G, Hadgu A, Mohammedamin MM. Neonatal Seizure Pattern, Outcome, and its Predictors Among Neonates Admitted to NICU of Ayder Comprehensive Specialized Hospital, Mekelle, Tigray, Ethiopia. Int J Gen Med. 2023;16:4343–55. pmid:37781273
- 30. Hailemeskel HS, Dagnaw FT, Demis S, Birhane BM, Azanaw MM, Chanie ES, et al. Neonatal outcomes of preterm neonates and its predictors in Ethiopian public hospitals: multicenter prospective follow-up study. Heliyon. 2023;9(8):e18534. pmid:37576212
- 31. Ogundare E, Akintayo A, Aladekomo T, Adeyemi L, Ogunlesi T, Oyelami O. Presentation and outcomes of early and late onset neonatal sepsis in a Nigerian Hospital. Afr Health Sci. 2019;19(3):2390–9. pmid:32127809
- 32. Kermorvant-Duchemin E, Laborie S, Rabilloud M, Lapillonne A, Claris O. Outcome and prognostic factors in neonates with septic shock. Pediatr Crit Care Med. 2008;9(2):186–91. pmid:18477932
- 33. Gurubacharya S, Aryal D, Misra M, Gurung R. Short-term outcome of mechanical ventilation in neonates. J Nepal Paedtr Soc. 2011;31(1):35–8.
- 34. Sasikumar D, Prabhu MA, Kurup R, Francis E, Kumar S, Gangadharan ST, et al. Outcomes of neonatal critical congenital heart disease: results of a prospective registry-based study from South India. Arch Dis Child. 2023;108(11):889–94. pmid:37328195
- 35.
Edwards MS. Neonatal sepsis. Martin RJ, Fanaroff AA, Walsh MC. Fanaroff and Martin’s Neonatal-Perinatal Medicine: Diseases of the Fetus and Infant. 9th ed. Philadelphia: Elsevier Mosby. 2010. 806–9.
- 36. Li Y-T, Li C-X, Huang C-J, Wen Q-Y, Deng S-M, Zhu L-P, et al. Meconium-stained amniotic fluid: impact on prognosis of neonatal bacterial meningitis. J Trop Pediatr. 2022;68(5):fmac064. pmid:35962981
- 37. Kamoun F, Dowlut MB, Ameur SB, Sfaihi L, Mezghani S, Chabchoub I, et al. Neonatal purulent meningitis in southern Tunisia: epidemiology, bacteriology, risk factors and prognosis. Fetal Pediatr Pathol. 2015;34(4):233–40. pmid:26083897
- 38. Barik KL, Biswas P, Das KK, Laha S, Paul S, Mondal S. Bacteriological profile, antibiotic susceptibility pattern and other factors related to neonatal meningitis: a cross-sectional hospital-based study from West Bengal. Asian J Med Sci. 2022;13(1):93–8.
- 39. Erickson TA, Munoz FM, Troisi CL, Nolan MS, Hasbun R, Brown EL, et al. The epidemiology of meningitis in infants under 90 days of age in a large pediatric hospital. Microorganisms. 2021;9(3):526. pmid:33806478
- 40. Ouchenir L, Renaud C, Khan S, Bitnun A, Boisvert A-A, McDonald J, et al. The epidemiology, management, and outcomes of bacterial meningitis in infants. Pediatrics. 2017;140(1):e20170476. pmid:28600447
- 41. Airede KI, Adeyemi O, Ibrahim T. Neonatal bacterial meningitis and dexamethasone adjunctive usage in Nigeria. Niger J Clin Pract. 2008;11(3):235–45. pmid:19140361
- 42. Ben Hamouda H, Ben Haj Khalifa A, Hamza MA, Ayadi A, Soua H, Khedher M, et al. Clinical outcome and prognosis of neonatal bacterial meningitis. Arch Pediatr. 2013;20(9):938–44. pmid:23829970
- 43. Lin M-C, Chi H, Chiu N-C, Huang F-Y, Ho C-S. Factors for poor prognosis of neonatal bacterial meningitis in a medical center in Northern Taiwan. J Microbiol Immunol Infect. 2012;45(6):442–7. pmid:22571998
- 44. Chang C-J, Chang W-N, Huang L-T, Huang S-C, Chang Y-C, Hung P-L, et al. Neonatal bacterial meningitis in southern Taiwan. Pediatr Neurol. 2003;29(4):288–94. pmid:14643389
- 45.
Volpe JJ. Volpe’s Neurology of the Newborn. 6th ed. Philadelphia: Elsevier. 2018.
- 46. Klinger G, Chin CN, Beyene J, Perlman M. Predicting the outcome of neonatal bacterial meningitis. Pediatrics. 2000;106(3):477–82. pmid:10969090