Skip to main content
Download PDF

Association of blood neutrophil-lymphocyte ratio with short-term prognosis and severity of tuberculosis meningitis patients without HIV infection

BMC Infectious Diseases volume 23, Article number: 449 (2023) Cite this article

Abstract

Background

Predicting the short-term prognosis and severity of tuberculosis meningitis (TBM) patients without HIV infection can be challenging, and there have been no prior studies examining the neutrophil lymphocyte ratio (NLR) as a potential predictor of short-term prognosis or its relationship to TBM severity. We hypothesized that NLR might serve as an independent indicator of short-term prognostic significance and that there might be a correlation between NLR and severity. The aim of this study was to investigate the role of NLR as a predictor of short-term prognosis and its relationship to severity of tuberculosis meningitis patients without HIV infection.

Methods

We retrospectively collected data from patients diagnosed with TBM in the West China Hospital, Sichuan University, from the period between January 1st, 2018 and August 1st, 2019. Multivariable analysis was executed by the logistic regression model to verify the independence of the 28-day mortality, the discriminative power for predicting short-term prognosis was evaluated using a Receiver Operating Characteristic (ROC) curve, survival outcomes were analyzed using the Kaplan-Meier method and Pearson’s correlation analysis was performed to discuss correlation between NLR and the severity of TBM.

Results

We collected data from 231 TBM patients without HIV infection. 68 (29.4%) patients are classified as stage (I) 138(59.8%) patients are stage (II) 25(10.8%) patients are stage (III) 16(6.9%) patients died during the follow-up period of 28 days. By multiple logistic regression analyses, the NLR (OR = 1.065, 95% CI = 1.001–1.133, P = 0.045), peripheral neurological deficit (OR 7.335, 95% CI 1.964–27.385, P = 0 0.003) and hydrocephalus (OR 11.338, 95% CI 2.397–53.633, P = 0 0.002) are independent risk factors of 28-day mortality. The area under the ROC curve (AUC) for predicting short prognosis using NLR is 0.683 (95% CI 0.540–0.826, P = 0.015), the optimal cutoff value is 9.99(sensitivity: 56.3%, specificity: 80.9%). The Kaplan-Meier analysis demonstrated that patients with higher NLR(>9.99) had significantly worse survival outcomes(P<0.01).Pearson’s correlation analysis presents a significant positive correlation between the severity of TBM and NLR (r = 0.234, P<0.01).

Conclusions

NLR, peripheral neurological deficit, and hydrocephalus are independent risk factors of 28-day mortality, NLR can predict the short-term prognosis of TBM patients without HIV infection. NLR is also found to be significantly and positively correlated with the severity of TBM.

Peer Review reports

Introduction

Tuberculosis (TB) is the major cause of death by an infectious disease worldwide [1]. However, tuberculosis meningitis (TBM) is considered the most devastating manifestation of Mycobacterium tuberculosis infection [2]. TBM is an inflammatory condition caused by the invasion of Mycobacterium tuberculosis into the human central nervous system, including the spinal cord, meninges, or brain parenchyma, which can lead to a series of secondary pathophysiological changes in the brain of affected patients [3]. The clinical course of TBM without HIV infection is nonspecific and quite variable. Additionally, various complex factors can impact the prognosis of patients with this disease. However, early identification of high-risk patients, along with intensive treatment, may help improve their prognosis [4]. So, assessment of the sufficient risk factor in patients with TBM is crucial in making clinical decisions.

Even given anti-tuberculosis treatment, The mortality rate of TBM patients as high as 10–50% [5]. Some studies indicated that factors such as disturbance of consciousness and hydrocephalus might be correlated with poor prognosis for patients with TBM [2, 5, 6]. However, the marker of inflammation in the blood has not be reported about the short-term prognosis of TBM patients.

Neutrophil-lymphocyte ratio (NLR) is defined as the number of neutrophils in whole blood divided by the number of lymphocytes in whole blood [7],it is a biomarker derived from leukocytes as a marker of inflammation. The NLR describes is a reliable parameter to describe the immune response to various stimuli/stressors [8] and it has been found to be a useful biomarker for predicting prognosis or severity in various clinical setting including sepsis, military tuberculosis and bacterial meningitis [8,9,10],but the association of NLR with clinical prognosis and severity in TBM patients without HIV infection has not been reported, This study is expected to determine whether NLR is an independent predictor of short-term prognosis in TBM patients without HIV infection and the relationship between NLR and the severity of TBM.

Methods

Patients and diagnosis of TBM

We retrospectively collected the data of all patients (≥ 18year-old) who were admitted to the West China Hospital, Sichuan University and diagnosed with TBM, from the period between January 1st, 2018 and August 1st, 2019. Patients were eligible for inclusion according to the standardized case definition of TBM proposed by Marais including the clinical criteria, CSF criteria, cerebral imaging criteria, evidence of tuberculosis elsewhere and exclusion of alternative diagnoses: An alternative diagnosis must be confirmed microbiologically, serologically, or histopathologically [11]. Patients with data was insufficient, HIV infection and pregnant were excluded from the study.

Collection of clinical data

The data information of patients was obtained by the patients’ electronic medical record management system and telephone. At the time of admission, the following data were collected, including demographic information (sex, age, disease duration), clinical criteria (fever (> 37.5℃) > 5 days, night sweats, weight loss, cough, headache, vomiting, peripheral neurological deficit, cognitive impairment, change in consciousness, cranial nerve palsy, and seizures), laboratory data (red blood cell, white blood cell, platelet, neutrophil, lymphocyte, the neutrophil- lymphocyte ratio(NLR), Serum sodium, Serum potassium, plasma glucose, albumin, CSF leukocyte count, CSF protein, CSF chlorine, CSF glucose, ratio of CSF to blood glucose), and cerebral imaging criteria (hydrocephalus, basal meningeal enhancement, tuberculoma, and infarct).We collected the severity of TBM at the time of admission which was assessed using the British Medical Research Council (BMRC) TBM stages modified as grade I (GCS 15; no focal neurological signs), grade II (GCS 11–14, or 15 with focal neurological signs), and grade III (GCS ≤ 10)disease [11] ,and also collected the outcome (survivors and non- survivors)after 28 day via telephone call.

Management

Patients received four TBM treatments, isoniazid (10–20 mg/kg/day; maximum 1200 mg/day), rifampicin (10–20 mg/kg/day; maximum 600 mg/day), pyrazinamide (20–30 mg/kg/day; maximum 1500 mg/ day), and ethambutol: (15–20 mg/kg/day; maximum 750 mg/day), they also received dexamethasone(0.4 mg/kg/day; maximum16mg/day) at the same time of diagnosis, administered for 4 weeks.

Statistical analysis

A chi-squared or Fisher’s exact test was implemented to compare the categorical variables. An independent-sample test was utilized to compare the continuous variables. Multivariable analysis was executed by the stepwise logistic regression model (forward) to verify the independence of the 28-day mortality, and the Lemeshow-Hosmer χ2 statistics was used to evaluate the Goodness-of-fit of the Multivariable logistic regression model. The discriminative power for predicting short-term prognosis was evaluated using a Receiver Operating Characteristic (ROC) curve, survival outcomes were analyzed using the Kaplan-Meier method. Pearson’s correlation analysis was performed to discuss correlation about and the severity of TBM. All statistical analyses were implemented with the use of SPSS software version 22.0 (USA, IBM analytics). A P value equal or less than 0.05 was statistically significant in all analyses.

Results

There were 245 patients with TBM who were treated at the West China Hospital, Sichuan University. 14 patients were excluded from the study because of insufficient data or HIV infection, finally, a total of 231 patients were analyzed in this study. During the study period, 16 patients (6.9%) died while the remaining 215 (93.1%) survived.

In the study, there are 129 (55.8%) men, the average age of all patients is 36 ± 16years. The patients are classified into three stages according to the severity: 68 (29.4%) are in stage I, 138 (59.8%) are in stage II, and 25 (10.8%) are in stage III.

Tables 1 and 2 describes the patients’ characteristics between the survivors and deaths. The most common symptoms of TBM are fever, headache, and vomiting, with an incidence rate of over 50%. Survivors exhibit a lower incidence of peripheral neurological deficit (P < 0.001), change in consciousness (P = 0.002), and hydrocephalus (P < 0.001) compared to those who died. NLR are higher in the deaths compared with survivors (P = 0.003), and albumin are lower in the deaths (P = 0.045). There is no significant statistical difference in the other factors.

Table 1 The TBM1 patient’s general characteristics without HIV infection
Full size table
Table 2 The TBM1 patient’s laboratory and imaging characteristics without HIV infection
Full size table

In this study, seven single factors including peripheral neurological deficit, change in consciousness, hydrocephalus, NLR, albumin, age, and seizures were included in a multiple logistic regression analysis, and it was found that the NLR is an independent risk factor for 28-day mortality (OR = 1.065, 95% CI = 1.001–1.133, P = 0.045). In addition, peripheral neurological deficit (OR 7.335, 95% CI 1.964–27.385, P = 0.003) and hydrocephalus (OR 11.338, 95% CI 2.397–53.633, P = 0 0.002) were significantly more likely in deceased patients than in survivors (refer to Table 3). Neither the rate of change in consciousness, albumin, age and seizures are independent risk factors for 28-day mortality of patients with TBM. The Hosmer-Lemeshowχ2 statistics of the multivariate logistic regression models is 2.260 (P = 0.972).

Table 3 The multivariate analysis result 1of 28-day mortality in TBM2 patients without HIV infection
Full size table

The area under the ROC curve (AUC) for predicting short-term prognosis in patients with TBM using NLR is 0.683 (95% CI 0.540–0.826, P = 0.015), with an optimal cutoff value of 9.99. When using this cutoff, NLR has a sensitivity of 56.3% and specificity of 80.9% for predicting short-term prognosis (refer to Fig. 1).

Fig. 1
figure 1

The ROC curves for predicting short-term prognosis in TBM patients without HIV infection by using NLR

Full size image

Patients were classified into the high NLR group and the low NLR group using a cutoff value of 9.99. Compared to the low NLR group, patients in the high NLR group exhibited higher incidence rates of changes in consciousness, hydrocephalus, and basal meningeal enhancement. Furthermore, they had significantly elevated levels of white blood cells and plasma glucose, and significantly reduced levels of albumin, serum sodium, CSF glucose, CSF chlorine, and the ratio of CSF to blood glucose (refer to Tables 4 and 5). Moreover, patients in the high NLR group had a higher 28-day mortality rate (refer to Table 5). The Kaplan-Meier analysis demonstrated that patients with high NLR had significantly worse survival outcomes (P < 0.05) (refer to Fig. 2).

Table 4 Comparison of general characteristics between patients with high and low NLR1
Full size table
Table 5 Comparison of laboratory characteristics, imaging characteristics and prognosis between patients with high NLR1 and low NLR1
Full size table
Fig. 2
figure 2

The results of the Kaplan-Meier analysis that TBM patients with high NLR and low NLR

Full size image

The Study also explored the relationship between the severity of TBM and the NLR. The NLR values for patients with stage I TBM are 6.00 ± 5.03, while those for patients with stage II TBM are 7.56 ± 6.33, and for patients with stage III TBM, the NLR values are 12.00 ± 9.92. Pearson’s correlation analysis presents a significant positive correlation between the severity of TBM and NLR (r = 0.234, P < 0.01).

Discussion

In this study, NLR was found to be an independent predictor of short-term prognosis in TBM patients without HIV infection. Patients with NLR greater than 9.99 had worse survival outcomes. In a number of studies, it has been reported that high NLR is associated with high mortality in cancers [12,13,14] or cardiovascular diseases [9, 15, 16]. NLR is a readily obtainable inflammatory marker that indicates the degree of neutrophil elevation or lymphocyte depletion. At present, the cause for the correlation between the increase in NLR and poor outcome has not yet been explained clearly. High neutrophil counts or lymphopenia may be associated with poor prognosis in several previous studies on TB [17,18,19], but NLR has not been represented in TBM patients. Chedid, C hypothesized that high neutrophil counts and low lymphocyte proportions had highly inflammatory clinical patterns by the context of mycobacterial infection [17], which are markers of persisting inflammation or failure to clear the bacteria [20]. High neutrophil counts may reflect the presence of delayed apoptosis in inflammatory condition, and inhibit the anti-inflammatory ability of neutrophil cells [21]. In chronic TB infection, sustained inflammation which was an impairment maker of the TB-specific immune response and a marker of active disease has be reported [22]. High NLR may represent relative lymphopenia, low lymphocyte counts are associated with a negative response to treatment [17, 23]in relation to cell-mediated immunity which is important in the immune response to M. tuberculosis [9]. So, the similar pathway may have affected the progression and prognosis of TBM.

The study also investigates the association of high NLR with the severity of TBM. The higher NLR represents the higher the clinical stage, as some studies have reported a link between high NLR and higher cancer stage [13, 19, 24] and the severity of pulmonary TB [25]. When the NLR of TBM patients is greater than 9.99, they are more likely to experience altered consciousness and develop complications such as hydrocephalus, hyponatremia, and hypoproteinemia. These factors indicate that the patient may have a higher severity.

In this study, peripheral neurological deficit is a predictor of poor prognosis in TBM patients. A series of studies had reported similar conclusion [26,27,28]. About 15–50% of patients with TBM have exist peripheral neurological deficit when they first present symptom [27,28,29,30], this study reported 30% (69/231) of patients with TBM. This condition may be associated with high rates of morbidity and mortality. Some studies also reported cranial nerve palsy is a risk factors association with bad prognosis [30, 31],but this study did not support it. This study focused the 28-day mortality however those studies had a long-term follow-up result.

Hydrocephalus is a quite common complication of TBM, as reported, up to 60% of patients with TBM be found to by cranial imaging such as MRI/CT [32]. Patients with hydrocephalus may be associated with the pathogenesis of meningeal exudate, as well as either overproduction of cerebrospinal fluid (CSF) or malfunctioning absorption of CSF in the subarachnoid space [33, 34], and it is considered to be an important risk factor for poor prognosis.

Limitations

This study suggests that NLR is a useful predictor of short-term prognosis for TBM patients without HIV infection, but it has several limitations. Firstly, the sample size was small, with only 16 deaths occurring within 28 days, which could potentially affect the stability of the logistic model. Additionally, the diagnosis primarily relied on clinical criteria, CSF criteria, and cerebral imaging criteria, which may introduce bias into the data. This study did not exclude patients who temporarily discontinued anti-tuberculosis treatment due to medication side effects. Furthermore, potential drug-resistant patients were not identified due to the lack of drug resistance testing. These factors have the potential to impact the study’s results. Further studies with larger sample sizes are necessary to validate the effect of NLR values on the short-term prognosis of TBM patients without HIV infection.

Conclusions

NLR, peripheral neurological deficit, and hydrocephalus are independent risk factors of 28-day mortality, NLR can predict the short-term prognosis in TBM patients without HIV infection. NLR is also found to be significantly and positively correlated with the severity of TBM. Therefore, TBM patients without HIV infection who have high NLR values should be closely monitored in clinical practice.

Data Availability

All data generated or analyzed during this study are included in this published article.

Abbreviations

BMRC:

British Medical Research Council

CI:

Confidence interval

CNS:

Central nervous system

CSF:

Cerebrospinal fluid

GCS:

Glasgow Coma Scale

HIV:

Human immunodeficiency virus

NLR:

Neutrophil-lymphocyte ratio

OR:

Odds ratio

ROC:

Receiver Operating Characteristic

TB:

Tuberculosis

TBM:

Tuberculosis meningitis

References

  1. Navarro-Flores A, Fernandez-Chinguel JE, Pacheco-Barrios N, Soriano-Moreno DR, Pacheco-Barrios K. Global morbidity and mortality of central nervous system tuberculosis: a systematic review and meta-analysis. J Neurol. 2022;269(7):3482–94.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Modi M, Sharma K, Prabhakar S, Goyal MK, Takkar A, Sharma N, Garg A, Faisal S, Khandelwal N, Singh P, et al. Clinical and radiological predictors of outcome in tubercular meningitis: a prospective study of 209 patients. Clin Neurol Neurosurg. 2017;161:29–34.

    Article  CAS  PubMed  Google Scholar 

  3. Hsu PC, Yang CC, Ye JJ, Huang PY, Chiang PC, Lee MH. Prognostic factors of tuberculous meningitis in adults: a 6-year retrospective study at a tertiary hospital in northern Taiwan. J Microbiol Immunol infection = Wei mian yu gan ran za zhi. 2010;43(2):111–8.

    Article  CAS  Google Scholar 

  4. van Crevel R, Ruslami R, Aarnoutse R. Therapy for tuberculous meningitis. N Engl J Med. 2016;374(22):2187.

    Article  PubMed  Google Scholar 

  5. Chou CH, Lin GM, Ku CH, Chang FY. Comparison of the APACHE II, GCS and MRC scores in predicting outcomes in patients with tuberculous meningitis. Int J tuberculosis lung disease: official J Int Union against Tuberculosis Lung Disease. 2010;14(1):86–92.

    Google Scholar 

  6. Van TT, Farrar J. Tuberculous meningitis. J Epidemiol Commun Health. 2014;68(3):195–6.

    Article  Google Scholar 

  7. Imtiaz F, Shafique K, Mirza SS, Ayoob Z, Vart P, Rao S. Neutrophil lymphocyte ratio as a measure of systemic inflammation in prevalent chronic diseases in asian population. Int archives Med. 2012;5(1):1–6.

    Article  Google Scholar 

  8. Zhou T, Zheng N, Li X, Zhu D, Han Y. Prognostic value of neutrophil-lymphocyte count ratio (NLCR) among adult ICU patients in comparison to APACHE II score and conventional inflammatory markers: a multi center retrospective cohort study. BMC Emerg Med. 2021;21(1):1–10.

    Article  Google Scholar 

  9. Han Y, Kim SJ, Lee SH, Sim YS, Ryu YJ, Chang JH, Shim SS, Kim Y, Lee JH. High blood neutrophil-lymphocyte ratio associated with poor outcomes in miliary tuberculosis. J Thorac disease. 2018;10(1):339.

    Article  Google Scholar 

  10. Widjaja H, Rusmawatiningtyas D, Makrufardi F, Arguni E. Neutrophil lymphocyte ratio as predictor of mortality in pediatric patients with bacterial meningitis: a retrospective cohort study. Annals of Medicine and Surgery. 2022;73:103191.

    Article  PubMed  Google Scholar 

  11. Marais S, Thwaites G, Schoeman JF, Török ME, Misra UK, Prasad K, Donald PR, Wilkinson RJ, Marais BJ. Tuberculous meningitis: a uniform case definition for use in clinical research. Lancet Infect Dis. 2010;10(11):803–12.

    Article  PubMed  Google Scholar 

  12. Cupp MA, Cariolou M, Tzoulaki I, Aune D, Evangelou E, Berlanga-Taylor AJ. Neutrophil to lymphocyte ratio and cancer prognosis: an umbrella review of systematic reviews and meta-analyses of observational studies. BMC Med. 2020;18(1):1–16.

    Article  Google Scholar 

  13. Marchetti C, D’Indinosante M, Bottoni C, Di Ilio C, Di Berardino S, Costantini B, Minucci A, Vertechy L, Scambia G, Fagotti A. NLR and BRCA mutational status in patients with high grade serous advanced ovarian cancer. Sci Rep. 2021;11(1):1–8.

    Article  Google Scholar 

  14. Ayers KL, Ma M, Debussche G, Corrigan D, McCafferty J, Lee K, Newman S, Zhou X, Hirsch FR, Mack PC. A composite biomarker of neutrophil-lymphocyte ratio and hemoglobin level correlates with clinical response to PD-1 and PD-L1 inhibitors in advanced non-small cell lung cancers. BMC Cancer. 2021;21(1):1–11.

    Article  Google Scholar 

  15. Papa A, Emdin M, Passino C, Michelassi C, Battaglia D, Cocci F. Predictive value of elevated neutrophil–lymphocyte ratio on cardiac mortality in patients with stable coronary artery disease. Clin Chim Acta. 2008;395(1–2):27–31.

    Article  CAS  PubMed  Google Scholar 

  16. Adamstein NH, MacFadyen JG, Rose LM, Glynn RJ, Dey AK, Libby P, Tabas IA, Mehta NN, Ridker PM. The neutrophil–lymphocyte ratio and incident atherosclerotic events: analyses from five contemporary randomized trials. Eur Heart J. 2021;42(9):896–903.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Chedid C, Kokhreidze E, Tukvadze N, Banu S, Uddin MKM, Biswas S, Russomando G, Acosta CCD, Arenas R, Ranaivomanana PP. Association of baseline white blood cell counts with tuberculosis treatment outcome: a prospective multicentered cohort study. Int J Infect Dis. 2020;100:199–206.

    Article  CAS  PubMed  Google Scholar 

  18. Okamura K, Nagata N, Wakamatsu K, Yonemoto K, Ikegame S, Kajiki A, Takayama K, Nakanishi Y. Hypoalbuminemia and lymphocytopenia are predictive risk factors for in-hospital mortality in patients with tuberculosis. Intern Med. 2013;52(4):439–44.

    Article  CAS  PubMed  Google Scholar 

  19. Naghavi M, Abajobir AA, Abbafati C, Abbas KM, Abd-Allah F, Abera SF, Aboyans V, Adetokunboh O, Afshin A, Agrawal A. Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016: a systematic analysis for the global burden of Disease Study 2016. The lancet. 2017;390(10100):1151–210.

    Article  Google Scholar 

  20. Srivastava S, Ernst JD, Desvignes L. Beyond macrophages: the diversity of mononuclear cells in tuberculosis. Immunol Rev. 2014;262(1):179–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Zahorec R. Ratio of neutrophil to lymphocyte counts-rapid and simple parameter of systemic inflammation and stress in critically ill. Bratisl Lek Listy. 2001;102(1):5–14.

    CAS  PubMed  Google Scholar 

  22. Sia JK, Rengarajan J. Immunology of Mycobacterium tuberculosis infections. Microbiol Spectr. 2019;7(4):7.

    Article  Google Scholar 

  23. Yin Y, Kuai S, Liu J, Zhang Y, Shan Z, Gu L, Huang Q, Pei H, Wang J. Pretreatment neutrophil-to-lymphocyte ratio in peripheral blood was associated with pulmonary tuberculosis retreatment. Archives of Medical Science. 2017;13(2):404–11.

    Article  PubMed  Google Scholar 

  24. Templeton AJ, McNamara MG, Šeruga B, Vera-Badillo FE, Aneja P, Ocaña A, Leibowitz-Amit R, Sonpavde G, Knox JJ, Tran B. Prognostic role of neutrophil-to-lymphocyte ratio in solid tumors: a systematic review and meta-analysis. JNCI: J Natl Cancer Inst 2014, 106(6).

  25. Abakay O, Abakay A, Sen HS, Tanrikulu AC. The relationship between inflammatory marker levels and pulmonary tuberculosis severity. Inflammation. 2015;38(2):691–6.

    Article  CAS  PubMed  Google Scholar 

  26. Cherian A, Thomas S. Central nervous system tuberculosis. Afr Health Sci 2011, 11(1).

  27. Misra U, Kalita J, Roy A, Mandal S, Srivastava M. Role of clinical, radiological, and neurophysiological changes in predicting the outcome of tuberculous meningitis: a multivariable analysis. J Neurol Neurosurg Psychiatry. 2000;68(3):300–3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Kalita J, Misra UK, Ranjan P. Predictors of long-term neurological sequelae of tuberculous meningitis: a multivariate analysis. Eur J Neurol. 2007;14(1):33–7.

    Article  CAS  PubMed  Google Scholar 

  29. Pehlivanoglu F, Kart Yasar K, Sengoz G. Tuberculous meningitis in adults: a review of 160 cases. The Scientific World Journal 2012, 2012.

  30. Li K, Tang H, Yang Y, Li Q, Zhou Y, Ren M, Long X, Shen W, Hu R, Wang X, et al. Clinical features, long-term clinical outcomes, and prognostic factors of tuberculous meningitis in West China: a multivariate analysis of 154 adults. Expert Rev anti-infective therapy. 2017;15(6):629–35.

    Article  CAS  PubMed  Google Scholar 

  31. Sharma P, Garg RK, Verma R, Singh MK, Shukla R. Incidence, predictors and prognostic value of cranial nerve involvement in patients with tuberculous meningitis: a retrospective evaluation. Eur J Intern Med. 2011;22(3):289–95.

    Article  PubMed  Google Scholar 

  32. Feng B, Fei X, Sun Y, Zhang X, Shang D, Zhou Y, Sheng M, Xu J, Zhang W, Ren W. Prognostic factors of adult tuberculous meningitis in intensive care unit: a single-center retrospective study in East China. BMC Neurol. 2021;21(1):1–11.

    CAS  Google Scholar 

  33. Sheu JJ, Hsu CY, Yuan RY, Yang CC. Clinical characteristics and treatment delay of cerebral infarction in tuberculous meningitis. Intern Med J. 2012;42(3):294–300.

    Article  PubMed  Google Scholar 

  34. Huang HJ, Ren ZZ, Dai YN, Tong YX, Yang DH, Chen MJ, Huang YC, Wang MS, Zhang JJ, Song WY, et al. Old age and hydrocephalus are associated with poor prognosis in patients with tuberculous meningitis: a retrospective study in a chinese adult population. Medicine. 2017;96(26):e7370.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We acknowledge all the participants for their cooperation.

Funding

No specific funding was available for this study.

Author information

Authors and Affiliations

  1. Department of Emergency Medicine, Laboratory of Emergency Medicine, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, China

    Zhihan Gu, Bofu Liu, Tao Cheng, Tianyong Han, Le Tong & Yu Cao

  2. Disaster Medical Center, Sichuan University, Chengdu, Sichuan, 610041, China

    Xiaomin Yu

Authors
  1. Zhihan Gu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bofu Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiaomin Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tao Cheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tianyong Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Le Tong
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Yu Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

ZG conceived the study, drafted the manuscript, analyzed the data and critically revised the manuscript for important intellectual content; BL analyzed of the data; XY, TC, TH and LT were involved in the diagnosis and confirmation of tuberculous meningitis patient. Corresponding author was responsible for study concept design; analysis, interpretation and integrity of the data, preparation of the manuscript and reviewed the manuscript for intellectual content. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Yu Cao.

Ethics declarations

Ethics approval and consent to participate

The study was approved by the Human Ethics Committee of West China Hospital of Sichuan University (ethics No.: 2018 − 598) and was conducted in accordance with the Declaration of Helsinki. Informed consent was obtained from all subjects and/or their legal guardian(s).All methods were performed in accordance with the relevant guidelines and regulations.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gu, Z., Liu, B., Yu, X. et al. Association of blood neutrophil-lymphocyte ratio with short-term prognosis and severity of tuberculosis meningitis patients without HIV infection. BMC Infect Dis 23, 449 (2023). https://doi.org/10.1186/s12879-023-08438-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12879-023-08438-y

Keywords

BMC Infectious Diseases

ISSN: 1471-2334

Contact us