Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-27T00:54:33.691Z Has data issue: false hasContentIssue false

Risk factors for death in tuberculosis patients requiring ICU care

Published online by Cambridge University Press:  05 January 2021

Jun-Li Wang
Affiliation:
Department of Lab Medicine, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China
Qi-Yun Yin
Affiliation:
Department of Intensive Care Unit, The First Affiliated Hospital of Shandong First Medical University, Jinan, China
Chao Han
Affiliation:
Department of Geriatrics, Shandong Mental Health Center, Jinan, China
Feng-Lin Liu*
Affiliation:
Department of Thoracic Surgery, Shandong Provincial Chest Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
Mao-Shui Wang*
Affiliation:
Department of Lab Medicine, Shandong Provincial Chest Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
*
Authors for correspondence: Feng-Lin Liu, E-mail: [email protected]; Mao-Shui Wang, E-mail: [email protected]
Authors for correspondence: Feng-Lin Liu, E-mail: [email protected]; Mao-Shui Wang, E-mail: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

The prognostic factor for in-hospital mortality in tuberculosis (TB) patients requiring intensive care unit (ICU) care remains unclear. Therefore, a retrospective study was conducted aiming to estimate the in-hospital mortality rate and the risk factors for mortality in a high-burden setting. All patients with culture-confirmed TB that were admitted to the ICU of the hospital between March 2012 and April 2019 were identified retrospectively. Data, such as demographic characteristics, comorbidities, laboratory measures and mortality, were obtained from medical records. The Cox proportional hazards regression model was used to identify prognostic factors that influence in-hospital mortality. A total of 82 ICU patients with confirmed TB were included in the analysis, and 22 deaths were observed during the hospital stay, 21 patients died in the ICU. In the multivariable model adjusted for sex and age, the levels of serum albumin and white blood cell (WBC) count were significantly associated with mortality in TB patients requiring ICU care (all P < 0.01), the hazard ratios were 0.8 (95% confidence interval (CI): 0.7–0.9) per 1 g/l and 1.1 (95% CI: 1.0–1.2) per 1 × 109/l, respectively. In conclusion, in-hospital mortality remains high in TB patients requiring ICU care. Low serum albumin level and high WBC count significantly impact the risk of mortality in these TB patients in China.

Type
Original Paper
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

Introduction

Tuberculosis (TB) remains the first cause of death from infectious disease worldwide despite available effective therapies. In 2016, there were an estimated 10.4 million new cases of TB, 490 000 new cases with multidrug-resistant TB (MDR-TB), and 1.7 million cases died from TB [Reference Floyd1].

Occasionally, patients with TB disease may require intensive care unit (ICU) admission, the proportion has been variably reported; it was seen in approximately 1–3% of all patients with TB [Reference Frame2Reference Mannle, Wiedemann and Ruchalla4]. Several studies have shown that TB patients requiring admission to the ICU carry a high mortality rate. The in-hospital mortality has been reported to be 25–63% [Reference Erbes5Reference Loh8], and the mean survival of patients who died was 53.6 days, and 50% of the patients died within the first 32 days [Reference Erbes5]. Delayed diagnosis and/or treatment may lead to severe clinical forms of the disease and are associated with higher mortality rates [Reference Tsai9, Reference Zahar10]. Many studies have evaluated risk factors for death in the treatment of TB, and many factors, such as age, sex, bacteriological status, comorbidities, immune and nutritional status of host and substance abuse, have been identified [Reference Kwon11]. However, the prognostic factor for in-hospital mortality in ICU TB patients remains unclear.

In the current study, we aimed to document the characteristics of TB patients requiring ICU care and to estimate the in-hospital mortality rate and the risk factors for mortality in a high-burden setting.

Methods

The retrospective study was approved by the Ethics Committee of Shandong Provincial Chest Hospital (SPCH). Written informed consent was waived because of the retrospective design of the study and the anonymous nature of the data collection.

All patients with culture-confirmed TB that were admitted to the ICU of the Shandong Provincial Chest Hospital, Jinan, China, between March 2012 and April 2019 were identified retrospectively. The hospital is a provincial public referral TB hospital, with most of patients admitted are from rural areas.

The following data were retrieved from the medical records: demographic characteristics (such as age, sex, molecular test use, TB contact history and smoking habits), comorbidities (such as forms of TB diseases, cancers and symptoms), laboratory measures (such as clinical chemistry, complete blood cell count and blood gas analysis), length of hospital/ICU stay and mortality. In addition, if multiple measurements for the same lab test were performed, the first one was collected and used for the statistical analysis.

For these analyses, death was defined as dying during treatment irrespective of cause. Time of delay was defined as the time from symptoms onset to hospital arrival. The overall survival time was defined as the interval from symptoms onset to discharge from hospital or death. Acute respiratory distress syndrome (ARDS) was diagnosed based on the criteria defined in the American-European consensus conference [Reference Bernard12]. The outcome was defined as death and hospitalisation time, which spent in the hospital from admission to discharge from hospital or death.

Data are expressed either as mean ± s.d. (continuous variables) or as a percentage for the group (categorical variables). Categorical variables were compared using the χ 2 test or Fisher's exact test, and continuous variables were compared using the Mann–Whitney U test or t test depending on the distribution of the data. Data were compared between survivors and patients who died during the hospital stay. The Cox proportional hazards regression model was used to identify prognostic factors that influence in-hospital mortality. Variables with a threshold value lower than 0.10 from univariate analysis were included in the multivariate model. Stepwise regression was used to inform the selection of a final model and P value less than 0.05 as a criterion to stay in the model.

Results

Patient characteristics

Demographic, clinical and laboratory characteristics of the enrolled patients are shown in Table 1. Between March 2012 and April 2019, a total of 82 ICU patients with confirmed TB were included in the analysis, the corresponding flowchart is shown in Figure 1. A total of 22 deaths were observed during the hospital stay, 21 patients died in the ICU. Of the 82 participants, 74% were male. Age of the study participants ranged from 1 to 90 years, and the mean age was 50.6 ± 24.3 years. Eleven cases (13%) had a TB contact history. Twenty-nine patients (35%) had a smoking habit. Sixty-five patients were screened for HIV infection and all were HIV-negative. Radiographic findings for the chest were abnormal in 100% of all cases (n = 70) examined with chest X-ray or computerised tomography.

Fig. 1. Flowchart for the selection of study patients.

Table 1. Baseline characteristics of the patients

s.d., standard deviation; HIV, human immunodeficiency virus; ICU, intensive care unit; TB, tuberculosis; ARDS, acute respiratory distress syndrome; CV, coefficient of variation.

The duration of these symptoms from onset to hospital arrival was 35 (median, interquartile range: 15, 180) days (defined as the time of delay in Table 1), the overall survival time was 503 ± 1245 days, the mean ICU stay time was 30 ± 54 days.

Of the participants, 74 patients (90%) had pulmonary TB, 30 (37%) tuberculous meningitis and 16 (20%) retreatment TB. Disseminated TB was diagnosed in 14 cases (17%). Among the 22 patients with the drug susceptibility test of M. TB isolates, two were confirmed as MDR-TB.

The most frequent comorbidities listed were as follows: ARDS 35%, cardiovascular diseases 28%, diabetes mellitus 11% and cancers 5%. The most common symptoms were fever (62%). In total, 32% of the patients presented with neurological symptoms (such as headache, mental confusion and coma).

The mean periods between the admission and laboratory examinations were as follows: complete blood cell count, 1.7 ± 5.6 days; arterial blood gases analysis, 4.6 ± 17.4 days and serum chemistry analysis, 1.7 ± 3.6 days. These detailed results were also presented in Table 1.

Univariate associations with mortality

Patient characteristics and their associations with in-hospital mortality were analysed with Cox proportional hazards regression analysis (Table 2). In the study, associations with mortality were observed for ARDS (hazard ratio: 3.7, 95% confidence interval (CI): 1.5–9.0, P = 0.004).

Table 2. Cox regression analysis of mortality for demographic, clinical and laboratory characteristics

95% CI, 95% confidence interval; ARDS, acute respiratory distress syndrome.

For laboratory measures, we also observed several variables associated with mortality, such as low levels of total protein and albumin, high levels of urea nitrogen, white blood cell (WBC) count and neutrophil count (all P < 0.01, Table 2).

Multivariate associations with mortality (sex-adjusted)

Table 2 also presents two parameters that are significantly associated with mortality in the multivariable model, namely, albumin and WBC count. In the multivariable model adjusted for sex and age, the levels of albumin and WBC count were significantly associated with mortality in TB patients requiring ICU care (all P < 0.01), the hazard ratios were 0.8 (95% CI: 0.7–0.9) per 1 g/l and 1.1 (95% CI: 1.0–1.2) per 1 × 109/l, respectively.

Discussion

Currently, in China, few studies were performed to evaluate the in-hospital mortality of TB cases requiring ICU care and their corresponding prognostic factors. In the study, it was found that the in-hospital mortality rate in TB patients requiring ICU care was 27%. Moreover, a number of risk factors associated with mortality were identified, such as albumin and WBC count.

In the study, the mortality rate appears to be consistent with what has been reported previously in another literature [Reference Erbes5]. However, it was below what was reported in a meta-analysis of the outcome of critically ill subjects with TB (ICU: 48% (95% CI: 41–55) [Reference Muthu13]. Although the mortality rate reported in the study appears low when compared to the meta study, the mortality rate of 27% is high when compared to other highly lethal acute diseases [Reference Tavares14].

The most common reasons for ICU admission of TB patients are the development of ARDS [Reference Valade6, Reference Duro7] and severe organ failure, such as renal failure [Reference Loh8, Reference Tsai9]. In a recent study, several primary causes for ICU admission were reported in patients with TB as follows: ARDS (63%), cardiopulmonary arrest (10%), septic shock (8%), sepsis (6%) and altered sensorium (6%). However, in the study, the most common reason was tuberculous meningitis (37%), which is the most severe form of TB diseases, followed by ARDS (35%), cardiovascular diseases (28%) and disseminated TB (17%). It is worth to be noted that, although all patients were HIV-negative in the cohort, disseminated TB was frequent. As is known, HIV-infected patients have been reported to be more likely to disseminated TB [Reference Hui15]. Therefore, the high frequency of disseminated TB in our study may indicate a high severity of these patients.

Univariate analysis identified ARDS, low levels of total protein and albumin, and high levels of urea nitrogen, WBC and neutrophil count as being significantly associated with mortality. Multivariate analysis showed that low albumin and high WBC count were the only two significant independent predictors of death. The variables for predicting outcomes, such as serum albumin and urea nitrogen, are objective, which is easily performed, inexpensive and available in most hospital laboratories. Therefore, these important variables should be considered by physicians for evaluating the severity of illness in ICU TB patients.

Previous studies have shown that lower serum albumin was associated with infection and increased mortality in the critically ill subjects [Reference Dominguez de Villota16Reference Hoeboer, Oudemans-van Straaten and Groeneveld18]. Hypoalbuminaemia was considered as an independent risk factor associated with mortality in community-acquired pneumonia (CAP) [Reference Lim19]. Similarly, Viasus et al. found that hypoalbuminaemia was significantly associated with the primary outcome in CAP [Reference Viasus20]. This is not surprising because albumin plays an important role in inflammation and suggests a state of malnutrition of patients [Reference Dominguez de Villota16]. Additionally, the initial value of serum albumin might also be a result of malnutrition and underlying disease that can worsen the nutritional status of the patient. Moreover, cytokines have a negative effect on albumin expression in the liver [Reference Rothschild, Oratz and Schreiber21]. Remarkably, in a recent meta-analysis, the administration of albumin-containing solutions for the resuscitation of patients with sepsis was associated with lower mortality compared with other fluid resuscitation regimens [Reference Delaney22]. This implied that the administration of albumin may improve the outcome of TB patients requiring ICU care.

Elevated WBC count is a well-known indicator for severe pneumonia and served as a diagnostic biomarker in pulmonary infections [Reference Kruger23Reference Assicot25]. In several studies, it was demonstrated that high WBC count was an independent predictor of in-hospital mortality of pneumonia [Reference Kruger23, Reference Kruger26, Reference Wang27]. Moreover, the WBC count has been reported to correlate with mortality in patients with any infection [Reference Archbald-Pannone28]. Hence, a high WBC count may relate to the severity of lung involvement in TB patients and gives an estimated risk of their mortality. In the study, we found that high WBC count was significantly associated with mortality in TB patients requiring ICU care. In a previous study by Kim et al., a similar result was reported that an increased value of WBCs was significantly associated with mortality in TB patients.

Our study also has some limitations. First, the sample size is relatively small, although the study included all consecutive patients who had ICU care in a 7-year period, this may limit the generalisability of the findings. Second, all information was retrieved retrospectively from medical records and probably was not uniformly complete and accurate. In fact, due to data availability, several important factors, such as C-reactive protein and procalcitonin which have been recognised as risk factors for the mortality in TB patients and may improve the management of TB patients requiring ICU stay [Reference Osawa29Reference Bedell32], were not included for analysis. Third, the study has a long duration. This may have significant effect on treatment regimens, criteria for ICU admission and others. Fourth, unfortunately, several factors were significant in the univariate analysis, which were also reported in other studies, such as sex, ARDS, cancer and haemoglobin [Reference Kwon11, Reference Tavares14]. However, when added to multivariate models, none of these variables reached significance. This may be due to the small sample size, confounding effect or weak associations. We believe that a larger prospective study, which has sufficient statistical power would be helpful to understand the baseline characteristics associated with mortality.

Conclusions

In conclusion, our study found a relatively high in-hospital mortality rate in TB patients requiring ICU care. Low albumin level and high WBC count could serve as prognostic factors for death in these TB patients in China. These findings are important for the appropriate management of these patients and may improve the outcome. Nevertheless, additional studies are necessary to confirm these data, taking into account other possible risk factors in the univariate analysis.

Conflict of interest

None.

Data availability statement

The data that support the findings of this study are available from the corresponding author (WMS) upon a reasonable request.

Footnotes

*

The first two authors have equal contribution to this study.

References

Floyd, K et al. (2018) The global tuberculosis epidemic and progress in care, prevention, and research: an overview in year 3 of the End TB era. Lancet Respiratory Medicine 6, 299314.CrossRefGoogle ScholarPubMed
Frame, RN et al. (1987) Active tuberculosis in the medical intensive care unit: a 15-year retrospective analysis. Critical Care Medicine 15, 10121014.CrossRefGoogle ScholarPubMed
Keim, LW, Schuldt, S and Bedell, GN (1977) Tuberculosis in the intensive care unit. Heart & Lung 6, 624634.Google ScholarPubMed
Mannle, C, Wiedemann, K and Ruchalla, E (1989) The incidence of tuberculosis at an intensive care unit. Anasthesie, Intensivtherapie, Notfallmedizin 24, 334340.Google ScholarPubMed
Erbes, R et al. (2006) Characteristics and outcome of patients with active pulmonary tuberculosis requiring intensive care. European Respiratory Journal 27, 12231228.CrossRefGoogle ScholarPubMed
Valade, S et al. (2012) Tuberculosis in the intensive care unit: a retrospective descriptive cohort study with determination of a predictive fatality score. Canadian Journal of Infectious Diseases & Medical Microbiology 23, 173178.CrossRefGoogle ScholarPubMed
Duro, RP et al. (2017) Severe Tuberculosis requiring intensive care: a descriptive analysis. Critical Care Research and Practice 2017, 9535463.CrossRefGoogle ScholarPubMed
Loh, WJ et al. (2017) Factors associated with mortality among patients with active pulmonary tuberculosis requiring intensive care. Singapore Medical Journal 58, 656659.CrossRefGoogle ScholarPubMed
Tsai, TC et al. (2008) Delayed diagnosis of active pulmonary tuberculosis in emergency department. American Journal of Emergency Medicine 26, 888892.CrossRefGoogle ScholarPubMed
Zahar, JR et al. (2001) Delayed treatment contributes to mortality in ICU patients with severe active pulmonary tuberculosis and acute respiratory failure. Intensive Care Medicine 27, 513520.CrossRefGoogle ScholarPubMed
Kwon, YS et al. (2014) Risk factors for death during pulmonary tuberculosis treatment in Korea: a multicenter retrospective cohort study. Journal of Korean Medical Science 29, 12261231.CrossRefGoogle ScholarPubMed
Bernard, GR et al. (1994) The American-European consensus conference on ARDS. Definitions, mechanisms, relevant outcomes, and clinical trial coordination. American Journal of Respiratory and Critical Care Medicine 149, 818824.CrossRefGoogle ScholarPubMed
Muthu, V et al. (2018) Outcome of critically ill subjects with Tuberculosis: systematic review and meta-analysis. Respiratory Care 63, 15411554.CrossRefGoogle ScholarPubMed
Tavares, C et al. (2013) Tuberculosis deaths in a tertiary hospital in Goiania, Brazil: a descriptive study. Le Infezioni in Medicina 21, 279286.Google Scholar
Hui, C et al. (2003) Features of severe pneumonia in patients with undiagnosed pulmonary tuberculosis in an intensive care unit. Journal of the Formosan Medical Association 102, 563569.Google Scholar
Dominguez de Villota, E et al. (1980) Association of a low serum albumin with infection and increased mortality in critically ill patients. Intensive Care Medicine 7, 1922.CrossRefGoogle ScholarPubMed
Sung, J et al. (2004) Admission serum albumin is predictive of outcome in critically ill trauma patients. American Surgeon 70, 10991102.Google ScholarPubMed
Hoeboer, SH, Oudemans-van Straaten, HM and Groeneveld, AB (2015) Albumin rather than C-reactive protein may be valuable in predicting and monitoring the severity and course of acute respiratory distress syndrome in critically ill patients with or at risk for the syndrome after new onset fever. BMC Pulmonary Medicine 15, 22.CrossRefGoogle ScholarPubMed
Lim, WS et al. (2003) Defining community acquired pneumonia severity on presentation to hospital: an international derivation and validation study. Thorax 58, 377382.CrossRefGoogle ScholarPubMed
Viasus, D et al. (2013) Prognostic value of serum albumin levels in hospitalized adults with community-acquired pneumonia. Journal of Infection 66, 415423.CrossRefGoogle ScholarPubMed
Rothschild, MA, Oratz, M and Schreiber, SS (1988) Serum albumin. Hepatology 8, 385401.CrossRefGoogle ScholarPubMed
Delaney, AP et al. (2011) The role of albumin as a resuscitation fluid for patients with sepsis: a systematic review and meta-analysis. Critical Care Medicine 39, 386391.CrossRefGoogle ScholarPubMed
Kruger, S et al. (2008) Procalcitonin predicts patients at low risk of death from community-acquired pneumonia across all CRB-65 classes. European Respiratory Journal 31, 349355.CrossRefGoogle ScholarPubMed
Thiem, U et al. (2009) C-reactive protein, severity of pneumonia and mortality in elderly, hospitalised patients with community-acquired pneumonia. Age and Ageing 38, 693697.CrossRefGoogle ScholarPubMed
Assicot, M et al. (1993) High serum procalcitonin concentrations in patients with sepsis and infection. Lancet (London, England) 341, 515518.CrossRefGoogle ScholarPubMed
Kruger, S et al. (2010) Assessment of inflammatory markers in patients with community-acquired pneumonia – influence of antimicrobial pre-treatment: results from the German competence network CAPNETZ. Clinica Chimica Acta 411, 19291934.CrossRefGoogle ScholarPubMed
Wang, X et al. (2017) A new method to predict hospital mortality in severe community acquired pneumonia. European Journal of Internal Medicine 40, 5663.CrossRefGoogle ScholarPubMed
Archbald-Pannone, LR et al. (2015) Delirium and other clinical factors with Clostridium difficile infection that predict mortality in hospitalized patients. American Journal of Infection Control 43, 690693.CrossRefGoogle ScholarPubMed
Osawa, T et al. (2020) Serum procalcitonin levels predict mortality risk in patients with pulmonary tuberculosis: a single-center prospective observational study. Journal of Infectious Diseases 222, 16511654.CrossRefGoogle ScholarPubMed
Tokman, S et al. (2014) Procalcitonin predicts mortality in HIV-infected Ugandan adults with lower respiratory tract infections. Respirology (Carlton, Vic.) 19, 382388.CrossRefGoogle ScholarPubMed
Wilson, D et al. (2018) Evaluation of tuberculosis treatment response with serial C-reactive protein measurements. Open Forum Infectious Diseases 5, ofy253.CrossRefGoogle ScholarPubMed
Bedell, RA et al. (2018) Predictive value of C-reactive protein for tuberculosis, bloodstream infection or death among HIV-infected individuals with chronic, non-specific symptoms and negative sputum smear microscopy. Tropical Medicine & International Health 23, 254262.CrossRefGoogle ScholarPubMed
Figure 0

Fig. 1. Flowchart for the selection of study patients.

Figure 1

Table 1. Baseline characteristics of the patients

Figure 2

Table 2. Cox regression analysis of mortality for demographic, clinical and laboratory characteristics