Predictors of In-Hospital Mortality among Patients with Pulmonary Tuberculosis: A Systematic Review and Meta-analysis.
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ABSTRACT:
SUBMITTER: de Almeida CPB
PROVIDER: S-EPMC5940698 | biostudies-literature | 2018 May
REPOSITORIES: biostudies-literature
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Predictors of In-Hospital Mortality among Patients with Pulmonary Tuberculosis: A Systematic Review and Meta-analysis.
de Almeida Carlos Podalirio Borges CPB Ziegelmann Patrícia Klarmann PK Couban Rachel R Wang Li L Busse Jason Walter JW Silva Denise Rossato DR
Scientific reports 20180508 1
<h4>Background</h4>There is uncertainty regarding which factors are associated with in-hospital mortality among patients with pulmonary TB (PTB). The aim of this systematic review and meta-analysis is to identify predictors of in-hospital mortality among patients with PTB.<h4>Methods</h4>We searched MEDLINE, EMBASE, and Global Health, for cohort and case-control studies that reported risk factors for in-hospital mortality in PTB. We pooled all factors that were assessed for an association, and p ...[more]
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Project description:BackgroundEven though the lives of millions have been saved in the past decades, the mortality rate in patients with drug-resistant tuberculosis is still high. Different factors are associated with this mortality. However, there is no comprehensive global report addressing these risk factors. This study aimed to determine the predictors of mortality using data generated at the global level.MethodsWe systematically searched five electronic major databases (PubMed/Medline, CINAHL, EMBASE, Scopus, Web of Science), and other sources (Google Scholar, Google). We used the Joanna Briggs Institute Critical Appraisal tools to assess the quality of included articles. Heterogeneity assessment was conducted using the forest plot and I2 heterogeneity test. Data were analyzed using STATA Version 15. The pooled hazard ratio, risk ratio, and odd's ratio were estimated along with their 95% CIs.ResultAfter reviewing 640 articles, 49 studies met the inclusion criteria and were included in the final analysis. The predictors of mortality were; being male (HR = 1.25,95%CI;1.08,1.41,I2;30.5%), older age (HR = 2.13, 95%CI;1.64,2.62,I2;59.0%,RR = 1.40,95%CI; 1.26, 1.53, I2; 48.4%) including a 1 year increase in age (HR = 1.01, 95%CI;1.00,1.03,I2;73.0%), undernutrition (HR = 1.62,95%CI;1.28,1.97,I2;87.2%, RR = 3.13, 95% CI; 2.17,4.09, I2;0.0%), presence of any type of co-morbidity (HR = 1.92,95%CI;1.50-2.33,I2;61.4%, RR = 1.61, 95%CI;1.29, 1.93,I2;0.0%), having diabetes (HR = 1.74, 95%CI; 1.24,2.24, I2;37.3%, RR = 1.60, 95%CI;1.13,2.07, I2;0.0%), HIV co-infection (HR = 2.15, 95%CI;1.69,2.61, I2; 48.2%, RR = 1.49, 95%CI;1.27,1.72, I2;19.5%), TB history (HR = 1.30,95%CI;1.06,1.54, I2;64.6%), previous second-line anti-TB treatment (HR = 2.52, 95% CI;2.15,2.88, I2;0.0%), being smear positive at the baseline (HR = 1.45, 95%CI;1.14,1.76, I2;49.2%, RR = 1.58,95%CI;1.46,1.69, I2;48.7%), having XDR-TB (HR = 2.01, 95%CI;1.50,2.52, I2;60.8%, RR = 2.44, 95%CI;2.16,2.73,I2;46.1%), and any type of clinical complication (HR = 2.98, 95%CI; 2.32, 3.64, I2; 69.9%). There are differences and overlaps of predictors of mortality across different drug-resistance categories. The common predictors of mortality among different drug-resistance categories include; older age, presence of any type of co-morbidity, and undernutrition.ConclusionDifferent patient-related demographic (male sex, older age), and clinical factors (undernutrition, HIV co-infection, co-morbidity, diabetes, clinical complications, TB history, previous second-line anti-TB treatment, smear-positive TB, and XDR-TB) were the predictors of mortality in patients with drug-resistant tuberculosis. The findings would be an important input to the global community to take important measures.
| S-EPMC8238236 | biostudies-literature
Project description:BackgroundBetter insight in patients' prognosis can help physicians to timely initiate advance care planning (ACP) discussions with patients with chronic obstructive pulmonary disease (COPD). We aimed to identify predictors of mortality.MethodsWe systematically searched databases Embase, PubMed, MEDLINE, Web of Science, and Cochrane Central in April 2020. Papers reporting on predictors or prognostic models for mortality at 3 months and up to 24 months were assessed on risk-of-bias. We performed a meta-analysis with a fixed or random-effects model, and evaluated the discriminative ability of multivariable prognostic models.ResultsWe included 42 studies (49-418,251 patients); 18 studies were included in the meta-analysis. Significant predictors of mortality within 3-24 months in the random-effects model were: previous hospitalization for acute exacerbation (hazard ratio [HR] 1.97; 95% confidence interval [CI] 1.32-2.95), hospital readmission within 30 days (HR 5.01; 95% CI 2.16-11.63), cardiovascular comorbidity (HR 1.89; 95% CI 1.25-2.87), age (HR 1.48; 95% CI 1.38-1.59), male sex (HR 1.68; 95% CI 1.38-1.59), and long-term oxygen therapy (HR 1.74; 95% CI 1.10-2.73). Nineteen previously developed multicomponent prognostic models, as examined in 11 studies, mostly had moderate discriminate ability.ConclusionIdentified predictors of mortality may aid physicians in selecting COPD patients who may benefit from ACP. However, better discriminative ability of prognostic models or development of a new prognostic model is needed for further large-scale implementation.RegistrationPROSPERO (CRD42016038494), https://www.crd.york.ac.uk/prospero/ .
| S-EPMC8978392 | biostudies-literature
Project description:BackgroundSevere pneumonia has consistently been associated with high mortality. We sought to identify risk factors for the mortality of severe pneumonia to assist in reducing mortality for medical treatment.MethodsElectronic databases including PubMed, Web of Science, EMBASE, Cochrane Library, and Scopus were systematically searched till June 1, 2023. All human research were incorporated into the analysis, regardless of language, publication date, or geographical location. To pool the estimate, a mixed-effect model was used. The Newcastle-Ottawa Scale (NOS) was employed for assessing the quality of included studies that were included in the analysis.ResultsIn total, 22 studies with a total of 3655 severe pneumonia patients and 1107 cases (30.29%) of death were included in the current meta-analysis. Significant associations were found between age [5.76 years, 95% confidence interval [CI] (3.43, 8.09), P < 0.00001], male gender [odds ratio (OR) = 1.47, 95% CI (1.07, 2.02), P = 0.02], and risk of death from severe pneumonia. The comorbidity of neoplasm [OR = 3.37, 95% CI (1.07, 10.57), P = 0.04], besides the presence of complications such as diastolic hypotension [OR = 2.60, 95% CI (1.45, 4.67), P = 0.001], ALI/ARDS [OR = 3.63, 95% CI (1.78, 7.39), P = 0.0004], septic shock [OR = 9.43, 95% CI (4.39, 20.28), P < 0.00001], MOF [OR = 4.34, 95% CI (2.36, 7.95), P < 0.00001], acute kidney injury [OR = 2.45, 95% CI (1.14, 5.26), P = 0.02], and metabolic acidosis [OR = 5.88, 95% CI (1.51, 22.88), P = 0.01] were associated with significantly higher risk of death among patients with severe pneumonia. Those who died, compared with those who survived, differed on multiple biomarkers on admission including serum creatinine [Scr: + 67.77 mmol/L, 95% CI (47.21, 88.34), P < 0.00001], blood urea nitrogen [BUN: + 6.26 mmol/L, 95% CI (1.49, 11.03), P = 0.01], C-reactive protein [CRP: + 33.09 mg/L, 95% CI (3.01, 63.18), P = 0.03], leukopenia [OR = 2.63, 95% CI (1.34, 5.18), P = 0.005], sodium < 136 mEq/L [OR = 2.63, 95% CI (1.34, 5.18), P = 0.005], albumin [- 5.17 g/L, 95% CI (- 7.09, - 3.25), P < 0.00001], PaO2/FiO2 [- 55.05 mmHg, 95% CI (- 60.11, - 50.00), P < 0.00001], arterial blood PH [- 0.09, 95% CI (- 0.15, - 0.04), P = 0.0005], gram-negative microorganism [OR = 2.56, 95% CI (1.17, 5.62), P = 0.02], and multilobar or bilateral involvement [OR = 3.65, 95% CI (2.70, 4.93), P < 0.00001].ConclusionsOlder age and male gender might face a greater risk of death in severe pneumonia individuals. The mortality of severe pneumonia may also be significantly impacted by complications such diastolic hypotension, ALI/ARDS, septic shock, MOF, acute kidney injury, and metabolic acidosis, as well as the comorbidity of neoplasm, and laboratory indicators involving Scr, BUN, CRP, leukopenia, sodium, albumin, PaO2/FiO2, arterial blood PH, gram-negative microorganism, and multilobar or bilateral involvement.Systematic review registrationPROSPERO Protocol Number: CRD 42023430684.
| S-EPMC11302088 | biostudies-literature
Project description:IntroductionStroke is the second leading cause of mortality worldwide, accounting for approximately 5.5 million deaths each year. Due to demographic and health changes, the epidemiology of stroke is shifting from industrialized to low- and middle-income nations. Ethiopia is a developing country with a population that reflects this shift. Therefore, this systematic review and meta-analysis are aimed at evaluating the extent of in-hospital mortality of both ischemic and hemorrhagic stroke in Ethiopia and determining relevant factors associated with the mortality.MethodsObservational studies published as of July 15, 2020, that reported the magnitude, predictors, and causes of in-hospital mortality of stroke were systematically and comprehensively retrieved using the PRISMA 2020 criteria from databases such as PubMed/MEDLINE, Science Direct, and Google Scholar. The review papers were chosen based on the study methodology (facility-based observational), the study area (Ethiopia), the study population (adult patients with stroke), the outcome (in-hospital mortality), and the fact that they were published in English.ResultA total of 3709 patients with stroke were included in this systematic review and meta-analysis, which included 19 publications. In-hospital mortality was 14.03 percent on average in the studies, with reports ranging from 6.04 percent to 37.37 percent. Patients with hemorrhagic type stroke, admission Glasgow Coma Scale less than or equal to 12, impaired mental status, National Institutes of Health Stroke Scale stroke level greater than 13, prolonged hospital stay, any incontinence, pneumonia, and/or swallowing trouble had an increased risk of death after stroke.ConclusionThe magnitude of in-hospital mortality of patients with stroke in Ethiopia is high. The assessment of the level of consciousness is vital for clinical management and as an indicator of prognosis. Patients with unfavorable prognostic signs, such as entry Glasgow Coma Scale, National Institutes of Health Stroke Scale stroke level > 13, hemorrhagic stroke, pneumonia, incontinence, and dysphagia, should be given priority.
| S-EPMC9155958 | biostudies-literature
Project description:To timely initiate advance care planning in patients with advanced cancer, physicians should identify patients with limited life expectancy. We aimed to identify predictors of mortality. To identify the relevant literature, we searched Embase, MEDLINE, Cochrane Central, Web of Science, and PubMed databases between January 2000-April 2020. Identified studies were assessed on risk-of-bias with a modified QUIPS tool. The main outcomes were predictors and prediction models of mortality within a period of 3-24 months. We included predictors that were studied in ≥2 cancer types in a meta-analysis using a fixed or random-effects model and summarized the discriminative ability of models. We included 68 studies (ranging from 42 to 66,112 patients), of which 24 were low risk-of-bias, and 39 were included in the meta-analysis. Using a fixed-effects model, the predictors of mortality were: the surprise question, performance status, cognitive impairment, (sub)cutaneous metastases, body mass index, comorbidity, serum albumin, and hemoglobin. Using a random-effects model, predictors were: disease stage IV (hazard ratio [HR] 7.58; 95% confidence interval [CI] 4.00-14.36), lung cancer (HR 2.51; 95% CI 1.24-5.06), ECOG performance status 1+ (HR 2.03; 95% CI 1.44-2.86) and 2+ (HR 4.06; 95% CI 2.36-6.98), age (HR 1.20; 95% CI 1.05-1.38), male sex (HR 1.24; 95% CI 1.14-1.36), and Charlson comorbidity score 3+ (HR 1.60; 95% CI 1.11-2.32). Thirteen studies reported on prediction models consisting of different sets of predictors with mostly moderate discriminative ability. To conclude, we identified reasonably accurate non-tumor specific predictors of mortality. Those predictors could guide in developing a more accurate prediction model and in selecting patients for advance care planning.
| S-EPMC8774229 | biostudies-literature
Project description:Mortality rates of coronavirus disease-2019 (COVID-19) continue to rise across the world. Information regarding the predictors of mortality in patients with COVID-19 remains scarce. Herein, we performed a systematic review of published articles, from 1 January to 24 April 2020, to evaluate the risk factors associated with mortality in COVID-19. Two investigators independently searched the articles and collected the data, in accordance with PRISMA guidelines. We looked for associations between mortality and patient characteristics, comorbidities, and laboratory abnormalities. A total of 14 studies documenting the outcomes of 4659 patients were included. The presence of comorbidities such as hypertension (odds ratio [OR], 2.5; 95% confidence interval [CI], 2.1-3.1; P < .00001), coronary heart disease (OR, 3.8; 95% CI, 2.1-6.9; P < .00001), and diabetes (OR, 2.0; 95% CI, 1.7-2.3; P < .00001) were associated with significantly higher risk of death amongst patients with COVID-19. Those who died, compared with those who survived, differed on multiple biomarkers on admission including elevated levels of cardiac troponin (+44.2 ng/L, 95% CI, 19.0-69.4; P = .0006); C-reactive protein (+66.3 µg/mL, 95% CI, 46.7-85.9; P < .00001); interleukin-6 (+4.6 ng/mL, 95% CI, 3.6-5.6; P < .00001); D-dimer (+4.6 µg/mL, 95% CI, 2.8-6.4; P < .00001); creatinine (+15.3 µmol/L, 95% CI, 6.2-24.3; P = .001); and alanine transaminase (+5.7 U/L, 95% CI, 2.6-8.8; P = .0003); as well as decreased levels of albumin (-3.7 g/L, 95% CI, -5.3 to -2.1; P < .00001). Individuals with underlying cardiometabolic disease and that present with evidence for acute inflammation and end-organ damage are at higher risk of mortality due to COVID-19 infection and should be managed with greater intensity.
| S-EPMC7280666 | biostudies-literature
Project description:BackgroundCoronavirus disease 2019 (COVID-19) is associated with a high mortality rate, especially in patients with severe illness. We conducted a systematic review and meta-analysis to assess the potential predictors of mortality in patients with COVID-19.MethodsPubMed, EMBASE, the Cochrane Library, and three electronic Chinese databases were searched from December 1, 2019 to April 29, 2020. Eligible studies reporting potential predictors of mortality in patients with COVID-19 were identified. Unadjusted prognostic effect estimates were pooled using the random-effects model if data from at least two studies were available. Adjusted prognostic effect estimates were presented by qualitative analysis.ResultsThirty-six observational studies were identified, of which 27 were included in the meta-analysis. A total of 106 potential risk factors were tested, and the following important predictors were associated with mortality: advanced age, male sex, current smoking status, preexisting comorbidities (especially chronic kidney, respiratory, and cardio-cerebrovascular diseases), symptoms of dyspnea, complications during hospitalization, corticosteroid therapy and a severe condition. Additionally, a series of abnormal laboratory biomarkers of hematologic parameters, hepatorenal function, inflammation, coagulation, and cardiovascular injury were also associated with fatal outcome.ConclusionWe identified predictors of mortality in patients with COVID-19. These findings could help healthcare providers take appropriate measures and improve clinical outcomes in such patients.
| S-EPMC8264491 | biostudies-literature
Project description:Background Recent studies have demonstrated a continuum in clinical risk related to mean pulmonary artery pressure that begins at >19 mm Hg, which is below the traditional threshold used to define pulmonary hypertension ( PH ) of 25 mm Hg. Because of the implications on patient diagnosis and prognosis, the generalizability and validity of these data need further confirmation. Methods and Results Databases were searched from inception through January 31, 2018, to identify studies comparing all-cause mortality between patients with mildly elevated mean pulmonary artery pressure near but <25 mm Hg versus the referent group. The meta-analysis included 15 nonrandomized studies and 16 482 patients (7451 [45.2%] with measured or calculated mean pulmonary artery pressure of 19-24 mm Hg by right heart catheterization [n=6037] and echocardiography [n=1414] [mild PH ]). The mean duration of follow-up was 5.2 years. Compared with the referent group, mild PH was associated with an increased risk of mortality (risk ratio, 1.52; 95% confidence interval, 1.32-1.74; P<0.001; I2=47%). Secondary analysis using risk-adjusted time-to-event estimates showed a similar result (hazard ratio, 1.19; 95% confidence interval, 1.09-1.31; P<0.001; I2=42%). The findings were consistent between subgroups of right heart catheterization and echocardiography studies ( Pinteraction>0.05). There was evidence of publication bias; however, this did not influence the risk estimate (Duval and Tweedie's trim and fill adjusted risk ratio, 1.34; 95% confidence interval, 1.15-1.56). Conclusions The risk of mortality is increased in patients with mild PH , defined as measured or calculated mean pulmonary artery pressure >19 mm Hg. These data emphasize a need for diagnosing patients with mild PH with consideration to enrollment in PH clinical studies investigating pharmacological and nonpharmacological interventions to attenuate clinical risk and improve outcomes.
| S-EPMC6222957 | biostudies-other
Project description:IntroductionMany studies have explored the relationship between diabetes mellitus (DM) and tuberculosis (TB) demonstrating increased risk of TB among patients with DM and poor prognosis of patients suffering from the association of DM/TB. Owing to a paucity of studies addressing this question, it remains unclear whether patients with DM and TB are more likely than TB patients without DM to be grouped into molecular clusters defined according to the genotype of the infecting Mycobacterium tuberculosis bacillus. That is, whether there is convincing molecular epidemiological evidence for TB transmission among DM patients. Objective: We performed a systematic review and meta-analysis to quantitatively evaluate the propensity for patients with DM and pulmonary TB (PTB) to cluster according to the genotype of the infecting M. tuberculosis bacillus.Materials and methodsWe conducted a systematic search in MEDLINE and LILACS from 1990 to June, 2016 with the following combinations of key words "tuberculosis AND transmission" OR "tuberculosis diabetes mellitus" OR "Mycobacterium tuberculosis molecular epidemiology" OR "RFLP-IS6110" OR "Spoligotyping" OR "MIRU-VNTR". Studies were included if they met the following criteria: (i) studies based on populations from defined geographical areas; (ii) use of genotyping by IS6110- restriction fragment length polymorphism (RFLP) analysis and spoligotyping or mycobacterial interspersed repetitive unit-variable number of tandem repeats (MIRU-VNTR) or other amplification methods to identify molecular clustering; (iii) genotyping and analysis of 50 or more cases of PTB; (iv) study duration of 11 months or more; (v) identification of quantitative risk factors for molecular clustering including DM; (vi) > 60% coverage of the study population; and (vii) patients with PTB confirmed bacteriologically. The exclusion criteria were: (i) Extrapulmonary TB; (ii) TB caused by nontuberculous mycobacteria; (iii) patients with PTB and HIV; (iv) pediatric PTB patients; (v) TB in closed environments (e.g. prisons, elderly homes, etc.); (vi) diabetes insipidus and (vii) outbreak reports. Hartung-Knapp-Sidik-Jonkman method was used to estimate the odds ratio (OR) of the association between DM with molecular clustering of cases with TB. In order to evaluate the degree of heterogeneity a statistical Q test was done. The publication bias was examined with Begg and Egger tests. Review Manager 5.3.5 CMA v.3 and Biostat and Software package R were used.ResultsSelection criteria were met by six articles which included 4076 patients with PTB of which 13% had DM. Twenty seven percent of the cases were clustered. The majority of cases (48%) were reported in a study in China with 31% clustering. The highest incidence of TB occurred in two studies from China. The global OR for molecular clustering was 0.84 (IC 95% 0.40-1.72). The heterogeneity between studies was moderate (I2 = 55%, p = 0.05), although there was no publication bias (Beggs test p = 0.353 and Eggers p = 0.429).ConclusionThere were very few studies meeting our selection criteria. The wide confidence interval indicates that there is not enough evidence to draw conclusions about the association. Clustering of patients with DM in TB transmission chains should be investigated in areas where both diseases are prevalent and focus on specific contexts.
| S-EPMC5597214 | biostudies-literature
Project description:This review aimed to summarize and estimate the TB treatment success rate and factors associated with unsuccessful TB treatment outcomes in Africa. Potentially eligible primary studies were retrieved from PubMed and Google Scholar. The risk of bias and quality of studies was assessed using The Joanna Briggs Institute's (JBI) appraisal criteria, while heterogeneity across studies was assessed using Cochran's Q test and I2 statistic. Publication bias was checked using the funnel plot and egger's test. The protocol was registered in PROSPERO, numbered CRD42019136986. A total of 26 eligible studies were considered. The overall pooled estimate of TB treatment success rate was found to be 79.0% (95% CI: 76-82%), ranging from 53% (95% CI: 47-58%) in Nigeria to 92% (95% CI: 90-93%) in Ethiopia. The majority of unsuccessful outcomes were attributed to 48% (95% CI: 40-57%) death and 47% (95% CI: 39-55%) of defaulter rate. HIV co-infection and retreatment were significantly associated with an increased risk of unsuccessful treatment outcomes compared to HIV negative and newly diagnosed TB patients with RR of 1.53 (95% CI: 1.36-1.71) and 1.48 (95% CI: 1.14-1.94), respectively. TB treatment success rate was 79% below the WHO defined threshold of 85% with significant variation across countries. Countries need to explore contextual underlining factors and more effort is required in providing TB preventive treatment, improve case screening and linkage for TB treatment among HIV high-risk groups and use confirmatory TB diagnostic modality. Countries in Africa need to strengthen counseling and follow-up, socio-economic support for patients at high risk of loss to follow-up and poor treatment success is also crucial for successful TB control programs.
| S-EPMC8536006 | biostudies-literature