Evaluation of clinical prediction rules for respiratory isolation of inpatients with suspected pulmonary tuberculosis

Hospital Practices for Respiratory Isolation for Patients With Suspected Tuberculosis and Potential Application of Prediction Models

Hospitalized persons with suspected pulmonary tuberculosis (PTB) are placed in airborne isolation to prevent nosocomial infection, as recommended by the Centers for Disease Control and Prevention (CDC). There is significant evidence that clinicians overuse this resource due to an abundance of caution when confronted with a patient with possible PTB. Many researchers have developed predictive tools based on clinical and radiographic data to assist clinicians in deciding which patients to place in respiratory isolation. We assessed the isolation practices for an urban hospital serving a large immigrant population and then retrospectively applied seven previously derived prediction models of isolation of PTB to our population. Our current clinical practice results in 76% of patients with PTB being placed in isolation on admission. However, 208 patients without PTB were placed in isolation unnecessarily for a total of 584 days. Four models had sensitivities greater than 90%, and two models had sensitivities of 100%. The use of these models would have potentially saved more than 150 days of patient isolation per year.

Impact of introducing fluorescent microscopy on hospital tuberculosis control: A before-after study at a high caseload medical center in Taiwan

Background

Undiagnosed tuberculosis (TB) patients hospitalized because of comorbidities constitute a challenge to TB control in hospitals. We aimed to assess the impact of introducing highly sensitive fluorescent microscopy for examining sputum smear to replace conventional microscopy under a high TB risk setting.

Methods

We measured the impact of switch to fluorescent microscopy on the smear detection rate of culture-confirmed pulmonary TB, timing of respiratory isolation, and total non-isolated infectious person-days in hospital at a high-caseload medical center (approximately 400 TB cases annually) in Taipei. Multivariable Cox regression was applied to adjust for effects of covariates. The effect attributable to the improved smear detection rate was determined using causal mediation analysis.

Results

After switch to fluorescence microscopy, median non-isolated infectious duration decreased from 12.5 days to 3 days (P<0.001). Compared with conventional microscopy, fluorescence microscopy increased sputum smear detection rate by two-fold (for all patients: from 22.8% to 48.1%, P<0.001; for patients with cavitary lung lesion: from 43% to 82%, P = 0.029) and was associated with a 2-fold higher likelihood of prompt respiratory isolation (odds ratio mediated by the increase in sputum smear detection rate: 1.8, 95% CI 1.3–2.5). Total non-isolated infectious patient-days in hospital decreased by 69% (from 4,778 patient-days per year to 1,502 patient-days per year).

Conclusions

In a high TB caseload setting, highly sensitive rapid diagnostic tools could substantially improve timing of respiratory isolation and reduce the risk of nosocomial TB transmission.

Effectiveness of interventions for reducing TB incidence in countries with low TB incidence: a systematic review of reviews

AIMS

What is the evidence base for the effectiveness of interventions to reduce tuberculosis (TB) incidence in countries which have low TB incidence?

METHODS

We conducted a systematic review of interventions for TB control and prevention relevant to low TB incidence settings (<10 cases per 100 000 population). Our analysis was stratified according to "direct" or "indirect" effects on TB incidence. Review quality was assessed using AMSTAR2 criteria. We summarised the strength of review level evidence for interventions as "sufficient", "tentative", "insufficient" or "no" using a framework based on the consistency of evidence within and between reviews.

RESULTS

We found sufficient review level evidence for direct effects on TB incidence/case prevention of vaccination and treatment of latent TB infection. We also found sufficient evidence of beneficial indirect effects attributable to drug susceptibility testing and adverse indirect effects (measured as sub-optimal treatment outcomes) in relation to use of standardised first-line drug regimens for isoniazid-resistant TB and intermittent dosing regimens. We found insufficient review level evidence for direct or indirect effects of interventions in other areas, including screening, adherence, multidrug-resistant TB, and healthcare-associated infection.

DISCUSSION

Our review has shown a need for stronger evidence to support expert opinion and country experience when formulating TB control policy.

Development of two artificial neural network models to support the diagnosis of pulmonary tuberculosis in hospitalized patients in Rio de Janeiro, Brazil

Pulmonary tuberculosis (PTB) remains a worldwide public health problem. Diagnostic algorithms to identify the best combination of diagnostic tests for PTB in each setting are needed for resource optimization. We developed one artificial neural network model for classification (multilayer perceptron-MLP) and another risk group assignment (self-organizing map-SOM) for PTB in hospitalized patients in a high complexity hospital in Rio de Janeiro City, using clinical and radiologic data collected from 315 presumed PTB cases admitted to isolation rooms from March 2003 to December 2004 (TB prevalence = 21.5 %). The MLP model included 7 variables-radiologic classification, age, gender, cough, night sweats, weight loss and anorexia. The sensitivity of the MLP model was 96.0 % (95 % CI ±2.0), the specificity was 89.0 % (95 % CI ±2.0), the positive predictive value was 72.5 % (95 % CI ±3.5) and the negative predictive value was 98.5 % (95 % CI ±0.5). The variable with the highest discriminative power was the radiologic classification. The high negative predictive value found in the MLP model suggests that the use of this model at the moment of hospital admission is safe. SOM model was able to correctly assign high-, medium- and low-risk groups to patients. If prospective validation in other series is confirmed, these models can become a tool for decision-making in tertiary health facilities in countries with limited resources.

Systematic review with meta-analyses and critical appraisal of clinical prediction rules for pulmonary tuberculosis in hospitals

OBJECTIVE

To systematically review studies evaluating clinical prediction rules (CPRs) for adult inpatients suspected to have pulmonary tuberculosis.

DESIGN

Systematic review with meta-analyses.

SETTING

Hospitals. Patients Inpatients at least 15 years of age admitted to acute care.

METHODS

A search was conducted in 5 indexed electronic databases with no language or year of publication restrictions. We performed a meta-analysis for those CPRs with at least 2 validation studies. Results were reported according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

RESULTS

Of the 461 abstracts selected, 36 articles were fully analyzed and 11 articles were included, yielding 8 CPRs derived in 4 countries. Broad validation studies were identified for 2 CPRs. The most frequent clinical predictors were fever and weight loss. All CPRs included chest imaging signs. Most CPRs were derived in countries with a low prevalence of pulmonary tuberculosis and included homeless, immigrants, and those who reacted to the purified protein derivative test. Both of the CPRs derived in countries with a high prevalence of pulmonary tuberculosis strongly relied on chest radiograph predictors. Accuracy of the different CPRs was high (area under receiver operating characteristic curve, 0.79-0.91). Meta-analysis of 4 validation studies for Wisnivesky's CPR indicates optimistic pooled results: sensitivity, 94.1% (95% CI, 89.7%-96.7%); negative likelihood ratio, 0.22 (95% CI, 0.12-0.40).

CONCLUSION

On the basis of a critical appraisal of the 2 best validated CPRs, the presence of weight loss and/or fever in inpatients warrants obtaining a chest radiograph, regardless of the presence of productive cough. If the chest radiograph is abnormal, the patient should be placed in isolation until more specific test results are available. Validation in different settings is required to maximize external generalization of existing CPRs.

The Bandim TBscore--reliability, further development, and evaluation of potential uses

Background

The tuberculosis (TB) case detection rate has stagnated at 60% due to disorganized case finding and insensitivity of sputum smear microscopy. Of the identified TB cases, 4% die while being treated, monitored with tools that insufficiently predict failure/mortality.

Objective

To explore the TBscore, a recently proposed clinical severity measure for pulmonary TB (PTB) patients, and to refine, validate, and investigate its place in case finding.

Design

The TBscore’s inter-observer agreement was assessed and compared to the Karnofsky Performance Score (KPS) (paper I). The TBscore’s variables underlying constructs were assessed, sorting out unrelated items, proposing a more easily assessable TBscoreII, which was validated internally and externally (paper II). Finally, TBscore and TBscoreII’s place in PTB-screening was examined in paper III.

Results

The inter-observer variability when grading PTB patients into severity classes was moderate for both TBscore (κ_W=0.52, 95% CI 0.46–0.56) and KPS (κ_W=0.49, 95% CI 0.33–0.65). KPS was influenced by HIV status, whereas TBscore was unaffected by it. In paper II, proposed TBscoreII was validated internally, in Guinea-Bissau, and externally, in Ethiopia. In both settings, a failure to bring down the score by ≥25% from baseline to 2 months of treatment predicted subsequent failure (p=0.007). Finally, in paper III, TBscore and TBscoreII were assessed in health-care-seeking adults and found to be higher in PTB-diagnosed patients, 4.9 (95% CI 4.6–5.2) and 3.9 (95% CI 3.8–4.0), respectively, versus patients not diagnosed with PTB, 3.0 (95% CI 2.7–3.2) and 2.4 (95% CI 2.3–2.5), respectively. Had we referred only patients with cough >2 weeks to sputum smear, we would have missed 32.1% of the smear confirmed cases in our cohort. A TBscoreII>=2 missed 8.6%.

Conclusions

TBscore and TBscoreII are useful monitoring tools for PTB patients on treatment, as they could fill the void which currently exists in risk grading of patients. They may also have a role in PTB screening; however, this requires our findings to be repeated elsewhere.

Symptom screen for identification of highly infectious tuberculosis in people living with HIV in Southeast Asia

BACKGROUND

Tuberculosis (TB) is the leading cause of death among people living with HIV and frequently transmitted among this susceptible group. Transmission can be reduced by infection control practices. Simple evidence-based methods to identify patients who should be isolated are not well described in the literature. We sought to identify a simple, sensitive symptom or symptom combination that healthcare providers in resource-limited settings can use to identify and isolate persons living with HIV with highly infectious TB.

METHODS

Participants from 8 outpatient facilities in Cambodia, Thailand, and Vietnam underwent an extensive evaluation for TB. Patients with ≥1 positive sputum smear and Mycobacterium tuberculosis culture growth from a pulmonary site were defined as having highly infectious TB. We calculated sensitivity and prevalence of individual symptoms and >1000 symptom combinations.

RESULTS

Of 1980 participants, 272 (14%) had TB. Forty percent (n = 109) were highly infectious. Sensitivity for detecting highly infectious TB was highest for having the following symptoms in the past month as follows: weight loss (84%), cough (83%), fever (81%), and fatigue (78%); however, these symptoms were found in 46%-54% of all participants. Having 2 or 3 of 4 symptoms (prevalence, 26%-47%)-weight loss, fever, current cough, and night sweats-was 72%-90% sensitive for highly infectious TB.

CONCLUSIONS

The 2 or 3 of 4 symptom combinations of weight loss, fever, current cough, and night sweats, which are the same symptoms comprising the current World Health Organization-recommended TB diagnostic screen, are sensitive for detecting highly infectious TB in people living with HIV.

Classification and regression tree (CART) model to predict pulmonary tuberculosis in hospitalized patients

Background

Tuberculosis (TB) remains a public health issue worldwide. The lack of specific clinical symptoms to diagnose TB makes the correct decision to admit patients to respiratory isolation a difficult task for the clinician. Isolation of patients without the disease is common and increases health costs. Decision models for the diagnosis of TB in patients attending hospitals can increase the quality of care and decrease costs, without the risk of hospital transmission. We present a predictive model for predicting pulmonary TB in hospitalized patients in a high prevalence area in order to contribute to a more rational use of isolation rooms without increasing the risk of transmission.

Methods

Cross sectional study of patients admitted to CFFH from March 2003 to December 2004. A classification and regression tree (CART) model was generated and validated. The area under the ROC curve (AUC), sensitivity, specificity, positive and negative predictive values were used to evaluate the performance of model. Validation of the model was performed with a different sample of patients admitted to the same hospital from January to December 2005.

Results

We studied 290 patients admitted with clinical suspicion of TB. Diagnosis was confirmed in 26.5% of them. Pulmonary TB was present in 83.7% of the patients with TB (62.3% with positive sputum smear) and HIV/AIDS was present in 56.9% of patients. The validated CART model showed sensitivity, specificity, positive predictive value and negative predictive value of 60.00%, 76.16%, 33.33%, and 90.55%, respectively. The AUC was 79.70%.

Conclusions

The CART model developed for these hospitalized patients with clinical suspicion of TB had fair to good predictive performance for pulmonary TB. The most important variable for prediction of TB diagnosis was chest radiograph results. Prospective validation is still necessary, but our model offer an alternative for decision making in whether to isolate patients with clinical suspicion of TB in tertiary health facilities in countries with limited resources.