Optimizing B-lines on lung ultrasound: an in-vitro to in-vivo pilot study with clinical implications.

B-lines on lung ultrasound (US) are the hallmark of pulmonary edema. It is unknown if ultrasound machine settings or probe type matter. We created an in-vitro gelatin model. Using lung presets as baseline, five blinded investigators assessed the impact of 32 distinct settings on B-line visibility based on a Likert-Scale (LS) from 0 to10 (< 5 worse, > 5 better) separately for two probes. The experiment was then repeated in-vivo in a patient with known pulmonary edema. Based on a multivariable regression LS-ratings were similar when comparing the in-vitro versus in-vivo experiment (P = 0.16; partial R2 = 0.2%) and when using the curvilinear versus linear probe (P = 0.69; partial R2 = 0.02%) but significantly different across machine settings (P < 0.0001; partial R2 = 34.4%). Limited by its pilot character, our study suggests that (1) certain US-machine settings heavily impact B-line visibility, with no clear difference between probes; (2) in-vitro models are a valid and practical alternative to more challenging patient-based research; (3) there is significant potential to improve B-line visibility and thus diagnostic yield in the clinical setting by using lung presets, centering the focal zone at the pleural line and increasing the distal time gain compensation, most of which are (in our experience) rarely done.

Decision support tool for differential diagnosis of Acute Respiratory Distress Syndrome (ARDS) vs Cardiogenic Pulmonary Edema (CPE): a prospective validation and meta-analysis.

INTRODUCTION: We recently presented a prediction score providing decision support with the often-challenging early differential diagnosis of acute lung injury (ALI) vs cardiogenic pulmonary edema (CPE). To facilitate clinical adoption, our objective was to prospectively validate its performance in an independent cohort. METHODS: Over 9 months, adult patients consecutively admitted to any intensive care unit of a tertiary-care center developing acute pulmonary edema were identified in real-time using validated electronic surveillance. For eligible patients, predictors were abstracted from medical records within 48 hours of the alert. Post-hoc expert review blinded to the prediction score established gold standard diagnosis. RESULTS: Of 1,516 patients identified by electronic surveillance, data were abstracted for 249 patients (93% within 48 hours of disease onset), of which expert review (kappa 0.93) classified 72 as ALI, 73 as CPE and excluded 104 as "other". With an area under the curve (AUC) of 0.81 (95% confidence interval = 0.73 to 0.88) the prediction score showed similar discrimination as in prior cohorts (development AUC = 0.81, P = 0.91; retrospective validation AUC = 0.80, P = 0.92). Hosmer-Lemeshow test was significant (P = 0.01), but across eight previously defined score ranges probabilities of ALI vs CPE were the same as in the development cohort (P = 0.60). Results were the same when comparing acute respiratory distress syndrome (ARDS, Berlin definition) vs CPE. CONCLUSION: The clinical prediction score reliably differentiates ARDS/ALI vs CPE. Pooled results provide precise estimates of the score's performance which can be used to screen patient populations or to assess the probability of ALI/ARDS vs CPE in specific patients. The score may thus facilitate early inclusion into research studies and expedite prompt treatment.

Drug-associated acute lung injury: a population-based cohort study.

BACKGROUND: A number of drugs have been reported as risk factors for acute lung injury (ALI) and ARDS. However, evidence is largely limited to case reports, and there is a paucity of data on the incidence and outcome of drug-associated ALI (DALI). METHODS: Using a population-based retrospective cohort study design, critically ill patients with a diagnosis of ALI were studied. These patients were classified as having DALI or non-DALI, based on whether they were exposed to prespecified drugs prior to development of ALI. Outcomes were compared between the two groups and frequencies and incidences reported. RESULTS: Among 514 patients with ALI, 49 (9.5%) had DALI with an estimated population-based incidence of 6.6 (95% CI, 4.8-8.5) per 100,000 person-years. Of the 49 patients with DALI,36 received chemotherapeutic/antiinflammatory agents, and 14 received amiodarone. Twelve patients had no additional risk factors for ALI (probable DALI), whereas 37 had alternative risk factors (possible DALI). Patients with and without DALI had similar baseline characteristics. However, the APACHE (Acute Physiology and Chronic Health Evaluation) III scores (median, 83 vs 70, P 5 .03), ICU mortality (35% vs 20%, P 5 .03), and hospital mortality (63% vs 32%, P , .001)were significantly higher in the DALI group compared with those of the non-DALI group. Hospital mortality remained significantly higher after adjusting for APACHE III score on admission and the presence of malignancy in logistic regression analysis (OR, 2.8; 95% CI, 1.3-6.4; P 5 .009). CONCLUSIONS: Drugs are important risk factors for ALI, and recognizing them as such may have important implications for early identification of patients at risk, discontinuation of the offending agent, and prognosis.

Decision support tool for early differential diagnosis of acute lung injury and cardiogenic pulmonary edema in medical critically ill patients.

BACKGROUND: At the onset of acute hypoxic respiratory failure, critically ill patients with acute lung injury (ALI) may be difficult to distinguish from those with cardiogenic pulmonary edema (CPE). No single clinical parameter provides satisfying prediction. We hypothesized that a combination of those will facilitate early differential diagnosis. METHODS: In a population-based retrospective development cohort, validated electronic surveillance identified critically ill adult patients with acute pulmonary edema. Recursive partitioning and logistic regression were used to develop a decision support tool based on routine clinical information to differentiate ALI from CPE. Performance of the score was validated in an independent cohort of referral patients. Blinded post hoc expert review served as gold standard. RESULTS: Of 332 patients in a development cohort, expert reviewers (κ, 0.86) classified 156 as having ALI and 176 as having CPE. The validation cohort had 161 patients (ALI = 113, CPE = 48). The score was based on risk factors for ALI and CPE, age, alcohol abuse, chemotherapy, and peripheral oxygen saturation/Fio(2) ratio. It demonstrated good discrimination (area under curve [AUC] = 0.81; 95% CI, 0.77-0.86) and calibration (Hosmer-Lemeshow [HL] P = .16). Similar performance was obtained in the validation cohort (AUC = 0.80; 95% CI, 0.72-0.88; HL P = .13). CONCLUSIONS: A simple decision support tool accurately classifies acute pulmonary edema, reserving advanced testing for a subset of patients in whom satisfying prediction cannot be made. This novel tool may facilitate early inclusion of patients with ALI and CPE into research studies as well as improve and rationalize clinical management and resource use.

Food insecurity is associated with acculturation and social networks in Puerto Rican households.

OBJECTIVE: To examine whether acculturation and social networks influence household food insecurity in an inner-city Puerto Rican community. METHODS: A survey was administered to 200 low-income female Puerto Rican caregivers with at least 1 child 12-72 months old living in Hartford, CT. Food insecurity was measured with the Radimer/Cornell Hunger Scale. Multivariate logistic regression analyses were used to identify food insecurity risk factors. RESULTS: Significant food insecurity risk factors included: being unemployed (odds ratio: 2.69), being single (2.34), being born in the United States (2.68), speaking only Spanish (3.15), planning to return to Puerto Rico (4.58), almost never/never attending Hispanic cultural events (6.85), and food stamps lasting less than a month (7.74). CONCLUSIONS AND IMPLICATIONS: Low levels of acculturation, lack of social networks, and poor food stamps management skills may influence household food insecurity.