Limiting ventilator-induced lung injury through individual electronic medical record surveillance.

BACKGROUND: To improve the safety of ventilator care and decrease the risk of ventilator-induced lung injury, we designed and tested an electronic algorithm that incorporates patient characteristics and ventilator settings, allowing near-real-time notification of bedside providers about potentially injurious ventilator settings. METHODS: Electronic medical records of consecutive patients who received invasive ventilation were screened in three Mayo Clinic Rochester intensive care units. The computer system alerted bedside providers via the text paging notification about potentially injurious ventilator settings. Alert criteria included a Pao2/Fio2 ratio of <300 mm Hg, free text search for the words "edema" or "bilateral + infiltrates" on the chest radiograph report, a tidal volume of >8 mL/kg predicted body weight (based on patient gender and height), a plateau pressure of >30 cm H2O, and a peak airway pressure of >35 cm H2O. Respiratory therapists answered a brief online satisfaction survey. Ventilator-induced lung injury risk was compared before and after the introduction of ventilator-induced lung injury alert. FINDINGS: The prevalence of acute lung injury was 42% (n = 490) among 1,159 patients receiving >24 hrs of invasive ventilation. The system sent 111 alerts for 80 patients, with a positive predictive value of 59%. The exposure to potentially injurious ventilation decreased after the intervention from 40.6 ± 74.6 hrs to 26.9 ± 77.3 hrs (p = .004). INTERPRETATIONS: Electronic medical record surveillance of mechanically ventilated patients accurately detects potentially injurious ventilator settings and is able to influence bedside practice at moderate costs. Its implementation is associated with decreased patient exposure to potentially injurious mechanical ventilation settings.

Incidence and transfusion risk factors for transfusion-associated circulatory overload among medical intensive care unit patients.

BACKGROUND: Transfusion-associated circulatory overload (TACO) is a frequent complication of blood transfusion. Investigations identifying risk factors for TACO in critically ill patients are lacking. STUDY DESIGN AND METHODS: We performed a 2-year prospective cohort study of consecutive patients receiving blood product transfusion in the medical intensive care unit (ICU) of the tertiary care institution. Patients were followed for development of transfusion-related complications. TACO was defined as acute hydrostatic pulmonary edema occurring within 6 hours of transfusion. In a nested case-control design, transfusion characteristics were compared between cases (TACO) and controls after matching by age, sex, and ICU admission diagnostic category. In a secondary analysis, patient characteristics before transfusion were compared between cases (TACO) and randomly selected controls. RESULTS: Fifty-one of 901 (6%) transfused patients developed TACO. Compared with matched controls, TACO cases had a more positive fluid balance (1.4 L vs. 0.8 L, p = 0.003), larger amount of plasma transfused (0.4 L vs. 0.07 L, p = 0.007), and faster rate of blood component transfusion (225 mL/hr vs. 168 mL/hr, p = 0.031). In a secondary analysis comparing TACO cases and random controls, left ventricular dysfunction before transfusion (odds ratio [OR], 8.23; 95% confidence interval [CI], 3.36-21.97) and plasma ordered for the reversal of anticoagulant (OR, 4.31; 95% CI, 1.45-14.30) were significantly related to the development of TACO. CONCLUSION: Volume of transfused plasma and the rate of transfusion were identified as transfusion-specific risk factors for TACO. Left ventricular dysfunction and fresh-frozen plasma ordered for the reversal of anticoagulant were strong predictors of TACO before the onset of transfusion.

Hemoptysis in a Patient with Elevated Immunoglobulin E.

Recurrent pneumonia with cavitation leading to pneumatoceles, secondary fungal infections, and hemoptysis are major causes of mortality and morbidity in patients with hyper-IgE syndrome. Prevention and aggressive treatment of pneumonia in these patients are essential to prevent further lung damage, but treatment may be delayed because the classic signs/symptoms of infection such as fever, chills, or rigors may be lacking. Early imaging to identify infection is essential for diagnosis and treatment. The mainstay of therapy is continuous, full-dose daily trimethoprim-sulfamethoxazole and commonly fungal coverage. Because hyper-IgE syndrome is a progressive disease, patients' condition may worsen despite compliance with prophylactic therapy.

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.