Association Between Alcohol Use Disorders and Outcomes of Patients Hospitalized With Community-Acquired Pneumonia

Importance: Patients with alcohol use disorder (AUD) are at elevated risk of developing pneumonia, but few studies have assessed the outcomes of pneumonia in patients with AUD. Objectives: To compare the causes, treatment, and outcomes of pneumonia in patients with and without AUD and to understand the associations of comorbid illnesses, alcohol withdrawal, and any residual effects due to alcohol itself with patient outcomes. Design, Setting, and Participants: A retrospective cohort study was conducted of 137496 patients 18 years or older with pneumonia who were admitted to 177 US hospitals participating in the Premier Healthcare Database from July 1, 2010, to June 30, 2015. Statistical analysis was conducted from October 27, 2017, to August 20, 2018. Exposure: Alcohol use disorders identified from International Classification of Diseases, Ninth Revision, Clinical Modification codes. Main Outcomes and Measures: Pneumonia cause, antibiotic treatment, inpatient mortality, clinical deterioration, length of stay, and cost. Associations of AUD with these variables were studied using generalized linear mixed models. Results: Of 137496 patients with community-acquired pneumonia (70 358 women and 67 138 men; mean [SD] age, 69.5 [16.2] years), 3.5% had an AUD. Patients with an AUD were younger than those without an AUD (median age, 58.0 vs 73.0 years; P \u3c .001), more often male (77.3% vs 47.8%; P \u3c .001), and more often had principal diagnoses of aspiration pneumonia (10.9% vs 9.8%; P \u3c .001), sepsis (38.6% vs 30.7%; P \u3c .001), or respiratory failure (9.3% vs 5.5%; P \u3c .001). Their cultures more often grew Streptococcus pneumoniae (43.7% vs 25.5%; P \u3c .001) and less frequently grew organisms resistant to guideline-recommended antibiotics (25.0% vs 43.7%; P \u3c .001). Patients with an AUD were treated more often with piperacillin-tazobactam (26.2% vs 22.5%; P \u3c .001) but equally as often with anti-methicillin-resistant Staphylococcus aureus agents (32.9% vs 31.8%; P = .11) compared with patients without AUDs. When adjusted for demographic characteristics and insurance, AUD was associated with higher mortality (odds ratio, 1.40; 95% CI, 1.25-1.56), length of stay (risk-adjusted geometric mean ratio, 1.24; 95% CI, 1.20-1.27), and costs (risk-adjusted geometric mean ratio, 1.33; 95% CI, 1.28-1.38). After additional adjustment for differences in comorbidities and risk factors for resistant organisms, AUD was no longer associated with mortality but remained associated with late mechanical ventilation (odds ratio, 1.28; 95% CI, 1.12-1.46), length of stay (risk-adjusted geometric mean ratio, 1.04; 95% CI, 1.01-1.06), and costs (risk-adjusted geometric mean ratio, 1.06; 95% CI, 1.03-1.09). Models segregating patients undergoing alcohol withdrawal showed that poorer outcomes among patients with AUD were confined to the subgroup undergoing alcohol withdrawal. Conclusions and Relevance: This study suggests that, compared with hospitalized patients with community-acquired pneumonia but without AUD, those with AUD less often harbor resistant organisms. The higher age-adjusted risk of death among patients with AUD appears to be largely attributable to differences in comorbidities, whereas greater use of health care resources may be attributable to alcohol withdrawal

Differential Etiology: Inferring Specific Causation in the Law from Group Data in Science

In every toxic-tort case, the plaintiff must prove that the defendant exposed the plaintiff to something that caused an injury. The causal proof is in two parts: proof of general causation and proof of specific causation. General causation addresses the question of whether the exposure can cause injury in anyone. In the area of toxic torts, the evidence available to answer this question comes in the form of groupbasedstudies in the fields of toxicology, epidemiology, and genetics—studies that search for the effects of causes. Proof of general causation, however, is not enough. Because court cases focus on the individual, the plaintiff must prove specific causation. The plaintiff must show by a preponderance of the evidence that the exposure—and not something else—caused the plaintiff’s harm. This typically is done through expert “differential etiology” testimony. This testimony is not focused on the search for the effects of causes but rather for the causes of effects. Unfortunately, there is no body of science to which experts can turn when addressing this issue. Ultimately, much of the evidence that can be brought to bear on this causal question is the same group-level data employed to prove general causation. Consequently, the expert testimony often feels jerry-rigged, an improvisation designed to get through a tough patch. Court opinions that rule on the admissibility of this testimony rarely offer any systematic guidance about what is and is not an adequate differential etiology. Too often lawyers and courts have treated differential etiology as a matter of logical deduction and not as what it actually is: an inferential process combining statistical reasoning with a conceptual model of the causal interrelationships underlying observed data. This Article seeks to bring clarity to the differential-etiology determination by offering a scientifically oriented exposition of differential etiology. It provides a taxonomy of specific-causation situations and a systematic discussion of the factors that courts should consider in making a specific-causation determination. Our goal is to assist lawyers and judges in reasoning from group data to individual cases, what is referred to in the literature as the G2i problem

Differential impact of systolic and diastolic heart failure on in-hospital treatment, outcomes, and cost of patients admitted for pneumonia

Background: Patients admitted with pneumonia and heart failure (HF) have increased mortality and cost compared to those without HF, but it is not known whether outcomes differ between systolic and diastolic HF. Management of concomitant pneumonia and HF is complicated because HF treatments can worsen complications of pneumonia. Methods: This is a retrospective cohort study from the Premier Database among patients admitted with pneumonia between 2010 and 2015. Patients were categorized based on systolic, diastolic, and combined HF using ICD-9 codes. The primary outcome was in-hospital mortality. Secondary outcomes included use of HF medications, length of stay, cost, intensive care unit (ICU) admission, as well as use of invasive mechanical ventilation (IMV), vasopressors and inotropes. Multivariable logistic regression was used to describe associations of these outcomes with type of HF. Results: Of 123,211 patients with pneumonia and HF, 41,196 (33.4%) had systolic HF, 69,982 (56.8%) diastolic HF, and 12,033 (9.8%) had combined HF. Compared to patients with diastolic HF, after multivariable adjustment systolic HF was associated with higher in-hospital mortality (OR 1.15; 95% CI:1.11–1.20), ICU admission, and use of IMV and vasoactive agents, but not with increased length of stay or cost. Among patients with systolic HF, 80% received a loop diuretic, 72% a beta blocker, 48% angiotensin converting enzyme inhibitor or angiotensin receptor blocker, and 12.5% a mineralocorticoid receptor antagonist. Conclusion: Systolic HF is associated with added risk in pneumonia compared to diastolic HF. There may also be an opportunity to optimize medications in systolic HF prior to discharge