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Impact of coexisting pneumonia in the patients admitted with Clostridium difficile infection: a retrospective study from a national inpatient database


Clostridium difficile is a gram-positive anaerobic spore forming bacillus that can cause infection in a setting of antibiotic use. Pneumonia is a major cause of morbidity and mortality in an inpatient setting and is frequently associated with significant antibiotic administration. This study aims to compare the outcomes of C. difficile infection (CDI) with and without pneumonia to determine the impact of pneumonia in hospitalized patients with CDI. This population-based retrospective observational propensity matched analysis study uses data from the National Inpatient Sample database for the years 2016 and 2017. The primary outcomes were in-hospital mortality, total hospital charges, and mean length of stay. Secondary outcomes were the rates of sepsis, septic shock, non-ST elevation myocardial infarction (NSTEMI), acute renal failure, deep vein thrombosis, and pulmonary embolism. In-hospital mortality was noted to be higher in patients with pneumonia than those without (6.5% vs 1.2%, adjusted OR (aOR) 3.85; 95% CI 2.90 to 5.11, p<0.001). The following outcomes were more prevalent in patients with pneumonia compared with those without pneumonia: sepsis (9.8% vs 1.8%, aOR 4.69, 95% CI 3.73 to 5.87, p<0.001), septic shock (4.0% vs 0.5%, aOR 6.32, 95% CI 4.43 to 9.03, p<0.001), NSTEMI (1.9% vs 0.5%, aOR 2.95, 95% CI 1.85 to 4.71, p<0.001), and acute renal failure (31.5% vs 23.1%, aOR 1.23, 95% CI 1.07 to 1.40, p=0.003). In conclusion, patients with pneumonia were associated with significantly higher rates of system-based complications and higher in-hospital mortality rates.

  • pneumonia
  • Clostridium difficile

Data availability statement

Data are available in a public, open access repository. We used and/or analyzed the NIS database, available online at http: // The NIS is a large publicly available all-payer inpatient care database in the USA, containing data on more than seven million hospital stays yearly. Its large sample size is ideal for developing national and regional estimates and enables analyses of rare conditions, uncommon treatments, and special populations.

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