Yiying Cai1,2, Jamie Jay-May Lo3, Indumathi Venkatachalam4, Andrea L Kwa1,5,6, Paul A Tambyah7,8, Li Yang Hsu3, Adrian Barnett9, Kalisvar Marimuthu7,10, Nicholas Graves11. 1. Department of Pharmacy, Singapore General Hospital, Singapore. 2. Department of Pharmacy, Faculty of Science, National University of Singapore, Singapore. 3. Saw Swee Hock School of Public Health, National University of Singapore and National University Health Systems, Singapore. 4. Department of Infectious Diseases, Singapore General Hospital, Singapore. 5. Emerging Infectious Diseases, Duke-NUS Medical School, Singapore. 6. SingHealth Duke-NUS Medicine Academic Programme, Singapore. 7. Division of Infectious Diseases, National University Health Systems, Singapore. 8. Yong Loo Lin School of Medicine, National University of Singapore, Singapore. 9. School of Public Health and Social Work, Queensland University of Technology, Queensland, Australia. 10. National Centre for Infectious Diseases, Tan Tock Seng Hospital, Singapore. 11. Programme in Health Services and Systems Research, Duke-NUS Medical School, Singapore.
Abstract
OBJECTIVE: Methods that include the time-varying nature of healthcare-associated infections (HAIs) avoid biases when estimating increased risk of death and excess length of stay. We determined the excess mortality risk and length of stay associated with HAIs among inpatients in Singapore using a multistate model that accommodates the timing of key events. DESIGN: Analysis of existing prospective cohort study data. SETTING: Seven public acute-care hospitals in Singapore. PATIENTS: Inpatients reviewed in a HAI point-prevalence survey (PPS) conducted between June 2015 and February 2016. METHODS: We modeled each patient's admission over time using 4 states: susceptible with no HAI, infected, died, and discharged alive. We estimated the excess mortality risk and length of stay associated with HAIs, with adjustment for the baseline characteristics between the groups for mortality risk. RESULTS: We included 4,428 patients, of whom 469 had ≥1 HAI. Using a multistate model, the expected excess length of stay due to any HAI was 1.68 days (95% confidence interval [CI], 1.15-2.21 days). Surgical site infections were associated with the longest excess length of stay of 4.68 days (95% CI, 2.60-6.76 days). After adjusting for baseline differences, HAIs were associated with increased hazards of in-hospital mortality (adjusted hazard ratio [aHR], 1.32; 95% CI, 1.09-1.65) and decreased hazards in being discharged (aHR, 0.75; 95% CI, 0.67-0.84). CONCLUSIONS: HAIs are associated with increased length of hospital stay and mortality in hospitalized patients. Avoiding nosocomial infections can improve patient outcomes and free valuable bed days.
OBJECTIVE: Methods that include the time-varying nature of healthcare-associated infections (HAIs) avoid biases when estimating increased risk of death and excess length of stay. We determined the excess mortality risk and length of stay associated with HAIs among inpatients in Singapore using a multistate model that accommodates the timing of key events. DESIGN: Analysis of existing prospective cohort study data. SETTING: Seven public acute-care hospitals in Singapore. PATIENTS: Inpatients reviewed in a HAI point-prevalence survey (PPS) conducted between June 2015 and February 2016. METHODS: We modeled each patient's admission over time using 4 states: susceptible with no HAI, infected, died, and discharged alive. We estimated the excess mortality risk and length of stay associated with HAIs, with adjustment for the baseline characteristics between the groups for mortality risk. RESULTS: We included 4,428 patients, of whom 469 had ≥1 HAI. Using a multistate model, the expected excess length of stay due to any HAI was 1.68 days (95% confidence interval [CI], 1.15-2.21 days). Surgical site infections were associated with the longest excess length of stay of 4.68 days (95% CI, 2.60-6.76 days). After adjusting for baseline differences, HAIs were associated with increased hazards of in-hospital mortality (adjusted hazard ratio [aHR], 1.32; 95% CI, 1.09-1.65) and decreased hazards in being discharged (aHR, 0.75; 95% CI, 0.67-0.84). CONCLUSIONS:HAIs are associated with increased length of hospital stay and mortality in hospitalized patients. Avoiding nosocomial infections can improve patient outcomes and free valuable bed days.
Authors: Miriam Viviane Baron; Paulo Eugênio Silva; Janine Koepp; Janete de Souza Urbanetto; Andres Felipe Mantilla Santamaria; Michele Paula Dos Santos; Marcus Vinicius de Mello Pinto; Cristine Brandenburg; Isabel Cristina Reinheimer; Sonia Carvalho; Mário Bernardes Wagner; Thomas Miliou; Carlos Eduardo Poli-de-Figueiredo; Bartira Ercília Pinheiro da Costa Journal: Ann Intensive Care Date: 2022-06-13 Impact factor: 10.318