Anaemia is highly prevalent among unselected internal medicine inpatients and is associated with increased mortality, earlier readmission and more prolonged hospital stay: an observational retrospective cohort study

Assessing the length of hospital stay (LOS) in patients with coronavirus disease 2019 (COVID-19) pneumonia is helpful in optimizing the use efficiency of hospital beds and medical resources and relieving medical resource shortages. This retrospective cohort study of 97 patients was conducted at Beijing You’An Hospital between January 21, 2020, and March 21, 2020. A multivariate Cox proportional hazards regression based on the smallest Akaike information criterion value was used to select demographic and clinical variables to construct a nomogram. Discrimination, area under the receiver operating characteristic curve (AUC), calibration, and Kaplan–Meier curves with the log-rank test were used to assess the nomogram model. The median LOS was 13 days (interquartile range [IQR]: 10–18). Age, alanine aminotransferase, pneumonia, platelet count, and PF ratio (PaO2/FiO2) were included in the final model. The C-index of the nomogram was 0.76 ( 95 % confidence interval CI = 0.69 – 0.83 ), and the AUC was 0.88 ( 95 % CI = 0.82 – 0.95 ). The adjusted C-index was 0.75 ( 95 % CI = 0.67 – 0.82 ) and adjusted AUC 0.86 ( 95 % CI = 0.73 – 0.95 ), both after 1000 bootstrap cross internal validations. A Brier score of 0.11 ( 95 % CI = 0.07 – 0.15 ) and adjusted Brier score of 0.130 ( 95 % CI = 0.07 – 0.20 ) for the calibration curve showed good agreement. The AUC values for the nomogram at LOS of 10, 20, and 30 days were 0.79 ( 95 % CI = 0.69 – 0.89 ), 0.89 ( 95 % CI = 0.83 – 0.96 ), and 0.96 ( 95 % CI = 0.92 – 1.00 ), respectively, and the high fit score of the nomogram model indicated a high probability of hospital stay. These results confirmed that the nomogram model accurately predicted the LOS of patients with COVID-19. We developed and validated a nomogram that incorporated five independent predictors of LOS. If validated in a future large cohort study, the model may help to optimize discharge strategies and, thus, shorten LOS in patients with COVID-19.

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Antifungal Resistance in Patients with Candidemia: A Retrospective Cohort Study

10.21203/rs.2.9663/v2 ◽

2019 ◽

Author(s):

Namareq Aldardeer ◽

Hadiel Albar ◽

Majda Al-Attas ◽

Abdelmoneim Eldali ◽

Mohammed Qutub ◽

...

Keyword(s):

Risk Factors ◽

Cohort Study ◽

Hospital Stay ◽

Retrospective Cohort Study ◽

Retrospective Cohort ◽

Antifungal Resistance ◽

Research Centre ◽

Median Length ◽

Resistant Group ◽

Sensitive Group

Abstract Background: Candidaemia is the most common form of invasive candidiasis. Resistant Candida blood stream infection (BSI) is rising, with limitations on the development of broader-spectrum antifungal agents worldwide. Our study aimed to identify the rate of antifungal-resistant candidaemia and the distribution of these species, determine the risk factors associated with antifungal resistance and evaluate the association of antifungal-resistant candidaemia with the length of intensive care unit (ICU) and hospital stay and with 30-day mortality. Methods: A retrospective cohort study was conducted at King Faisal Specialist Hospital and Research Centre, Jeddah, Saudi Arabia. Adult patients diagnosed with candidaemia from January 2006 to December 2017 were included. Results: A total of 196 BSIs were identified in 94 males (49.74%) and 95 females (50.26%). C. glabrata was the most commonly isolated Candida species, with 59 (30%), followed by C. albicans with 46 (23%). Susceptibility data were available for 122/189 patients, of whom 26/122 (21%) were resistant to one or more antifungals. C. parapsilosis with available sensitivity data were found in 30/122 isolates, of which 10/30 (33%) were resistant to fluconazole. Risk factors significantly associated with antifungal-resistant candidaemia included previous echinocandin exposure (odds ratio (OR) =1.38; 95% confidence interval (CI) (1.02-1.85); P= 0.006) and invasive ventilation (OR=1.3; 95% CI (1.08-1.57); P= 0.005). The median length of ICU stay was 29 days [range 12-49 days] in the antifungal-resistant group and 18 days [range 6.7-37.5 days] in the antifungal-sensitive group. The median length of hospital stay was 51 days [range 21-138 days] in the antifungal-resistant group and 35 days [range 17-77 days] in the antifungal-sensitive group. Thirty-day mortality was 15 (57.7%) and 54 (56.25%) among the antifungal-resistant and antifungal-sensitive groups, respectively (OR=1.01; 95% CI (0.84-1.21); P= 0.89).Conclusions: Our results indicate an increase in the rate of non-C. albicans candidaemia. The rise in C. parapsilosis resistance to fluconazole is alarming. Further studies are required to confirm this finding

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Comparison of QSOFA and sirs scores for the prediction of adverse outcomes of secondary peritonitis among patients admitted on the adult surgical ward in a tertiary teaching hospital in Uganda: a prospective cohort study

BMC Emergency Medicine ◽

10.1186/s12873-021-00528-x ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Emmanuel Nkonge ◽

Olivia Kituuka ◽

William Ocen ◽

Herbert Ariaka ◽

Alfred Ogwal ◽

...

Keyword(s):

Cohort Study ◽

Hospital Stay ◽

Teaching Hospital ◽

Adverse Outcomes ◽

Secondary Peritonitis ◽

Prolonged Hospital Stay ◽

Resource Limited ◽

Tertiary Teaching ◽

Tertiary Teaching Hospital ◽

Prolonged Hospital

Abstract Background SIRS and qSOFA are two ancillary scoring tools that have been used globally, inside and outside of ICU to predict adverse outcomes of infections such as secondary peritonitis. A tertiary teaching hospital in Uganda uses SIRS outside the ICU to identify patients with secondary peritonitis, who are at risk of adverse outcomes. However, there are associated delays in decision making given SIRS partial reliance on laboratory parameters which are often not quickly available in a resource limited emergency setting. In response to the practical limitations of SIRS, the sepsis-3 task force recommends qSOFA as a better tool. However, its performance in patients with secondary peritonitis in comparison to that of SIRS has not been evaluated in a resource limited setting of a tertiary teaching hospital in a low and middle income country like Uganda. Objective To compare the performance of qSOFA and SIRS scores in predicting adverse outcomes of secondary peritonitis among patients on the adult surgical wards in a tertiary teaching hospital in Uganda. Methods This was a prospective cohort study of patients with clinically confirmed secondary peritonitis, from March 2018 to January 2019 at the Accident and Emergency unit and the adult surgical wards of a tertiary teaching hospital in Uganda. QSOFA and SIRS scores were generated for each patient, with a score of ≥2 recorded as high risk, while a score of < 2 recorded as low risk for the adverse outcome respectively. After surgery, patients were followed up until discharge or death. In-hospital mortality and prolonged hospital stay were the primary and secondary adverse outcomes, respectively. Sensitivity, specificity, PPV, NPV and accuracy at 95% confidence interval were calculated for each of the scores using STATA v.13. Results A total of 153 patients were enrolled. Of these, 151(M: F, 2.4:1) completed follow up and were analysed, 2 were excluded. Mortality rate was 11.9%. Fourty (26.5%) patients had a prolonged hospital stay. QSOFA predicted in-hospital mortality with AUROC of 0.52 versus 0.62, for SIRS. Similarly, qSOFA predicted prolonged hospital stay with AUROC of 0.54 versus 0.57, for SIRS. Conclusion SIRS is superior to qSOFA in predicting both mortality and prolonged hospital stay among patients with secondary peritonitis. However, overall, both scores showed a poor discrimination for both adverse outcomes and therefore not ideal tools.

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