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Objectives <p><i>Providencia</i> infections are rare but emerging clinical entities with limited published evidence. We performed a pooled descriptive analysis by extracting data from case reports and case series to elucidate the clinical characteristics, outcomes, and potential predictors of adverse events.</p> Methods <p>A total of 69 cases of <i>Providencia</i> infection were analyzed (mean age: 52.77 ± 21.04 years; 61.19% male). Descriptive statistics were used to summarize patient demographics, clinical characteristics, and infection types. Complete-case data were used for regression analyses specifically, 63 cases for the sepsis outcome, 64 cases for urinary tract infections (UTIs), 62 cases for tracheal aspirates (TAs), and 46 cases for mortality. Logistic regression models with cluster-robust standard errors were applied to account for intra-study dependencies. Variables were selected for multivariable modeling using a backward stepwise approach with a p-value threshold of ≤ 0.3.</p> Results <p>The overall in-hospital mortality was 20.0% (13/69). The predominant infection types were bloodstream infections (sepsis) in 21 cases (30.43%), UTIs in 18 cases (26.09%), and surgical site infections in 17 cases (24.64%). In multivariable regression analysis, the experience of shock during hospitalization emerged as a significant predictor of poor outcome; patients who experienced shock had an adjusted odds ratio of 5.57 (95% confidence interval: 1.26–24.61, <i>p</i> = 0.023) for adverse events. Other factors, such as gender, underlying comorbidities, and various antibiotic administrations (e.g., cephalosporine, beta-lactam, carbapenem), were not independently associated with the outcomes in the final models. Notable exploratory signals: shock→mortality; cephalosporins→UTI; fluoroquinolones→SSI; longer antibiotic duration→lower TA positivity (all imprecise).</p> Conclusions <p>Our pooled descriptive analysis of <i>Providencia</i> infections reveals an overall mortality rate of 20.0% and identifies shock during hospitalization as an independent predictor of adverse outcomes. Because the evidence is derived from heterogeneous case reports and small case series with substantial missing data, all adjusted estimates are imprecise and should be considered hypothesis‑generating; they must not be used to guide clinical practice without confirmation in prospective studies.</p> Clinical trial number <p>Not applicable.</p>

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Antimicrobial interventions in multi drug resistance providencia associated infection; a systematic review and meta-analysis of case reports

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月26日

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  • Sara Salarian,
  • Maryam Hatam,
  • Mitra Mahmoudi Meymand,
  • Saeed Mohammad Soleymani,
  • Hadi Esmaily

摘要

Objectives

Providencia infections are rare but emerging clinical entities with limited published evidence. We performed a pooled descriptive analysis by extracting data from case reports and case series to elucidate the clinical characteristics, outcomes, and potential predictors of adverse events.

Methods

A total of 69 cases of Providencia infection were analyzed (mean age: 52.77 ± 21.04 years; 61.19% male). Descriptive statistics were used to summarize patient demographics, clinical characteristics, and infection types. Complete-case data were used for regression analyses specifically, 63 cases for the sepsis outcome, 64 cases for urinary tract infections (UTIs), 62 cases for tracheal aspirates (TAs), and 46 cases for mortality. Logistic regression models with cluster-robust standard errors were applied to account for intra-study dependencies. Variables were selected for multivariable modeling using a backward stepwise approach with a p-value threshold of ≤ 0.3.

Results

The overall in-hospital mortality was 20.0% (13/69). The predominant infection types were bloodstream infections (sepsis) in 21 cases (30.43%), UTIs in 18 cases (26.09%), and surgical site infections in 17 cases (24.64%). In multivariable regression analysis, the experience of shock during hospitalization emerged as a significant predictor of poor outcome; patients who experienced shock had an adjusted odds ratio of 5.57 (95% confidence interval: 1.26–24.61, p = 0.023) for adverse events. Other factors, such as gender, underlying comorbidities, and various antibiotic administrations (e.g., cephalosporine, beta-lactam, carbapenem), were not independently associated with the outcomes in the final models. Notable exploratory signals: shock→mortality; cephalosporins→UTI; fluoroquinolones→SSI; longer antibiotic duration→lower TA positivity (all imprecise).

Conclusions

Our pooled descriptive analysis of Providencia infections reveals an overall mortality rate of 20.0% and identifies shock during hospitalization as an independent predictor of adverse outcomes. Because the evidence is derived from heterogeneous case reports and small case series with substantial missing data, all adjusted estimates are imprecise and should be considered hypothesis‑generating; they must not be used to guide clinical practice without confirmation in prospective studies.

Clinical trial number

Not applicable.