In-Class Cross-Reactivity among Hospitalized Patients with Hypersensitivity Reactions to Fluoroquinolones

Results from this large, multicenter study suggest that patients with a confirmed ciprofloxacin, moxifloxacin, or levofloxacin hypersensitivity reaction are likely to tolerate other fluoroquinolones. Avoiding different fluoroquinolones in patients labeled with a ciprofloxacin, moxifloxacin, or levofloxacin allergy may not always be mandatory. This was a study of patients with a ciprofloxacin, moxifloxacin, or levofloxacin hypersensitivity reaction and a documented electronic medical record administration of a different fluoroquinolone. Numerically, the most common reaction risk occurred with a challenge to moxifloxacin (2/19; 9.5%), followed by ciprofloxacin (6/89; 6.3%), and levofloxacin (1/44; 2.2%).

Effect of mild COVID-19 on health-related quality of life

Background

Little is known about the effects of a mild SARS-CoV-2 infection on health-related quality of life.

Methods

This prospective observational study of symptomatic adults (18-87 years) who sought outpatient care for an acute respiratory illness, was conducted from 3/30/2020 to 4/30/2021. Participants completed the Short Form Health Survey (SF-12) at enrollment and 6-8 weeks later, to report their physical and mental health function levels as measured by the physical health and mental health composite scores (PHC and MHC, respectively). PHC and MHC scores for COVID-19 cases and non-COVID cases were compared using t-tests. Multivariable regression modeling was used to determine predictors of physical and mental health function at follow-up.

Results

Of 2301 enrollees, 426 COVID-19 cases and 547 non-COVID cases completed both surveys. PHC improved significantly from enrollment to follow-up for both COVID-19 cases (5.4 ± 0.41; P < 0.001) and non-COVID cases (3.3 ± 0.32; P < 0.001); whereas MHC improved significantly for COVID-19 cases (1.4 ± 0.51; P < 0.001) and decreased significantly for non-COVID cases (-0.8 ± 0.37; P < 0.05). Adjusting for enrollment PHC, the most important predictors of PHC at follow-up included male sex (β = 1.17; SE = 0.5; P = 0.021), having COVID-19 (β = 1.99; SE = 0.54; P < 0.001); and non-white race (β = -2.01; SE = 0.70; P = 0.004). Adjusting for enrollment MHC, the most important predictors of MHC at follow-up included male sex (β = 1.92; SE = 0.63; P = 0.002) and having COVID-19 (β = 2.42; SE = 0.67; P < 0.001).

Conclusion

Both COVID-19 cases and non-COVID cases reported improved physical health function at 6-8 weeks' convalescence; whereas mental health function improved among COVID-19 cases but declined among non-COVID cases. Both physical and mental health functioning were significantly better among males with COVID-19 than females.

Epidemiology and Clinical Outcomes of non-HACEK Gram-negative Infective Endocarditis

Background

The objectives of this study were to describe the changing epidemiology of GNIE and identify factors associated with treatment failure and death.

Methods

Adult patients with GNIE were included if they met modified Duke criteria for definitive IE between April 2010 and December 2021. Patients were identified using Boolean Search terms. Clinical failure was a defined as a composite of all-cause 42-day mortality or microbiologic failure. All analyses were performed using Stata version 15.1.

Results

One-hundred twenty-three patients were included. The most common pathogens were Serratia spp. (43%), Pseudomonas aeruginosa (21%), and Klebsiella spp. (14%). Fifty-two percent of cases were among persons who injection drugs (PWID; n=64) for whom Serratia spp. (70%) was the most common cause of GNIE. Overall, patients infected with P. aeruginosa had higher microbiologic failure rates than other patients (23% vs 6%; P=0.004). Patients who received combination therapy (n=53) had comparable median lengths of stay (23 days vs 19.5, P=0.412), microbiologic failure rates (11.3% vs 7.1%, P=0.528), clinical failure rates (18.9% vs 22.9%, P=0.592), and 90-day mortality rates (13.2% vs 25.7%, P=0.088) as those treated with monotherapy. After applying stepwise logistic regression, male gender, Pitt Bacteremia Score, and not receiving surgical intervention despite a surgical indication were associated with clinical failure.

Conclusions

This is the first study to identify Serratia spp. as the most common etiology of GNIE, which was particularly true among PWID. Microbiologic failures occurred most commonly among P. aeruginosa, and use of combination antimicrobial therapy did not improve clinical outcomes.

Changing Epidemiology and Decreased Mortality Associated With Carbapenem-resistant Gram-negative Bacteria, 2000-2017

BACKGROUND

Carbapenem-resistant gram-negative bacteria (CRGNB) continue to present a global healthcare crisis. We aimed to identify emerging trends of CRGNB over nearly 2 decades and describe the impact of CRGNB on patient outcomes.

METHODS

Patients from whom CRGNB were isolated between 2000 and 2017 were included in the study. Carbapenem resistance was defined by the most recent breakpoints and applied across the study period. Patient demographics, clinical characteristics, and outcomes were retrieved from the electronic health record.

RESULTS

A total of 94 888 isolates from 64 422 patients were identified; 9882 (10%) isolates from 4038 patients were carbapenem-resistant. Pseudomonas aeruginosa was the most common CRGNB each year. The second most common CRGNB emerged in waves over time. Carbapenem daily defined doses increased in parallel with CRGNB rates (R2 = 0.8131). The overall 30-day mortality rate was 19%, which decreased from 24% in 2000 to 17% in 2017 (P = .003; R2 = .4330). Among patients with CRGNB bloodstream infections (n = 319), overall 30- and 90-day mortality rates were 27% and 38%, respectively. Charlson score (adjusted odds ratio [aOR], 1.11 per point), intensive care unit residence (aOR, 7.32), and severe liver disease (aOR, 4.8.4) were independent predictors of 30-day mortality, while receipt of transplantation was associated with lower rates of death (aOR, 0.39). Among patients admitted between 2011 and 2017 (n = 2230), 17% died during hospitalization, 32% were transferred to long-term care facilities, and 38% were discharged home.

CONCLUSIONS

CRGNB emerged in waves over time, causing high rates of mortality. Despite increasing rates of CRGNB, overall patient outcomes have improved, suggesting that recognition and novel therapeutics have made a major impact.

Using capture-recapture methods to estimate influenza hospitalization incidence rates

Background

Accurate population estimates of disease incidence and burden are needed to set appropriate public health policy. The capture–recapture (C‐R) method combines data from multiple sources to provide better estimates than is possible using single sources.

Methods

Data were derived from clinical virology test results and from an influenza vaccine effectiveness study from seasons 2016–2017 to 2018–2019. The Petersen C‐R method was used to estimate the population size of influenza cases; these estimates were then used to calculate adult influenza hospitalization burden using a Centers for Disease Control and Prevention (CDC) multiplier method.

Results

Over all seasons, 343 influenza cases were reported in the clinical database, and 313 in the research database. Fifty‐nine cases (17%) reported in the clinical database were not captured in the research database, and 29 (9%) cases in the research database were not captured in the clinical database. Influenza hospitalizations were higher among vaccinated (58%) than the unvaccinated (35%) in the current season and were similar among unvaccinated (51%) and vaccinated (49%) in the previous year. Completeness of the influenza hospitalization capture was estimated to be 76%. The incidence rates for influenza hospitalizations varied by age and season and averaged 307–309 cases/100,000 adult population annually.

Conclusion

Using C‐R methods with more than one database, along with a multiplier method with adjustments improves the population estimates of influenza disease burden compared with relying on a single‐data source.

Proposed clinical indicators for efficient screening and testing for COVID-19 infection using Classification and Regression Trees (CART) analysis

The introduction and rapid transmission of SARS-CoV-2 in the United States resulted in methods to assess, mitigate, and contain the resulting COVID-19 disease derived from limited knowledge. Screening for testing has been based on symptoms typically observed in inpatients, yet outpatient symptoms may differ. Classification and regression trees recursive partitioning created a decision tree classifying participants into laboratory-confirmed cases and non-cases. Demographic and symptom data from patients ages 18-87 years enrolled from March 29-June 8, 2020 were included. Presence or absence of SARS-CoV-2 was the target variable. Of 832 tested, 77 (9.3%) tested positive. Cases significantly more often reported diarrhea (12 percentage points (PP)), fever (15 PP), nausea/vomiting (9 PP), loss of taste/smell (52 PP), and contact with a COVID-19 case (54 PP), but less frequently reported sore throat (-27 PP). The 4-terminal node optimal tree had sensitivity of 69%, specificity of 78%, positive predictive value of 20%, negative predictive value of 97%, and AUC of 76%. Among those referred for testing, negative responses to two questions could classify about half (49%) of tested persons with low risk for SARS-CoV-2 and would save limited testing resources. Outpatient symptoms of COVID-19 appear to be broader than the inpatient syndrome.Initial supplies of anticipated COVID-19 vaccines may be limited and administration of first such available vaccines may need to be prioritized for essential workers, the most vulnerable, or those likely to have a robust response to vaccine. Another priority group could be those not previously infected. Those who screen out of testing may be less likely to have been infected by SARS-CoV-2 virus thus may be prioritized for vaccination when supplies are limited.

Using Capture-Recapture Methods to Estimate Local Influenza Hospitalization Incidence Rates

Background

Accurate population estimates of disease incidence and burden are needed to set appropriate public health policy. The capture-recapture (C-R) method combines data from multiple sources to better estimate prevalence than is possible using single sources. This study used the C-R method to estimate influenza cases using research and administrative databases to calculate county-wide influenza hospitalization burden.

Methods

Data were derived from a database of clinical virology test results and research data from an influenza vaccine effectiveness study from seasons 2015-2016 to 2018-2019. Missed influenza cases were estimated using C-R method. These estimates were used to calculate disease burden using the multiplier method to correct for underreporting due to curtailing data collection before the end of influenza circulation.

Results

Over all seasons, 422 influenza cases were reported in the administrative database and 382 influenza cases in the research database. Seventy-five cases (18%) reported in the administrative database were not captured in the research database, and 35 (9%) cases in the research database were not captured in the administrative database. Completeness of the influenza hospitalization was estimated to be 76%. Influenza hospitalizations were higher among unvaccinated (32%) than vaccinated (22%) in the current season and among unvaccinated (28%) than vaccinated (23%) in the previous year. The incidence rates for influenza hospitalizations varied by age and season and averaged 421 cases/100,000 population annually.

Conclusion

The capture-recapture method offers a more accurate method for estimating influenza hospitalization than relying on a single data source. Using the multiplier method with adjustments improves the detection of influenza disease burden through a matched database. The incidence rates are consistent with national estimates.

Clinical and Genomic Epidemiology of Carbapenem-Nonsusceptible Citrobacter spp. at a Tertiary Health Care Center over 2 Decades

Carbapenem-nonsusceptible Citrobacter spp. (CNSC) are increasingly recognized as health care-associated pathogens. Information regarding their clinical epidemiology, genetic diversity, and mechanisms of carbapenem resistance is lacking. We examined microbiology records of adult patients at the University of Pittsburgh Medical Center (UMPC) Presbyterian Hospital (PUH) from 2000 to 2018 for CNSC, as defined by ertapenem nonsusceptibility. Over this time frame, the proportion of CNSC increased from 4% to 10% (P = 0.03), as did daily defined carbapenem doses/1,000 patient days (6.52 to 34.5; R2 = 0.831; P < 0.001), which correlated with the observed increase in CNSC (lag = 0 years; R2 = 0.660). Twenty CNSC isolates from 19 patients at PUH and other UPMC hospitals were available for further analysis, including whole-genome short-read sequencing and additional antimicrobial susceptibility testing. Of the 19 patients, nearly all acquired CNSC in the health care setting and over half had polymicrobial cultures containing at least one other organism. Among the 20 CNSC isolates, Citrobacter freundii was the predominant species identified (60%). CNSC genomes were compared with genomes of carbapenem-susceptible Citrobacter spp. from UPMC and with other publicly available CNSC genomes. Isolates carrying genes encoding carbapenemases (blaKPC-2,blaKPC-3, and blaNDM-1) were also long-read sequenced, and their carbapenemase-encoding plasmid sequences were compared with one another and with publicly available sequences. Phylogenetic analysis of 102 UPMC Citrobacter genomes showed that CNSC from our setting did not cluster together. Similarly, a global phylogeny of 64 CNSC genomes showed a diverse population structure. Our findings suggest that both local and global CNSC populations are genetically diverse and that CNSC harbor carbapenemase-encoding plasmids found in other Enterobacterales.

Defining the incidence and risk factors of colistin-induced acute kidney injury by KDIGO criteria

Background

Acute kidney injury (AKI) remains a treatment-limiting toxicity of colistin. Recently developed clinical practice guidelines from the Kidney Disease: Improving Global Outcomes (KDIGO) group have harmonized definitions of AKI, but have not been widely applied to patients receiving colistin.

Methods

We retrospectively defined AKI by KDIGO definitions among adult patients receiving intravenous colistin for ≥ 3 days. Risk factors for AKI within 48 hours and 7 days of initiating colistin were determined by multivariable logistic regression.

Results

Among 249 patients treated with colistin, rates of AKI were 12% and 29% at 48 hours and 7 days, respectively. At 48 hours, patients in the intensive care unit were at increased risk for AKI. Within 7 days, colistin daily doses >5mg/kg, chronic liver disease, and concomitant vancomycin were independent predictors. Seven percent of patients required renal replacement therapy at a median of 5 days (range: 3–7) following colistin initiation.

Conclusion

Safe use of colistin is promoted by early detection of AKI with KDIGO criteria, avoiding nephrotoxins, and limiting duration of therapy.

Targeted versus universal antifungal prophylaxis among liver transplant recipients

Guidelines recommend targeted antifungal prophylaxis for liver transplant (LT) recipients based on tiers of risk, rather than universal prophylaxis. The feasibility and efficacy of tiered, targeted prophylaxis is not well established. We performed a retrospective study of LT recipients who received targeted prophylaxis (n = 145; voriconazole [VORI; 54%], fluconazole [8%], no antifungal [38%]) versus universal VORI prophylaxis (n = 237). Median durations of targeted and universal prophylaxis were 11 and 6 days, respectively (p < 0.0001). The incidence of invasive fungal infections (IFIs) in targeted and universal groups was 6.9% and 4.2% (p = 0.34). Overall, intra-abdominal candidiasis (73%) was the most common IFI. Posttransplant bile leaks (p = 0.001) and living donor transplants (p = 0.04) were independent risk factors for IFI. IFIs occurred in 6% of high-risk transplants who received prophylaxis and 4% of low-risk transplants who did not receive prophylaxis (p = 1.0). Mortality rates (100 days) were 10% (targeted) and 7% (universal) (p = 0.26); attributable mortality due to IFI was 10%. Compliance with prophylaxis recommendations was 97%. Prophylaxis was discontinued for toxicity in 2% of patients. Targeted antifungal prophylaxis in LT recipients was feasible and safe, effectively prevented IFIs and reduced the number of patients exposed to antifungals. Bile leaks and living donor transplants should be considered high-risk indications for prophylaxis.

Risk factors for acquisition of multidrug-resistant Acinetobacter baumannii among cancer patients

BACKGROUND

Data regarding multidrug-resistant (MDR) Acinetobacter baumannii infections among cancer patients are limited.

METHODS

We conducted a case-control study to investigate the risk factors for acquisition of MDR A baumannii and the outcomes among cancer patients. Cases were inpatients with malignancy who had MDR A baumannii from any cultures between 2008 and 2011. Controls were inpatients with malignancy but no MDR A baumannii.

RESULTS

A total of 31 case patients were matched with 62 control patients. Hematologic malignancy (P = .036), need for dialysis (P = .01), admission for other reasons except elective surgery (P = .03), transfer from other health care facilities (P = .02), prolonged intensive care unit stay (P = .004), mechanical ventilation (P < .001), pressor use (P = .001), tube feeding (P < .001), transfusion (P = .009), and prior antimicrobial use (P < .001) were identified as significant risk factors in univariate analysis. Need for dialysis (odds ratio [OR], 18.23; P = .04) and prolonged intensive care unit stay (OR, 19.28; P = .01) remained significant in multivariate analysis. Lengths of stay were 28 days for the case patients and 10 days for the control patients (P = .001). The 90-day mortality rates were 41.9% and 29.0%, respectively (P = .20).

CONCLUSIONS

Acquisition of MDR A baumannii among cancer patients appears to be associated with general nosocomial infection risk factors rather than underlying malignancies.