To send content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about sending content to .
To send content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about sending to your Kindle.
Note you can select to send to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Identifying routes of transmission among hospitalized patients during a healthcare-associated outbreak can be tedious, particularly among patients with complex hospital stays and multiple exposures. Data mining of the electronic health record (EHR) has the potential to rapidly identify common exposures among patients suspected of being part of an outbreak.
We retrospectively analyzed 9 hospital outbreaks that occurred during 2011–2016 and that had previously been characterized both according to transmission route and by molecular characterization of the bacterial isolates. We determined (1) the ability of data mining of the EHR to identify the correct route of transmission, (2) how early the correct route was identified during the timeline of the outbreak, and (3) how many cases in the outbreaks could have been prevented had the system been running in real time.
Correct routes were identified for all outbreaks at the second patient, except for one outbreak involving >1 transmission route that was detected at the eighth patient. Up to 40 or 34 infections (78% or 66% of possible preventable infections, respectively) could have been prevented if data mining had been implemented in real time, assuming the initiation of an effective intervention within 7 or 14 days of identification of the transmission route, respectively.
Data mining of the EHR was accurate for identifying routes of transmission among patients who were part of the outbreak. Prospective validation of this approach using routine whole-genome sequencing and data mining of the EHR for both outbreak detection and route attribution is ongoing.
To determine risk factors for the development of surgical site infections (SSIs) in neurosurgery patients undergoing spinal fusion.
Retrospective case-control study.
Large, academic, quaternary care center.
The study population included all neurosurgery patients who underwent spinal fusion between August 1, 2009, and August 31, 2013. Cases were defined as patients in the study cohort who developed an SSI. Controls were patients in the study cohort who did not develop an SSI.
To achieve 80% power with an ability to detect an odds ratio (OR) of 2, we performed an unmatched case-control study with equal numbers of cases and controls.
During the study period, 5,473 spinal fusion procedures were performed by neurosurgeons in our hospital. With 161 SSIs recorded during the study period, the incidence of SSIs associated with these procedures was 2.94%. While anterior surgical approach was found to be a protective factor (OR, 0.20; 95% confidence interval [CI], 0.08–0.52), duration of procedure (OR, 1.58; 95% CI, 1.29–1.93), American Society of Anesthesiologists score of 3 or 4 (OR, 1.79; 95% CI, 1.00–3.18), and hospitalization within the prior 30 days (OR, 5.8; 95% CI, 1.37–24.57) were found in multivariate analysis to be independent predictors of SSI following spinal fusion. Prior methicillin-resistant Staphylococcus aureus (MRSA) nares colonization was highly associated with odds 20 times higher of SSI following spinal fusion (OR, 20.30; 95% CI, 4.64–8.78).
In additional to nonmodifiable risk factors, prior colonization with MRSA is a modifiable risk factor very strongly associated with development of SSI following spinal fusion.
Nasal swab culture is the standard method for identifying methicillin-resistant Staphylococcus aureus (MRSA) carriers. However, this method is known to miss a substantial portion of those carrying MRSA elsewhere. We hypothesized that the additional use of a sponge to collect skin culture samples would significantly improve the sensitivity of MRSA detection.
Hospitalized patients with recent MRSA infection were enrolled and underwent MRSA screening of the forehead, nostrils, pharynx, axilla, and groin with separate swabs and the forehead, axilla, and groin with separate sponges. Staphylococcal cassette chromosome mec (SCCmec) typing was conducted by polymerase chain reaction (PCR).
A total of 105 MRSA patients were included in the study.
At least 1 specimen from 56.2% of the patients grew MRSA. Among patients with at least 1 positive specimen, the detection sensitivities were 79.7% for the swabs and 64.4% for the sponges. Notably, 86.4% were detected by a combination of sponges and nasal swab, and 72.9% were detected by a combination of pharyngeal and nasal swabs, whereas only 50.9% were detected by nasal swab alone (P<0.0001 and P=0.0003, respectively). Most isolates had SCCmec type II (59.9%) and IV (35.7%). No correlation was observed between the SCCmec types and collection sites.
Screening using a sponge significantly improves MRSA detection when used in addition to screening with the standard nasal swab.
Determining risk factors for acquisition of methicillin-resistant Staphylococcus aureus (MRSA) in hospitals is important for defining infection-control measures that may lead to fewer hospital-acquired infections.
To determine patient-associated risk factors for acquisition of MRSA in a tertiary care hospital with the goal of identifying modifiable risk factors.
A retrospective matched case-control study was performed. Case patients who acquired MRSA during hospitalization and 2 matched control patients were selected among inpatients admitted to target units during the period from 2001 through 2008. The odds of exposure to potential risk factors were compared between case patients and control patients, using matched univariate conditional logistic regression. A single multivariate conditional logistic regression model identifying independent patient-specific risk factors was generated.
A total of 451 case patients and 866 control patients were analyzed. Factors positively associated with MRSA acquisition were as follows: target unit stay before index culture; primary diagnosis of respiratory disease, digestive tract disease, injury or trauma, or other diagnosis compared with cardiocirculatory disease; peripheral vascular disease; mechanical ventilation with pneumonia; ventricular shunting or ventriculostomy; and ciprofloxacin use. Factors associated with decreased risk were receipt of a solid-organ transplant and use of penicillins, cephalosporins, rifamycins, daptomycin or linezolid, and proton pump inhibitors.
Among the factors associated with increased risk, few are modifiable. Patients with at-risk conditions could be targeted for intensive surveillance to detect acquisition sooner. The association of MRSA acquisition with target unit exposure argues for rigorous application of hand hygiene, appropriate barriers, environmental control, and strict aseptic technique for all procedures performed on such Patients. Our findings support focusing efforts to prevent MRSA transmission and restriction of ciprofloxacin use.
The rate of influenza vaccination among healthcare workers (HCWs) is approximately 40%. Differences in vaccination rates among HCW groups and reasons for accepting or rejecting vaccination are poorly understood.
To determine vaccination rates and motivators among different HCW groups during the 2004-2005 influenza season.
Cross-sectional survey conducted between July 10 and September 30, 2005.
Two tertiary care teaching hospitals in an urban center.
Physicians, nurses, nursing aides, and other staff. Surveys were collected from 1,042 HCWs (response rate, 42%).
Sixty-nine percent of physicians (n = 282) and 63% of medical students (n = 145) were vaccinated, compared with 46% of nurses (n = 336), 42% of nursing aides (n = 135), and 29% of administrative personnel (n = 144). Physicians and medical students were significantly more likely to be vaccinated than all other groups (P < .0001). Pediatricians (84%) were more likely than internists (69%) and surgeons (43%) to be vaccinated (P < .0001). Among the HCWs who were vaccinated, 33.4% received the live attenuated influenza vaccine (LAIV) and 66.6% received trivalent inactivated influenza vaccine (TIV). Vaccinated HCWs were less likely than unvaccinated HCWs to report an influenza-like illness (P = .03). Vaccination with LAIV resulted in fewer episodes of influenza-like illness than did receiving no vaccine (P = .03). The most common reason for rejecting vaccination was a concern about availability. Understanding that HCWs may transmit the virus to patients correlated with vaccine acceptance (P = .0004).
Significant differences in vaccination exist among physician specialties and employee groups, and there are inadequate vaccination rates among those with the greatest amount of patient contact, potentially providing a basis for group-specific interventions.
Fluoroquinolones have not been frequently implicated as a cause of Clostridium difficile outbreaks. Nosocomial C. difficile infections increased from 2.7 to 6.8 cases per 1,000 discharges (P < .001). During the first 2 years of the outbreak, there were 253 nosocomial C. difficile infections; of these, 26 resulted in colectomy and 18 resulted in death. We conducted an investigation of a large C. difficile outbreak in our hospital to identify risk factors and characterize the outbreak.
A retrospective case-control study of case-patients with C. difficile infection from January 2000 through April 2001 and control-patients matched by date of hospital admission, type of medical service, and length of stay; an analysis of inpatient antibiotic use; and antibiotic susceptibility testing and molecular subtyping of isolates were performed.
On logistic regression analysis, clindamycin (odds ratio [OR], 4.8; 95% confidence interval [CI95], 1.9-12.0), ceftriaxone (OR, 5.4; CI95, 1.8-15.8), and levofloxacin (OR, 2.0; CI95, 1.2-3.3) were independently associated with infection. The etiologic fractions for these three agents were 10.0%, 6.7%, and 30.8%, respectively. Fluoroquinolone use increased before the onset of the outbreak (P < .001); 59% of case-patients and 41% of control-patients had received this antibiotic class. The outbreak was polyclonal, although 52% of isolates belonged to two highly related molecular subtypes.
Exposure to levofloxacin was an independent risk factor for C. difficile-associated diarrhea and appeared to contribute substantially to the outbreak. Restricted use of levofloxacin and the other implicated antibiotics may be required to control the outbreak.
Email your librarian or administrator to recommend adding this to your organisation's collection.