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Sanjay Saint

Publications and source records attributed to Sanjay Saint.

94 records · Page 6Linked to original sources

Does this woman have an acute uncomplicated urinary tract infection?

CONTEXT: Symptoms suggestive of acute urinary tract infection (UTI) constitute one of the most common reasons for women to visit clinicians. Although the clinical encounter typically involves taking a history and performing a physical examination, the diagnostic accuracy of the clinical assessment for UTI remains uncertain. OBJECTIVE: To review the accuracy and precision of history taking and physical examination for the diagnosis of UTI in women. DATA SOURCES: We conducted a MEDLINE search for articles published from 1966 through September 2001 and manually reviewed bibliographies, 3 commonly used clinical skills textbooks, and contacted experts in the field. STUDY SELECTION: Studies were included if they contained original data on the accuracy or precision of history or physical examination for diagnosing acute uncomplicated UTI in women. One author initially screened titles and abstracts found by our search. Nine of 464 identified studies met inclusion criteria. DATA EXTRACTION: Two authors independently abstracted data from the included studies. Disagreements were resolved by discussion and consensus with a third author. DATA SYNTHESIS: Four symptoms and 1 sign significantly increased the probability of UTI: dysuria (summary positive likelihood ratio [LR], 1.5; 95% confidence interval [CI], 1.2-2.0), frequency (LR, 1.8; 95% CI, 1.1-3.0), hematuria (LR, 2.0; 95% CI, 1.3-2.9), back pain (LR, 1.6; 95% CI, 1.2-2.1), and costovertebral angle tenderness (LR, 1.7; 95% CI, 1.1-2.5). Four symptoms and 1 sign significantly decreased the probability of UTI: absence of dysuria (summary negative LR, 0.5; 95% CI, 0.3-0.7), absence of back pain (LR, 0.8; 95% CI, 0.7-0.9), history of vaginal discharge (LR, 0.3; 95% CI, 0.1-0.9), history of vaginal irritation (LR, 0.2; 95% CI, 0.1-0.9), and vaginal discharge on examination (LR, 0.7; 95% CI, 0.5-0.9). Of all individual diagnostic signs and symptoms, the 2 most powerful were history of vaginal discharge and history of vaginal irritation, which significantly decreased the likelihood of UTI when present (LRs, 0.3 and 0.2, respectively). One study examined combinations of symptoms, and the resulting LRs were more powerful (24.6 for the combination of dysuria and frequency but no vaginal discharge or irritation). One study of patients with recurrent UTI found that self-diagnosis significantly increased the probability of UTI (LR, 4.0). CONCLUSIONS: In women who present with 1 or more symptoms of UTI, the probability of infection is approximately 50%. Specific combinations of symptoms (eg, dysuria and frequency without vaginal discharge or irritation) raise the probability of UTI to more than 90%, effectively ruling in the diagnosis based on history alone. In contrast, history taking, physical examination, and dipstick urinalysis are not able to reliably lower the posttest probability of disease to a level where a UTI can be ruled out when a patient presents with 1 or more symptoms.

Acute Disease↗

Hospital readmission for bronchiolitis.

The objectives of this study were to determine the rate and risk factors for hospital readmission after inpatient treatment for bronchiolitis. We conducted a retrospective cohort study from 2000 to 2002. The readmission rate within 30 days was 3.7% (95% Confidence Interval: 2.1%-6.0%). Readmission was not associated with age, prematurity, respiratory syncytial virus status, receipt of intensive care, or the observation period off supplemental oxygen. Those who required supplemental oxygen had a lower risk of readmission. Identifying children at risk for readmission is challenging. Children who did not require supplemental oxygen may be at greater risk because they are progressing in their illness.

Bronchiolitis↗

Expanding the avenues for addressing patient safety.

The Safety Case Management Committee, initiated in 1999, is a core component of the safety program at the Department of Veterans Affairs Medical Center in Ann Arbor. It is one of several approaches the facility uses to address error prevention or to contain its damaging effects.

Hospitals, Veterans↗