Predictive Value of Clinical and Laboratory Findings in the Diagnosis of Enteric Fever
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Abstract
Background: Enteric fever remains endemic in Pakistan, where limited access to blood culture and increasing antimicrobial resistance complicate early diagnosis and treatment. Clinical signs and routine laboratory parameters are commonly used in resource-limited settings, but their predictive value against confirmed non-enteric febrile illnesses remains uncertain. Objective: To identify independent clinical and laboratory predictors of culture-confirmed enteric fever and evaluate the diagnostic performance of individual and combined findings. Methods: This retrospective diagnostic case–control study was conducted at Pak-Emirates Military Hospital, Rawalpindi, from January 2021 to December 2022. Sixty patients with culture-confirmed Salmonella Typhi or Salmonella Paratyphi infection were compared with 58 patients with microbiologically, serologically, antigenically, or molecularly confirmed non-enteric febrile illnesses. Clinical findings, hematological parameters, liver enzymes, and Widal titres were analyzed using group comparisons and multivariable logistic regression. Diagnostic performance was assessed using sensitivity, specificity, positive predictive value, and negative predictive value. Results: Salmonella Typhi accounted for 42/60 cases, with multidrug resistance in 28/42 and extensively drug-resistant phenotype in 8/42 isolates. Splenomegaly, relative bradycardia, rose spots, thrombocytopenia, elevated aspartate aminotransferase, and Widal O titre ≥1:160 were independent predictors of enteric fever. The model showed good discrimination, with an area under the receiver operating characteristic curve of 0.84. Combined findings showed high specificity but low sensitivity. Conclusion: Clinical and routine laboratory findings may support rule-in diagnosis of enteric fever when present but cannot replace microbiological confirmation or reliably exclude disease when absent. Prospective validation is required before these predictors can be used as a formal diagnostic algorithm
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