Rapid diagnosis of alprazolam poisoning by Fourier transform infrared spectroscopy on saliva samples

Abstract

Alprazolam benzodiazepine misuse is increasingly a public health concern, evidenced by rising cases of overdose and toxicity. Timely and accurate diagnosis is crucial for effective emergency room treatment. This study investigates the use of Fourier Transform Infrared (FTIR) spectroscopy as a rapid diagnostic tool for assessing alprazolam toxicity using saliva samples. Saliva samples were collected from 30 individuals, including healthy subjects and patients with confirmed alprazolam poisoning. FTIR spectroscopy in the form of Attenuated Total Reflectance (ATR) was used to study the spectral profiles of the samples. Statistical analyses, such as Gaussian peak fitting and Receiver Operating Characteristic (ROC) tests, were carried out to assess the diagnostic ability of the found spectral features. The designed protocol was subsequently applied to 55 additional saliva samples obtained from emergency room patients with suspected alprazolam poisoning, some of whom may have also used other drugs, but without confirmed multi-drug toxicity. Spectral differences between the two groups were evident, particularly in the 1200-1400 cm⁻¹ and 3000-3600 cm⁻¹ regions. ROC analysis demonstrated high diagnostic accuracy, differentiating healthy subjects from poisoned ones with 90% classification accuracy at 1200-1400 cm⁻¹ and perfect separation with 100% sensitivity and specificity at 3000-3600 cm⁻¹. A Fisher's exact test confirmed the diagnostic utility of this method for identifying alprazolam-poisoned individuals, yielding a p-value of less than 0.0002. The results affirm FTIR spectroscopy's potential as a precise, non-invasive diagnostic tool for alprazolam intoxication. Its ability to quickly distinguish between toxic and non-toxic levels is crucial for improving patient care in emergencies. Moreover, its application was effective even in cases with potential co-medication, provided that alprazolam was the primary suspected agent. FTIR spectroscopy is an effective method for diagnosing alprazolam toxicity in saliva samples, offering a quick, efficient, and non-invasive alternative to traditional techniques. This study opens the door for further research on FTIR in toxicological screening, with the potential to transform clinical practices in drug overdose management.

Keywords: Alprazolam toxicity; Diagnosis; FTIR spectroscopy; Saliva analysis; Toxicology.

Fig. 1

Comparative IR spectral analysis of alprazolam-exposed individuals versus healthy volunteers (400–4000 cm⁻¹). The spectra (Mean as solid lines ± SE as shadow around each line) reveal distinct alterations in molecular vibrations and functional group signatures, highlighting key biochemical disruptions induced by alprazolam toxicity in the affected group. Notable shifts in peak positions, intensities, and band broadening reflect changes in bond dynamics and conformational rearrangements, providing spectroscopic evidence of alprazolam’s metabolic impact.

Fig. 2

Stepwise spectral processing workflow for FTIR analysis of saliva samples from healthy and alprazolam-poisoned individuals. The pipeline includes (1) raw spectral acquisition, (2) normalization (Min-Max normalization), (3) baseline correction, (4) peak picking, (5) peak extraction (deconvolution). Critical spectral regions were identified, and differential peaks were quantified to distinguish drug-induced biochemical alterations from healthy baselines.

Fig. 3

Receiver Operating Characteristic (ROC) analysis of FTIR spectral intensities (1200–1400 cm⁻¹) to assess diagnostic significance of peak differences between healthy and alprazolam-poisoned saliva samples. The ROC curve assessed biomarker peak sensitivity and specificity, with an area-under-curve (AUC) of 90% indicating high predictive accuracy.

Fig. 4

Receiver Operating Characteristic (ROC) analysis of FTIR spectral intensities (3000–3600 cm⁻¹) to assess diagnostic significance of peak differences between healthy and alprazolam-poisoned saliva samples. The ROC curve assessed biomarker peak sensitivity and specificity, with an area-under-curve (AUC) of 100% indicating high predictive accuracy.