Adverse drug–related skin eruptions are among the most conspicuous expressions of drug harm. Some are fleeting and pruritic; others progress to severe, occasionally fatal syndromes such as Stevens–Johnson syndrome (SJS), toxic epidermal necrolysis (TEN), or drug reaction with eosinophilia and systemic symptoms (DRESS). Conceptually, these events reflect an interplay between immune reactivity, metabolic activation, and host genetics, consistent with contemporary definitions of adverse drug reactions that emphasize clinically meaningful harm and the need for treatment modification [1].In hospitals worldwide, cutaneous adverse drug reactions (CADRs) are not rare. Point estimates commonly fall around 1–3% of inpatients and may climb higher in referral settings where polypharmacy is routine; some modern reviews report upper ranges approaching ~10% depending on case-mix and ascertainment [2,3]. In India, the burden is shaped by prescribing patterns and access to common medicines. Systematic summaries indicate maculopapular eruptions, fixed drug eruptions, urticaria, and SJS/TEN as dominant phenotypes, with antimicrobials, NSAIDs/analgesics, and antiepileptics as leading culprits [4]. Standardized tools have improved recognition and prognostication across the severe end of the spectrum. RegiSCAR criteria have clarified the multisystem phenotype of DRESS and aided comparability between studies, while SCORTEN remains the best-validated mortality score for SJS/TEN and is recommended for early risk stratification [5,6]. Against this backdrop, the present study aimed to describe, prospectively, the clinical spectrum of adverse cutaneous drug reactions. Specifically, we profile presenting morphologies, identify frequently implicated drugs, map time-to-onset after exposure, and document mucosal involvement. The practical goal is to generate locally relevant evidence that can sharpen bedside recognition and support safer prescribing.

Study Design and Setting This was a prospective observational study conducted in the Department of Dermatology at the Department of Dermatology Venerology& Leprosy, KAP Vishwanadham Government Medical College & Hospital, Tiruchirappalli, Tamil Nadu, India, in the year between January 2023 and December 2024. All patients presenting with clinical evidence of an adverse cutaneous drug reaction (ACDR) and willing to participate were included. Participants and Eligibility Both inpatients and outpatients of any age and gender were eligible. Patients were excluded if the reaction could not be confidently attributed to a specific drug, if the medication history was incomplete, or if reactions were due solely to herbal or alternative preparations. Sample Size and Sampling Technique Consecutive sampling was used until seventy-five patients were enrolled. The sample size was estimated using the formula: n = Z² × p × (1 – p) / d², Where Z = 1.96 (for 95% confidence), p = 0.5 (expected prevalence of ACDR), and d = 0.12 (allowable error).The calculated sample size was 67; 75 patients were finally included to account for possible data loss. Data Collection A structured proforma was used to record demographic details, suspected drug(s), dosage, duration of intake, lag time between exposure and rash onset, and mucocutaneous involvement. Each participant underwent a complete dermatological and systemic examination, and lesions were photographed with consent for documentation. Variables Studied The primary variable was the clinical pattern of the ACDR. Secondary variables included the suspected drug class, lag time, presence of mucosal lesions, and constitutional symptoms such as fever, pruritus, or edema. Statistical Analysis Data were entered in Microsoft Excel and analyzed using SPSS version 26 (IBM Corp, USA). Continuous variables were expressed as mean ± standard deviation, while categorical data were presented as frequencies and percentages. Associations between categorical variables were tested using the Chi-square test or Fisher’s exact test as appropriate. A p-value < 0.05 was considered statistically significant. Ethical Considerations The study protocol received clearance from the Institutional Ethics Committee before enrolment. Informed written consent was obtained from all adult participants and from guardians for minors. Patient identity was kept confidential at every stage of analysis and reporting.

Table 1. Demographic characteristics of study participants Variable Value Sample size (n) 75 Mean age ± SD (years) 41.95 ± 15.95 Age range (years) 0.5 – 84 Male, n (%) 44 (58.7%) Female, n (%) 31 (41.3%) Table 1 shows that middle-aged adults formed the majority, with a modest male predominance. A total of seventy-five patients met the inclusion criteria during the study period. The mean age was 41.95 ± 15.95 years (range: 0.5–84), and males constituted 58.7% of the cohort. Most participants were middle-aged. No significant gender-based difference was noted in reaction severity or pattern. Table 2. Distribution of clinical diagnoses among patients with ACDRs Diagnosis Frequency (n) Percentage (%) Fixed drug eruption (FDE) 17 22.7 Bullous FDE 13 17.3 Drug-induced exanthem 8 10.7 Urticaria 8 10.7 Stevens–Johnson syndrome (SJS) 7 9.3 DRESS 3 4.0 Pruritus 4 5.3 Lichenoid drug eruption 2 2.7 Papular eruption 2 2.7 Drug-induced vasculitis 1 1.3 Angioneurotic edema 1 1.3 Sweet syndrome 1 1.3 Others (ALEP, EMF, etc.) 7 9.4 Total 75 100 Table 2 reveals that fixed drug eruption predominated, accounting for nearly one-fourth of all ACDRs. The range of clinical morphologies encountered is detailed. Fixed drug eruption (FDE) was most frequent (22.7%), followed by bullous FDE (17.3%), drug-induced exanthem (10.7%), and urticaria (10.7%). Severe forms such as Stevens–Johnson syndrome (9.3%) and DRESS (4%) were less common. A few rare entities, like Sweet syndrome, angioneurotic edema, and vasculitic eruptions, were seen only once each. Table 3. Drugs implicated in adverse cutaneous reactions Causative Drug Frequency (n) Percentage (%) Paracetamol 15 20.0 Phenytoin 12 16.0 Anti-tuberculosis therapy (ATT) 9 12.0 Doxycycline 4 5.3 Carbamazepine 3 4.0 Ciprofloxacin 3 4.0 Septran 2 2.7 Sodium valproate 2 2.7 Diclofenac 2 2.7 Others (individual antibiotics, psychotropics, vaccines) 23 30.6 Total 75 100 Table 3 highlights the dominance of easily available medications such as paracetamol and phenytoin in triggering ACDRs. The suspected medications responsible for the observed reactions are summarized. Paracetamol was implicated most frequently (20%), followed by phenytoin (16%), anti-tuberculosis therapy (12%), and doxycycline (5.3%). Anticonvulsants and antipyretic analgesics together contributed nearly half of all reactions. Rare causes included selective antibiotics and psychotropics. Lag-Time between Drug Intake and Rash Onset Most reactions occurred within 48 hours of drug exposure. Figure 2 illustrates this pattern, with 26.7% developing within 24 hours and another 35% within the next two days. About 19% of cases occurred between 8–21 days, while delayed reactions (≥1 month) made up 12%. Mucosal Involvement Out of 75 patients, 14 (18.7%) showed mucosal lesions. The lip mucosa was most commonly affected (16%), followed by the buccal mucosa (2.7%). The remaining 61 (81.3%) had no mucosal lesions. A gender-wise distribution (Figure 4) revealed slightly higher mucosal changes among males (7 vs. 5), but this difference lacked statistical significance (p > 0.05). Associated Symptoms and Recurrence Additional systemic symptoms were infrequent. Mild itching was seen in 6.7%, pain and pedal edema in 2.7% each, and fever in a single patient (1.3%). Only one participant reported recurrence on re-exposure to the suspected drug (1.3%). Overall, descriptive analysis (Tables 1–3 and Figures 1–4) demonstrated clear clustering by reaction type, onset time, and drug category.

In this prospective cohort of seventy-five patients, adverse cutaneous drug reactions clustered around a limited set of morphologies and drug classes. Fixed drug eruption and bullous FDE together accounted for nearly two-fifths of eruptions (Table 2, Figure 1). Paracetamol, phenytoin, and ATT were the most frequent culprits (Table 3). Most reactions appeared within 48 hours of exposure (Figure 2). Mucosal involvement occurred in about one-fifth of patients, predominantly at the lips (Figures 3–4). Indian datasets repeatedly identify antimicrobials, NSAIDs or analgesics, and antiepileptics as dominant triggers, with antiepileptics overrepresented among severe reactions [7]. Pharmacovigilance center reports from India also show a predominance of maculopapular eruptions and a high share of early onset events [8]. Recent clinico epidemiologic series continue to report fixed drug eruption as a leading morphology, sometimes approaching half of all CADRs, consistent with our pattern in Table 2 and Figure 1 [9]. Together, these observations suggest that access to common analgesics and antibiotics, programmatic antitubercular therapy, and anticonvulsant use shape the clinical spectrum seen in tertiary care. Severe cutaneous adverse reactions: implications Although SCAR phenotypes were a minority here, for example, SJS at 9.3 percent, the potential for harm is substantial. Contemporary reviews and cohorts estimate mortality from approximately 5 to 10 percent for SJS to 15 to 40 percent for TEN, depending on case mix and supportive care [10]. SCORTEN remains the most validated bedside mortality score, while ABCD 10 offers an alternative with comparable performance in some series [11,12]. Clinically, our distribution in Figure 1 argues for early recognition pathways, prompt culprit drug cessation, supportive care, and immediate prognostic scoring when morphology flags SJS or TEN. Culprit profiling and early time to onset, practical steps That paracetamol led the list (Table 3) likely reflects ubiquity more than high intrinsic risk, yet clinicians should remember it can produce fixed drug eruption, including mucosal variants, as documented in published reports [13]. The early clustering of onset (Figure 2) is a pragmatic triage cue. In the first 48 hours after starting any new analgesic, antibiotic, or antipyretic, a fresh eruption should trigger a prescription review and a brief drug timeline worksheet at the bedside. This simple workflow improves attribution and reduces unnecessary polypharmacy. Mucosal disease, relevance beyond SCAR Most patients lacked mucosal lesions (Figures 3–4). When present, changes clustered at the lips and occasionally the buccal mucosa. Even in non-SCAR phenotypes, mucosal findings warrant careful oral and ocular assessment, attention to pain control, and a low threshold for reconsidering early SJS, particularly if constitutional symptoms develop. Systems perspective and pharmacovigilance Tightening the reporting loop can align bedside practice with policy. The Pharmacovigilance Programme of India encourages routine reporting of suspected adverse drug reactions by clinicians, trainees, and nursing staff [14]. Practical levers include discharge summary prompts for ACDR cases and unit-level dashboards that feed signals back into safer prescribing. Strengths and limitations Strengths include the prospective design, standardized variable capture, and explicit linkage between text and visuals (Tables 1–3, Figures 1–4). Important limitations remain, including single-center scope, a modest sample size of seventy-five, limiting subgroup inference, lack of systematic causality scoring, such as Naranjo or ALDEN, and prognostic indices such as SCORTEN or ABCD 10, incomplete biopsy or immunologic workup, and absence of long-term outcomes. These could bias phenotype proportions and understate late sequelae. Clinical takeaways Expect fixed drug eruption dominant profiles in similar Indian settings (Table 2, Figure 1). Treat the first 48 hours after a new prescription as a high-risk window (Figure 2). Keep anticonvulsants, antituberculars, and common analgesics high in the suspect list (Table 3). For suspected SCAR, act fast, stop the drug, score risk, and escalate care [10–12]. These steps dovetail with national pharmacovigilance aims and can reduce preventable harm [14].

Fixed drug eruption emerged as the leading presentation of adverse cutaneous drug reactions, followed by bullous variants and urticaria. Paracetamol, phenytoin, and antituberculosis drugs were the most frequent culprits, with most reactions occurring within 48 hours of exposure. Although severe forms such as SJS and DRESS were uncommon, their early identification remains vital. Strengthening pharmacovigilance and promoting cautious prescribing, especially for commonly used analgesics and anticonvulsants, can significantly reduce preventable morbidity. Future multicentric studies incorporating genetic and immunologic profiling are needed to better define susceptibility patterns in Indian patients.

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