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Pharmacist-driven Evaluation of QTc Interval Prolongation in Cardiac Patients: Integrating Rautaharju’s Heart Rate Correction Formula and the Tisdale Risk Score
*Corresponding author: Ahmad Ullah Humza, Department of Pharmacology, Faculty of Pharmacy and Pharmaceutical Sciences, University of Karachi, Karachi, Pakistan. ahmadullah.humza@gmail.com
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Received: ,
Accepted: ,
How to cite this article: Humza AU, Baig SG, Siddiq A, Shakeel S, Iqbal Z, Ali J. Pharmacist-driven Evaluation of QT Interval Prolongation in Cardiac Patients: Integrating Rautaharju’s Heart Rate Correction Formula and the Tisdale Risk Score. J Card Crit Care TSS. 2026;10:182-9. doi: 10.25259/JCCC_74_2025
Abstract
Objectives:
In critically ill patients, the hazard of developing torsade de pointes (TdP) is a major concern. These patients are often on multiple medications and are liable to heart-rate corrected QT interval (QTc) prolongation, which can lead to fatal arrhythmias. This highlights the significance of monitoring the QTc and evaluating the risk to prevent such complications. The study aimed to evaluate a pharmacist-driven assessment of QTc prolongation using Rautaharju’s heart-rate-corrected formula and the Tisdale risk score (TRS) for the stratification of TdP risk.
Material and Methods:
We conducted an observational study at the National Institute of Cardiovascular Diseases in Karachi, enrolling 485 adult patients between November 2022 and August 2023. QTc intervals were manually calculated using Rautaharju’s formula from electrocardiographic lead II and V5. We applied the TRS both before and after the pharmacist’s interventions and used logistic regression to identify the key predictors of QTc prolongation.
Results:
The prevalence of prolonged QTc was 28.6%, with 4.1% crossing the critical threshold of QTc ≥500 ms. Among individual TRS components, hypokalaemia (OR: 1.55, 95% CI: 1.03–2.32, p=0.035) was a significant risk factor of QTc prolongation. Pharmacist interventions led to a significant shift in patient risk, reducing the proportion of prolonged QTc patients in the high-risk TRS category from 57.6% pre-intervention to 30.2% post-intervention.
Conclusion:
This study demonstrates that a pharmacist-led approach to QTc assessment can effectively identify and reduce arrhythmia risks in patients. By incorporating Rautaharju’s formula and the TRS into clinical care, we can make more informed decisions, potentially reducing the occurrence of drug-induced arrhythmias and improving patient safety.
Keywords
Cardiac patients
Pakistan
QT interval prolongation
Rautaharju’s heart rate correction formula
Tisdale risk score
INTRODUCTION
Prolongation of the heart rate-corrected QT interval (QTc) indicates delayed ventricular repolarization and is considered a key marker of the risk of torsade de pointes (TdP). This condition is often triggered by drug use and underlying clinical risk factors, necessitating thorough evaluation by both clinicians and pharmacists to manage potential risks effectively.[1]The importance of this issue is underscored by numerous population studies that consistently associate a prolonged QTc with increased cardiac mortality. This connection underscores the importance of precise measurement and practical risk assessment, particularly among hospitalized patients at increased risk.[2]
Critically ill patients are experiencing a combination of risk factors that significantly intensify their chances of QTc prolongation. These factors include complex medication regimens, electrolyte imbalances, and severe multi-organ dysfunction, making them far more susceptible to complications.[3] The challenge arises from the condition’s complex nature, including renal or hepatic dysfunction that can interfere with drug metabolism and metabolic imbalances that can directly disrupt cardiac repolarization.[4]
CredibleMeds® (www.crediblemeds.org), managed by the University of Arizona’s Center for Education and Research on Therapeutics (AzCERT), provides a comprehensive database of over 250 medications connected with TdP risk. The system classifies these drugs into distinct categories: those with a known risk (KR) of TdP, those with a possible risk (PR), those with a conditional risk (CR), and medications avoided in patients with congenital long QT syndrome.[5]
To accurately assess the risk, precise measurement of the QTc is essential. Bazett’s formula is commonly used in clinical settings, but it tends to overestimate the QTc.[2,6] For this study, we chose Rautaharju’s correction formula due to its superior accuracy in providing consistent QTc measurements across a broad range of heart rates. This approach helps minimize the rate-dependent bias commonly seen with Bazett’s formula.[7,8]
To convert this accurate measurement into practical clinical guidance, we incorporated the Tisdale risk score (TRS), a validated tool for predicting risk of TdP.[9] The TRS is widely used in clinical settings where prolonged QTc predictors are commonly prescribed, including cardiology, gastroenterology, and intensive care units (ICUs).[10]
In view of these gaps, we conducted a prospective study in Pakistan to determine the prevalence of QTc prolongation and to assess the integration of Rautaharju’s QTc formula with the TRS. The goal was to enhance risk stratification and guide interventions to protect these highly vulnerable patients.
MATERIAL AND METHODS
Study setting and design
We conducted a prospective, observational study at the National Institute of Cardiovascular Diseases (NICVD) in Karachi, Pakistan, a leading tertiary referral center for cardiac care. To ensure a well-powered sample, we calculated the required sample size. Based on a 30% prevalence of QTc prolongation with a 5% margin of error, we enrolled a final cohort of 485 patients after accounting for potential random errors. The study was approved by the NICVD Ethical Review Committee (ERC-48/2022).
The study included consecutive patients aged 18 years or older admitted to the NICVD ICUs with an admission diagnosis of triple vessel disease, valvular heart disease, and heart failure. To ensure an accurate assessment of acquired QTc prolongation, we excluded patients with active ventricular arrhythmias at presentation, atrial fibrillation, cardiac pacemaker, bundle branch block, congenital long QT syndrome, or ICU stays ≤ 24 h.
Data assortment and pharmacological assessment
We gathered patient demographics, clinical characteristics, and medication profiles using structured forms. A thorough review of all medications administered during the ICU stay, including intravenous and oral medications, was conducted. QTc-prolonging drug categorization was evaluated using the QT-Drug List from the CredibleMeds® database. In addition, we screened for pDDIs using the Lexidrug® reference platform.
QTc interval measurement and risk stratification
The QTc interval was manually calculated from standard 12-lead electrocardiographics (ECGs), with a primary focus on leads II and V5, using Rautaharju’s correction formula. We considered QTc prolonged if it was ≥450 ms in males, ≥460 ms in females, or increased by ≥60 ms from baseline. To ensure accuracy and minimize bias, two independent investigators, trained in ECG interpretation, reviewed all ECGs. A consulting cardiologist resolved any disagreements to reach a consensus on each measurement.
Patient risk was stratified using the validated TRS. Based on the score, patients were classified as low risk (≤6 points), moderate risk (7–10 points), or high risk (≥11 points) for TdP. All patients were prospectively monitored during hospitalization to track arrhythmic events and other clinical outcomes.
Pharmacist interventions
Upon identifying patients at high risk of TdP or with a prolonged QTc, the clinical pharmacist initiated a structured intervention protocol. These interventions included:
Alerting the on-call physician about the patient’s risk status.
Recommending the discontinuation or dose reduction of non-essential QTc-prolonging medications (e.g., switching from undesirable antibiotics or antiemetics to safer alternatives).
Suggesting correction of electrolyte abnormalities, specifically hypokalemia.
Increasing the frequency of ECG monitoring for high-risk patients.
The medical team’s acceptance of these recommendations was recorded, and risk scores were recalculated post-intervention.
Statistical analysis
All statistical analyses were conducted using the Statistical Package for the Social Sciences (version 23.0). To identify independent predictors of QTc prolongation, we used logistic regression and reported results as odds ratios (ORs) and 95% confidence intervals (CIs). A p < 0.05 was reflected as statistically significant.
RESULTS
Demographic and clinical profile with prolonged and normal QTc
Out of 485 patients analyzed using Rautaharju’s formula, 346 (71.3%) had normal QTc, while 139 (28.6%) had QTc with prolongation [Table 1]. Males accounted for 251 (72.5%) of the normal QTc group and 105 (75.5%) of the prolonged QTc group. Among female patients, 95 (27.5%) had a normal QTc, while 34 (10.5%) were classified as having a prolonged QTc. Among patients aged 40–59 years, the majority were in the normal QTc group (n = 192, 55.5%), while 62 (44.6%) were in the prolonged QTc group. The average hospital stay was slightly longer in the prolonged QTc group (2.4 ± 1.1 vs. 2 ± 1 days), with a significant difference (p < 0.001).
| Variable | QTc (Normal) Male <450, Female <460 | QTc (Prolonged) Male >450, Female >460 | p-value |
|---|---|---|---|
| Total (n) | 346 | 139 | - |
| Gender | |||
| Male | 251 (72.5%) | 105 (75.5%) | 0.500 |
| Female | 95 (27.5%) | 34 (24.5%) | |
| Age (years) | 52.5±12.1 | 52.1±13.6 | 0.812 |
| 18–39 | 49 (14.2%) | 26 (18.7%) | 0.090 |
| 40–59 | 192 (55.5%) | 62 (44.6%) | |
| ≥60 | 105 (30.3%) | 51 (36.7%) | |
| Length of stay | 2±1 | 2.4±1.1 | <0.001 |
| Comorbidities | |||
| None | 50 (14.5%) | 31 (22.3%) | 0.071 |
| Single | 117 (33.8%) | 37 (26.6%) | |
| Multiple | 179 (51.7%) | 71 (51.1%) | |
| Overall drugs | 11±2.1 | 10.6±2.4 | 0.067 |
| 0–4 drugs | 0 (0%) | 2 (1.4%) | 0.022 |
| 5–10 drugs | 131 (37.9%) | 63 (45.3%) | |
| ≥11 drugs | 215 (62.1%) | 74 (53.2%) | |
| QTc drugs | 3.4±1.1 | 3.4±1.2 | 0.514 |
| 0–4 drugs | 298 (86.1%) | 118 (84.9%) | 0.725 |
| 5–8 drugs | 48 (13.9%) | 21 (15.1%) | |
| ≥9 drugs | 0 (0%) | 0 (0%) | |
| AzCERT classification | |||
| Known risk | 269 (77.7%) | 108 (77.7%) | 0.991 |
| Possible risk | 50 (14.5%) | 21 (15.1%) | 0.853 |
| Conditional risk | 326 (94.2%) | 131 (94.2%) | 0.992 |
| Special risk | 79 (22.8%) | 28 (20.1%) | 0.519 |
| Hypokalemia | 100 (28.9%) | 51 (36.7%) | 0.094 |
| EF <40% | 78 (22.5%) | 35 (25.2%) | 0.535 |
| Pre-TRS | |||
| Low | 6 (1.7%) | 0 (0%) | 0.033 |
| Moderate | 180 (52%) | 59 (42.4%) | |
| High | 160 (46.2%) | 80 (57.6%) | |
| Post-TRS | |||
| Low | 28 (8.1%) | 7 (5%) | 0.095 |
| Moderate | 243 (70.2%) | 90 (64.7%) | |
| High | 75 (21.7%) | 42 (30.2%) | |
p < 0.05 statistically significant, TRS: Tisdale risk score, QTc: QT interval, EF: Ejection fraction, AzCERT: Arizona’s Center for Education and Research on Therapeutics
Over half of the patients had multiple comorbidities, both in the normal QTc group (179, 51.7%) and the prolonged QTc group (71, 51.1%). Patients with normal QTc were prescribed slightly more medications on average (11 ± 2.1) than those with prolonged QTc (10.6 ± 2.4), with this difference statistically significant when stratified (p = 0.022). However, the number of QTc-prolonging medications prescribed (mean 3.4) was similar between the two groups and did not differ significantly (p = 0.514).
AzCERT classification showed comparable exposure to QTc-prolonging agents. Drugs with KR were prescribed to 77.7% in both groups, and CR drugs were the most common (94.2% in each group). Hypokalemia was more frequent in the prolonged QTc group (36.7% vs. 28.9%), although the difference was not statistically significant. A reduced ejection fraction (EF) (<40%) was also comparable between the groups.
The TRS showed a significant difference after the pharmacist-led intervention compared with pre-intervention assessments. Before intervention, patients categorized as high risk according to TRS were observed more frequently in the prolonged QTc group (80, 57.6%) than in the normal QTc group (160, 46.2%; p = 0.033). Following the intervention, the proportion of high-risk patients decreased in both groups (normal: 75 (21.7%), prolonged: 42 (30.2%), although the difference was not statistically significant.
Demographic and clinical profile by QTc interval (<500 ms vs. ≥500 ms)
Among 485 patients, 20 (4.1%) had a QTc ≥ 500 ms, while 465 (95.9%) had a QTc < 500 ms [Table 2]. Although males dominated both groups, females were more represented in the QTc ≥500 ms group (8/20; 40%) than in the QTc <500 ms group (121/465; 26%), although the difference was not statistically significant (p = 0.166). The mean age was slightly lower in those with a QTc ≥500 ms (49.7 ± 17.2 vs. 52.5 ± 12.3 years). In addition, patients aged 40–59 years were significantly more common in the QTc <500 ms group (n = 248, 53.3%).
| Variable | QTc <500 | QTc ≥500 | p-value |
|---|---|---|---|
| Total (n) | 465 | 20 | - |
| Gender | |||
| Male | 344 (74%) | 12 (60%) | 0.166 |
| Female | 121 (26%) | 8 (40%) | |
| Age (years) | 52.5±12.3 | 49.7±17.2 | 0.474 |
| 18–39 | 68 (14.6%) | 7 (35%) | 0.027 |
| 40–59 | 248 (53.3%) | 6 (30%) | |
| ≥60 | 149 (32%) | 7 (35%) | |
| Length of stay | 2.1±1.1 | 2.4±0.7 | 0.349 |
| Comorbidities | |||
| None | 77 (16.6%) | 4 (20%) | 0.920 |
| Single | 148 (31.8%) | 6 (30%) | |
| Multiple | 240 (51.6%) | 10 (50%) | |
| Overall drugs | 10.9±2.1 | 9.8±2.9 | 0.109 |
| 0–4 drugs | 1 (0.2%) | 1 (5%) | 0.004 |
| 5–10 drugs | 185 (39.8%) | 9 (45%) | |
| ≥11 drugs | 279 (60%) | 10 (50%) | |
| QTc drugs | 3.4±1.1 | 3.1±1.1 | 0.223 |
| 0–4 drugs | 398 (85.6%) | 18 (90%) | 0.581 |
| 5–8 drugs | 67 (14.4%) | 2 (10%) | |
| ≥9 drugs | 0 (0%) | 0 (0%) | |
| AzCERT classification | |||
| Known risk | 366 (78.7%) | 11 (55%) | 0.013 |
| Possible risk | 66 (14.2%) | 5 (25%) | 0.181 |
| Conditional risk | 437 (94%) | 20 (100%) | 0.258 |
| Special risk | 102 (21.9%) | 5 (25%) | 0.746 |
| Hypokalemia | 142 (30.5%) | 9 (45%) | 0.171 |
| EF <40% | 102 (21.9%) | 11 (55%) | 0.001 |
| Pre-TRS | |||
| Low | 6 (1.3%) | 0 (0%) | 0.020 |
| Moderate | 235 (50.5%) | 4 (20%) | |
| High | 224 (48.2%) | 16 (80%) | |
| Post-TRS | |||
| Low | 34 (7.3%) | 1 (5%) | 0.022 |
| Moderate | 324 (69.7%) | 9 (45%) | |
| High | 107 (23%) | 10 (50%) | |
p < 0.05 statistically significant, TRS: Tisdale risk score, QTc: QT interval, EF: Ejection fraction, AzCERT: Arizona’s Center for Education and Research on Therapeutics
Patients with a QTc ≥500 ms had a slightly longer hospital stay (2.4 ± 0.7 days vs. 2.1 ± 1.1 days), though the difference was not statistically significant. The total medication burden was somewhat lower in patients with a QTc ≥500 ms (mean 9.8 ± 2.9 vs. 10.9 ± 2.1), but the difference was significant when the number of medications was stratified (p = 0.004). Rather than under-medication, this likely reflects clinician caution in prescribing multiple agents to patients already identified as high-risk or critically ill. Among the patients, 279 (60%) with a QTc <500 ms and 10 (50%) with a QTc ≥500 ms were prescribed 11 or more medications.
The use of QTc-prolonging drugs (mean 3.1 ± 1.1 vs. 3.4 ± 1.1) was similar between the groups. The most frequently identified QTc-prolonging agents in our cohort included proton pump inhibitors (omeprazole), antibiotics (ciprofloxacin), and antiemetics (domperidone). According to the AzCERT classification, the KR category of QTc-prolonging drug was prescribed significantly less often to patients with a QTc ≥500 ms (11/20; 55%) than to those with a QTc <500 ms (366/465; 78.7%; p = 0.013). Nearly all patients were prescribed drugs classified as conditional risk. In addition, a reduced (EF <40%) was more common in patients with a QTc ≥500 ms (11/20; 55%) compared to those with a QTc <500 ms (102/465; 21.9%, p = 0.001), indicating a strong cardiac connection to QTc prolongation. Hypokalemia was also more frequent in the former group (9/20; 45% vs. 142/465; 30.5%), but the difference was not statistically significant.
A substantial reduction in the proportion of patients categorized as high risk on the TRS was observed after the intervention, particularly in those with significantly prolonged QTc. In pre-intervention, 224/465; 48.2% of patients had QTc <500 ms and 16/20; 80% of those with QTc ≥500 ms were categorized as high risk, whereas in post- intervention, these values declined to 107/465; 23% and 10/20; 50%, respectively.
Correlation of TRS with QTc prolongation
We assessed the individual components of the TRS for their correlation with QTc prolongation (QTc ≥450 ms) in our cohort using logistic regression [Table 3]. Our findings highlighted several key observations, some of which aligned with expected clinical risk patterns, while one result was particularly unexpected. As anticipated, hypokalemia was categorized as a significant predictor of QTc prolongation (OR: 1.55, 95% CI: 1.03–2.32, p = 0.035). In addition, traditional risk factors, such as female sex and advanced age (≥68 years), showed non-significant trends toward increased risk, with ORs of 1.32 and 1.53, respectively. Other clinical factors included in the TRS did not demonstrate a statistically significant link with QTc prolongation in this study.
| Tisdale risk score | QTc (Rautaharju) ≥450 ms |
|---|---|
| Sex (Female) | 1.32 (0.87–2.03), p=0.196 |
| Age ≥68 years | 1.53 (0.79–2.97), p=0.209 |
| Furosemide as a loop diuretic | 0.4 (0.2–0.78), p=0.007 |
| Hypokalemia (Serum potassium ≤3.5 mEq/L) | 1.55 (1.03–2.32), p=0.035 |
| Acute myocardial infarction | 0.66 (0.28–1.57), p=0.344 |
| Two or more QTc-prolonging medications | 0.53 (0.16–1.78), p=0.307 |
| Sepsis | 2.25 (0.64–7.9), p=0.204 |
| Acute heart failure (<40% EF) | 1.16 (0.74–1.82), p=0.513 |
TRS: Tisdale risk score, QTc: QT interval, EF: Ejection fraction
During the study period, no episodes of TdP or sudden cardiac arrest were documented among the study participants. Furthermore, there were no statistically significant differences in in-hospital mortality between the normal and prolonged QTc groups (p > 0.05).
DISCUSSION
Our study confirms a clinically significant burden of QTc prolongation among hospitalized cardiac patients, with over a quarter of our cohort affected and 4.1% reaching the critical threshold of QTc ≥500 ms. This prevalence is consistent with reports from other settings.[11,12] The current findings revealed that among 485 hospitalized cardiac patients, a substantial proportion (28.6%) exhibited prolonged QTc, with a smaller subset (4.1%) showing severe prolongation (QTc ≥500 ms). In another study by Birda et al., 95 (34.1%) of 279 patients exhibited QTc prolongation, with 15% having a QTc ≥500 ms.[13] Another study of 422 hospitalized elderly adults found that 32% of participants had QTc prolongation.[14]
The gender distribution showed male predominance across all QTc groups; however, the proportion of females increased notably in the QTc ≥500 ms subgroup (40%), suggesting a possible trend toward a higher risk of severe QTc prolongation in females, although this was not statistically significant. A similar study reported no significant difference between genders.[3] When the age distribution was examined, it was observed that the prolonged QTc group had a considerably higher proportion of patients (≥60 years) (36.7%) than the normal QTc group (30.3%). Rossi et al. revealed that the prevalence of QTc ≥500 ms was more than 10% in geriatric inpatients, and they were frequently using QT-prolonging medications upon admission.[15] Al-Azayzih et al. reported that the likelihood of prescribing TdP-associated drugs decreased with age (OR = 0.989, p < 0.001), although the odds were higher for patients taking more than five medications (OR = 4.281, p < 0.001).[16] It has been reported that QTc prolongation occurs more frequently in the presence of one or more key risk factors, including sex, age above 65 years, electrolyte disturbances, underlying cardiac conditions such as heart failure or bradycardia, renal or hepatic impairment, and multiple QTc-prolonging medications.[17,18] The risk is especially intensified when two or more of these factors coexist, underscoring the need for careful assessment and monitoring when initiating QT-prolonging therapies.[19]
In the current study, more than 50% of patients in both the normal QTc and prolonged QTc groups had multiple comorbidities. Similarly, a study conducted in Taiwan reported findings almost identical to those reported.[20] Another study reported the association between QTc prolongation and chronic kidney disease.[21] Longer hospital admissions and higher mortality from cardiovascular events have been linked to this ECG change.[22] Likewise, in the current study, hospital stays were consistently longer in patients with QTc prolongation, underscoring its clinical impact, as extended hospitalization is often necessary for continuous monitoring and interventions to manage underlying causes, such as electrolyte imbalances or medication adjustments.[23] In the current study, each patient took an average of three drugs associated with QTc prolongation. Another study reported that 74/218 (34.0%) were taking as a minimum one prescription with a KR of TdP, whereas a large percentage (218/243 [89.7%]) were prescribed at minimum one QTc-prolonging medicine.[15] Numerous studies have demonstrated that hospitalized individuals have a much increased chance of getting TdP as a result of receiving medications that raise the risk correlated with QTc prolongation.[13,24]
More than 250 cardiac and non-cardiac medicines have the potential to prolong the QTc.[25] A known TdP risk is assigned to drugs with a well-documented proarrhythmic potential under standard prescribing conditions.[26] Despite a comparable overall burden of medications and QTc-prolonging drugs between the two cohorts, a substantial majority of patients (over 75%) were prescribed medications classified as high-risk by the AzCERT criteria.[25] This finding may indicate a lack of cautious prescribing practices or suggest that high-risk QTc-prolonging medications are not always adequately recognized during clinical decision-making. Conversely, we observed that QTc-prolonging drugs were prescribed less frequently to patients with severe QTc prolongation (QTc ≥500 ms). This observation likely represents a “risk-treatment paradox,” where clinicians intentionally withheld potential offending agents in patients who presented with severe baseline instability or pre-existing prolongation.[17] Macrolides, including azithromycin, have long been associated with QTc prolongation, TdP, and even sudden cardiac death.[27] Several case reports published between 2001 and 2007 documented arrhythmias associated with azithromycin, leading the U.S. Food and Drug Administration to issue a cardiac safety warning about the drug in 2013.[28] The American Heart Association consensus statement recommends that, in hospitalized patients at risk of TdP, the use of QTc-prolonging drugs should be on an individual basis. This guidance emphasizes the importance of carefully selecting treatments to limit the usage of drugs known to cause TdP, particularly in high-risk patients.[29]
Certain risk factors suggest an increased likelihood of QTc prolongation, as it is well established that patients with cardiovascular conditions are more prone to QTc prolongation.[22] Our findings highlight that a combination of clinical risk factors influences cardiac patients’ susceptibility to QTc prolongation. We confirmed that hypokalemia is a significant and modifiable risk factor (OR = 1.55, p = 0.035), supporting its well-recognized role in increasing arrhythmia risk.[30] The prevalence of this electrolyte disturbance in our cohort is consistent with studies reporting rates of up to 40% in cardiac ICUs,[31,32] highlighting it as a critical target for intervention. Furthermore, the strong association between reduced (EF<40%) and severe QTc prolongation (>500 ms) underscores the intrinsic link between a weakened myocardium and electrical instability.[30] In these patients, structural heart disease provides a conducive environment for repolarization abnormalities, requiring heightened vigilance in monitoring.[33]
The most compelling evidence of our intervention’s effectiveness lies in the significant risk reduction observed. After pharmacist-led interventions, there was a noticeable shift in the TRS categories. For example, the percentage of high-risk patients with prolonged QTc decreased from 57.6% to 30.2%, and even among the most vulnerable group (QTc ≥500 ms), the high-risk cohort was reduced from 80% to 50%. Although the p-value for this change (0.095) did not reach the traditional threshold for statistical significance – likely due to sample size – the consistent and substantial decrease across all groups reflects a meaningful improvement in patient safety. This highlights that the Tisdale score is not only a predictive tool but also a practical framework for guiding and evaluating the impact of clinical pharmacy services.
QTc prolongation is influenced by multiple factors and cannot be reliably measured or predicted using a single parameter in clinical practice.[9] The TRS is advantageous because it is straightforward to calculate, and the necessary factors are readily available in clinical practice. In contrast, other QTc risk stratification scores, such as the RISQ-PATH (RIsk Score for QT-prolonging drugs - a Patient Adverse Tailored Healthcare tool) score are more challenging to calculate manually due to their complexity and the large number of parameters required.[34] In addition, many of these scores have either not demonstrated strong performance outside the patient populations for which they were initially designed or have not been extensively validated in other patient groups.
In general, risk scores show great potential for recognizing patients at risk for QTc prolongation. Using the TRS can help identify individuals at higher risk, enabling timely, targeted interventions, such as adjusting or reducing QTc-prolonging medications, which could ultimately lower overall risk.[26] This approach also generated more relevant alerts for physicians and pharmacists regarding QTc prolongation, while reducing the excessive notifications often seen in traditional clinical decision support systems. As a result, future studies should assess the effectiveness of the TRS and its value as a risk-stratification tool to guide pharmacist-led interventions across diverse patient populations.[35-38]
A primary limitation of this research is its conduct within a single tertiary care institution. However, the protocols and patient population at our institution closely reflect those of major cardiac centers across Pakistan. More importantly, this study offers important foundational evidence for an area that has been largely overlooked in our region: pharmacist-led management of QTc prolongation. The lack of local data in this field further emphasizes the significance of our findings and underscores the need for future validation through larger, multicenter studies. Such research will be crucial for confirming the broader relevance of this pharmacist-led model and ensuring its integration into standard cardiac care practices.
CONCLUSION
This study provides strong evidence in support of a structured, pharmacist-led approach to managing the risk of QTc prolongation. We have demonstrated that incorporating the Tisdale score into routine clinical care facilitates the early identification of high-risk cardiac patients and enables targeted, effective interventions. Our findings advocate for the formal inclusion of pharmacist-led QTc risk assessments in cardiac care pathways, offering a cost-effective strategy to improve medication safety. By proactively addressing modifiable risks, such as hypokalemia, and optimizing pharmacotherapy, this approach can reduce arrhythmia risk and enhance outcomes.
Ethical approval:
The research/study was approved by the Institutional Review Board at the National Institute of Cardiovascular Diseases, number ERC-48/2022, dated 16th November 2022.
Declaration of patient consent:
The authors certify that they have obtained all appropriate patient consent forms. In the form, the patient has given consent for clinical information to be reported in the journal. The patient understands that the patient’s names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.
Conflicts of interest:
There are no conflicts of interest.
Use of artificial intelligence (AI)-assisted technology for manuscript preparation:
The authors confirm that they have used artificial intelligence (AI)-assisted technology, Paperpal tool solely for language refinement and to improve the clarity of writing.
Financial support and sponsorship: Nil.
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