PURPOSE: To determine the differences in tear physiology between aqueous deficiency dry eye (ADDE) and evaporative dry eye (EDE), and evaluate their utility in diagnosis. METHODS: Fifty-six dry eye patients were classified into 30 ADDE and 26 EDE according to the recently published Dry Eye Workshop criteria. A range of tear physiology measures comprising of tear evaporation, turnover rate (TTR), distribution, volume and osmolarity, and meibomian gland dropout were measured in these patients. The effectiveness of the tests, singly and in combinations, in differentiating between the dry eye subtypes was evaluated by retrospective allocation into groups and by Receiver Operative Characteristics (ROC) curve analysis. RESULTS: Statistically significant differences were seen for TTR and tear evaporation (with lower values for ADDE) between ADDE and EDE, but no significant differences were seen for tear osmolarity, volume, distribution, and meibomian gland dropout scores. Differentiation of ADDE and EDE by a cut-off value of 11%/min for TTR was found to have a sensitivity of 86%, specificity of 75%, positive predictive value 89%, negative predictive value 69%, and overall accuracy 83%. The area under the curve on the ROC curve was 0.83. For tear evaporation, a cut-off of 60 g/mh was found to have a sensitivity of 77%, specificity of 55%, positive predictive value 38%, negative predictive value 80%, and overall accuracy 58% in subtype differentiation. The area under the curve was 0.59 on the ROC curve. The distribution curve of the evaporation rates for ADDE and EDE, showed an overlap coefficient of 0.76 indicating that tear evaporation is within a similar range in these two dry eye subtypes. CONCLUSIONS: Tear turnover is significantly lower in ADDE than EDE, but there is considerable overlap of tear evaporation between the two dry eye subtypes. Tear osmolarity and turn over tests can be conducted sequentially to effectively diagnose dry eye and its subtypes.
PURPOSE: To determine the differences in tear physiology between aqueous deficiency dry eye (ADDE) and evaporative dry eye (EDE), and evaluate their utility in diagnosis. METHODS: Fifty-six dry eyepatients were classified into 30 ADDE and 26 EDE according to the recently published Dry Eye Workshop criteria. A range of tear physiology measures comprising of tear evaporation, turnover rate (TTR), distribution, volume and osmolarity, and meibomian gland dropout were measured in these patients. The effectiveness of the tests, singly and in combinations, in differentiating between the dry eye subtypes was evaluated by retrospective allocation into groups and by Receiver Operative Characteristics (ROC) curve analysis. RESULTS: Statistically significant differences were seen for TTR and tear evaporation (with lower values for ADDE) between ADDE and EDE, but no significant differences were seen for tear osmolarity, volume, distribution, and meibomian gland dropout scores. Differentiation of ADDE and EDE by a cut-off value of 11%/min for TTR was found to have a sensitivity of 86%, specificity of 75%, positive predictive value 89%, negative predictive value 69%, and overall accuracy 83%. The area under the curve on the ROC curve was 0.83. For tear evaporation, a cut-off of 60 g/mh was found to have a sensitivity of 77%, specificity of 55%, positive predictive value 38%, negative predictive value 80%, and overall accuracy 58% in subtype differentiation. The area under the curve was 0.59 on the ROC curve. The distribution curve of the evaporation rates for ADDE and EDE, showed an overlap coefficient of 0.76 indicating that tear evaporation is within a similar range in these two dry eye subtypes. CONCLUSIONS: Tear turnover is significantly lower in ADDE than EDE, but there is considerable overlap of tear evaporation between the two dry eye subtypes. Tear osmolarity and turn over tests can be conducted sequentially to effectively diagnose dry eye and its subtypes.
Authors: Alan Tomlinson; Anthony J Bron; Donald R Korb; Shiro Amano; Jerry R Paugh; E Ian Pearce; Richard Yee; Norihiko Yokoi; Reiko Arita; Murat Dogru Journal: Invest Ophthalmol Vis Sci Date: 2011-03-30 Impact factor: 4.799
Authors: Mark D P Willcox; Pablo Argüeso; Georgi A Georgiev; Juha M Holopainen; Gordon W Laurie; Tom J Millar; Eric B Papas; Jannick P Rolland; Tannin A Schmidt; Ulrike Stahl; Tatiana Suarez; Lakshman N Subbaraman; Omür Ö Uçakhan; Lyndon Jones Journal: Ocul Surf Date: 2017-07-20 Impact factor: 5.033
Authors: Ali A Abusharha; Tariq M AlShehri; Abdullah Y Hakami; Ali M Alsaqr; Raied A Fagehi; Saud A Alanazi; Ali M Masmali Journal: Ther Adv Ophthalmol Date: 2018-08-21
Authors: Liana Basova; Geraint J Parfitt; Alex Richardson; Vanessa Delcroix; Takeshi Umazume; Daniel Pelaez; David T Tse; Ivo Kalajzic; Nick Di Girolamo; James V Jester; Helen P Makarenkova Journal: iScience Date: 2020-06-02